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circle{fill:var(--md-mermaid-label-bg-color)}.actor{fill:var(--md-mermaid-sequence-actor-bg-color);stroke:var(--md-mermaid-sequence-actor-border-color)}text.actor>tspan{fill:var(--md-mermaid-sequence-actor-fg-color);font-family:var(--md-mermaid-font-family)}line{stroke:var(--md-mermaid-sequence-actor-line-color)}.actor-man circle,.actor-man line{fill:var(--md-mermaid-sequence-actorman-bg-color);stroke:var(--md-mermaid-sequence-actorman-line-color)}.messageLine0,.messageLine1{stroke:var(--md-mermaid-sequence-message-line-color)}.note{fill:var(--md-mermaid-sequence-note-bg-color);stroke:var(--md-mermaid-sequence-note-border-color)}.loopText,.loopText>tspan,.messageText,.noteText>tspan{stroke:none;font-family:var(--md-mermaid-font-family)!important}.messageText{fill:var(--md-mermaid-sequence-message-fg-color)}.loopText,.loopText>tspan{fill:var(--md-mermaid-sequence-loop-fg-color)}.noteText>tspan{fill:var(--md-mermaid-sequence-note-fg-color)}#arrowhead path{fill:var(--md-mermaid-sequence-message-line-color);stroke:none}.loopLine{fill:var(--md-mermaid-sequence-loop-bg-color);stroke:var(--md-mermaid-sequence-loop-border-color)}.labelBox{fill:var(--md-mermaid-sequence-label-bg-color);stroke:none}.labelText,.labelText>span{fill:var(--md-mermaid-sequence-label-fg-color);font-family:var(--md-mermaid-font-family)}.sequenceNumber{fill:var(--md-mermaid-sequence-number-fg-color)}rect.rect{fill:var(--md-mermaid-sequence-box-bg-color);stroke:none}rect.rect+text.text{fill:var(--md-mermaid-sequence-box-fg-color)}defs #sequencenumber{fill:var(--md-mermaid-sequence-number-bg-color)!important}";var Br,Da=0;function Va(){return typeof mermaid=="undefined"||mermaid instanceof Element?Et("https://unpkg.com/mermaid@10.7.0/dist/mermaid.min.js"):I(void 0)}function In(e){return e.classList.remove("mermaid"),Br||(Br=Va().pipe(y(()=>mermaid.initialize({startOnLoad:!1,themeCSS:Rn,sequence:{actorFontSize:"16px",messageFontSize:"16px",noteFontSize:"16px"}})),m(()=>{}),B(1))),Br.subscribe(()=>ao(this,null,function*(){e.classList.add("mermaid");let t=`__mermaid_${Da++}`,r=E("div",{class:"mermaid"}),o=e.textContent,{svg:n,fn:i}=yield mermaid.render(t,o),a=r.attachShadow({mode:"closed"});a.innerHTML=n,e.replaceWith(r),i==null||i(a)})),Br.pipe(m(()=>({ref:e})))}var Fn=E("table");function jn(e){return e.replaceWith(Fn),Fn.replaceWith(On(e)),I({ref:e})}function Na(e){let t=e.find(r=>r.checked)||e[0];return S(...e.map(r=>d(r,"change").pipe(m(()=>P(`label[for="${r.id}"]`))))).pipe(Q(P(`label[for="${t.id}"]`)),m(r=>({active:r})))}function Wn(e,{viewport$:t,target$:r}){let o=P(".tabbed-labels",e),n=$(":scope > input",e),i=Qr("prev");e.append(i);let a=Qr("next");return e.append(a),C(()=>{let s=new g,p=s.pipe(X(),ne(!0));z([s,ge(e)]).pipe(U(p),Le(1,me)).subscribe({next([{active:c},l]){let f=Ue(c),{width:u}=ce(c);e.style.setProperty("--md-indicator-x",`${f.x}px`),e.style.setProperty("--md-indicator-width",`${u}px`);let h=pr(o);(f.xh.x+l.width)&&o.scrollTo({left:Math.max(0,f.x-16),behavior:"smooth"})},complete(){e.style.removeProperty("--md-indicator-x"),e.style.removeProperty("--md-indicator-width")}}),z([De(o),ge(o)]).pipe(U(p)).subscribe(([c,l])=>{let f=wt(o);i.hidden=c.x<16,a.hidden=c.x>f.width-l.width-16}),S(d(i,"click").pipe(m(()=>-1)),d(a,"click").pipe(m(()=>1))).pipe(U(p)).subscribe(c=>{let{width:l}=ce(o);o.scrollBy({left:l*c,behavior:"smooth"})}),r.pipe(U(p),b(c=>n.includes(c))).subscribe(c=>c.click()),o.classList.add("tabbed-labels--linked");for(let c of n){let l=P(`label[for="${c.id}"]`);l.replaceChildren(E("a",{href:`#${l.htmlFor}`,tabIndex:-1},...Array.from(l.childNodes))),d(l.firstElementChild,"click").pipe(U(p),b(f=>!(f.metaKey||f.ctrlKey)),y(f=>{f.preventDefault(),f.stopPropagation()})).subscribe(()=>{history.replaceState({},"",`#${l.htmlFor}`),l.click()})}return G("content.tabs.link")&&s.pipe(Ce(1),ee(t)).subscribe(([{active:c},{offset:l}])=>{let f=c.innerText.trim();if(c.hasAttribute("data-md-switching"))c.removeAttribute("data-md-switching");else{let u=e.offsetTop-l.y;for(let w of $("[data-tabs]"))for(let A of $(":scope > input",w)){let te=P(`label[for="${A.id}"]`);if(te!==c&&te.innerText.trim()===f){te.setAttribute("data-md-switching",""),A.click();break}}window.scrollTo({top:e.offsetTop-u});let h=__md_get("__tabs")||[];__md_set("__tabs",[...new Set([f,...h])])}}),s.pipe(U(p)).subscribe(()=>{for(let c of $("audio, video",e))c.pause()}),Na(n).pipe(y(c=>s.next(c)),L(()=>s.complete()),m(c=>R({ref:e},c)))}).pipe(Qe(se))}function Un(e,{viewport$:t,target$:r,print$:o}){return S(...$(".annotate:not(.highlight)",e).map(n=>Cn(n,{target$:r,print$:o})),...$("pre:not(.mermaid) > code",e).map(n=>$n(n,{target$:r,print$:o})),...$("pre.mermaid",e).map(n=>In(n)),...$("table:not([class])",e).map(n=>jn(n)),...$("details",e).map(n=>Pn(n,{target$:r,print$:o})),...$("[data-tabs]",e).map(n=>Wn(n,{viewport$:t,target$:r})),...$("[title]",e).filter(()=>G("content.tooltips")).map(n=>pt(n,{viewport$:t})))}function za(e,{alert$:t}){return t.pipe(v(r=>S(I(!0),I(!1).pipe(Ge(2e3))).pipe(m(o=>({message:r,active:o})))))}function Dn(e,t){let r=P(".md-typeset",e);return C(()=>{let o=new g;return o.subscribe(({message:n,active:i})=>{e.classList.toggle("md-dialog--active",i),r.textContent=n}),za(e,t).pipe(y(n=>o.next(n)),L(()=>o.complete()),m(n=>R({ref:e},n)))})}var qa=0;function Qa(e,t){document.body.append(e);let{width:r}=ce(e);e.style.setProperty("--md-tooltip-width",`${r}px`),e.remove();let o=cr(t),n=typeof o!="undefined"?De(o):I({x:0,y:0}),i=S(et(t),kt(t)).pipe(K());return z([i,n]).pipe(m(([a,s])=>{let{x:p,y:c}=Ue(t),l=ce(t),f=t.closest("table");return f&&t.parentElement&&(p+=f.offsetLeft+t.parentElement.offsetLeft,c+=f.offsetTop+t.parentElement.offsetTop),{active:a,offset:{x:p-s.x+l.width/2-r/2,y:c-s.y+l.height+8}}}))}function Vn(e){let t=e.title;if(!t.length)return M;let r=`__tooltip_${qa++}`,o=Pt(r,"inline"),n=P(".md-typeset",o);return n.innerHTML=t,C(()=>{let i=new g;return i.subscribe({next({offset:a}){o.style.setProperty("--md-tooltip-x",`${a.x}px`),o.style.setProperty("--md-tooltip-y",`${a.y}px`)},complete(){o.style.removeProperty("--md-tooltip-x"),o.style.removeProperty("--md-tooltip-y")}}),S(i.pipe(b(({active:a})=>a)),i.pipe(_e(250),b(({active:a})=>!a))).subscribe({next({active:a}){a?(e.insertAdjacentElement("afterend",o),e.setAttribute("aria-describedby",r),e.removeAttribute("title")):(o.remove(),e.removeAttribute("aria-describedby"),e.setAttribute("title",t))},complete(){o.remove(),e.removeAttribute("aria-describedby"),e.setAttribute("title",t)}}),i.pipe(Le(16,me)).subscribe(({active:a})=>{o.classList.toggle("md-tooltip--active",a)}),i.pipe(st(125,me),b(()=>!!e.offsetParent),m(()=>e.offsetParent.getBoundingClientRect()),m(({x:a})=>a)).subscribe({next(a){a?o.style.setProperty("--md-tooltip-0",`${-a}px`):o.style.removeProperty("--md-tooltip-0")},complete(){o.style.removeProperty("--md-tooltip-0")}}),Qa(o,e).pipe(y(a=>i.next(a)),L(()=>i.complete()),m(a=>R({ref:e},a)))}).pipe(Qe(se))}function Ka({viewport$:e}){if(!G("header.autohide"))return I(!1);let t=e.pipe(m(({offset:{y:n}})=>n),Ye(2,1),m(([n,i])=>[nMath.abs(i-n.y)>100),m(([,[n]])=>n),K()),o=Ve("search");return z([e,o]).pipe(m(([{offset:n},i])=>n.y>400&&!i),K(),v(n=>n?r:I(!1)),Q(!1))}function Nn(e,t){return C(()=>z([ge(e),Ka(t)])).pipe(m(([{height:r},o])=>({height:r,hidden:o})),K((r,o)=>r.height===o.height&&r.hidden===o.hidden),B(1))}function zn(e,{header$:t,main$:r}){return C(()=>{let o=new g,n=o.pipe(X(),ne(!0));o.pipe(Z("active"),We(t)).subscribe(([{active:a},{hidden:s}])=>{e.classList.toggle("md-header--shadow",a&&!s),e.hidden=s});let i=ue($("[title]",e)).pipe(b(()=>G("content.tooltips")),oe(a=>Vn(a)));return r.subscribe(o),t.pipe(U(n),m(a=>R({ref:e},a)),Pe(i.pipe(U(n))))})}function Ya(e,{viewport$:t,header$:r}){return mr(e,{viewport$:t,header$:r}).pipe(m(({offset:{y:o}})=>{let{height:n}=ce(e);return{active:o>=n}}),Z("active"))}function qn(e,t){return C(()=>{let r=new g;r.subscribe({next({active:n}){e.classList.toggle("md-header__title--active",n)},complete(){e.classList.remove("md-header__title--active")}});let o=fe(".md-content h1");return typeof o=="undefined"?M:Ya(o,t).pipe(y(n=>r.next(n)),L(()=>r.complete()),m(n=>R({ref:e},n)))})}function Qn(e,{viewport$:t,header$:r}){let o=r.pipe(m(({height:i})=>i),K()),n=o.pipe(v(()=>ge(e).pipe(m(({height:i})=>({top:e.offsetTop,bottom:e.offsetTop+i})),Z("bottom"))));return z([o,n,t]).pipe(m(([i,{top:a,bottom:s},{offset:{y:p},size:{height:c}}])=>(c=Math.max(0,c-Math.max(0,a-p,i)-Math.max(0,c+p-s)),{offset:a-i,height:c,active:a-i<=p})),K((i,a)=>i.offset===a.offset&&i.height===a.height&&i.active===a.active))}function Ba(e){let t=__md_get("__palette")||{index:e.findIndex(o=>matchMedia(o.getAttribute("data-md-color-media")).matches)},r=Math.max(0,Math.min(t.index,e.length-1));return I(...e).pipe(oe(o=>d(o,"change").pipe(m(()=>o))),Q(e[r]),m(o=>({index:e.indexOf(o),color:{media:o.getAttribute("data-md-color-media"),scheme:o.getAttribute("data-md-color-scheme"),primary:o.getAttribute("data-md-color-primary"),accent:o.getAttribute("data-md-color-accent")}})),B(1))}function Kn(e){let t=$("input",e),r=E("meta",{name:"theme-color"});document.head.appendChild(r);let o=E("meta",{name:"color-scheme"});document.head.appendChild(o);let n=$t("(prefers-color-scheme: light)");return C(()=>{let i=new g;return i.subscribe(a=>{if(document.body.setAttribute("data-md-color-switching",""),a.color.media==="(prefers-color-scheme)"){let s=matchMedia("(prefers-color-scheme: light)"),p=document.querySelector(s.matches?"[data-md-color-media='(prefers-color-scheme: light)']":"[data-md-color-media='(prefers-color-scheme: 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Gr=Vt(Yr());function Ga(e){e.setAttribute("data-md-copying","");let t=e.closest("[data-copy]"),r=t?t.getAttribute("data-copy"):e.innerText;return e.removeAttribute("data-md-copying"),r.trimEnd()}function Bn({alert$:e}){Gr.default.isSupported()&&new F(t=>{new Gr.default("[data-clipboard-target], [data-clipboard-text]",{text:r=>r.getAttribute("data-clipboard-text")||Ga(P(r.getAttribute("data-clipboard-target")))}).on("success",r=>t.next(r))}).pipe(y(t=>{t.trigger.focus()}),m(()=>ye("clipboard.copied"))).subscribe(e)}function Gn(e,t){return e.protocol=t.protocol,e.hostname=t.hostname,e}function Ja(e,t){let r=new Map;for(let o of $("url",e)){let n=P("loc",o),i=[Gn(new URL(n.textContent),t)];r.set(`${i[0]}`,i);for(let a of $("[rel=alternate]",o)){let s=a.getAttribute("href");s!=null&&i.push(Gn(new URL(s),t))}}return r}function ur(e){return mn(new URL("sitemap.xml",e)).pipe(m(t=>Ja(t,new URL(e))),ve(()=>I(new Map)))}function Xa(e,t){if(!(e.target instanceof Element))return M;let r=e.target.closest("a");if(r===null)return M;if(r.target||e.metaKey||e.ctrlKey)return M;let o=new URL(r.href);return o.search=o.hash="",t.has(`${o}`)?(e.preventDefault(),I(new URL(r.href))):M}function Jn(e){let t=new Map;for(let r of $(":scope > *",e.head))t.set(r.outerHTML,r);return t}function Xn(e){for(let t of $("[href], [src]",e))for(let r of["href","src"]){let o=t.getAttribute(r);if(o&&!/^(?:[a-z]+:)?\/\//i.test(o)){t[r]=t[r];break}}return I(e)}function Za(e){for(let o of["[data-md-component=announce]","[data-md-component=container]","[data-md-component=header-topic]","[data-md-component=outdated]","[data-md-component=logo]","[data-md-component=skip]",...G("navigation.tabs.sticky")?["[data-md-component=tabs]"]:[]]){let n=fe(o),i=fe(o,e);typeof n!="undefined"&&typeof i!="undefined"&&n.replaceWith(i)}let t=Jn(document);for(let[o,n]of Jn(e))t.has(o)?t.delete(o):document.head.appendChild(n);for(let o of t.values()){let n=o.getAttribute("name");n!=="theme-color"&&n!=="color-scheme"&&o.remove()}let r=Se("container");return je($("script",r)).pipe(v(o=>{let n=e.createElement("script");if(o.src){for(let i of o.getAttributeNames())n.setAttribute(i,o.getAttribute(i));return o.replaceWith(n),new F(i=>{n.onload=()=>i.complete()})}else return n.textContent=o.textContent,o.replaceWith(n),M}),X(),ne(document))}function Zn({location$:e,viewport$:t,progress$:r}){let o=Te();if(location.protocol==="file:")return M;let n=ur(o.base);I(document).subscribe(Xn);let i=d(document.body,"click").pipe(We(n),v(([p,c])=>Xa(p,c)),pe()),a=d(window,"popstate").pipe(m(xe),pe());i.pipe(ee(t)).subscribe(([p,{offset:c}])=>{history.replaceState(c,""),history.pushState(null,"",p)}),S(i,a).subscribe(e);let s=e.pipe(Z("pathname"),v(p=>ln(p,{progress$:r}).pipe(ve(()=>(ct(p,!0),M)))),v(Xn),v(Za),pe());return 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g,o=r.pipe(X(),ne(!0));z([t.pipe(Ae(It)),r],(i,a)=>a).pipe(Z("value")).subscribe(({value:i})=>t.next({type:2,data:i})),r.pipe(Z("focus")).subscribe(({focus:i})=>{i&&Je("search",i)}),d(e.form,"reset").pipe(U(o)).subscribe(()=>e.focus());let n=P("header [for=__search]");return d(n,"click").subscribe(()=>e.focus()),ns(e,{worker$:t}).pipe(y(i=>r.next(i)),L(()=>r.complete()),m(i=>R({ref:e},i)),B(1))}function si(e,{worker$:t,query$:r}){let o=new g,n=tn(e.parentElement).pipe(b(Boolean)),i=e.parentElement,a=P(":scope > :first-child",e),s=P(":scope > :last-child",e);Ve("search").subscribe(l=>s.setAttribute("role",l?"list":"presentation")),o.pipe(ee(r),Ur(t.pipe(Ae(It)))).subscribe(([{items:l},{value:f}])=>{switch(l.length){case 0:a.textContent=f.length?ye("search.result.none"):ye("search.result.placeholder");break;case 1:a.textContent=ye("search.result.one");break;default:let u=sr(l.length);a.textContent=ye("search.result.other",u)}});let 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g,n=Se("search-query"),i=S(d(n,"keydown"),d(n,"focus")).pipe(be(se),m(()=>n.value),K());return o.pipe(We(i),m(([{suggest:s},p])=>{let c=p.split(/([\s-]+)/);if(s!=null&&s.length&&c[c.length-1]){let l=s[s.length-1];l.startsWith(c[c.length-1])&&(c[c.length-1]=l)}else c.length=0;return c})).subscribe(s=>e.innerHTML=s.join("").replace(/\s/g," ")),r.pipe(b(({mode:s})=>s==="search")).subscribe(s=>{switch(s.type){case"ArrowRight":e.innerText.length&&n.selectionStart===n.value.length&&(n.value=e.innerText);break}}),t.pipe(b(dr),m(({data:s})=>s)).pipe(y(s=>o.next(s)),L(()=>o.complete()),m(()=>({ref:e})))}function li(e,{index$:t,keyboard$:r}){let o=Te();try{let n=ni(o.search,t),i=Se("search-query",e),a=Se("search-result",e);d(e,"click").pipe(b(({target:p})=>p instanceof Element&&!!p.closest("a"))).subscribe(()=>Je("search",!1)),r.pipe(b(({mode:p})=>p==="search")).subscribe(p=>{let c=Re();switch(p.type){case"Enter":if(c===i){let l=new Map;for(let f of $(":first-child [href]",a)){let 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z([t,r.pipe(Q(xe()),b(o=>!!o.searchParams.get("h")))]).pipe(m(([o,n])=>oi(o.config)(n.searchParams.get("h"))),m(o=>{var a;let n=new Map,i=document.createNodeIterator(e,NodeFilter.SHOW_TEXT);for(let s=i.nextNode();s;s=i.nextNode())if((a=s.parentElement)!=null&&a.offsetHeight){let p=s.textContent,c=o(p);c.length>p.length&&n.set(s,c)}for(let[s,p]of n){let{childNodes:c}=E("span",null,p);s.replaceWith(...Array.from(c))}return{ref:e,nodes:n}}))}function as(e,{viewport$:t,main$:r}){let o=e.closest(".md-grid"),n=o.offsetTop-o.parentElement.offsetTop;return z([r,t]).pipe(m(([{offset:i,height:a},{offset:{y:s}}])=>(a=a+Math.min(n,Math.max(0,s-i))-n,{height:a,locked:s>=i+n})),K((i,a)=>i.height===a.height&&i.locked===a.locked))}function Jr(e,o){var n=o,{header$:t}=n,r=io(n,["header$"]);let i=P(".md-sidebar__scrollwrap",e),{y:a}=Ue(i);return C(()=>{let s=new g,p=s.pipe(X(),ne(!0)),c=s.pipe(Le(0,me));return c.pipe(ee(t)).subscribe({next([{height:l},{height:f}]){i.style.height=`${l-2*a}px`,e.style.top=`${f}px`},complete(){i.style.height="",e.style.top=""}}),c.pipe(Ae()).subscribe(()=>{for(let l of $(".md-nav__link--active[href]",e)){if(!l.clientHeight)continue;let f=l.closest(".md-sidebar__scrollwrap");if(typeof f!="undefined"){let u=l.offsetTop-f.offsetTop,{height:h}=ce(f);f.scrollTo({top:u-h/2})}}}),ue($("label[tabindex]",e)).pipe(oe(l=>d(l,"click").pipe(be(se),m(()=>l),U(p)))).subscribe(l=>{let f=P(`[id="${l.htmlFor}"]`);P(`[aria-labelledby="${l.id}"]`).setAttribute("aria-expanded",`${f.checked}`)}),as(e,r).pipe(y(l=>s.next(l)),L(()=>s.complete()),m(l=>R({ref:e},l)))})}function fi(e,t){if(typeof t!="undefined"){let r=`https://api.github.com/repos/${e}/${t}`;return Ct(Ne(`${r}/releases/latest`).pipe(ve(()=>M),m(o=>({version:o.tag_name})),Be({})),Ne(r).pipe(ve(()=>M),m(o=>({stars:o.stargazers_count,forks:o.forks_count})),Be({}))).pipe(m(([o,n])=>R(R({},o),n)))}else{let r=`https://api.github.com/users/${e}`;return Ne(r).pipe(m(o=>({repositories:o.public_repos})),Be({}))}}function ui(e,t){let r=`https://${e}/api/v4/projects/${encodeURIComponent(t)}`;return Ne(r).pipe(ve(()=>M),m(({star_count:o,forks_count:n})=>({stars:o,forks:n})),Be({}))}function di(e){let t=e.match(/^.+github\.com\/([^/]+)\/?([^/]+)?/i);if(t){let[,r,o]=t;return fi(r,o)}if(t=e.match(/^.+?([^/]*gitlab[^/]+)\/(.+?)\/?$/i),t){let[,r,o]=t;return ui(r,o)}return M}var ss;function cs(e){return ss||(ss=C(()=>{let t=__md_get("__source",sessionStorage);if(t)return I(t);if(ae("consent").length){let o=__md_get("__consent");if(!(o&&o.github))return M}return di(e.href).pipe(y(o=>__md_set("__source",o,sessionStorage)))}).pipe(ve(()=>M),b(t=>Object.keys(t).length>0),m(t=>({facts:t})),B(1)))}function hi(e){let t=P(":scope > :last-child",e);return C(()=>{let r=new g;return 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n=t.pipe(m(({offset:{y:a}})=>a),Ye(2,1),m(([a,s])=>a>s&&s>0),K()),i=r.pipe(m(({active:a})=>a));return z([i,n]).pipe(m(([a,s])=>!(a&&s)),K(),U(o.pipe(Ce(1))),ne(!0),at({delay:250}),m(a=>({hidden:a})))}function gi(e,{viewport$:t,header$:r,main$:o,target$:n}){let i=new g,a=i.pipe(X(),ne(!0));return i.subscribe({next({hidden:s}){e.hidden=s,s?(e.setAttribute("tabindex","-1"),e.blur()):e.removeAttribute("tabindex")},complete(){e.style.top="",e.hidden=!0,e.removeAttribute("tabindex")}}),r.pipe(U(a),Z("height")).subscribe(({height:s})=>{e.style.top=`${s+16}px`}),d(e,"click").subscribe(s=>{s.preventDefault(),window.scrollTo({top:0})}),ms(e,{viewport$:t,main$:o,target$:n}).pipe(y(s=>i.next(s)),L(()=>i.complete()),m(s=>R({ref:e},s)))}function xi({document$:e,viewport$:t}){e.pipe(v(()=>$(".md-ellipsis")),oe(r=>Tt(r).pipe(U(e.pipe(Ce(1))),b(o=>o),m(()=>r),we(1))),b(r=>r.offsetWidth{let o=r.innerText,n=r.closest("a")||r;return n.title=o,pt(n,{viewport$:t}).pipe(U(e.pipe(Ce(1))),L(()=>n.removeAttribute("title")))})).subscribe(),e.pipe(v(()=>$(".md-status")),oe(r=>pt(r,{viewport$:t}))).subscribe()}function yi({document$:e,tablet$:t}){e.pipe(v(()=>$(".md-toggle--indeterminate")),y(r=>{r.indeterminate=!0,r.checked=!1}),oe(r=>d(r,"change").pipe(Dr(()=>r.classList.contains("md-toggle--indeterminate")),m(()=>r))),ee(t)).subscribe(([r,o])=>{r.classList.remove("md-toggle--indeterminate"),o&&(r.checked=!1)})}function fs(){return/(iPad|iPhone|iPod)/.test(navigator.userAgent)}function Ei({document$:e}){e.pipe(v(()=>$("[data-md-scrollfix]")),y(t=>t.removeAttribute("data-md-scrollfix")),b(fs),oe(t=>d(t,"touchstart").pipe(m(()=>t)))).subscribe(t=>{let r=t.scrollTop;r===0?t.scrollTop=1:r+t.offsetHeight===t.scrollHeight&&(t.scrollTop=r-1)})}function wi({viewport$:e,tablet$:t}){z([Ve("search"),t]).pipe(m(([r,o])=>r&&!o),v(r=>I(r).pipe(Ge(r?400:100))),ee(e)).subscribe(([r,{offset:{y:o}}])=>{if(r)document.body.setAttribute("data-md-scrolllock",""),document.body.style.top=`-${o}px`;else{let n=-1*parseInt(document.body.style.top,10);document.body.removeAttribute("data-md-scrolllock"),document.body.style.top="",n&&window.scrollTo(0,n)}})}Object.entries||(Object.entries=function(e){let t=[];for(let r of Object.keys(e))t.push([r,e[r]]);return t});Object.values||(Object.values=function(e){let t=[];for(let r of Object.keys(e))t.push(e[r]);return t});typeof Element!="undefined"&&(Element.prototype.scrollTo||(Element.prototype.scrollTo=function(e,t){typeof e=="object"?(this.scrollLeft=e.left,this.scrollTop=e.top):(this.scrollLeft=e,this.scrollTop=t)}),Element.prototype.replaceWith||(Element.prototype.replaceWith=function(...e){let t=this.parentNode;if(t){e.length===0&&t.removeChild(this);for(let r=e.length-1;r>=0;r--){let o=e[r];typeof o=="string"?o=document.createTextNode(o):o.parentNode&&o.parentNode.removeChild(o),r?t.insertBefore(this.previousSibling,o):t.replaceChild(o,this)}}}));function us(){return location.protocol==="file:"?Et(`${new URL("search/search_index.js",Xr.base)}`).pipe(m(()=>__index),B(1)):Ne(new URL("search/search_index.json",Xr.base))}document.documentElement.classList.remove("no-js");document.documentElement.classList.add("js");var rt=Yo(),jt=nn(),Ot=cn(jt),Zr=on(),Oe=bn(),hr=$t("(min-width: 960px)"),Si=$t("(min-width: 1220px)"),Oi=pn(),Xr=Te(),Mi=document.forms.namedItem("search")?us():Ke,eo=new g;Bn({alert$:eo});var to=new g;G("navigation.instant")&&Zn({location$:jt,viewport$:Oe,progress$:to}).subscribe(rt);var Ti;((Ti=Xr.version)==null?void 0:Ti.provider)==="mike"&&ii({document$:rt});S(jt,Ot).pipe(Ge(125)).subscribe(()=>{Je("drawer",!1),Je("search",!1)});Zr.pipe(b(({mode:e})=>e==="global")).subscribe(e=>{switch(e.type){case"p":case",":let t=fe("link[rel=prev]");typeof t!="undefined"&&ct(t);break;case"n":case".":let r=fe("link[rel=next]");typeof r!="undefined"&&ct(r);break;case"Enter":let o=Re();o instanceof HTMLLabelElement&&o.click()}});xi({viewport$:Oe,document$:rt});yi({document$:rt,tablet$:hr});Ei({document$:rt});wi({viewport$:Oe,tablet$:hr});var tt=Nn(Se("header"),{viewport$:Oe}),Ft=rt.pipe(m(()=>Se("main")),v(e=>Qn(e,{viewport$:Oe,header$:tt})),B(1)),ds=S(...ae("consent").map(e=>xn(e,{target$:Ot})),...ae("dialog").map(e=>Dn(e,{alert$:eo})),...ae("header").map(e=>zn(e,{viewport$:Oe,header$:tt,main$:Ft})),...ae("palette").map(e=>Kn(e)),...ae("progress").map(e=>Yn(e,{progress$:to})),...ae("search").map(e=>li(e,{index$:Mi,keyboard$:Zr})),...ae("source").map(e=>hi(e))),hs=C(()=>S(...ae("announce").map(e=>gn(e)),...ae("content").map(e=>Un(e,{viewport$:Oe,target$:Ot,print$:Oi})),...ae("content").map(e=>G("search.highlight")?mi(e,{index$:Mi,location$:jt}):M),...ae("header-title").map(e=>qn(e,{viewport$:Oe,header$:tt})),...ae("sidebar").map(e=>e.getAttribute("data-md-type")==="navigation"?Nr(Si,()=>Jr(e,{viewport$:Oe,header$:tt,main$:Ft})):Nr(hr,()=>Jr(e,{viewport$:Oe,header$:tt,main$:Ft}))),...ae("tabs").map(e=>bi(e,{viewport$:Oe,header$:tt})),...ae("toc").map(e=>vi(e,{viewport$:Oe,header$:tt,main$:Ft,target$:Ot})),...ae("top").map(e=>gi(e,{viewport$:Oe,header$:tt,main$:Ft,target$:Ot})))),Li=rt.pipe(v(()=>hs),Pe(ds),B(1));Li.subscribe();window.document$=rt;window.location$=jt;window.target$=Ot;window.keyboard$=Zr;window.viewport$=Oe;window.tablet$=hr;window.screen$=Si;window.print$=Oi;window.alert$=eo;window.progress$=to;window.component$=Li;})(); 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"sourcesContent": ["(function (global, factory) {\n typeof exports === 'object' && typeof module !== 'undefined' ? factory() :\n typeof define === 'function' && define.amd ? define(factory) :\n (factory());\n}(this, (function () { 'use strict';\n\n /**\n * Applies the :focus-visible polyfill at the given scope.\n * A scope in this case is either the top-level Document or a Shadow Root.\n *\n * @param {(Document|ShadowRoot)} scope\n * @see https://github.com/WICG/focus-visible\n */\n function applyFocusVisiblePolyfill(scope) {\n var hadKeyboardEvent = true;\n var hadFocusVisibleRecently = false;\n var hadFocusVisibleRecentlyTimeout = null;\n\n var inputTypesAllowlist = {\n text: true,\n search: true,\n url: true,\n tel: true,\n email: true,\n password: true,\n number: true,\n date: true,\n month: true,\n week: true,\n time: true,\n datetime: true,\n 'datetime-local': true\n };\n\n /**\n * Helper function for legacy browsers and iframes which sometimes focus\n * elements like document, body, and non-interactive SVG.\n * @param {Element} el\n */\n function isValidFocusTarget(el) {\n if (\n el &&\n el !== document &&\n el.nodeName !== 'HTML' &&\n el.nodeName !== 'BODY' &&\n 'classList' in el &&\n 'contains' in el.classList\n ) {\n return true;\n }\n return false;\n }\n\n /**\n * Computes whether the given element should automatically trigger the\n * `focus-visible` class being added, i.e. whether it should always match\n * `:focus-visible` when focused.\n * @param {Element} el\n * @return {boolean}\n */\n function focusTriggersKeyboardModality(el) {\n var type = el.type;\n var tagName = el.tagName;\n\n if (tagName === 'INPUT' && inputTypesAllowlist[type] && !el.readOnly) {\n return true;\n }\n\n if (tagName === 'TEXTAREA' && !el.readOnly) {\n return true;\n }\n\n if (el.isContentEditable) {\n return true;\n }\n\n return false;\n }\n\n /**\n * Add the `focus-visible` class to the given element if it was not added by\n * the author.\n * @param {Element} el\n */\n function addFocusVisibleClass(el) {\n if (el.classList.contains('focus-visible')) {\n return;\n }\n el.classList.add('focus-visible');\n el.setAttribute('data-focus-visible-added', '');\n }\n\n /**\n * Remove the `focus-visible` class from the given element if it was not\n * originally added by the author.\n * @param {Element} el\n */\n function removeFocusVisibleClass(el) {\n if (!el.hasAttribute('data-focus-visible-added')) {\n return;\n }\n el.classList.remove('focus-visible');\n el.removeAttribute('data-focus-visible-added');\n }\n\n /**\n * If the most recent user interaction was via the keyboard;\n * and the key press did not include a meta, alt/option, or control key;\n * then the modality is keyboard. Otherwise, the modality is not keyboard.\n * Apply `focus-visible` to any current active element and keep track\n * of our keyboard modality state with `hadKeyboardEvent`.\n * @param {KeyboardEvent} e\n */\n function onKeyDown(e) {\n if (e.metaKey || e.altKey || e.ctrlKey) {\n return;\n }\n\n if (isValidFocusTarget(scope.activeElement)) {\n addFocusVisibleClass(scope.activeElement);\n }\n\n hadKeyboardEvent = true;\n }\n\n /**\n * If at any point a user clicks with a pointing device, ensure that we change\n * the modality away from keyboard.\n * This avoids the situation where a user presses a key on an already focused\n * element, and then clicks on a different element, focusing it with a\n * pointing device, while we still think we're in keyboard modality.\n * @param {Event} e\n */\n function onPointerDown(e) {\n hadKeyboardEvent = false;\n }\n\n /**\n * On `focus`, add the `focus-visible` class to the target if:\n * - the target received focus as a result of keyboard navigation, or\n * - the event target is an element that will likely require interaction\n * via the keyboard (e.g. a text box)\n * @param {Event} e\n */\n function onFocus(e) {\n // Prevent IE from focusing the document or HTML element.\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (hadKeyboardEvent || focusTriggersKeyboardModality(e.target)) {\n addFocusVisibleClass(e.target);\n }\n }\n\n /**\n * On `blur`, remove the `focus-visible` class from the target.\n * @param {Event} e\n */\n function onBlur(e) {\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (\n e.target.classList.contains('focus-visible') ||\n e.target.hasAttribute('data-focus-visible-added')\n ) {\n // To detect a tab/window switch, we look for a blur event followed\n // rapidly by a visibility change.\n // If we don't see a visibility change within 100ms, it's probably a\n // regular focus change.\n hadFocusVisibleRecently = true;\n window.clearTimeout(hadFocusVisibleRecentlyTimeout);\n hadFocusVisibleRecentlyTimeout = window.setTimeout(function() {\n hadFocusVisibleRecently = false;\n }, 100);\n removeFocusVisibleClass(e.target);\n }\n }\n\n /**\n * If the user changes tabs, keep track of whether or not the previously\n * focused element had .focus-visible.\n * @param {Event} e\n */\n function onVisibilityChange(e) {\n if (document.visibilityState === 'hidden') {\n // If the tab becomes active again, the browser will handle calling focus\n // on the element (Safari actually calls it twice).\n // If this tab change caused a blur on an element with focus-visible,\n // re-apply the class when the user switches back to the tab.\n if (hadFocusVisibleRecently) {\n hadKeyboardEvent = true;\n }\n addInitialPointerMoveListeners();\n }\n }\n\n /**\n * Add a group of listeners to detect usage of any pointing devices.\n * These listeners will be added when the polyfill first loads, and anytime\n * the window is blurred, so that they are active when the window regains\n * focus.\n */\n function addInitialPointerMoveListeners() {\n document.addEventListener('mousemove', onInitialPointerMove);\n document.addEventListener('mousedown', onInitialPointerMove);\n document.addEventListener('mouseup', onInitialPointerMove);\n document.addEventListener('pointermove', onInitialPointerMove);\n document.addEventListener('pointerdown', onInitialPointerMove);\n document.addEventListener('pointerup', onInitialPointerMove);\n document.addEventListener('touchmove', onInitialPointerMove);\n document.addEventListener('touchstart', onInitialPointerMove);\n document.addEventListener('touchend', onInitialPointerMove);\n }\n\n function removeInitialPointerMoveListeners() {\n document.removeEventListener('mousemove', onInitialPointerMove);\n document.removeEventListener('mousedown', onInitialPointerMove);\n document.removeEventListener('mouseup', onInitialPointerMove);\n document.removeEventListener('pointermove', onInitialPointerMove);\n document.removeEventListener('pointerdown', onInitialPointerMove);\n document.removeEventListener('pointerup', onInitialPointerMove);\n document.removeEventListener('touchmove', onInitialPointerMove);\n document.removeEventListener('touchstart', onInitialPointerMove);\n document.removeEventListener('touchend', onInitialPointerMove);\n }\n\n /**\n * When the polfyill first loads, assume the user is in keyboard modality.\n * If any event is received from a pointing device (e.g. mouse, pointer,\n * touch), turn off keyboard modality.\n * This accounts for situations where focus enters the page from the URL bar.\n * @param {Event} e\n */\n function onInitialPointerMove(e) {\n // Work around a Safari quirk that fires a mousemove on whenever the\n // window blurs, even if you're tabbing out of the page. \u00AF\\_(\u30C4)_/\u00AF\n if (e.target.nodeName && e.target.nodeName.toLowerCase() === 'html') {\n return;\n }\n\n hadKeyboardEvent = false;\n removeInitialPointerMoveListeners();\n }\n\n // For some kinds of state, we are interested in changes at the global scope\n // only. For example, global pointer input, global key presses and global\n // visibility change should affect the state at every scope:\n document.addEventListener('keydown', onKeyDown, true);\n document.addEventListener('mousedown', onPointerDown, true);\n document.addEventListener('pointerdown', onPointerDown, true);\n document.addEventListener('touchstart', onPointerDown, true);\n document.addEventListener('visibilitychange', onVisibilityChange, true);\n\n addInitialPointerMoveListeners();\n\n // For focus and blur, we specifically care about state changes in the local\n // scope. This is because focus / blur events that originate from within a\n // shadow root are not re-dispatched from the host element if it was already\n // the active element in its own scope:\n scope.addEventListener('focus', onFocus, true);\n scope.addEventListener('blur', onBlur, true);\n\n // We detect that a node is a ShadowRoot by ensuring that it is a\n // DocumentFragment and also has a host property. This check covers native\n // implementation and polyfill implementation transparently. If we only cared\n // about the native implementation, we could just check if the scope was\n // an instance of a ShadowRoot.\n if (scope.nodeType === Node.DOCUMENT_FRAGMENT_NODE && scope.host) {\n // Since a ShadowRoot is a special kind of DocumentFragment, it does not\n // have a root element to add a class to. So, we add this attribute to the\n // host element instead:\n scope.host.setAttribute('data-js-focus-visible', '');\n } else if (scope.nodeType === Node.DOCUMENT_NODE) {\n document.documentElement.classList.add('js-focus-visible');\n document.documentElement.setAttribute('data-js-focus-visible', '');\n }\n }\n\n // It is important to wrap all references to global window and document in\n // these checks to support server-side rendering use cases\n // @see https://github.com/WICG/focus-visible/issues/199\n if (typeof window !== 'undefined' && typeof document !== 'undefined') {\n // Make the polyfill helper globally available. This can be used as a signal\n // to interested libraries that wish to coordinate with the polyfill for e.g.,\n // applying the polyfill to a shadow root:\n window.applyFocusVisiblePolyfill = applyFocusVisiblePolyfill;\n\n // Notify interested libraries of the polyfill's presence, in case the\n // polyfill was loaded lazily:\n var event;\n\n try {\n event = new CustomEvent('focus-visible-polyfill-ready');\n } catch (error) {\n // IE11 does not support using CustomEvent as a constructor directly:\n event = document.createEvent('CustomEvent');\n event.initCustomEvent('focus-visible-polyfill-ready', false, false, {});\n }\n\n window.dispatchEvent(event);\n }\n\n if (typeof document !== 'undefined') {\n // Apply the polyfill to the global document, so that no JavaScript\n // coordination is required to use the polyfill in the top-level document:\n applyFocusVisiblePolyfill(document);\n }\n\n})));\n", "/*!\n * clipboard.js v2.0.11\n * https://clipboardjs.com/\n *\n * Licensed MIT \u00A9 Zeno Rocha\n */\n(function webpackUniversalModuleDefinition(root, factory) {\n\tif(typeof exports === 'object' && typeof module === 'object')\n\t\tmodule.exports = factory();\n\telse if(typeof define === 'function' && define.amd)\n\t\tdefine([], factory);\n\telse if(typeof exports === 'object')\n\t\texports[\"ClipboardJS\"] = factory();\n\telse\n\t\troot[\"ClipboardJS\"] = factory();\n})(this, function() {\nreturn /******/ (function() { // webpackBootstrap\n/******/ \tvar __webpack_modules__ = ({\n\n/***/ 686:\n/***/ (function(__unused_webpack_module, __webpack_exports__, __webpack_require__) {\n\n\"use strict\";\n\n// EXPORTS\n__webpack_require__.d(__webpack_exports__, {\n \"default\": function() { return /* binding */ clipboard; }\n});\n\n// EXTERNAL MODULE: ./node_modules/tiny-emitter/index.js\nvar tiny_emitter = __webpack_require__(279);\nvar tiny_emitter_default = /*#__PURE__*/__webpack_require__.n(tiny_emitter);\n// EXTERNAL MODULE: ./node_modules/good-listener/src/listen.js\nvar listen = __webpack_require__(370);\nvar listen_default = /*#__PURE__*/__webpack_require__.n(listen);\n// EXTERNAL MODULE: ./node_modules/select/src/select.js\nvar src_select = __webpack_require__(817);\nvar select_default = /*#__PURE__*/__webpack_require__.n(src_select);\n;// CONCATENATED MODULE: ./src/common/command.js\n/**\n * Executes a given operation type.\n * @param {String} type\n * @return {Boolean}\n */\nfunction command(type) {\n try {\n return document.execCommand(type);\n } catch (err) {\n return false;\n }\n}\n;// CONCATENATED MODULE: ./src/actions/cut.js\n\n\n/**\n * Cut action wrapper.\n * @param {String|HTMLElement} target\n * @return {String}\n */\n\nvar ClipboardActionCut = function ClipboardActionCut(target) {\n var selectedText = select_default()(target);\n command('cut');\n return selectedText;\n};\n\n/* harmony default export */ var actions_cut = (ClipboardActionCut);\n;// CONCATENATED MODULE: ./src/common/create-fake-element.js\n/**\n * Creates a fake textarea element with a value.\n * @param {String} value\n * @return {HTMLElement}\n */\nfunction createFakeElement(value) {\n var isRTL = document.documentElement.getAttribute('dir') === 'rtl';\n var fakeElement = document.createElement('textarea'); // Prevent zooming on iOS\n\n fakeElement.style.fontSize = '12pt'; // Reset box model\n\n fakeElement.style.border = '0';\n fakeElement.style.padding = '0';\n fakeElement.style.margin = '0'; // Move element out of screen horizontally\n\n fakeElement.style.position = 'absolute';\n fakeElement.style[isRTL ? 'right' : 'left'] = '-9999px'; // Move element to the same position vertically\n\n var yPosition = window.pageYOffset || document.documentElement.scrollTop;\n fakeElement.style.top = \"\".concat(yPosition, \"px\");\n fakeElement.setAttribute('readonly', '');\n fakeElement.value = value;\n return fakeElement;\n}\n;// CONCATENATED MODULE: ./src/actions/copy.js\n\n\n\n/**\n * Create fake copy action wrapper using a fake element.\n * @param {String} target\n * @param {Object} options\n * @return {String}\n */\n\nvar fakeCopyAction = function fakeCopyAction(value, options) {\n var fakeElement = createFakeElement(value);\n options.container.appendChild(fakeElement);\n var selectedText = select_default()(fakeElement);\n command('copy');\n fakeElement.remove();\n return selectedText;\n};\n/**\n * Copy action wrapper.\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @return {String}\n */\n\n\nvar ClipboardActionCopy = function ClipboardActionCopy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n var selectedText = '';\n\n if (typeof target === 'string') {\n selectedText = fakeCopyAction(target, options);\n } else if (target instanceof HTMLInputElement && !['text', 'search', 'url', 'tel', 'password'].includes(target === null || target === void 0 ? void 0 : target.type)) {\n // If input type doesn't support `setSelectionRange`. Simulate it. https://developer.mozilla.org/en-US/docs/Web/API/HTMLInputElement/setSelectionRange\n selectedText = fakeCopyAction(target.value, options);\n } else {\n selectedText = select_default()(target);\n command('copy');\n }\n\n return selectedText;\n};\n\n/* harmony default export */ var actions_copy = (ClipboardActionCopy);\n;// CONCATENATED MODULE: ./src/actions/default.js\nfunction _typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { _typeof = function _typeof(obj) { return typeof obj; }; } else { _typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return _typeof(obj); }\n\n\n\n/**\n * Inner function which performs selection from either `text` or `target`\n * properties and then executes copy or cut operations.\n * @param {Object} options\n */\n\nvar ClipboardActionDefault = function ClipboardActionDefault() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n // Defines base properties passed from constructor.\n var _options$action = options.action,\n action = _options$action === void 0 ? 'copy' : _options$action,\n container = options.container,\n target = options.target,\n text = options.text; // Sets the `action` to be performed which can be either 'copy' or 'cut'.\n\n if (action !== 'copy' && action !== 'cut') {\n throw new Error('Invalid \"action\" value, use either \"copy\" or \"cut\"');\n } // Sets the `target` property using an element that will be have its content copied.\n\n\n if (target !== undefined) {\n if (target && _typeof(target) === 'object' && target.nodeType === 1) {\n if (action === 'copy' && target.hasAttribute('disabled')) {\n throw new Error('Invalid \"target\" attribute. Please use \"readonly\" instead of \"disabled\" attribute');\n }\n\n if (action === 'cut' && (target.hasAttribute('readonly') || target.hasAttribute('disabled'))) {\n throw new Error('Invalid \"target\" attribute. You can\\'t cut text from elements with \"readonly\" or \"disabled\" attributes');\n }\n } else {\n throw new Error('Invalid \"target\" value, use a valid Element');\n }\n } // Define selection strategy based on `text` property.\n\n\n if (text) {\n return actions_copy(text, {\n container: container\n });\n } // Defines which selection strategy based on `target` property.\n\n\n if (target) {\n return action === 'cut' ? actions_cut(target) : actions_copy(target, {\n container: container\n });\n }\n};\n\n/* harmony default export */ var actions_default = (ClipboardActionDefault);\n;// CONCATENATED MODULE: ./src/clipboard.js\nfunction clipboard_typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { clipboard_typeof = function _typeof(obj) { return typeof obj; }; } else { clipboard_typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return clipboard_typeof(obj); }\n\nfunction _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\nfunction _defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } }\n\nfunction _createClass(Constructor, protoProps, staticProps) { if (protoProps) _defineProperties(Constructor.prototype, protoProps); if (staticProps) _defineProperties(Constructor, staticProps); return Constructor; }\n\nfunction _inherits(subClass, superClass) { if (typeof superClass !== \"function\" && superClass !== null) { throw new TypeError(\"Super expression must either be null or a function\"); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, writable: true, configurable: true } }); if (superClass) _setPrototypeOf(subClass, superClass); }\n\nfunction _setPrototypeOf(o, p) { _setPrototypeOf = Object.setPrototypeOf || function _setPrototypeOf(o, p) { o.__proto__ = p; return o; }; return _setPrototypeOf(o, p); }\n\nfunction _createSuper(Derived) { var hasNativeReflectConstruct = _isNativeReflectConstruct(); return function _createSuperInternal() { var Super = _getPrototypeOf(Derived), result; if (hasNativeReflectConstruct) { var NewTarget = _getPrototypeOf(this).constructor; result = Reflect.construct(Super, arguments, NewTarget); } else { result = Super.apply(this, arguments); } return _possibleConstructorReturn(this, result); }; }\n\nfunction _possibleConstructorReturn(self, call) { if (call && (clipboard_typeof(call) === \"object\" || typeof call === \"function\")) { return call; } return _assertThisInitialized(self); }\n\nfunction _assertThisInitialized(self) { if (self === void 0) { throw new ReferenceError(\"this hasn't been initialised - super() hasn't been called\"); } return self; }\n\nfunction _isNativeReflectConstruct() { if (typeof Reflect === \"undefined\" || !Reflect.construct) return false; if (Reflect.construct.sham) return false; if (typeof Proxy === \"function\") return true; try { Date.prototype.toString.call(Reflect.construct(Date, [], function () {})); return true; } catch (e) { return false; } }\n\nfunction _getPrototypeOf(o) { _getPrototypeOf = Object.setPrototypeOf ? Object.getPrototypeOf : function _getPrototypeOf(o) { return o.__proto__ || Object.getPrototypeOf(o); }; return _getPrototypeOf(o); }\n\n\n\n\n\n\n/**\n * Helper function to retrieve attribute value.\n * @param {String} suffix\n * @param {Element} element\n */\n\nfunction getAttributeValue(suffix, element) {\n var attribute = \"data-clipboard-\".concat(suffix);\n\n if (!element.hasAttribute(attribute)) {\n return;\n }\n\n return element.getAttribute(attribute);\n}\n/**\n * Base class which takes one or more elements, adds event listeners to them,\n * and instantiates a new `ClipboardAction` on each click.\n */\n\n\nvar Clipboard = /*#__PURE__*/function (_Emitter) {\n _inherits(Clipboard, _Emitter);\n\n var _super = _createSuper(Clipboard);\n\n /**\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n * @param {Object} options\n */\n function Clipboard(trigger, options) {\n var _this;\n\n _classCallCheck(this, Clipboard);\n\n _this = _super.call(this);\n\n _this.resolveOptions(options);\n\n _this.listenClick(trigger);\n\n return _this;\n }\n /**\n * Defines if attributes would be resolved using internal setter functions\n * or custom functions that were passed in the constructor.\n * @param {Object} options\n */\n\n\n _createClass(Clipboard, [{\n key: \"resolveOptions\",\n value: function resolveOptions() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n this.action = typeof options.action === 'function' ? options.action : this.defaultAction;\n this.target = typeof options.target === 'function' ? options.target : this.defaultTarget;\n this.text = typeof options.text === 'function' ? options.text : this.defaultText;\n this.container = clipboard_typeof(options.container) === 'object' ? options.container : document.body;\n }\n /**\n * Adds a click event listener to the passed trigger.\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n */\n\n }, {\n key: \"listenClick\",\n value: function listenClick(trigger) {\n var _this2 = this;\n\n this.listener = listen_default()(trigger, 'click', function (e) {\n return _this2.onClick(e);\n });\n }\n /**\n * Defines a new `ClipboardAction` on each click event.\n * @param {Event} e\n */\n\n }, {\n key: \"onClick\",\n value: function onClick(e) {\n var trigger = e.delegateTarget || e.currentTarget;\n var action = this.action(trigger) || 'copy';\n var text = actions_default({\n action: action,\n container: this.container,\n target: this.target(trigger),\n text: this.text(trigger)\n }); // Fires an event based on the copy operation result.\n\n this.emit(text ? 'success' : 'error', {\n action: action,\n text: text,\n trigger: trigger,\n clearSelection: function clearSelection() {\n if (trigger) {\n trigger.focus();\n }\n\n window.getSelection().removeAllRanges();\n }\n });\n }\n /**\n * Default `action` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultAction\",\n value: function defaultAction(trigger) {\n return getAttributeValue('action', trigger);\n }\n /**\n * Default `target` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultTarget\",\n value: function defaultTarget(trigger) {\n var selector = getAttributeValue('target', trigger);\n\n if (selector) {\n return document.querySelector(selector);\n }\n }\n /**\n * Allow fire programmatically a copy action\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @returns Text copied.\n */\n\n }, {\n key: \"defaultText\",\n\n /**\n * Default `text` lookup function.\n * @param {Element} trigger\n */\n value: function defaultText(trigger) {\n return getAttributeValue('text', trigger);\n }\n /**\n * Destroy lifecycle.\n */\n\n }, {\n key: \"destroy\",\n value: function destroy() {\n this.listener.destroy();\n }\n }], [{\n key: \"copy\",\n value: function copy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n return actions_copy(target, options);\n }\n /**\n * Allow fire programmatically a cut action\n * @param {String|HTMLElement} target\n * @returns Text cutted.\n */\n\n }, {\n key: \"cut\",\n value: function cut(target) {\n return actions_cut(target);\n }\n /**\n * Returns the support of the given action, or all actions if no action is\n * given.\n * @param {String} [action]\n */\n\n }, {\n key: \"isSupported\",\n value: function isSupported() {\n var action = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : ['copy', 'cut'];\n var actions = typeof action === 'string' ? [action] : action;\n var support = !!document.queryCommandSupported;\n actions.forEach(function (action) {\n support = support && !!document.queryCommandSupported(action);\n });\n return support;\n }\n }]);\n\n return Clipboard;\n}((tiny_emitter_default()));\n\n/* harmony default export */ var clipboard = (Clipboard);\n\n/***/ }),\n\n/***/ 828:\n/***/ (function(module) {\n\nvar DOCUMENT_NODE_TYPE = 9;\n\n/**\n * A polyfill for Element.matches()\n */\nif (typeof Element !== 'undefined' && !Element.prototype.matches) {\n var proto = Element.prototype;\n\n proto.matches = proto.matchesSelector ||\n proto.mozMatchesSelector ||\n proto.msMatchesSelector ||\n proto.oMatchesSelector ||\n proto.webkitMatchesSelector;\n}\n\n/**\n * Finds the closest parent that matches a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @return {Function}\n */\nfunction closest (element, selector) {\n while (element && element.nodeType !== DOCUMENT_NODE_TYPE) {\n if (typeof element.matches === 'function' &&\n element.matches(selector)) {\n return element;\n }\n element = element.parentNode;\n }\n}\n\nmodule.exports = closest;\n\n\n/***/ }),\n\n/***/ 438:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar closest = __webpack_require__(828);\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction _delegate(element, selector, type, callback, useCapture) {\n var listenerFn = listener.apply(this, arguments);\n\n element.addEventListener(type, listenerFn, useCapture);\n\n return {\n destroy: function() {\n element.removeEventListener(type, listenerFn, useCapture);\n }\n }\n}\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element|String|Array} [elements]\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction delegate(elements, selector, type, callback, useCapture) {\n // Handle the regular Element usage\n if (typeof elements.addEventListener === 'function') {\n return _delegate.apply(null, arguments);\n }\n\n // Handle Element-less usage, it defaults to global delegation\n if (typeof type === 'function') {\n // Use `document` as the first parameter, then apply arguments\n // This is a short way to .unshift `arguments` without running into deoptimizations\n return _delegate.bind(null, document).apply(null, arguments);\n }\n\n // Handle Selector-based usage\n if (typeof elements === 'string') {\n elements = document.querySelectorAll(elements);\n }\n\n // Handle Array-like based usage\n return Array.prototype.map.call(elements, function (element) {\n return _delegate(element, selector, type, callback, useCapture);\n });\n}\n\n/**\n * Finds closest match and invokes callback.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Function}\n */\nfunction listener(element, selector, type, callback) {\n return function(e) {\n e.delegateTarget = closest(e.target, selector);\n\n if (e.delegateTarget) {\n callback.call(element, e);\n }\n }\n}\n\nmodule.exports = delegate;\n\n\n/***/ }),\n\n/***/ 879:\n/***/ (function(__unused_webpack_module, exports) {\n\n/**\n * Check if argument is a HTML element.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.node = function(value) {\n return value !== undefined\n && value instanceof HTMLElement\n && value.nodeType === 1;\n};\n\n/**\n * Check if argument is a list of HTML elements.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.nodeList = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return value !== undefined\n && (type === '[object NodeList]' || type === '[object HTMLCollection]')\n && ('length' in value)\n && (value.length === 0 || exports.node(value[0]));\n};\n\n/**\n * Check if argument is a string.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.string = function(value) {\n return typeof value === 'string'\n || value instanceof String;\n};\n\n/**\n * Check if argument is a function.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.fn = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return type === '[object Function]';\n};\n\n\n/***/ }),\n\n/***/ 370:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar is = __webpack_require__(879);\nvar delegate = __webpack_require__(438);\n\n/**\n * Validates all params and calls the right\n * listener function based on its target type.\n *\n * @param {String|HTMLElement|HTMLCollection|NodeList} target\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listen(target, type, callback) {\n if (!target && !type && !callback) {\n throw new Error('Missing required arguments');\n }\n\n if (!is.string(type)) {\n throw new TypeError('Second argument must be a String');\n }\n\n if (!is.fn(callback)) {\n throw new TypeError('Third argument must be a Function');\n }\n\n if (is.node(target)) {\n return listenNode(target, type, callback);\n }\n else if (is.nodeList(target)) {\n return listenNodeList(target, type, callback);\n }\n else if (is.string(target)) {\n return listenSelector(target, type, callback);\n }\n else {\n throw new TypeError('First argument must be a String, HTMLElement, HTMLCollection, or NodeList');\n }\n}\n\n/**\n * Adds an event listener to a HTML element\n * and returns a remove listener function.\n *\n * @param {HTMLElement} node\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNode(node, type, callback) {\n node.addEventListener(type, callback);\n\n return {\n destroy: function() {\n node.removeEventListener(type, callback);\n }\n }\n}\n\n/**\n * Add an event listener to a list of HTML elements\n * and returns a remove listener function.\n *\n * @param {NodeList|HTMLCollection} nodeList\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNodeList(nodeList, type, callback) {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.addEventListener(type, callback);\n });\n\n return {\n destroy: function() {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.removeEventListener(type, callback);\n });\n }\n }\n}\n\n/**\n * Add an event listener to a selector\n * and returns a remove listener function.\n *\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenSelector(selector, type, callback) {\n return delegate(document.body, selector, type, callback);\n}\n\nmodule.exports = listen;\n\n\n/***/ }),\n\n/***/ 817:\n/***/ (function(module) {\n\nfunction select(element) {\n var selectedText;\n\n if (element.nodeName === 'SELECT') {\n element.focus();\n\n selectedText = element.value;\n }\n else if (element.nodeName === 'INPUT' || element.nodeName === 'TEXTAREA') {\n var isReadOnly = element.hasAttribute('readonly');\n\n if (!isReadOnly) {\n element.setAttribute('readonly', '');\n }\n\n element.select();\n element.setSelectionRange(0, element.value.length);\n\n if (!isReadOnly) {\n element.removeAttribute('readonly');\n }\n\n selectedText = element.value;\n }\n else {\n if (element.hasAttribute('contenteditable')) {\n element.focus();\n }\n\n var selection = window.getSelection();\n var range = document.createRange();\n\n range.selectNodeContents(element);\n selection.removeAllRanges();\n selection.addRange(range);\n\n selectedText = selection.toString();\n }\n\n return selectedText;\n}\n\nmodule.exports = select;\n\n\n/***/ }),\n\n/***/ 279:\n/***/ (function(module) {\n\nfunction E () {\n // Keep this empty so it's easier to inherit from\n // (via https://github.com/lipsmack from 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liveEvents.push(evts[i]);\n }\n }\n\n // Remove event from queue to prevent memory leak\n // Suggested by https://github.com/lazd\n // Ref: https://github.com/scottcorgan/tiny-emitter/commit/c6ebfaa9bc973b33d110a84a307742b7cf94c953#commitcomment-5024910\n\n (liveEvents.length)\n ? e[name] = liveEvents\n : delete e[name];\n\n return this;\n }\n};\n\nmodule.exports = E;\nmodule.exports.TinyEmitter = E;\n\n\n/***/ })\n\n/******/ \t});\n/************************************************************************/\n/******/ \t// The module cache\n/******/ \tvar __webpack_module_cache__ = {};\n/******/ \t\n/******/ \t// The require function\n/******/ \tfunction __webpack_require__(moduleId) {\n/******/ \t\t// Check if module is in cache\n/******/ \t\tif(__webpack_module_cache__[moduleId]) {\n/******/ \t\t\treturn __webpack_module_cache__[moduleId].exports;\n/******/ \t\t}\n/******/ \t\t// Create a new module (and put it into the cache)\n/******/ \t\tvar module = __webpack_module_cache__[moduleId] = {\n/******/ \t\t\t// no module.id needed\n/******/ \t\t\t// no module.loaded needed\n/******/ \t\t\texports: {}\n/******/ \t\t};\n/******/ \t\n/******/ \t\t// Execute the module function\n/******/ \t\t__webpack_modules__[moduleId](module, module.exports, __webpack_require__);\n/******/ \t\n/******/ \t\t// Return the exports of the module\n/******/ \t\treturn module.exports;\n/******/ \t}\n/******/ \t\n/************************************************************************/\n/******/ \t/* webpack/runtime/compat get default export */\n/******/ \t!function() {\n/******/ \t\t// getDefaultExport function for compatibility with non-harmony modules\n/******/ \t\t__webpack_require__.n = function(module) {\n/******/ \t\t\tvar getter = module && module.__esModule ?\n/******/ \t\t\t\tfunction() { return module['default']; } :\n/******/ \t\t\t\tfunction() { return module; };\n/******/ \t\t\t__webpack_require__.d(getter, { a: getter });\n/******/ \t\t\treturn getter;\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/define property getters */\n/******/ \t!function() {\n/******/ \t\t// define getter functions for harmony exports\n/******/ \t\t__webpack_require__.d = function(exports, definition) {\n/******/ \t\t\tfor(var key in definition) {\n/******/ \t\t\t\tif(__webpack_require__.o(definition, key) && !__webpack_require__.o(exports, key)) {\n/******/ \t\t\t\t\tObject.defineProperty(exports, key, { enumerable: true, get: definition[key] });\n/******/ \t\t\t\t}\n/******/ \t\t\t}\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/hasOwnProperty shorthand */\n/******/ \t!function() {\n/******/ \t\t__webpack_require__.o = function(obj, prop) { return Object.prototype.hasOwnProperty.call(obj, prop); }\n/******/ \t}();\n/******/ \t\n/************************************************************************/\n/******/ \t// module exports must be returned from runtime so entry inlining is disabled\n/******/ \t// startup\n/******/ \t// Load entry module and return exports\n/******/ \treturn __webpack_require__(686);\n/******/ })()\n.default;\n});", "/*!\n * escape-html\n * Copyright(c) 2012-2013 TJ Holowaychuk\n * Copyright(c) 2015 Andreas Lubbe\n * Copyright(c) 2015 Tiancheng \"Timothy\" Gu\n * MIT Licensed\n */\n\n'use strict';\n\n/**\n * Module variables.\n * @private\n */\n\nvar matchHtmlRegExp = /[\"'&<>]/;\n\n/**\n * Module exports.\n * @public\n */\n\nmodule.exports = escapeHtml;\n\n/**\n * Escape special characters in the given string of html.\n *\n * @param {string} string The string to escape for inserting into HTML\n * @return {string}\n * @public\n */\n\nfunction escapeHtml(string) {\n var str = '' + string;\n var match = matchHtmlRegExp.exec(str);\n\n if (!match) {\n return str;\n }\n\n var escape;\n var html = '';\n var index = 0;\n var lastIndex = 0;\n\n for (index = match.index; index < str.length; index++) {\n switch (str.charCodeAt(index)) {\n case 34: // \"\n escape = '"';\n break;\n case 38: // &\n escape = '&';\n break;\n case 39: // '\n escape = ''';\n break;\n case 60: // <\n escape = '<';\n break;\n case 62: // >\n escape = '>';\n break;\n default:\n continue;\n }\n\n if (lastIndex !== index) {\n html += str.substring(lastIndex, index);\n }\n\n lastIndex = index + 1;\n html += escape;\n }\n\n return lastIndex !== index\n ? html + str.substring(lastIndex, index)\n : html;\n}\n", "/*\n * Copyright (c) 2016-2024 Martin Donath \n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport \"focus-visible\"\n\nimport {\n EMPTY,\n NEVER,\n Observable,\n Subject,\n defer,\n delay,\n filter,\n map,\n merge,\n mergeWith,\n shareReplay,\n switchMap\n} from \"rxjs\"\n\nimport { configuration, feature } from \"./_\"\nimport {\n at,\n getActiveElement,\n getOptionalElement,\n requestJSON,\n setLocation,\n setToggle,\n watchDocument,\n watchKeyboard,\n watchLocation,\n watchLocationTarget,\n watchMedia,\n watchPrint,\n watchScript,\n watchViewport\n} from \"./browser\"\nimport {\n getComponentElement,\n getComponentElements,\n mountAnnounce,\n mountBackToTop,\n mountConsent,\n mountContent,\n mountDialog,\n mountHeader,\n mountHeaderTitle,\n mountPalette,\n mountProgress,\n mountSearch,\n mountSearchHiglight,\n mountSidebar,\n mountSource,\n mountTableOfContents,\n mountTabs,\n watchHeader,\n watchMain\n} from \"./components\"\nimport {\n SearchIndex,\n setupClipboardJS,\n setupInstantNavigation,\n setupVersionSelector\n} from \"./integrations\"\nimport {\n patchEllipsis,\n patchIndeterminate,\n patchScrollfix,\n patchScrolllock\n} from \"./patches\"\nimport \"./polyfills\"\n\n/* ----------------------------------------------------------------------------\n * Functions - @todo refactor\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch search index\n *\n * @returns Search index observable\n */\nfunction fetchSearchIndex(): Observable {\n if (location.protocol === \"file:\") {\n return watchScript(\n `${new URL(\"search/search_index.js\", config.base)}`\n )\n .pipe(\n // @ts-ignore - @todo fix typings\n map(() => __index),\n shareReplay(1)\n )\n } else {\n return requestJSON(\n new URL(\"search/search_index.json\", config.base)\n )\n }\n}\n\n/* ----------------------------------------------------------------------------\n * Application\n * ------------------------------------------------------------------------- */\n\n/* Yay, JavaScript is available */\ndocument.documentElement.classList.remove(\"no-js\")\ndocument.documentElement.classList.add(\"js\")\n\n/* Set up navigation observables and subjects */\nconst document$ = watchDocument()\nconst location$ = watchLocation()\nconst target$ = watchLocationTarget(location$)\nconst keyboard$ = watchKeyboard()\n\n/* Set up media observables */\nconst viewport$ = watchViewport()\nconst tablet$ = watchMedia(\"(min-width: 960px)\")\nconst screen$ = watchMedia(\"(min-width: 1220px)\")\nconst print$ = watchPrint()\n\n/* Retrieve search index, if search is enabled */\nconst config = configuration()\nconst index$ = document.forms.namedItem(\"search\")\n ? fetchSearchIndex()\n : NEVER\n\n/* Set up Clipboard.js integration */\nconst alert$ = new Subject()\nsetupClipboardJS({ alert$ })\n\n/* Set up progress indicator */\nconst progress$ = new Subject()\n\n/* Set up instant navigation, if enabled */\nif (feature(\"navigation.instant\"))\n setupInstantNavigation({ location$, viewport$, progress$ })\n .subscribe(document$)\n\n/* Set up version selector */\nif (config.version?.provider === \"mike\")\n setupVersionSelector({ document$ })\n\n/* Always close drawer and search on navigation */\nmerge(location$, target$)\n .pipe(\n delay(125)\n )\n .subscribe(() => {\n setToggle(\"drawer\", false)\n setToggle(\"search\", false)\n })\n\n/* Set up global keyboard handlers */\nkeyboard$\n .pipe(\n filter(({ mode }) => mode === \"global\")\n )\n .subscribe(key => {\n switch (key.type) {\n\n /* Go to previous page */\n case \"p\":\n case \",\":\n const prev = getOptionalElement(\"link[rel=prev]\")\n if (typeof prev !== \"undefined\")\n setLocation(prev)\n break\n\n /* Go to next page */\n case \"n\":\n case \".\":\n const next = getOptionalElement(\"link[rel=next]\")\n if (typeof next !== \"undefined\")\n setLocation(next)\n break\n\n /* Expand navigation, see https://bit.ly/3ZjG5io */\n case \"Enter\":\n const active = getActiveElement()\n if (active instanceof HTMLLabelElement)\n active.click()\n }\n })\n\n/* Set up patches */\npatchEllipsis({ viewport$, document$ })\npatchIndeterminate({ document$, tablet$ })\npatchScrollfix({ document$ })\npatchScrolllock({ viewport$, tablet$ })\n\n/* Set up header and main area observable */\nconst header$ = watchHeader(getComponentElement(\"header\"), { viewport$ })\nconst main$ = document$\n .pipe(\n map(() => getComponentElement(\"main\")),\n switchMap(el => watchMain(el, { viewport$, header$ })),\n shareReplay(1)\n )\n\n/* Set up control component observables */\nconst control$ = merge(\n\n /* Consent */\n ...getComponentElements(\"consent\")\n .map(el => mountConsent(el, { target$ })),\n\n /* Dialog */\n ...getComponentElements(\"dialog\")\n .map(el => mountDialog(el, { alert$ })),\n\n /* Header */\n ...getComponentElements(\"header\")\n .map(el => mountHeader(el, { viewport$, header$, main$ })),\n\n /* Color palette */\n ...getComponentElements(\"palette\")\n .map(el => mountPalette(el)),\n\n /* Progress bar */\n ...getComponentElements(\"progress\")\n .map(el => mountProgress(el, { progress$ })),\n\n /* Search */\n ...getComponentElements(\"search\")\n .map(el => mountSearch(el, { index$, keyboard$ })),\n\n /* Repository information */\n ...getComponentElements(\"source\")\n .map(el => mountSource(el))\n)\n\n/* Set up content component observables */\nconst content$ = defer(() => merge(\n\n /* Announcement bar */\n ...getComponentElements(\"announce\")\n .map(el => mountAnnounce(el)),\n\n /* Content */\n ...getComponentElements(\"content\")\n .map(el => mountContent(el, { viewport$, target$, print$ })),\n\n /* Search highlighting */\n ...getComponentElements(\"content\")\n .map(el => feature(\"search.highlight\")\n ? mountSearchHiglight(el, { index$, location$ })\n : EMPTY\n ),\n\n /* Header title */\n ...getComponentElements(\"header-title\")\n .map(el => mountHeaderTitle(el, { viewport$, header$ })),\n\n /* Sidebar */\n ...getComponentElements(\"sidebar\")\n .map(el => el.getAttribute(\"data-md-type\") === \"navigation\"\n ? at(screen$, () => mountSidebar(el, { viewport$, header$, main$ }))\n : at(tablet$, () => mountSidebar(el, { viewport$, header$, main$ }))\n ),\n\n /* Navigation tabs */\n ...getComponentElements(\"tabs\")\n .map(el => mountTabs(el, { viewport$, header$ })),\n\n /* Table of contents */\n ...getComponentElements(\"toc\")\n .map(el => mountTableOfContents(el, {\n viewport$, header$, main$, target$\n })),\n\n /* Back-to-top button */\n ...getComponentElements(\"top\")\n .map(el => mountBackToTop(el, { viewport$, header$, main$, target$ }))\n))\n\n/* Set up component observables */\nconst component$ = document$\n .pipe(\n switchMap(() => content$),\n mergeWith(control$),\n shareReplay(1)\n )\n\n/* Subscribe to all components */\ncomponent$.subscribe()\n\n/* ----------------------------------------------------------------------------\n * Exports\n * ------------------------------------------------------------------------- */\n\nwindow.document$ = document$ /* Document observable */\nwindow.location$ = location$ /* Location subject */\nwindow.target$ = target$ /* Location target observable */\nwindow.keyboard$ = keyboard$ /* Keyboard observable */\nwindow.viewport$ = viewport$ /* Viewport observable */\nwindow.tablet$ = tablet$ /* Media tablet observable */\nwindow.screen$ = screen$ /* Media screen observable */\nwindow.print$ = print$ /* Media print observable */\nwindow.alert$ = alert$ /* Alert subject */\nwindow.progress$ = progress$ /* Progress indicator subject */\nwindow.component$ = component$ /* Component observable */\n", "/*! *****************************************************************************\r\nCopyright (c) Microsoft Corporation.\r\n\r\nPermission to use, copy, modify, and/or distribute this software for any\r\npurpose with or without fee is hereby granted.\r\n\r\nTHE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\r\nREGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\r\nAND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\r\nINDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\r\nLOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\r\nOTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\r\nPERFORMANCE OF THIS SOFTWARE.\r\n***************************************************************************** */\r\n/* global Reflect, Promise */\r\n\r\nvar extendStatics = function(d, b) {\r\n extendStatics = Object.setPrototypeOf ||\r\n ({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||\r\n function (d, b) { for (var p in b) if (Object.prototype.hasOwnProperty.call(b, p)) d[p] = b[p]; };\r\n return extendStatics(d, b);\r\n};\r\n\r\nexport function __extends(d, b) {\r\n if (typeof b !== \"function\" && b !== null)\r\n throw new TypeError(\"Class extends value \" + String(b) + \" is not a constructor or null\");\r\n extendStatics(d, b);\r\n function __() { this.constructor = d; }\r\n d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());\r\n}\r\n\r\nexport var __assign = function() {\r\n __assign = Object.assign || function __assign(t) {\r\n for (var s, i = 1, n = arguments.length; i < n; i++) {\r\n s = arguments[i];\r\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p)) t[p] = s[p];\r\n }\r\n return t;\r\n }\r\n return __assign.apply(this, arguments);\r\n}\r\n\r\nexport function __rest(s, e) {\r\n var t = {};\r\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)\r\n t[p] = s[p];\r\n if (s != null && typeof Object.getOwnPropertySymbols === \"function\")\r\n for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {\r\n if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))\r\n t[p[i]] = s[p[i]];\r\n }\r\n return t;\r\n}\r\n\r\nexport function __decorate(decorators, target, key, desc) {\r\n var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;\r\n if (typeof Reflect === \"object\" && typeof Reflect.decorate === \"function\") r = Reflect.decorate(decorators, target, key, desc);\r\n else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;\r\n return c > 3 && r && Object.defineProperty(target, key, r), r;\r\n}\r\n\r\nexport function __param(paramIndex, decorator) {\r\n return function (target, key) { decorator(target, key, paramIndex); }\r\n}\r\n\r\nexport function __metadata(metadataKey, metadataValue) {\r\n if (typeof Reflect === \"object\" && typeof Reflect.metadata === \"function\") return Reflect.metadata(metadataKey, metadataValue);\r\n}\r\n\r\nexport function __awaiter(thisArg, _arguments, P, generator) {\r\n function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }\r\n return new (P || (P = Promise))(function (resolve, reject) {\r\n function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }\r\n function rejected(value) { try { step(generator[\"throw\"](value)); } catch (e) { reject(e); } }\r\n function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }\r\n step((generator = generator.apply(thisArg, _arguments || [])).next());\r\n });\r\n}\r\n\r\nexport function __generator(thisArg, body) {\r\n var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g;\r\n return g = { next: verb(0), \"throw\": verb(1), \"return\": verb(2) }, typeof Symbol === \"function\" && (g[Symbol.iterator] = function() { return this; }), g;\r\n function verb(n) { return function (v) { return step([n, v]); }; }\r\n function step(op) {\r\n if (f) throw new TypeError(\"Generator is already executing.\");\r\n while (_) try {\r\n if (f = 1, y && (t = op[0] & 2 ? y[\"return\"] : op[0] ? y[\"throw\"] || ((t = y[\"return\"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;\r\n if (y = 0, t) op = [op[0] & 2, t.value];\r\n switch (op[0]) {\r\n case 0: case 1: t = op; break;\r\n case 4: _.label++; return { value: op[1], done: false };\r\n case 5: _.label++; y = op[1]; op = [0]; continue;\r\n case 7: op = _.ops.pop(); _.trys.pop(); continue;\r\n default:\r\n if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }\r\n if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }\r\n if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }\r\n if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }\r\n if (t[2]) _.ops.pop();\r\n _.trys.pop(); continue;\r\n }\r\n op = body.call(thisArg, _);\r\n } catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }\r\n if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };\r\n }\r\n}\r\n\r\nexport var __createBinding = Object.create ? (function(o, m, k, k2) {\r\n if (k2 === undefined) k2 = k;\r\n Object.defineProperty(o, k2, { enumerable: true, get: function() { return m[k]; } });\r\n}) : (function(o, m, k, k2) {\r\n if (k2 === undefined) k2 = k;\r\n o[k2] = m[k];\r\n});\r\n\r\nexport function __exportStar(m, o) {\r\n for (var p in m) if (p !== \"default\" && !Object.prototype.hasOwnProperty.call(o, p)) __createBinding(o, m, p);\r\n}\r\n\r\nexport function __values(o) {\r\n var s = typeof Symbol === \"function\" && Symbol.iterator, m = s && o[s], i = 0;\r\n if (m) return m.call(o);\r\n if (o && typeof o.length === \"number\") return {\r\n next: function () {\r\n if (o && i >= o.length) o = void 0;\r\n return { value: o && o[i++], done: !o };\r\n }\r\n };\r\n throw new TypeError(s ? \"Object is not iterable.\" : \"Symbol.iterator is not defined.\");\r\n}\r\n\r\nexport function __read(o, n) {\r\n var m = typeof Symbol === \"function\" && o[Symbol.iterator];\r\n if (!m) return o;\r\n var i = m.call(o), r, ar = [], e;\r\n try {\r\n while ((n === void 0 || n-- > 0) && !(r = i.next()).done) ar.push(r.value);\r\n }\r\n catch (error) { e = { error: error }; }\r\n finally {\r\n try {\r\n if (r && !r.done && (m = i[\"return\"])) m.call(i);\r\n }\r\n finally { if (e) throw e.error; }\r\n }\r\n return ar;\r\n}\r\n\r\n/** @deprecated */\r\nexport function __spread() {\r\n for (var ar = [], i = 0; i < arguments.length; i++)\r\n ar = ar.concat(__read(arguments[i]));\r\n return ar;\r\n}\r\n\r\n/** @deprecated */\r\nexport function __spreadArrays() {\r\n for (var s = 0, i = 0, il = arguments.length; i < il; i++) s += arguments[i].length;\r\n for (var r = Array(s), k = 0, i = 0; i < il; i++)\r\n for (var a = arguments[i], j = 0, jl = a.length; j < jl; j++, k++)\r\n r[k] = a[j];\r\n return r;\r\n}\r\n\r\nexport function __spreadArray(to, from, pack) {\r\n if (pack || arguments.length === 2) for (var i = 0, l = from.length, ar; i < l; i++) {\r\n if (ar || !(i in from)) {\r\n if (!ar) ar = Array.prototype.slice.call(from, 0, i);\r\n ar[i] = from[i];\r\n }\r\n }\r\n return to.concat(ar || Array.prototype.slice.call(from));\r\n}\r\n\r\nexport function __await(v) {\r\n return this instanceof __await ? (this.v = v, this) : new __await(v);\r\n}\r\n\r\nexport function __asyncGenerator(thisArg, _arguments, generator) {\r\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\r\n var g = generator.apply(thisArg, _arguments || []), i, q = [];\r\n return i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i;\r\n function verb(n) { if (g[n]) i[n] = function (v) { return new Promise(function (a, b) { q.push([n, v, a, b]) > 1 || resume(n, v); }); }; }\r\n function resume(n, v) { try { step(g[n](v)); } catch (e) { settle(q[0][3], e); } }\r\n function step(r) { r.value instanceof __await ? Promise.resolve(r.value.v).then(fulfill, reject) : settle(q[0][2], r); }\r\n function fulfill(value) { resume(\"next\", value); }\r\n function reject(value) { resume(\"throw\", value); }\r\n function settle(f, v) { if (f(v), q.shift(), q.length) resume(q[0][0], q[0][1]); }\r\n}\r\n\r\nexport function __asyncDelegator(o) {\r\n var i, p;\r\n return i = {}, verb(\"next\"), verb(\"throw\", function (e) { throw e; }), verb(\"return\"), i[Symbol.iterator] = function () { return this; }, i;\r\n function verb(n, f) { i[n] = o[n] ? function (v) { return (p = !p) ? { value: __await(o[n](v)), done: n === \"return\" } : f ? f(v) : v; } : f; }\r\n}\r\n\r\nexport function __asyncValues(o) {\r\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\r\n var m = o[Symbol.asyncIterator], i;\r\n return m ? m.call(o) : (o = typeof __values === \"function\" ? __values(o) : o[Symbol.iterator](), i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i);\r\n function verb(n) { i[n] = o[n] && function (v) { return new Promise(function (resolve, reject) { v = o[n](v), settle(resolve, reject, v.done, v.value); }); }; }\r\n function settle(resolve, reject, d, v) { Promise.resolve(v).then(function(v) { resolve({ value: v, done: d }); }, reject); }\r\n}\r\n\r\nexport function __makeTemplateObject(cooked, raw) {\r\n if (Object.defineProperty) { Object.defineProperty(cooked, \"raw\", { value: raw }); } else { cooked.raw = raw; }\r\n return cooked;\r\n};\r\n\r\nvar __setModuleDefault = Object.create ? (function(o, v) {\r\n Object.defineProperty(o, \"default\", { enumerable: true, value: v });\r\n}) : function(o, v) {\r\n o[\"default\"] = v;\r\n};\r\n\r\nexport function __importStar(mod) {\r\n if (mod && mod.__esModule) return mod;\r\n var result = {};\r\n if (mod != null) for (var k in mod) if (k !== \"default\" && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);\r\n __setModuleDefault(result, mod);\r\n return result;\r\n}\r\n\r\nexport function __importDefault(mod) {\r\n return (mod && mod.__esModule) ? mod : { default: mod };\r\n}\r\n\r\nexport function __classPrivateFieldGet(receiver, state, kind, f) {\r\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a getter\");\r\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot read private member from an object whose class did not declare it\");\r\n return kind === \"m\" ? f : kind === \"a\" ? f.call(receiver) : f ? f.value : state.get(receiver);\r\n}\r\n\r\nexport function __classPrivateFieldSet(receiver, state, value, kind, f) {\r\n if (kind === \"m\") throw new TypeError(\"Private method is not writable\");\r\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a setter\");\r\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot write private member to an object whose class did not declare it\");\r\n return (kind === \"a\" ? f.call(receiver, value) : f ? f.value = value : state.set(receiver, value)), value;\r\n}\r\n", "/**\n * Returns true if the object is a function.\n * @param value The value to check\n */\nexport function isFunction(value: any): value is (...args: any[]) => any {\n return typeof value === 'function';\n}\n", "/**\n * Used to create Error subclasses until the community moves away from ES5.\n *\n * This is because compiling from TypeScript down to ES5 has issues with subclassing Errors\n * as well as other built-in types: https://github.com/Microsoft/TypeScript/issues/12123\n *\n * @param createImpl A factory function to create the actual constructor implementation. The returned\n * function should be a named function that calls `_super` internally.\n */\nexport function createErrorClass(createImpl: (_super: any) => any): T {\n const _super = (instance: any) => {\n Error.call(instance);\n instance.stack = new Error().stack;\n };\n\n const ctorFunc = createImpl(_super);\n ctorFunc.prototype = Object.create(Error.prototype);\n ctorFunc.prototype.constructor = ctorFunc;\n return ctorFunc;\n}\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface UnsubscriptionError extends Error {\n readonly errors: any[];\n}\n\nexport interface UnsubscriptionErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (errors: any[]): UnsubscriptionError;\n}\n\n/**\n * An error thrown when one or more errors have occurred during the\n * `unsubscribe` of a {@link Subscription}.\n */\nexport const UnsubscriptionError: UnsubscriptionErrorCtor = createErrorClass(\n (_super) =>\n function UnsubscriptionErrorImpl(this: any, errors: (Error | string)[]) {\n _super(this);\n this.message = errors\n ? `${errors.length} errors occurred during unsubscription:\n${errors.map((err, i) => `${i + 1}) ${err.toString()}`).join('\\n ')}`\n : '';\n this.name = 'UnsubscriptionError';\n this.errors = errors;\n }\n);\n", "/**\n * Removes an item from an array, mutating it.\n * @param arr The array to remove the item from\n * @param item The item to remove\n */\nexport function arrRemove(arr: T[] | undefined | null, item: T) {\n if (arr) {\n const index = arr.indexOf(item);\n 0 <= index && arr.splice(index, 1);\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { UnsubscriptionError } from './util/UnsubscriptionError';\nimport { SubscriptionLike, TeardownLogic, Unsubscribable } from './types';\nimport { arrRemove } from './util/arrRemove';\n\n/**\n * Represents a disposable resource, such as the execution of an Observable. A\n * Subscription has one important method, `unsubscribe`, that takes no argument\n * and just disposes the resource held by the subscription.\n *\n * Additionally, subscriptions may be grouped together through the `add()`\n * method, which will attach a child Subscription to the current Subscription.\n * When a Subscription is unsubscribed, all its children (and its grandchildren)\n * will be unsubscribed as well.\n *\n * @class Subscription\n */\nexport class Subscription implements SubscriptionLike {\n /** @nocollapse */\n public static EMPTY = (() => {\n const empty = new Subscription();\n empty.closed = true;\n return empty;\n })();\n\n /**\n * A flag to indicate whether this Subscription has already been unsubscribed.\n */\n public closed = false;\n\n private _parentage: Subscription[] | Subscription | null = null;\n\n /**\n * The list of registered finalizers to execute upon unsubscription. Adding and removing from this\n * list occurs in the {@link #add} and {@link #remove} methods.\n */\n private _finalizers: Exclude[] | null = null;\n\n /**\n * @param initialTeardown A function executed first as part of the finalization\n * process that is kicked off when {@link #unsubscribe} is called.\n */\n constructor(private initialTeardown?: () => void) {}\n\n /**\n * Disposes the resources held by the subscription. May, for instance, cancel\n * an ongoing Observable execution or cancel any other type of work that\n * started when the Subscription was created.\n * @return {void}\n */\n unsubscribe(): void {\n let errors: any[] | undefined;\n\n if (!this.closed) {\n this.closed = true;\n\n // Remove this from it's parents.\n const { _parentage } = this;\n if (_parentage) {\n this._parentage = null;\n if (Array.isArray(_parentage)) {\n for (const parent of _parentage) {\n parent.remove(this);\n }\n } else {\n _parentage.remove(this);\n }\n }\n\n const { initialTeardown: initialFinalizer } = this;\n if (isFunction(initialFinalizer)) {\n try {\n initialFinalizer();\n } catch (e) {\n errors = e instanceof UnsubscriptionError ? e.errors : [e];\n }\n }\n\n const { _finalizers } = this;\n if (_finalizers) {\n this._finalizers = null;\n for (const finalizer of _finalizers) {\n try {\n execFinalizer(finalizer);\n } catch (err) {\n errors = errors ?? [];\n if (err instanceof UnsubscriptionError) {\n errors = [...errors, ...err.errors];\n } else {\n errors.push(err);\n }\n }\n }\n }\n\n if (errors) {\n throw new UnsubscriptionError(errors);\n }\n }\n }\n\n /**\n * Adds a finalizer to this subscription, so that finalization will be unsubscribed/called\n * when this subscription is unsubscribed. If this subscription is already {@link #closed},\n * because it has already been unsubscribed, then whatever finalizer is passed to it\n * will automatically be executed (unless the finalizer itself is also a closed subscription).\n *\n * Closed Subscriptions cannot be added as finalizers to any subscription. Adding a closed\n * subscription to a any subscription will result in no operation. (A noop).\n *\n * Adding a subscription to itself, or adding `null` or `undefined` will not perform any\n * operation at all. (A noop).\n *\n * `Subscription` instances that are added to this instance will automatically remove themselves\n * if they are unsubscribed. Functions and {@link Unsubscribable} objects that you wish to remove\n * will need to be removed manually with {@link #remove}\n *\n * @param teardown The finalization logic to add to this subscription.\n */\n add(teardown: TeardownLogic): void {\n // Only add the finalizer if it's not undefined\n // and don't add a subscription to itself.\n if (teardown && teardown !== this) {\n if (this.closed) {\n // If this subscription is already closed,\n // execute whatever finalizer is handed to it automatically.\n execFinalizer(teardown);\n } else {\n if (teardown instanceof Subscription) {\n // We don't add closed subscriptions, and we don't add the same subscription\n // twice. Subscription unsubscribe is idempotent.\n if (teardown.closed || teardown._hasParent(this)) {\n return;\n }\n teardown._addParent(this);\n }\n (this._finalizers = this._finalizers ?? []).push(teardown);\n }\n }\n }\n\n /**\n * Checks to see if a this subscription already has a particular parent.\n * This will signal that this subscription has already been added to the parent in question.\n * @param parent the parent to check for\n */\n private _hasParent(parent: Subscription) {\n const { _parentage } = this;\n return _parentage === parent || (Array.isArray(_parentage) && _parentage.includes(parent));\n }\n\n /**\n * Adds a parent to this subscription so it can be removed from the parent if it\n * unsubscribes on it's own.\n *\n * NOTE: THIS ASSUMES THAT {@link _hasParent} HAS ALREADY BEEN CHECKED.\n * @param parent The parent subscription to add\n */\n private _addParent(parent: Subscription) {\n const { _parentage } = this;\n this._parentage = Array.isArray(_parentage) ? (_parentage.push(parent), _parentage) : _parentage ? [_parentage, parent] : parent;\n }\n\n /**\n * Called on a child when it is removed via {@link #remove}.\n * @param parent The parent to remove\n */\n private _removeParent(parent: Subscription) {\n const { _parentage } = this;\n if (_parentage === parent) {\n this._parentage = null;\n } else if (Array.isArray(_parentage)) {\n arrRemove(_parentage, parent);\n }\n }\n\n /**\n * Removes a finalizer from this subscription that was previously added with the {@link #add} method.\n *\n * Note that `Subscription` instances, when unsubscribed, will automatically remove themselves\n * from every other `Subscription` they have been added to. This means that using the `remove` method\n * is not a common thing and should be used thoughtfully.\n *\n * If you add the same finalizer instance of a function or an unsubscribable object to a `Subscription` instance\n * more than once, you will need to call `remove` the same number of times to remove all instances.\n *\n * All finalizer instances are removed to free up memory upon unsubscription.\n *\n * @param teardown The finalizer to remove from this subscription\n */\n remove(teardown: Exclude): void {\n const { _finalizers } = this;\n _finalizers && arrRemove(_finalizers, teardown);\n\n if (teardown instanceof Subscription) {\n teardown._removeParent(this);\n }\n }\n}\n\nexport const EMPTY_SUBSCRIPTION = Subscription.EMPTY;\n\nexport function isSubscription(value: any): value is Subscription {\n return (\n value instanceof Subscription ||\n (value && 'closed' in value && isFunction(value.remove) && isFunction(value.add) && isFunction(value.unsubscribe))\n );\n}\n\nfunction execFinalizer(finalizer: Unsubscribable | (() => void)) {\n if (isFunction(finalizer)) {\n finalizer();\n } else {\n finalizer.unsubscribe();\n }\n}\n", "import { Subscriber } from './Subscriber';\nimport { ObservableNotification } from './types';\n\n/**\n * The {@link GlobalConfig} object for RxJS. It is used to configure things\n * like how to react on unhandled errors.\n */\nexport const config: GlobalConfig = {\n onUnhandledError: null,\n onStoppedNotification: null,\n Promise: undefined,\n useDeprecatedSynchronousErrorHandling: false,\n useDeprecatedNextContext: false,\n};\n\n/**\n * The global configuration object for RxJS, used to configure things\n * like how to react on unhandled errors. Accessible via {@link config}\n * object.\n */\nexport interface GlobalConfig {\n /**\n * A registration point for unhandled errors from RxJS. These are errors that\n * cannot were not handled by consuming code in the usual subscription path. For\n * example, if you have this configured, and you subscribe to an observable without\n * providing an error handler, errors from that subscription will end up here. This\n * will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onUnhandledError: ((err: any) => void) | null;\n\n /**\n * A registration point for notifications that cannot be sent to subscribers because they\n * have completed, errored or have been explicitly unsubscribed. By default, next, complete\n * and error notifications sent to stopped subscribers are noops. However, sometimes callers\n * might want a different behavior. For example, with sources that attempt to report errors\n * to stopped subscribers, a caller can configure RxJS to throw an unhandled error instead.\n * This will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onStoppedNotification: ((notification: ObservableNotification, subscriber: Subscriber) => void) | null;\n\n /**\n * The promise constructor used by default for {@link Observable#toPromise toPromise} and {@link Observable#forEach forEach}\n * methods.\n *\n * @deprecated As of version 8, RxJS will no longer support this sort of injection of a\n * Promise constructor. If you need a Promise implementation other than native promises,\n * please polyfill/patch Promise as you see appropriate. Will be removed in v8.\n */\n Promise?: PromiseConstructorLike;\n\n /**\n * If true, turns on synchronous error rethrowing, which is a deprecated behavior\n * in v6 and higher. This behavior enables bad patterns like wrapping a subscribe\n * call in a try/catch block. It also enables producer interference, a nasty bug\n * where a multicast can be broken for all observers by a downstream consumer with\n * an unhandled error. DO NOT USE THIS FLAG UNLESS IT'S NEEDED TO BUY TIME\n * FOR MIGRATION REASONS.\n *\n * @deprecated As of version 8, RxJS will no longer support synchronous throwing\n * of unhandled errors. All errors will be thrown on a separate call stack to prevent bad\n * behaviors described above. Will be removed in v8.\n */\n useDeprecatedSynchronousErrorHandling: boolean;\n\n /**\n * If true, enables an as-of-yet undocumented feature from v5: The ability to access\n * `unsubscribe()` via `this` context in `next` functions created in observers passed\n * to `subscribe`.\n *\n * This is being removed because the performance was severely problematic, and it could also cause\n * issues when types other than POJOs are passed to subscribe as subscribers, as they will likely have\n * their `this` context overwritten.\n *\n * @deprecated As of version 8, RxJS will no longer support altering the\n * context of next functions provided as part of an observer to Subscribe. Instead,\n * you will have access to a subscription or a signal or token that will allow you to do things like\n * unsubscribe and test closed status. Will be removed in v8.\n */\n useDeprecatedNextContext: boolean;\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetTimeoutFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearTimeoutFunction = (handle: TimerHandle) => void;\n\ninterface TimeoutProvider {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n delegate:\n | {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n }\n | undefined;\n}\n\nexport const timeoutProvider: TimeoutProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setTimeout(handler: () => void, timeout?: number, ...args) {\n const { delegate } = timeoutProvider;\n if (delegate?.setTimeout) {\n return delegate.setTimeout(handler, timeout, ...args);\n }\n return setTimeout(handler, timeout, ...args);\n },\n clearTimeout(handle) {\n const { delegate } = timeoutProvider;\n return (delegate?.clearTimeout || clearTimeout)(handle as any);\n },\n delegate: undefined,\n};\n", "import { config } from '../config';\nimport { timeoutProvider } from '../scheduler/timeoutProvider';\n\n/**\n * Handles an error on another job either with the user-configured {@link onUnhandledError},\n * or by throwing it on that new job so it can be picked up by `window.onerror`, `process.on('error')`, etc.\n *\n * This should be called whenever there is an error that is out-of-band with the subscription\n * or when an error hits a terminal boundary of the subscription and no error handler was provided.\n *\n * @param err the error to report\n */\nexport function reportUnhandledError(err: any) {\n timeoutProvider.setTimeout(() => {\n const { onUnhandledError } = config;\n if (onUnhandledError) {\n // Execute the user-configured error handler.\n onUnhandledError(err);\n } else {\n // Throw so it is picked up by the runtime's uncaught error mechanism.\n throw err;\n }\n });\n}\n", "/* tslint:disable:no-empty */\nexport function noop() { }\n", "import { CompleteNotification, NextNotification, ErrorNotification } from './types';\n\n/**\n * A completion object optimized for memory use and created to be the\n * same \"shape\" as other notifications in v8.\n * @internal\n */\nexport const COMPLETE_NOTIFICATION = (() => createNotification('C', undefined, undefined) as CompleteNotification)();\n\n/**\n * Internal use only. Creates an optimized error notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function errorNotification(error: any): ErrorNotification {\n return createNotification('E', undefined, error) as any;\n}\n\n/**\n * Internal use only. Creates an optimized next notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function nextNotification(value: T) {\n return createNotification('N', value, undefined) as NextNotification;\n}\n\n/**\n * Ensures that all notifications created internally have the same \"shape\" in v8.\n *\n * TODO: This is only exported to support a crazy legacy test in `groupBy`.\n * @internal\n */\nexport function createNotification(kind: 'N' | 'E' | 'C', value: any, error: any) {\n return {\n kind,\n value,\n error,\n };\n}\n", "import { config } from '../config';\n\nlet context: { errorThrown: boolean; error: any } | null = null;\n\n/**\n * Handles dealing with errors for super-gross mode. Creates a context, in which\n * any synchronously thrown errors will be passed to {@link captureError}. Which\n * will record the error such that it will be rethrown after the call back is complete.\n * TODO: Remove in v8\n * @param cb An immediately executed function.\n */\nexport function errorContext(cb: () => void) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n const isRoot = !context;\n if (isRoot) {\n context = { errorThrown: false, error: null };\n }\n cb();\n if (isRoot) {\n const { errorThrown, error } = context!;\n context = null;\n if (errorThrown) {\n throw error;\n }\n }\n } else {\n // This is the general non-deprecated path for everyone that\n // isn't crazy enough to use super-gross mode (useDeprecatedSynchronousErrorHandling)\n cb();\n }\n}\n\n/**\n * Captures errors only in super-gross mode.\n * @param err the error to capture\n */\nexport function captureError(err: any) {\n if (config.useDeprecatedSynchronousErrorHandling && context) {\n context.errorThrown = true;\n context.error = err;\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { Observer, ObservableNotification } from './types';\nimport { isSubscription, Subscription } from './Subscription';\nimport { config } from './config';\nimport { reportUnhandledError } from './util/reportUnhandledError';\nimport { noop } from './util/noop';\nimport { nextNotification, errorNotification, COMPLETE_NOTIFICATION } from './NotificationFactories';\nimport { timeoutProvider } from './scheduler/timeoutProvider';\nimport { captureError } from './util/errorContext';\n\n/**\n * Implements the {@link Observer} interface and extends the\n * {@link Subscription} class. While the {@link Observer} is the public API for\n * consuming the values of an {@link Observable}, all Observers get converted to\n * a Subscriber, in order to provide Subscription-like capabilities such as\n * `unsubscribe`. Subscriber is a common type in RxJS, and crucial for\n * implementing operators, but it is rarely used as a public API.\n *\n * @class Subscriber\n */\nexport class Subscriber extends Subscription implements Observer {\n /**\n * A static factory for a Subscriber, given a (potentially partial) definition\n * of an Observer.\n * @param next The `next` callback of an Observer.\n * @param error The `error` callback of an\n * Observer.\n * @param complete The `complete` callback of an\n * Observer.\n * @return A Subscriber wrapping the (partially defined)\n * Observer represented by the given arguments.\n * @nocollapse\n * @deprecated Do not use. Will be removed in v8. There is no replacement for this\n * method, and there is no reason to be creating instances of `Subscriber` directly.\n * If you have a specific use case, please file an issue.\n */\n static create(next?: (x?: T) => void, error?: (e?: any) => void, complete?: () => void): Subscriber {\n return new SafeSubscriber(next, error, complete);\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected isStopped: boolean = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected destination: Subscriber | Observer; // this `any` is the escape hatch to erase extra type param (e.g. R)\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * There is no reason to directly create an instance of Subscriber. This type is exported for typings reasons.\n */\n constructor(destination?: Subscriber | Observer) {\n super();\n if (destination) {\n this.destination = destination;\n // Automatically chain subscriptions together here.\n // if destination is a Subscription, then it is a Subscriber.\n if (isSubscription(destination)) {\n destination.add(this);\n }\n } else {\n this.destination = EMPTY_OBSERVER;\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `next` from\n * the Observable, with a value. The Observable may call this method 0 or more\n * times.\n * @param {T} [value] The `next` value.\n * @return {void}\n */\n next(value?: T): void {\n if (this.isStopped) {\n handleStoppedNotification(nextNotification(value), this);\n } else {\n this._next(value!);\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `error` from\n * the Observable, with an attached `Error`. Notifies the Observer that\n * the Observable has experienced an error condition.\n * @param {any} [err] The `error` exception.\n * @return {void}\n */\n error(err?: any): void {\n if (this.isStopped) {\n handleStoppedNotification(errorNotification(err), this);\n } else {\n this.isStopped = true;\n this._error(err);\n }\n }\n\n /**\n * The {@link Observer} callback to receive a valueless notification of type\n * `complete` from the Observable. Notifies the Observer that the Observable\n * has finished sending push-based notifications.\n * @return {void}\n */\n complete(): void {\n if (this.isStopped) {\n handleStoppedNotification(COMPLETE_NOTIFICATION, this);\n } else {\n this.isStopped = true;\n this._complete();\n }\n }\n\n unsubscribe(): void {\n if (!this.closed) {\n this.isStopped = true;\n super.unsubscribe();\n this.destination = null!;\n }\n }\n\n protected _next(value: T): void {\n this.destination.next(value);\n }\n\n protected _error(err: any): void {\n try {\n this.destination.error(err);\n } finally {\n this.unsubscribe();\n }\n }\n\n protected _complete(): void {\n try {\n this.destination.complete();\n } finally {\n this.unsubscribe();\n }\n }\n}\n\n/**\n * This bind is captured here because we want to be able to have\n * compatibility with monoid libraries that tend to use a method named\n * `bind`. In particular, a library called Monio requires this.\n */\nconst _bind = Function.prototype.bind;\n\nfunction bind any>(fn: Fn, thisArg: any): Fn {\n return _bind.call(fn, thisArg);\n}\n\n/**\n * Internal optimization only, DO NOT EXPOSE.\n * @internal\n */\nclass ConsumerObserver implements Observer {\n constructor(private partialObserver: Partial>) {}\n\n next(value: T): void {\n const { partialObserver } = this;\n if (partialObserver.next) {\n try {\n partialObserver.next(value);\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n\n error(err: any): void {\n const { partialObserver } = this;\n if (partialObserver.error) {\n try {\n partialObserver.error(err);\n } catch (error) {\n handleUnhandledError(error);\n }\n } else {\n handleUnhandledError(err);\n }\n }\n\n complete(): void {\n const { partialObserver } = this;\n if (partialObserver.complete) {\n try {\n partialObserver.complete();\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n}\n\nexport class SafeSubscriber extends Subscriber {\n constructor(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((e?: any) => void) | null,\n complete?: (() => void) | null\n ) {\n super();\n\n let partialObserver: Partial>;\n if (isFunction(observerOrNext) || !observerOrNext) {\n // The first argument is a function, not an observer. The next\n // two arguments *could* be observers, or they could be empty.\n partialObserver = {\n next: (observerOrNext ?? undefined) as (((value: T) => void) | undefined),\n error: error ?? undefined,\n complete: complete ?? undefined,\n };\n } else {\n // The first argument is a partial observer.\n let context: any;\n if (this && config.useDeprecatedNextContext) {\n // This is a deprecated path that made `this.unsubscribe()` available in\n // next handler functions passed to subscribe. This only exists behind a flag\n // now, as it is *very* slow.\n context = Object.create(observerOrNext);\n context.unsubscribe = () => this.unsubscribe();\n partialObserver = {\n next: observerOrNext.next && bind(observerOrNext.next, context),\n error: observerOrNext.error && bind(observerOrNext.error, context),\n complete: observerOrNext.complete && bind(observerOrNext.complete, context),\n };\n } else {\n // The \"normal\" path. Just use the partial observer directly.\n partialObserver = observerOrNext;\n }\n }\n\n // Wrap the partial observer to ensure it's a full observer, and\n // make sure proper error handling is accounted for.\n this.destination = new ConsumerObserver(partialObserver);\n }\n}\n\nfunction handleUnhandledError(error: any) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n captureError(error);\n } else {\n // Ideal path, we report this as an unhandled error,\n // which is thrown on a new call stack.\n reportUnhandledError(error);\n }\n}\n\n/**\n * An error handler used when no error handler was supplied\n * to the SafeSubscriber -- meaning no error handler was supplied\n * do the `subscribe` call on our observable.\n * @param err The error to handle\n */\nfunction defaultErrorHandler(err: any) {\n throw err;\n}\n\n/**\n * A handler for notifications that cannot be sent to a stopped subscriber.\n * @param notification The notification being sent\n * @param subscriber The stopped subscriber\n */\nfunction handleStoppedNotification(notification: ObservableNotification, subscriber: Subscriber) {\n const { onStoppedNotification } = config;\n onStoppedNotification && timeoutProvider.setTimeout(() => onStoppedNotification(notification, subscriber));\n}\n\n/**\n * The observer used as a stub for subscriptions where the user did not\n * pass any arguments to `subscribe`. Comes with the default error handling\n * behavior.\n */\nexport const EMPTY_OBSERVER: Readonly> & { closed: true } = {\n closed: true,\n next: noop,\n error: defaultErrorHandler,\n complete: noop,\n};\n", "/**\n * Symbol.observable or a string \"@@observable\". Used for interop\n *\n * @deprecated We will no longer be exporting this symbol in upcoming versions of RxJS.\n * Instead polyfill and use Symbol.observable directly *or* use https://www.npmjs.com/package/symbol-observable\n */\nexport const observable: string | symbol = (() => (typeof Symbol === 'function' && Symbol.observable) || '@@observable')();\n", "/**\n * This function takes one parameter and just returns it. Simply put,\n * this is like `(x: T): T => x`.\n *\n * ## Examples\n *\n * This is useful in some cases when using things like `mergeMap`\n *\n * ```ts\n * import { interval, take, map, range, mergeMap, identity } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(5));\n *\n * const result$ = source$.pipe(\n * map(i => range(i)),\n * mergeMap(identity) // same as mergeMap(x => x)\n * );\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * Or when you want to selectively apply an operator\n *\n * ```ts\n * import { interval, take, identity } from 'rxjs';\n *\n * const shouldLimit = () => Math.random() < 0.5;\n *\n * const source$ = interval(1000);\n *\n * const result$ = source$.pipe(shouldLimit() ? take(5) : identity);\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * @param x Any value that is returned by this function\n * @returns The value passed as the first parameter to this function\n */\nexport function identity(x: T): T {\n return x;\n}\n", "import { identity } from './identity';\nimport { UnaryFunction } from '../types';\n\nexport function pipe(): typeof identity;\nexport function pipe(fn1: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction, fn3: UnaryFunction): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction,\n ...fns: UnaryFunction[]\n): UnaryFunction;\n\n/**\n * pipe() can be called on one or more functions, each of which can take one argument (\"UnaryFunction\")\n * and uses it to return a value.\n * It returns a function that takes one argument, passes it to the first UnaryFunction, and then\n * passes the result to the next one, passes that result to the next one, and so on. \n */\nexport function pipe(...fns: Array>): UnaryFunction {\n return pipeFromArray(fns);\n}\n\n/** @internal */\nexport function pipeFromArray(fns: Array>): UnaryFunction {\n if (fns.length === 0) {\n return identity as UnaryFunction;\n }\n\n if (fns.length === 1) {\n return fns[0];\n }\n\n return function piped(input: T): R {\n return fns.reduce((prev: any, fn: UnaryFunction) => fn(prev), input as any);\n };\n}\n", "import { Operator } from './Operator';\nimport { SafeSubscriber, Subscriber } from './Subscriber';\nimport { isSubscription, Subscription } from './Subscription';\nimport { TeardownLogic, OperatorFunction, Subscribable, Observer } from './types';\nimport { observable as Symbol_observable } from './symbol/observable';\nimport { pipeFromArray } from './util/pipe';\nimport { config } from './config';\nimport { isFunction } from './util/isFunction';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A representation of any set of values over any amount of time. This is the most basic building block\n * of RxJS.\n *\n * @class Observable\n */\nexport class Observable implements Subscribable {\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n source: Observable | undefined;\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n operator: Operator | undefined;\n\n /**\n * @constructor\n * @param {Function} subscribe the function that is called when the Observable is\n * initially subscribed to. This function is given a Subscriber, to which new values\n * can be `next`ed, or an `error` method can be called to raise an error, or\n * `complete` can be called to notify of a successful completion.\n */\n constructor(subscribe?: (this: Observable, subscriber: Subscriber) => TeardownLogic) {\n if (subscribe) {\n this._subscribe = subscribe;\n }\n }\n\n // HACK: Since TypeScript inherits static properties too, we have to\n // fight against TypeScript here so Subject can have a different static create signature\n /**\n * Creates a new Observable by calling the Observable constructor\n * @owner Observable\n * @method create\n * @param {Function} subscribe? the subscriber function to be passed to the Observable constructor\n * @return {Observable} a new observable\n * @nocollapse\n * @deprecated Use `new Observable()` instead. Will be removed in v8.\n */\n static create: (...args: any[]) => any = (subscribe?: (subscriber: Subscriber) => TeardownLogic) => {\n return new Observable(subscribe);\n };\n\n /**\n * Creates a new Observable, with this Observable instance as the source, and the passed\n * operator defined as the new observable's operator.\n * @method lift\n * @param operator the operator defining the operation to take on the observable\n * @return a new observable with the Operator applied\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * If you have implemented an operator using `lift`, it is recommended that you create an\n * operator by simply returning `new Observable()` directly. See \"Creating new operators from\n * scratch\" section here: https://rxjs.dev/guide/operators\n */\n lift(operator?: Operator): Observable {\n const observable = new Observable();\n observable.source = this;\n observable.operator = operator;\n return observable;\n }\n\n subscribe(observerOrNext?: Partial> | ((value: T) => void)): Subscription;\n /** @deprecated Instead of passing separate callback arguments, use an observer argument. Signatures taking separate callback arguments will be removed in v8. Details: https://rxjs.dev/deprecations/subscribe-arguments */\n subscribe(next?: ((value: T) => void) | null, error?: ((error: any) => void) | null, complete?: (() => void) | null): Subscription;\n /**\n * Invokes an execution of an Observable and registers Observer handlers for notifications it will emit.\n *\n * Use it when you have all these Observables, but still nothing is happening.\n *\n * `subscribe` is not a regular operator, but a method that calls Observable's internal `subscribe` function. It\n * might be for example a function that you passed to Observable's constructor, but most of the time it is\n * a library implementation, which defines what will be emitted by an Observable, and when it be will emitted. This means\n * that calling `subscribe` is actually the moment when Observable starts its work, not when it is created, as it is often\n * the thought.\n *\n * Apart from starting the execution of an Observable, this method allows you to listen for values\n * that an Observable emits, as well as for when it completes or errors. You can achieve this in two\n * of the following ways.\n *\n * The first way is creating an object that implements {@link Observer} interface. It should have methods\n * defined by that interface, but note that it should be just a regular JavaScript object, which you can create\n * yourself in any way you want (ES6 class, classic function constructor, object literal etc.). In particular, do\n * not attempt to use any RxJS implementation details to create Observers - you don't need them. Remember also\n * that your object does not have to implement all methods. If you find yourself creating a method that doesn't\n * do anything, you can simply omit it. Note however, if the `error` method is not provided and an error happens,\n * it will be thrown asynchronously. Errors thrown asynchronously cannot be caught using `try`/`catch`. Instead,\n * use the {@link onUnhandledError} configuration option or use a runtime handler (like `window.onerror` or\n * `process.on('error)`) to be notified of unhandled errors. Because of this, it's recommended that you provide\n * an `error` method to avoid missing thrown errors.\n *\n * The second way is to give up on Observer object altogether and simply provide callback functions in place of its methods.\n * This means you can provide three functions as arguments to `subscribe`, where the first function is equivalent\n * of a `next` method, the second of an `error` method and the third of a `complete` method. Just as in case of an Observer,\n * if you do not need to listen for something, you can omit a function by passing `undefined` or `null`,\n * since `subscribe` recognizes these functions by where they were placed in function call. When it comes\n * to the `error` function, as with an Observer, if not provided, errors emitted by an Observable will be thrown asynchronously.\n *\n * You can, however, subscribe with no parameters at all. This may be the case where you're not interested in terminal events\n * and you also handled emissions internally by using operators (e.g. using `tap`).\n *\n * Whichever style of calling `subscribe` you use, in both cases it returns a Subscription object.\n * This object allows you to call `unsubscribe` on it, which in turn will stop the work that an Observable does and will clean\n * up all resources that an Observable used. Note that cancelling a subscription will not call `complete` callback\n * provided to `subscribe` function, which is reserved for a regular completion signal that comes from an Observable.\n *\n * Remember that callbacks provided to `subscribe` are not guaranteed to be called asynchronously.\n * It is an Observable itself that decides when these functions will be called. For example {@link of}\n * by default emits all its values synchronously. Always check documentation for how given Observable\n * will behave when subscribed and if its default behavior can be modified with a `scheduler`.\n *\n * #### Examples\n *\n * Subscribe with an {@link guide/observer Observer}\n *\n * ```ts\n * import { of } from 'rxjs';\n *\n * const sumObserver = {\n * sum: 0,\n * next(value) {\n * console.log('Adding: ' + value);\n * this.sum = this.sum + value;\n * },\n * error() {\n * // We actually could just remove this method,\n * // since we do not really care about errors right now.\n * },\n * complete() {\n * console.log('Sum equals: ' + this.sum);\n * }\n * };\n *\n * of(1, 2, 3) // Synchronously emits 1, 2, 3 and then completes.\n * .subscribe(sumObserver);\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Subscribe with functions ({@link deprecations/subscribe-arguments deprecated})\n *\n * ```ts\n * import { of } from 'rxjs'\n *\n * let sum = 0;\n *\n * of(1, 2, 3).subscribe(\n * value => {\n * console.log('Adding: ' + value);\n * sum = sum + value;\n * },\n * undefined,\n * () => console.log('Sum equals: ' + sum)\n * );\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Cancel a subscription\n *\n * ```ts\n * import { interval } from 'rxjs';\n *\n * const subscription = interval(1000).subscribe({\n * next(num) {\n * console.log(num)\n * },\n * complete() {\n * // Will not be called, even when cancelling subscription.\n * console.log('completed!');\n * }\n * });\n *\n * setTimeout(() => {\n * subscription.unsubscribe();\n * console.log('unsubscribed!');\n * }, 2500);\n *\n * // Logs:\n * // 0 after 1s\n * // 1 after 2s\n * // 'unsubscribed!' after 2.5s\n * ```\n *\n * @param {Observer|Function} observerOrNext (optional) Either an observer with methods to be called,\n * or the first of three possible handlers, which is the handler for each value emitted from the subscribed\n * Observable.\n * @param {Function} error (optional) A handler for a terminal event resulting from an error. If no error handler is provided,\n * the error will be thrown asynchronously as unhandled.\n * @param {Function} complete (optional) A handler for a terminal event resulting from successful completion.\n * @return {Subscription} a subscription reference to the registered handlers\n * @method subscribe\n */\n subscribe(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((error: any) => void) | null,\n complete?: (() => void) | null\n ): Subscription {\n const subscriber = isSubscriber(observerOrNext) ? observerOrNext : new SafeSubscriber(observerOrNext, error, complete);\n\n errorContext(() => {\n const { operator, source } = this;\n subscriber.add(\n operator\n ? // We're dealing with a subscription in the\n // operator chain to one of our lifted operators.\n operator.call(subscriber, source)\n : source\n ? // If `source` has a value, but `operator` does not, something that\n // had intimate knowledge of our API, like our `Subject`, must have\n // set it. We're going to just call `_subscribe` directly.\n this._subscribe(subscriber)\n : // In all other cases, we're likely wrapping a user-provided initializer\n // function, so we need to catch errors and handle them appropriately.\n this._trySubscribe(subscriber)\n );\n });\n\n return subscriber;\n }\n\n /** @internal */\n protected _trySubscribe(sink: Subscriber): TeardownLogic {\n try {\n return this._subscribe(sink);\n } catch (err) {\n // We don't need to return anything in this case,\n // because it's just going to try to `add()` to a subscription\n // above.\n sink.error(err);\n }\n }\n\n /**\n * Used as a NON-CANCELLABLE means of subscribing to an observable, for use with\n * APIs that expect promises, like `async/await`. You cannot unsubscribe from this.\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * #### Example\n *\n * ```ts\n * import { interval, take } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(4));\n *\n * async function getTotal() {\n * let total = 0;\n *\n * await source$.forEach(value => {\n * total += value;\n * console.log('observable -> ' + value);\n * });\n *\n * return total;\n * }\n *\n * getTotal().then(\n * total => console.log('Total: ' + total)\n * );\n *\n * // Expected:\n * // 'observable -> 0'\n * // 'observable -> 1'\n * // 'observable -> 2'\n * // 'observable -> 3'\n * // 'Total: 6'\n * ```\n *\n * @param next a handler for each value emitted by the observable\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n */\n forEach(next: (value: T) => void): Promise;\n\n /**\n * @param next a handler for each value emitted by the observable\n * @param promiseCtor a constructor function used to instantiate the Promise\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n * @deprecated Passing a Promise constructor will no longer be available\n * in upcoming versions of RxJS. This is because it adds weight to the library, for very\n * little benefit. If you need this functionality, it is recommended that you either\n * polyfill Promise, or you create an adapter to convert the returned native promise\n * to whatever promise implementation you wanted. Will be removed in v8.\n */\n forEach(next: (value: T) => void, promiseCtor: PromiseConstructorLike): Promise;\n\n forEach(next: (value: T) => void, promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n const subscriber = new SafeSubscriber({\n next: (value) => {\n try {\n next(value);\n } catch (err) {\n reject(err);\n subscriber.unsubscribe();\n }\n },\n error: reject,\n complete: resolve,\n });\n this.subscribe(subscriber);\n }) as Promise;\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): TeardownLogic {\n return this.source?.subscribe(subscriber);\n }\n\n /**\n * An interop point defined by the es7-observable spec https://github.com/zenparsing/es-observable\n * @method Symbol.observable\n * @return {Observable} this instance of the observable\n */\n [Symbol_observable]() {\n return this;\n }\n\n /* tslint:disable:max-line-length */\n pipe(): Observable;\n pipe(op1: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction, op3: OperatorFunction): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction,\n ...operations: OperatorFunction[]\n ): Observable;\n /* tslint:enable:max-line-length */\n\n /**\n * Used to stitch together functional operators into a chain.\n * @method pipe\n * @return {Observable} the Observable result of all of the operators having\n * been called in the order they were passed in.\n *\n * ## Example\n *\n * ```ts\n * import { interval, filter, map, scan } from 'rxjs';\n *\n * interval(1000)\n * .pipe(\n * filter(x => x % 2 === 0),\n * map(x => x + x),\n * scan((acc, x) => acc + x)\n * )\n * .subscribe(x => console.log(x));\n * ```\n */\n pipe(...operations: OperatorFunction[]): Observable {\n return pipeFromArray(operations)(this);\n }\n\n /* tslint:disable:max-line-length */\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: typeof Promise): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: PromiseConstructorLike): Promise;\n /* tslint:enable:max-line-length */\n\n /**\n * Subscribe to this Observable and get a Promise resolving on\n * `complete` with the last emission (if any).\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * @method toPromise\n * @param [promiseCtor] a constructor function used to instantiate\n * the Promise\n * @return A Promise that resolves with the last value emit, or\n * rejects on an error. If there were no emissions, Promise\n * resolves with undefined.\n * @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise\n */\n toPromise(promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n let value: T | undefined;\n this.subscribe(\n (x: T) => (value = x),\n (err: any) => reject(err),\n () => resolve(value)\n );\n }) as Promise;\n }\n}\n\n/**\n * Decides between a passed promise constructor from consuming code,\n * A default configured promise constructor, and the native promise\n * constructor and returns it. If nothing can be found, it will throw\n * an error.\n * @param promiseCtor The optional promise constructor to passed by consuming code\n */\nfunction getPromiseCtor(promiseCtor: PromiseConstructorLike | undefined) {\n return promiseCtor ?? config.Promise ?? Promise;\n}\n\nfunction isObserver(value: any): value is Observer {\n return value && isFunction(value.next) && isFunction(value.error) && isFunction(value.complete);\n}\n\nfunction isSubscriber(value: any): value is Subscriber {\n return (value && value instanceof Subscriber) || (isObserver(value) && isSubscription(value));\n}\n", "import { Observable } from '../Observable';\nimport { Subscriber } from '../Subscriber';\nimport { OperatorFunction } from '../types';\nimport { isFunction } from './isFunction';\n\n/**\n * Used to determine if an object is an Observable with a lift function.\n */\nexport function hasLift(source: any): source is { lift: InstanceType['lift'] } {\n return isFunction(source?.lift);\n}\n\n/**\n * Creates an `OperatorFunction`. Used to define operators throughout the library in a concise way.\n * @param init The logic to connect the liftedSource to the subscriber at the moment of subscription.\n */\nexport function operate(\n init: (liftedSource: Observable, subscriber: Subscriber) => (() => void) | void\n): OperatorFunction {\n return (source: Observable) => {\n if (hasLift(source)) {\n return source.lift(function (this: Subscriber, liftedSource: Observable) {\n try {\n return init(liftedSource, this);\n } catch (err) {\n this.error(err);\n }\n });\n }\n throw new TypeError('Unable to lift unknown Observable type');\n };\n}\n", "import { Subscriber } from '../Subscriber';\n\n/**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional teardown logic here. This will only be called on teardown if the\n * subscriber itself is not already closed. This is called after all other teardown logic is executed.\n */\nexport function createOperatorSubscriber(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n onFinalize?: () => void\n): Subscriber {\n return new OperatorSubscriber(destination, onNext, onComplete, onError, onFinalize);\n}\n\n/**\n * A generic helper for allowing operators to be created with a Subscriber and\n * use closures to capture necessary state from the operator function itself.\n */\nexport class OperatorSubscriber extends Subscriber {\n /**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional finalization logic here. This will only be called on finalization if the\n * subscriber itself is not already closed. This is called after all other finalization logic is executed.\n * @param shouldUnsubscribe An optional check to see if an unsubscribe call should truly unsubscribe.\n * NOTE: This currently **ONLY** exists to support the strange behavior of {@link groupBy}, where unsubscription\n * to the resulting observable does not actually disconnect from the source if there are active subscriptions\n * to any grouped observable. (DO NOT EXPOSE OR USE EXTERNALLY!!!)\n */\n constructor(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n private onFinalize?: () => void,\n private shouldUnsubscribe?: () => boolean\n ) {\n // It's important - for performance reasons - that all of this class's\n // members are initialized and that they are always initialized in the same\n // order. This will ensure that all OperatorSubscriber instances have the\n // same hidden class in V8. This, in turn, will help keep the number of\n // hidden classes involved in property accesses within the base class as\n // low as possible. If the number of hidden classes involved exceeds four,\n // the property accesses will become megamorphic and performance penalties\n // will be incurred - i.e. inline caches won't be used.\n //\n // The reasons for ensuring all instances have the same hidden class are\n // further discussed in this blog post from Benedikt Meurer:\n // https://benediktmeurer.de/2018/03/23/impact-of-polymorphism-on-component-based-frameworks-like-react/\n super(destination);\n this._next = onNext\n ? function (this: OperatorSubscriber, value: T) {\n try {\n onNext(value);\n } catch (err) {\n destination.error(err);\n }\n }\n : super._next;\n this._error = onError\n ? function (this: OperatorSubscriber, err: any) {\n try {\n onError(err);\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._error;\n this._complete = onComplete\n ? function (this: OperatorSubscriber) {\n try {\n onComplete();\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._complete;\n }\n\n unsubscribe() {\n if (!this.shouldUnsubscribe || this.shouldUnsubscribe()) {\n const { closed } = this;\n super.unsubscribe();\n // Execute additional teardown if we have any and we didn't already do so.\n !closed && this.onFinalize?.();\n }\n }\n}\n", "import { Subscription } from '../Subscription';\n\ninterface AnimationFrameProvider {\n schedule(callback: FrameRequestCallback): Subscription;\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n delegate:\n | {\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n }\n | undefined;\n}\n\nexport const animationFrameProvider: AnimationFrameProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n schedule(callback) {\n let request = requestAnimationFrame;\n let cancel: typeof cancelAnimationFrame | undefined = cancelAnimationFrame;\n const { delegate } = animationFrameProvider;\n if (delegate) {\n request = delegate.requestAnimationFrame;\n cancel = delegate.cancelAnimationFrame;\n }\n const handle = request((timestamp) => {\n // Clear the cancel function. The request has been fulfilled, so\n // attempting to cancel the request upon unsubscription would be\n // pointless.\n cancel = undefined;\n callback(timestamp);\n });\n return new Subscription(() => cancel?.(handle));\n },\n requestAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.requestAnimationFrame || requestAnimationFrame)(...args);\n },\n cancelAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.cancelAnimationFrame || cancelAnimationFrame)(...args);\n },\n delegate: undefined,\n};\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface ObjectUnsubscribedError extends Error {}\n\nexport interface ObjectUnsubscribedErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (): ObjectUnsubscribedError;\n}\n\n/**\n * An error thrown when an action is invalid because the object has been\n * unsubscribed.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n *\n * @class ObjectUnsubscribedError\n */\nexport const ObjectUnsubscribedError: ObjectUnsubscribedErrorCtor = createErrorClass(\n (_super) =>\n function ObjectUnsubscribedErrorImpl(this: any) {\n _super(this);\n this.name = 'ObjectUnsubscribedError';\n this.message = 'object unsubscribed';\n }\n);\n", "import { Operator } from './Operator';\nimport { Observable } from './Observable';\nimport { Subscriber } from './Subscriber';\nimport { Subscription, EMPTY_SUBSCRIPTION } from './Subscription';\nimport { Observer, SubscriptionLike, TeardownLogic } from './types';\nimport { ObjectUnsubscribedError } from './util/ObjectUnsubscribedError';\nimport { arrRemove } from './util/arrRemove';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A Subject is a special type of Observable that allows values to be\n * multicasted to many Observers. Subjects are like EventEmitters.\n *\n * Every Subject is an Observable and an Observer. You can subscribe to a\n * Subject, and you can call next to feed values as well as error and complete.\n */\nexport class Subject extends Observable implements SubscriptionLike {\n closed = false;\n\n private currentObservers: Observer[] | null = null;\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n observers: Observer[] = [];\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n isStopped = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n hasError = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n thrownError: any = null;\n\n /**\n * Creates a \"subject\" by basically gluing an observer to an observable.\n *\n * @nocollapse\n * @deprecated Recommended you do not use. Will be removed at some point in the future. Plans for replacement still under discussion.\n */\n static create: (...args: any[]) => any = (destination: Observer, source: Observable): AnonymousSubject => {\n return new AnonymousSubject(destination, source);\n };\n\n constructor() {\n // NOTE: This must be here to obscure Observable's constructor.\n super();\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n lift(operator: Operator): Observable {\n const subject = new AnonymousSubject(this, this);\n subject.operator = operator as any;\n return subject as any;\n }\n\n /** @internal */\n protected _throwIfClosed() {\n if (this.closed) {\n throw new ObjectUnsubscribedError();\n }\n }\n\n next(value: T) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n if (!this.currentObservers) {\n this.currentObservers = Array.from(this.observers);\n }\n for (const observer of this.currentObservers) {\n observer.next(value);\n }\n }\n });\n }\n\n error(err: any) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.hasError = this.isStopped = true;\n this.thrownError = err;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.error(err);\n }\n }\n });\n }\n\n complete() {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.isStopped = true;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.complete();\n }\n }\n });\n }\n\n unsubscribe() {\n this.isStopped = this.closed = true;\n this.observers = this.currentObservers = null!;\n }\n\n get observed() {\n return this.observers?.length > 0;\n }\n\n /** @internal */\n protected _trySubscribe(subscriber: Subscriber): TeardownLogic {\n this._throwIfClosed();\n return super._trySubscribe(subscriber);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._checkFinalizedStatuses(subscriber);\n return this._innerSubscribe(subscriber);\n }\n\n /** @internal */\n protected _innerSubscribe(subscriber: Subscriber) {\n const { hasError, isStopped, observers } = this;\n if (hasError || isStopped) {\n return EMPTY_SUBSCRIPTION;\n }\n this.currentObservers = null;\n observers.push(subscriber);\n return new Subscription(() => {\n this.currentObservers = null;\n arrRemove(observers, subscriber);\n });\n }\n\n /** @internal */\n protected _checkFinalizedStatuses(subscriber: Subscriber) {\n const { hasError, thrownError, isStopped } = this;\n if (hasError) {\n subscriber.error(thrownError);\n } else if (isStopped) {\n subscriber.complete();\n }\n }\n\n /**\n * Creates a new Observable with this Subject as the source. You can do this\n * to create custom Observer-side logic of the Subject and conceal it from\n * code that uses the Observable.\n * @return {Observable} Observable that the Subject casts to\n */\n asObservable(): Observable {\n const observable: any = new Observable();\n observable.source = this;\n return observable;\n }\n}\n\n/**\n * @class AnonymousSubject\n */\nexport class AnonymousSubject extends Subject {\n constructor(\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n public destination?: Observer,\n source?: Observable\n ) {\n super();\n this.source = source;\n }\n\n next(value: T) {\n this.destination?.next?.(value);\n }\n\n error(err: any) {\n this.destination?.error?.(err);\n }\n\n complete() {\n this.destination?.complete?.();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n return this.source?.subscribe(subscriber) ?? EMPTY_SUBSCRIPTION;\n }\n}\n", "import { Subject } from './Subject';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\n\n/**\n * A variant of Subject that requires an initial value and emits its current\n * value whenever it is subscribed to.\n *\n * @class BehaviorSubject\n */\nexport class BehaviorSubject extends Subject {\n constructor(private _value: T) {\n super();\n }\n\n get value(): T {\n return this.getValue();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n const subscription = super._subscribe(subscriber);\n !subscription.closed && subscriber.next(this._value);\n return subscription;\n }\n\n getValue(): T {\n const { hasError, thrownError, _value } = this;\n if (hasError) {\n throw thrownError;\n }\n this._throwIfClosed();\n return _value;\n }\n\n next(value: T): void {\n super.next((this._value = value));\n }\n}\n", "import { TimestampProvider } from '../types';\n\ninterface DateTimestampProvider extends TimestampProvider {\n delegate: TimestampProvider | undefined;\n}\n\nexport const dateTimestampProvider: DateTimestampProvider = {\n now() {\n // Use the variable rather than `this` so that the function can be called\n // without being bound to the provider.\n return (dateTimestampProvider.delegate || Date).now();\n },\n delegate: undefined,\n};\n", "import { Subject } from './Subject';\nimport { TimestampProvider } from './types';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * A variant of {@link Subject} that \"replays\" old values to new subscribers by emitting them when they first subscribe.\n *\n * `ReplaySubject` has an internal buffer that will store a specified number of values that it has observed. Like `Subject`,\n * `ReplaySubject` \"observes\" values by having them passed to its `next` method. When it observes a value, it will store that\n * value for a time determined by the configuration of the `ReplaySubject`, as passed to its constructor.\n *\n * When a new subscriber subscribes to the `ReplaySubject` instance, it will synchronously emit all values in its buffer in\n * a First-In-First-Out (FIFO) manner. The `ReplaySubject` will also complete, if it has observed completion; and it will\n * error if it has observed an error.\n *\n * There are two main configuration items to be concerned with:\n *\n * 1. `bufferSize` - This will determine how many items are stored in the buffer, defaults to infinite.\n * 2. `windowTime` - The amount of time to hold a value in the buffer before removing it from the buffer.\n *\n * Both configurations may exist simultaneously. So if you would like to buffer a maximum of 3 values, as long as the values\n * are less than 2 seconds old, you could do so with a `new ReplaySubject(3, 2000)`.\n *\n * ### Differences with BehaviorSubject\n *\n * `BehaviorSubject` is similar to `new ReplaySubject(1)`, with a couple of exceptions:\n *\n * 1. `BehaviorSubject` comes \"primed\" with a single value upon construction.\n * 2. `ReplaySubject` will replay values, even after observing an error, where `BehaviorSubject` will not.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n * @see {@link shareReplay}\n */\nexport class ReplaySubject extends Subject {\n private _buffer: (T | number)[] = [];\n private _infiniteTimeWindow = true;\n\n /**\n * @param bufferSize The size of the buffer to replay on subscription\n * @param windowTime The amount of time the buffered items will stay buffered\n * @param timestampProvider An object with a `now()` method that provides the current timestamp. This is used to\n * calculate the amount of time something has been buffered.\n */\n constructor(\n private _bufferSize = Infinity,\n private _windowTime = Infinity,\n private _timestampProvider: TimestampProvider = dateTimestampProvider\n ) {\n super();\n this._infiniteTimeWindow = _windowTime === Infinity;\n this._bufferSize = Math.max(1, _bufferSize);\n this._windowTime = Math.max(1, _windowTime);\n }\n\n next(value: T): void {\n const { isStopped, _buffer, _infiniteTimeWindow, _timestampProvider, _windowTime } = this;\n if (!isStopped) {\n _buffer.push(value);\n !_infiniteTimeWindow && _buffer.push(_timestampProvider.now() + _windowTime);\n }\n this._trimBuffer();\n super.next(value);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._trimBuffer();\n\n const subscription = this._innerSubscribe(subscriber);\n\n const { _infiniteTimeWindow, _buffer } = this;\n // We use a copy here, so reentrant code does not mutate our array while we're\n // emitting it to a new subscriber.\n const copy = _buffer.slice();\n for (let i = 0; i < copy.length && !subscriber.closed; i += _infiniteTimeWindow ? 1 : 2) {\n subscriber.next(copy[i] as T);\n }\n\n this._checkFinalizedStatuses(subscriber);\n\n return subscription;\n }\n\n private _trimBuffer() {\n const { _bufferSize, _timestampProvider, _buffer, _infiniteTimeWindow } = this;\n // If we don't have an infinite buffer size, and we're over the length,\n // use splice to truncate the old buffer values off. Note that we have to\n // double the size for instances where we're not using an infinite time window\n // because we're storing the values and the timestamps in the same array.\n const adjustedBufferSize = (_infiniteTimeWindow ? 1 : 2) * _bufferSize;\n _bufferSize < Infinity && adjustedBufferSize < _buffer.length && _buffer.splice(0, _buffer.length - adjustedBufferSize);\n\n // Now, if we're not in an infinite time window, remove all values where the time is\n // older than what is allowed.\n if (!_infiniteTimeWindow) {\n const now = _timestampProvider.now();\n let last = 0;\n // Search the array for the first timestamp that isn't expired and\n // truncate the buffer up to that point.\n for (let i = 1; i < _buffer.length && (_buffer[i] as number) <= now; i += 2) {\n last = i;\n }\n last && _buffer.splice(0, last + 1);\n }\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Subscription } from '../Subscription';\nimport { SchedulerAction } from '../types';\n\n/**\n * A unit of work to be executed in a `scheduler`. An action is typically\n * created from within a {@link SchedulerLike} and an RxJS user does not need to concern\n * themselves about creating and manipulating an Action.\n *\n * ```ts\n * class Action extends Subscription {\n * new (scheduler: Scheduler, work: (state?: T) => void);\n * schedule(state?: T, delay: number = 0): Subscription;\n * }\n * ```\n *\n * @class Action\n */\nexport class Action extends Subscription {\n constructor(scheduler: Scheduler, work: (this: SchedulerAction, state?: T) => void) {\n super();\n }\n /**\n * Schedules this action on its parent {@link SchedulerLike} for execution. May be passed\n * some context object, `state`. May happen at some point in the future,\n * according to the `delay` parameter, if specified.\n * @param {T} [state] Some contextual data that the `work` function uses when\n * called by the Scheduler.\n * @param {number} [delay] Time to wait before executing the work, where the\n * time unit is implicit and defined by the Scheduler.\n * @return {void}\n */\n public schedule(state?: T, delay: number = 0): Subscription {\n return this;\n }\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetIntervalFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearIntervalFunction = (handle: TimerHandle) => void;\n\ninterface IntervalProvider {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n delegate:\n | {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n }\n | undefined;\n}\n\nexport const intervalProvider: IntervalProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setInterval(handler: () => void, timeout?: number, ...args) {\n const { delegate } = intervalProvider;\n if (delegate?.setInterval) {\n return delegate.setInterval(handler, timeout, ...args);\n }\n return setInterval(handler, timeout, ...args);\n },\n clearInterval(handle) {\n const { delegate } = intervalProvider;\n return (delegate?.clearInterval || clearInterval)(handle as any);\n },\n delegate: undefined,\n};\n", "import { Action } from './Action';\nimport { SchedulerAction } from '../types';\nimport { Subscription } from '../Subscription';\nimport { AsyncScheduler } from './AsyncScheduler';\nimport { intervalProvider } from './intervalProvider';\nimport { arrRemove } from '../util/arrRemove';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncAction extends Action {\n public id: TimerHandle | undefined;\n public state?: T;\n // @ts-ignore: Property has no initializer and is not definitely assigned\n public delay: number;\n protected pending: boolean = false;\n\n constructor(protected scheduler: AsyncScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (this.closed) {\n return this;\n }\n\n // Always replace the current state with the new state.\n this.state = state;\n\n const id = this.id;\n const scheduler = this.scheduler;\n\n //\n // Important implementation note:\n //\n // Actions only execute once by default, unless rescheduled from within the\n // scheduled callback. This allows us to implement single and repeat\n // actions via the same code path, without adding API surface area, as well\n // as mimic traditional recursion but across asynchronous boundaries.\n //\n // However, JS runtimes and timers distinguish between intervals achieved by\n // serial `setTimeout` calls vs. a single `setInterval` call. An interval of\n // serial `setTimeout` calls can be individually delayed, which delays\n // scheduling the next `setTimeout`, and so on. `setInterval` attempts to\n // guarantee the interval callback will be invoked more precisely to the\n // interval period, regardless of load.\n //\n // Therefore, we use `setInterval` to schedule single and repeat actions.\n // If the action reschedules itself with the same delay, the interval is not\n // canceled. If the action doesn't reschedule, or reschedules with a\n // different delay, the interval will be canceled after scheduled callback\n // execution.\n //\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, delay);\n }\n\n // Set the pending flag indicating that this action has been scheduled, or\n // has recursively rescheduled itself.\n this.pending = true;\n\n this.delay = delay;\n // If this action has already an async Id, don't request a new one.\n this.id = this.id ?? this.requestAsyncId(scheduler, this.id, delay);\n\n return this;\n }\n\n protected requestAsyncId(scheduler: AsyncScheduler, _id?: TimerHandle, delay: number = 0): TimerHandle {\n return intervalProvider.setInterval(scheduler.flush.bind(scheduler, this), delay);\n }\n\n protected recycleAsyncId(_scheduler: AsyncScheduler, id?: TimerHandle, delay: number | null = 0): TimerHandle | undefined {\n // If this action is rescheduled with the same delay time, don't clear the interval id.\n if (delay != null && this.delay === delay && this.pending === false) {\n return id;\n }\n // Otherwise, if the action's delay time is different from the current delay,\n // or the action has been rescheduled before it's executed, clear the interval id\n if (id != null) {\n intervalProvider.clearInterval(id);\n }\n\n return undefined;\n }\n\n /**\n * Immediately executes this action and the `work` it contains.\n * @return {any}\n */\n public execute(state: T, delay: number): any {\n if (this.closed) {\n return new Error('executing a cancelled action');\n }\n\n this.pending = false;\n const error = this._execute(state, delay);\n if (error) {\n return error;\n } else if (this.pending === false && this.id != null) {\n // Dequeue if the action didn't reschedule itself. Don't call\n // unsubscribe(), because the action could reschedule later.\n // For example:\n // ```\n // scheduler.schedule(function doWork(counter) {\n // /* ... I'm a busy worker bee ... */\n // var originalAction = this;\n // /* wait 100ms before rescheduling the action */\n // setTimeout(function () {\n // originalAction.schedule(counter + 1);\n // }, 100);\n // }, 1000);\n // ```\n this.id = this.recycleAsyncId(this.scheduler, this.id, null);\n }\n }\n\n protected _execute(state: T, _delay: number): any {\n let errored: boolean = false;\n let errorValue: any;\n try {\n this.work(state);\n } catch (e) {\n errored = true;\n // HACK: Since code elsewhere is relying on the \"truthiness\" of the\n // return here, we can't have it return \"\" or 0 or false.\n // TODO: Clean this up when we refactor schedulers mid-version-8 or so.\n errorValue = e ? e : new Error('Scheduled action threw falsy error');\n }\n if (errored) {\n this.unsubscribe();\n return errorValue;\n }\n }\n\n unsubscribe() {\n if (!this.closed) {\n const { id, scheduler } = this;\n const { actions } = scheduler;\n\n this.work = this.state = this.scheduler = null!;\n this.pending = false;\n\n arrRemove(actions, this);\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, null);\n }\n\n this.delay = null!;\n super.unsubscribe();\n }\n }\n}\n", "import { Action } from './scheduler/Action';\nimport { Subscription } from './Subscription';\nimport { SchedulerLike, SchedulerAction } from './types';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * An execution context and a data structure to order tasks and schedule their\n * execution. Provides a notion of (potentially virtual) time, through the\n * `now()` getter method.\n *\n * Each unit of work in a Scheduler is called an `Action`.\n *\n * ```ts\n * class Scheduler {\n * now(): number;\n * schedule(work, delay?, state?): Subscription;\n * }\n * ```\n *\n * @class Scheduler\n * @deprecated Scheduler is an internal implementation detail of RxJS, and\n * should not be used directly. Rather, create your own class and implement\n * {@link SchedulerLike}. Will be made internal in v8.\n */\nexport class Scheduler implements SchedulerLike {\n public static now: () => number = dateTimestampProvider.now;\n\n constructor(private schedulerActionCtor: typeof Action, now: () => number = Scheduler.now) {\n this.now = now;\n }\n\n /**\n * A getter method that returns a number representing the current time\n * (at the time this function was called) according to the scheduler's own\n * internal clock.\n * @return {number} A number that represents the current time. May or may not\n * have a relation to wall-clock time. May or may not refer to a time unit\n * (e.g. milliseconds).\n */\n public now: () => number;\n\n /**\n * Schedules a function, `work`, for execution. May happen at some point in\n * the future, according to the `delay` parameter, if specified. May be passed\n * some context object, `state`, which will be passed to the `work` function.\n *\n * The given arguments will be processed an stored as an Action object in a\n * queue of actions.\n *\n * @param {function(state: ?T): ?Subscription} work A function representing a\n * task, or some unit of work to be executed by the Scheduler.\n * @param {number} [delay] Time to wait before executing the work, where the\n * time unit is implicit and defined by the Scheduler itself.\n * @param {T} [state] Some contextual data that the `work` function uses when\n * called by the Scheduler.\n * @return {Subscription} A subscription in order to be able to unsubscribe\n * the scheduled work.\n */\n public schedule(work: (this: SchedulerAction, state?: T) => void, delay: number = 0, state?: T): Subscription {\n return new this.schedulerActionCtor(this, work).schedule(state, delay);\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Action } from './Action';\nimport { AsyncAction } from './AsyncAction';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncScheduler extends Scheduler {\n public actions: Array> = [];\n /**\n * A flag to indicate whether the Scheduler is currently executing a batch of\n * queued actions.\n * @type {boolean}\n * @internal\n */\n public _active: boolean = false;\n /**\n * An internal ID used to track the latest asynchronous task such as those\n * coming from `setTimeout`, `setInterval`, `requestAnimationFrame`, and\n * others.\n * @type {any}\n * @internal\n */\n public _scheduled: TimerHandle | undefined;\n\n constructor(SchedulerAction: typeof Action, now: () => number = Scheduler.now) {\n super(SchedulerAction, now);\n }\n\n public flush(action: AsyncAction): void {\n const { actions } = this;\n\n if (this._active) {\n actions.push(action);\n return;\n }\n\n let error: any;\n this._active = true;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions.shift()!)); // exhaust the scheduler queue\n\n this._active = false;\n\n if (error) {\n while ((action = actions.shift()!)) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\n/**\n *\n * Async Scheduler\n *\n * Schedule task as if you used setTimeout(task, duration)\n *\n * `async` scheduler schedules tasks asynchronously, by putting them on the JavaScript\n * event loop queue. It is best used to delay tasks in time or to schedule tasks repeating\n * in intervals.\n *\n * If you just want to \"defer\" task, that is to perform it right after currently\n * executing synchronous code ends (commonly achieved by `setTimeout(deferredTask, 0)`),\n * better choice will be the {@link asapScheduler} scheduler.\n *\n * ## Examples\n * Use async scheduler to delay task\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * const task = () => console.log('it works!');\n *\n * asyncScheduler.schedule(task, 2000);\n *\n * // After 2 seconds logs:\n * // \"it works!\"\n * ```\n *\n * Use async scheduler to repeat task in intervals\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * function task(state) {\n * console.log(state);\n * this.schedule(state + 1, 1000); // `this` references currently executing Action,\n * // which we reschedule with new state and delay\n * }\n *\n * asyncScheduler.schedule(task, 3000, 0);\n *\n * // Logs:\n * // 0 after 3s\n * // 1 after 4s\n * // 2 after 5s\n * // 3 after 6s\n * ```\n */\n\nexport const asyncScheduler = new AsyncScheduler(AsyncAction);\n\n/**\n * @deprecated Renamed to {@link asyncScheduler}. Will be removed in v8.\n */\nexport const async = asyncScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { Subscription } from '../Subscription';\nimport { QueueScheduler } from './QueueScheduler';\nimport { SchedulerAction } from '../types';\nimport { TimerHandle } from './timerHandle';\n\nexport class QueueAction extends AsyncAction {\n constructor(protected scheduler: QueueScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (delay > 0) {\n return super.schedule(state, delay);\n }\n this.delay = delay;\n this.state = state;\n this.scheduler.flush(this);\n return this;\n }\n\n public execute(state: T, delay: number): any {\n return delay > 0 || this.closed ? super.execute(state, delay) : this._execute(state, delay);\n }\n\n protected requestAsyncId(scheduler: QueueScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n\n if ((delay != null && delay > 0) || (delay == null && this.delay > 0)) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n\n // Otherwise flush the scheduler starting with this action.\n scheduler.flush(this);\n\n // HACK: In the past, this was returning `void`. However, `void` isn't a valid\n // `TimerHandle`, and generally the return value here isn't really used. So the\n // compromise is to return `0` which is both \"falsy\" and a valid `TimerHandle`,\n // as opposed to refactoring every other instanceo of `requestAsyncId`.\n return 0;\n }\n}\n", "import { AsyncScheduler } from './AsyncScheduler';\n\nexport class QueueScheduler extends AsyncScheduler {\n}\n", "import { QueueAction } from './QueueAction';\nimport { QueueScheduler } from './QueueScheduler';\n\n/**\n *\n * Queue Scheduler\n *\n * Put every next task on a queue, instead of executing it immediately\n *\n * `queue` scheduler, when used with delay, behaves the same as {@link asyncScheduler} scheduler.\n *\n * When used without delay, it schedules given task synchronously - executes it right when\n * it is scheduled. However when called recursively, that is when inside the scheduled task,\n * another task is scheduled with queue scheduler, instead of executing immediately as well,\n * that task will be put on a queue and wait for current one to finish.\n *\n * This means that when you execute task with `queue` scheduler, you are sure it will end\n * before any other task scheduled with that scheduler will start.\n *\n * ## Examples\n * Schedule recursively first, then do something\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(() => {\n * queueScheduler.schedule(() => console.log('second')); // will not happen now, but will be put on a queue\n *\n * console.log('first');\n * });\n *\n * // Logs:\n * // \"first\"\n * // \"second\"\n * ```\n *\n * Reschedule itself recursively\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(function(state) {\n * if (state !== 0) {\n * console.log('before', state);\n * this.schedule(state - 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * console.log('after', state);\n * }\n * }, 0, 3);\n *\n * // In scheduler that runs recursively, you would expect:\n * // \"before\", 3\n * // \"before\", 2\n * // \"before\", 1\n * // \"after\", 1\n * // \"after\", 2\n * // \"after\", 3\n *\n * // But with queue it logs:\n * // \"before\", 3\n * // \"after\", 3\n * // \"before\", 2\n * // \"after\", 2\n * // \"before\", 1\n * // \"after\", 1\n * ```\n */\n\nexport const queueScheduler = new QueueScheduler(QueueAction);\n\n/**\n * @deprecated Renamed to {@link queueScheduler}. Will be removed in v8.\n */\nexport const queue = queueScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\nimport { SchedulerAction } from '../types';\nimport { animationFrameProvider } from './animationFrameProvider';\nimport { TimerHandle } from './timerHandle';\n\nexport class AnimationFrameAction extends AsyncAction {\n constructor(protected scheduler: AnimationFrameScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n protected requestAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay is greater than 0, request as an async action.\n if (delay !== null && delay > 0) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n // Push the action to the end of the scheduler queue.\n scheduler.actions.push(this);\n // If an animation frame has already been requested, don't request another\n // one. If an animation frame hasn't been requested yet, request one. Return\n // the current animation frame request id.\n return scheduler._scheduled || (scheduler._scheduled = animationFrameProvider.requestAnimationFrame(() => scheduler.flush(undefined)));\n }\n\n protected recycleAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle | undefined {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n if (delay != null ? delay > 0 : this.delay > 0) {\n return super.recycleAsyncId(scheduler, id, delay);\n }\n // If the scheduler queue has no remaining actions with the same async id,\n // cancel the requested animation frame and set the scheduled flag to\n // undefined so the next AnimationFrameAction will request its own.\n const { actions } = scheduler;\n if (id != null && actions[actions.length - 1]?.id !== id) {\n animationFrameProvider.cancelAnimationFrame(id as number);\n scheduler._scheduled = undefined;\n }\n // Return undefined so the action knows to request a new async id if it's rescheduled.\n return undefined;\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\nexport class AnimationFrameScheduler extends AsyncScheduler {\n public flush(action?: AsyncAction): void {\n this._active = true;\n // The async id that effects a call to flush is stored in _scheduled.\n // Before executing an action, it's necessary to check the action's async\n // id to determine whether it's supposed to be executed in the current\n // flush.\n // Previous implementations of this method used a count to determine this,\n // but that was unsound, as actions that are unsubscribed - i.e. cancelled -\n // are removed from the actions array and that can shift actions that are\n // scheduled to be executed in a subsequent flush into positions at which\n // they are executed within the current flush.\n const flushId = this._scheduled;\n this._scheduled = undefined;\n\n const { actions } = this;\n let error: any;\n action = action || actions.shift()!;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions[0]) && action.id === flushId && actions.shift());\n\n this._active = false;\n\n if (error) {\n while ((action = actions[0]) && action.id === flushId && actions.shift()) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AnimationFrameAction } from './AnimationFrameAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\n\n/**\n *\n * Animation Frame Scheduler\n *\n * Perform task when `window.requestAnimationFrame` would fire\n *\n * When `animationFrame` scheduler is used with delay, it will fall back to {@link asyncScheduler} scheduler\n * behaviour.\n *\n * Without delay, `animationFrame` scheduler can be used to create smooth browser animations.\n * It makes sure scheduled task will happen just before next browser content repaint,\n * thus performing animations as efficiently as possible.\n *\n * ## Example\n * Schedule div height animation\n * ```ts\n * // html:
\n * import { animationFrameScheduler } from 'rxjs';\n *\n * const div = document.querySelector('div');\n *\n * animationFrameScheduler.schedule(function(height) {\n * div.style.height = height + \"px\";\n *\n * this.schedule(height + 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * }, 0, 0);\n *\n * // You will see a div element growing in height\n * ```\n */\n\nexport const animationFrameScheduler = new AnimationFrameScheduler(AnimationFrameAction);\n\n/**\n * @deprecated Renamed to {@link animationFrameScheduler}. Will be removed in v8.\n */\nexport const animationFrame = animationFrameScheduler;\n", "import { Observable } from '../Observable';\nimport { SchedulerLike } from '../types';\n\n/**\n * A simple Observable that emits no items to the Observer and immediately\n * emits a complete notification.\n *\n * Just emits 'complete', and nothing else.\n *\n * ![](empty.png)\n *\n * A simple Observable that only emits the complete notification. It can be used\n * for composing with other Observables, such as in a {@link mergeMap}.\n *\n * ## Examples\n *\n * Log complete notification\n *\n * ```ts\n * import { EMPTY } from 'rxjs';\n *\n * EMPTY.subscribe({\n * next: () => console.log('Next'),\n * complete: () => console.log('Complete!')\n * });\n *\n * // Outputs\n * // Complete!\n * ```\n *\n * Emit the number 7, then complete\n *\n * ```ts\n * import { EMPTY, startWith } from 'rxjs';\n *\n * const result = EMPTY.pipe(startWith(7));\n * result.subscribe(x => console.log(x));\n *\n * // Outputs\n * // 7\n * ```\n *\n * Map and flatten only odd numbers to the sequence `'a'`, `'b'`, `'c'`\n *\n * ```ts\n * import { interval, mergeMap, of, EMPTY } from 'rxjs';\n *\n * const interval$ = interval(1000);\n * const result = interval$.pipe(\n * mergeMap(x => x % 2 === 1 ? of('a', 'b', 'c') : EMPTY),\n * );\n * result.subscribe(x => console.log(x));\n *\n * // Results in the following to the console:\n * // x is equal to the count on the interval, e.g. (0, 1, 2, 3, ...)\n * // x will occur every 1000ms\n * // if x % 2 is equal to 1, print a, b, c (each on its own)\n * // if x % 2 is not equal to 1, nothing will be output\n * ```\n *\n * @see {@link Observable}\n * @see {@link NEVER}\n * @see {@link of}\n * @see {@link throwError}\n */\nexport const EMPTY = new Observable((subscriber) => subscriber.complete());\n\n/**\n * @param scheduler A {@link SchedulerLike} to use for scheduling\n * the emission of the complete notification.\n * @deprecated Replaced with the {@link EMPTY} constant or {@link scheduled} (e.g. `scheduled([], scheduler)`). Will be removed in v8.\n */\nexport function empty(scheduler?: SchedulerLike) {\n return scheduler ? emptyScheduled(scheduler) : EMPTY;\n}\n\nfunction emptyScheduled(scheduler: SchedulerLike) {\n return new Observable((subscriber) => scheduler.schedule(() => subscriber.complete()));\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport function isScheduler(value: any): value is SchedulerLike {\n return value && isFunction(value.schedule);\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\nimport { isScheduler } from './isScheduler';\n\nfunction last(arr: T[]): T | undefined {\n return arr[arr.length - 1];\n}\n\nexport function popResultSelector(args: any[]): ((...args: unknown[]) => unknown) | undefined {\n return isFunction(last(args)) ? args.pop() : undefined;\n}\n\nexport function popScheduler(args: any[]): SchedulerLike | undefined {\n return isScheduler(last(args)) ? args.pop() : undefined;\n}\n\nexport function popNumber(args: any[], defaultValue: number): number {\n return typeof last(args) === 'number' ? args.pop()! : defaultValue;\n}\n", "export const isArrayLike = ((x: any): x is ArrayLike => x && typeof x.length === 'number' && typeof x !== 'function');", "import { isFunction } from \"./isFunction\";\n\n/**\n * Tests to see if the object is \"thennable\".\n * @param value the object to test\n */\nexport function isPromise(value: any): value is PromiseLike {\n return isFunction(value?.then);\n}\n", "import { InteropObservable } from '../types';\nimport { observable as Symbol_observable } from '../symbol/observable';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being Observable (but not necessary an Rx Observable) */\nexport function isInteropObservable(input: any): input is InteropObservable {\n return isFunction(input[Symbol_observable]);\n}\n", "import { isFunction } from './isFunction';\n\nexport function isAsyncIterable(obj: any): obj is AsyncIterable {\n return Symbol.asyncIterator && isFunction(obj?.[Symbol.asyncIterator]);\n}\n", "/**\n * Creates the TypeError to throw if an invalid object is passed to `from` or `scheduled`.\n * @param input The object that was passed.\n */\nexport function createInvalidObservableTypeError(input: any) {\n // TODO: We should create error codes that can be looked up, so this can be less verbose.\n return new TypeError(\n `You provided ${\n input !== null && typeof input === 'object' ? 'an invalid object' : `'${input}'`\n } where a stream was expected. You can provide an Observable, Promise, ReadableStream, Array, AsyncIterable, or Iterable.`\n );\n}\n", "export function getSymbolIterator(): symbol {\n if (typeof Symbol !== 'function' || !Symbol.iterator) {\n return '@@iterator' as any;\n }\n\n return Symbol.iterator;\n}\n\nexport const iterator = getSymbolIterator();\n", "import { iterator as Symbol_iterator } from '../symbol/iterator';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being an Iterable */\nexport function isIterable(input: any): input is Iterable {\n return isFunction(input?.[Symbol_iterator]);\n}\n", "import { ReadableStreamLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport async function* readableStreamLikeToAsyncGenerator(readableStream: ReadableStreamLike): AsyncGenerator {\n const reader = readableStream.getReader();\n try {\n while (true) {\n const { value, done } = await reader.read();\n if (done) {\n return;\n }\n yield value!;\n }\n } finally {\n reader.releaseLock();\n }\n}\n\nexport function isReadableStreamLike(obj: any): obj is ReadableStreamLike {\n // We don't want to use instanceof checks because they would return\n // false for instances from another Realm, like an ` + +### 4. Diagrams with Mermaid + +- **Flowcharts**: + +```mermaid + graph TD + A[Start] --> B[Analyze Data] + B --> C{Is Data Large?} + C -->|Yes| D[Apply Big Data Solutions] + C -->|No| E[Use Traditional Methods] + D --> F[Machine Learning] + E --> G[Statistical Analysis] + F --> H{Model Accurate?} + G --> I[Report Results] + H -->|Yes| J[Deploy Model] + H -->|No| K[Refine Model] + J --> L[Monitor Performance] + K --> F + L --> M[End: Success] + I --> N[End: Report Generated] + style A fill:#f9f,stroke:#333,stroke-width:2px + style M fill:#9f9,stroke:#333,stroke-width:2px + style N fill:#9f9,stroke:#333,stroke-width:2px +``` + +- **Mind Maps**: +```mermaid + mindmap + root((ESIIL)) + section Data Sources + Satellite Imagery + ::icon(fa fa-satellite) + Remote Sensing Data + Drones + Aircraft + On-ground Sensors + Weather Stations + IoT Devices + Open Environmental Data + Public Datasets + ::icon(fa fa-database) + section Research Focus + Climate Change Analysis + Ice Melt Patterns + Sea Level Rise + Biodiversity Monitoring + Species Distribution + Habitat Fragmentation + Geospatial Analysis Techniques + Machine Learning Models + Predictive Analytics + section Applications + Conservation Strategies + ::icon(fa fa-leaf) + Urban Planning + Green Spaces + Disaster Response + Flood Mapping + Wildfire Tracking + section Tools and Technologies + GIS Software + QGIS + ArcGIS + Programming Languages + Python + R + Cloud Computing Platforms + AWS + Google Earth Engine + Data Visualization + D3.js + Tableau +``` + +- **Timelines**: + +```mermaid +gantt + title ESIIL Year 2 Project Schedule + dateFormat YYYY-MM-DD + section CI + Sovereign OASIS via private jupiterhubs :2024-08-01, 2024-10-30 + OASIS documentation :2024-09-15, 70d + Data cube OASIS via cyverse account :2024-09-15, 100d + Integrate with ESIIL User Management system :2024-08-01, 2024-11-30 + Build badges to deploy DE from mkdoc :2024-09-01, 2024-12-15 + Streamline Github ssh key management :2024-10-01, 2024-12-31 + Cyverse support (R proxy link) :2024-11-01, 2024-12-31 + Cyverse use summary and statistics :2024-08-01, 2024-12-15 + + section CI Consultation and Education + Conferences/Invited talks :2024-08-01, 2024-12-31 + Office hours :2024-08-15, 2024-12-15 + Proposals :2024-09-01, 2024-11-15 + Private lessons :2024-09-15, 2024-11-30 + Pre-event trainings :2024-10-01, 2024-12-15 + Textbook development w/ education team :2024-08-01, 2024-12-15 + Train the trainers / group lessons :2024-08-15, 2024-11-30 + Tribal engagement :2024-09-01, 2024-12-15 + Ethical Space training :2024-09-15, 2024-12-31 + + section CI Design and Build + Data library (repository) :2024-08-01, 2024-10-30 + Analytics library (repository) :2024-08-15, 2024-11-15 + Containers (repository) :2024-09-01, 2024-11-30 + Cloud infrastructure templates (repository) :2024-09-15, 2024-12-15 + Tribal resilience Data Cube :2024-10-01, 2024-12-31 +``` + +```mermaid + +%%{init: { 'logLevel': 'debug', 'theme': 'base', 'gitGraph': {'rotateCommitLabel': true}} }%% +gitGraph + commit id: "Start from template" + branch c1 + commit id: "Set up SSH key pair" + commit id: "Modify _config.yml for GitHub Pages" + commit id: "Initial website structure" + commit id: "Add new markdown pages" + commit id: "Update navigation tree" + commit id: "Edit existing pages" + commit id: "Delete old markdown pages" + commit id: "Finalize website updates" + commit id: "Add new markdown pages" + commit id: "Update navigation tree" +checkout c1 + + branch b1 + + commit + commit + checkout c1 + merge b1 +``` + +```mermaid +%%{init: {"quadrantChart": {"chartWidth": 400, "chartHeight": 400}, "themeVariables": {"quadrant1TextFill": "#ff0000"} }}%% +quadrantChart + x-axis Urgent --> Not Urgent + y-axis Not Important --> "Important ❤" + quadrant-1 Plan + quadrant-2 Do + quadrant-3 Delegate + quadrant-4 Delete +``` + + +```mermaid +timeline + title Major Events in Environmental Science and Data Science + section Environmental Science + 19th century : Foundations in Ecology and Conservation + 1962 : Publication of 'Silent Spring' by Rachel Carson + 1970 : First Earth Day + 1987 : Brundtland Report introduces Sustainable Development + 1992 : Rio Earth Summit + 2015 : Paris Agreement on Climate Change + section Data Science + 1960s-1970s : Development of Database Management Systems + 1980s : Emergence of Data Warehousing + 1990s : Growth of the World Wide Web and Data Mining + 2000s : Big Data and Predictive Analytics + 2010s : AI and Machine Learning Revolution + 2020s : Integration of AI in Environmental Research +``` + + + + +```mermaid +erDiagram + CAR ||--o{ NAMED-DRIVER : allows + CAR { + string registrationNumber + string make + string model + } + PERSON ||--o{ NAMED-DRIVER : is + PERSON { + string firstName + string lastName + int age + } +``` + +```mermaid +--- +config: + sankey: + showValues: false +--- +sankey-beta + +NASA Data,Big Data Harmonization,100 + Satellite Imagery,Big Data Harmonization,80 + Open Environmental Data,Big Data Harmonization,70 + Remote Sensing Data,Big Data Harmonization,90 + Big Data Harmonization, Data Analysis and Integration,340 + Data Analysis and Integration,Climate Change Research,100 + Data Analysis and Integration,Biodiversity Monitoring,80 + Data Analysis and Integration,Geospatial Mapping,60 + Data Analysis and Integration,Urban Planning,50 + Data Analysis and Integration,Disaster Response,50 +``` + + +### 5. Interactive Elements + +- **Hyperlinks**: Use the format `[link text](URL)`. + - [Google](https://www.google.com) + - [Play Tetris](https://tetris.com/play-tetris) + +- **Embedding Interactive Content**: Use HTML tags or specific platform embed codes. + - `` + + + + +### 6. Math Notation + +Markdown can be combined with LaTeX for mathematical notation, useful in environmental data science for expressing statistical distributions, coordinate systems, and more. This requires a Markdown renderer with LaTeX support (like MathJax or KaTeX). + +- **Inline Math**: Use single dollar signs for inline math expressions. Representing the normal distribution. + + Example: The probability density function of the normal distribution is given by $f(x|\mu,\sigma) = \frac{1}{\sigma\sqrt{2\pi}}e^{-\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2}$.` + +- **Display Math**: Use double dollar signs for standalone equations. + + Example: + $$ + f(x|\mu,\sigma) = \frac{1}{\sigma\sqrt{2\pi}}e^{-\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2} + $$ + + +- **Common LaTeX Elements for Environmental Data Science**: + - **Statistical Distributions**: + - Normal Distribution: `\frac{1}{\sigma\sqrt{2\pi}}e^{-\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2}` for $\frac{1}{\sigma\sqrt{2\pi}}e^{-\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2}$ + - Poisson Distribution: `P(k; \lambda) = \frac{\lambda^k e^{-\lambda}}{k!}` for $P(k; \lambda) = \frac{\lambda^k e^{-\lambda}}{k!}$ + - **Coordinate Systems**: + - Spherical Coordinates: `(r, \theta, \phi)` for $(r, \theta, \phi)$ + - Cartesian Coordinates: `(x, y, z)` for $(x, y, z)$ + - **Geospatial Equations**: + - Haversine Formula for Distance: `a = \sin^2\left(\frac{\Delta\phi}{2}\right) + \cos(\phi_1)\cos(\phi_2)\sin^2\left(\frac{\Delta\lambda}{2}\right)` for $a = \sin^2\left(\frac{\Delta\phi}{2}\right) + \cos(\phi_1)\cos(\phi_2)\sin^2\left(\frac{\Delta\lambda}{2}\right)$ + +Note: The rendering of these equations as formatted math will depend on your Markdown viewer's LaTeX capabilities. + + + +### 7. Effective Citations in Markdown + +## Inline Citations + +- **Objective:** Learn how to use inline citations in Markdown. +- **Example Usage:** + - Inline citation of a single work: + - Some text with an inline citation. [@jones:envstudy:2020] + - Inline citation with specific page or section: + - More text with a specific section cited. [See @jones:envstudy:2020, §4.2] + - Contrasting views: + - Discussion of a topic with a contrasting view. [Contra @smith:climatechange:2019, p. 78] + +## Footnote Citations + +- **Objective:** Understand how to use footnote citations in Markdown. +- **Example Usage:** + - Citing with a footnote: + - Some statement in the text.[^1] + - Multiple references to the same footnote: + - Another statement referring to the same source.[^1] + - A different citation: + - Additional comment with a new citation.[^2] + +## Creating Footnotes + +- **Example Syntax:** + - [^1]: First reference details. Example: Emma Jones, "Environmental Study," Nature Journal, May 2020, https://nature-journal.com/envstudy2020. + - [^2]: Second reference details. Example: David Smith, "Climate Change Controversies," Science Daily, August 2019, https://sciencedaily.com/climatechange2019. + + diff --git a/resources/notes_from_readings/index.html b/resources/notes_from_readings/index.html new file mode 100644 index 0000000..01d05d2 --- /dev/null +++ b/resources/notes_from_readings/index.html @@ -0,0 +1,1249 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Notes from readings - Keiko Seafood Supply Chain Anaysis + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Literature Reading Notes

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Reference Information

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  • Title:
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  • Authors:
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  • Publication Year:
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  • Journal/Source:
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  • DOI/URL:
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Summary

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  • Brief summary of the main objective, research question, or thesis of the literature.
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Key Findings

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  • Major findings or conclusions:
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  • Finding 1
    • +
  • Finding 2
    • +
  • ...
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Methodology

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  • Description of research methodology, techniques, or approaches.
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  • Notable tools, datasets, or analytical methods used.
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Theoretical Framework

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  • Theoretical models or frameworks underpinning the research.
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  • Positioning within the broader field.
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Critical Analysis

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  • Strengths: Well-executed aspects or convincing arguments.
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  • Limitations: Weaknesses, gaps, or biases.
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  • Insights: New understandings or perspectives gained.
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Connections to Other Work

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  • Similarities or differences with other readings.
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  • Complementarity to other studies.
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Quotations and Notes

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  • Significant quotes:
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  • "Quote here." - Author Name, page number
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  • Additional notes or comments.
    • +
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Personal Reflections

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  • Influence on understanding or perspective.
    • +
  • Potential impact on future research or studies.
    • +
+

Action Items

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    +
  • Follow-up actions such as readings, discussions, or research activities:
    • +
  • [ ] Action item 1
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  • [ ] Action item 2
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  • ...
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+ + + + + + + + + + \ No newline at end of file diff --git a/resources/notes_from_readings/notes_from_readings.md b/resources/notes_from_readings/notes_from_readings.md new file mode 100644 index 0000000..f0dcbb8 --- /dev/null +++ b/resources/notes_from_readings/notes_from_readings.md @@ -0,0 +1,59 @@ +# Literature Reading Notes + +## Reference Information + +- **Title:** +- **Authors:** +- **Publication Year:** +- **Journal/Source:** +- **DOI/URL:** + +## Summary + +- Brief summary of the main objective, research question, or thesis of the literature. + +## Key Findings + +- Major findings or conclusions: + - Finding 1 + - Finding 2 + - ... + +## Methodology + +- Description of research methodology, techniques, or approaches. +- Notable tools, datasets, or analytical methods used. + +## Theoretical Framework + +- Theoretical models or frameworks underpinning the research. +- Positioning within the broader field. + +## Critical Analysis + +- **Strengths:** Well-executed aspects or convincing arguments. +- **Limitations:** Weaknesses, gaps, or biases. +- **Insights:** New understandings or perspectives gained. + +## Connections to Other Work + +- Similarities or differences with other readings. +- Complementarity to other studies. + +## Quotations and Notes + +- Significant quotes: + - "Quote here." - Author Name, page number +- Additional notes or comments. + +## Personal Reflections + +- Influence on understanding or perspective. +- Potential impact on future research or studies. + +## Action Items + +- Follow-up actions such as readings, discussions, or research activities: + - [ ] Action item 1 + - [ ] Action item 2 + - ... diff --git a/resources/participant_agreement/index.html b/resources/participant_agreement/index.html new file mode 100644 index 0000000..ca15c39 --- /dev/null +++ b/resources/participant_agreement/index.html @@ -0,0 +1,1192 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Participant agreement - Keiko Seafood Supply Chain Anaysis + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Participant Agreement

+

This Participant Agreement (“Agreement”) is a contract between you (“You/Your” or “Participant”) and THE REGENTS OF THE UNIVERSITY OF COLORADO, a body corporate, acting on behalf of the University of Colorado Boulder, a public institution of higher education created under the Constitution and the Law of the State of Colorado (the “University”), having offices located at 3100 Marine Street, Boulder, CO 80309.

+

In consideration of Your participation in the Forest Carbon Codefest (the “Codefest”), the sufficiency of which is hereby acknowledged, You agree as follows:

+

Environmental Data Science Innovation & Inclusion Lab (“ESIIL”) is a National Science Foundation (“NSF”) funded data synthesis center led by the University. Earth Lab is part of the Cooperative Institute for Research in Environmental Sciences (CIRES) specializing in data-intensive open, reproducible environmental science. Earth Lab and ESIIL will co-host the Codefest in person from March 12 through March 14, 2023.

+

Codefest Description

+

The Codefest aims to use big data to understand aboveground forest carbon dynamics. It brings together environmental scientists, data analysts, and forest experts from academia, non-profits, and the private sector under one roof to collaborate and provide solutions to on-the-ground needs in a respectful and inclusive environment. The Codefest provides resources to address environmental challenges, such as participation in training on Environmental Data Science and cyberinfrastructure. You will work on a cloud-based, highly secure platform that allows for the seamless integration of data sets and analytical tools. The Codefest encourages individuals participating to create a solution in the form of a research project, computer code, and models (individually and/or collectively, a “Solution”).

+

How to Participate

+

You will join a team of environmental scientists, data experts, and coders to explore curated data, consider the objectivity of the data, propose a scientific question that can be addressed with all or some of the data sets, and analyze the data in an attempt to answer your scientific question by the end of the event. You will present your Solution to the event community. Earth Lab and ESIIL will provide environmental data, cyberinfrastructure, cyberinfrastructure and data analytics training, and technical support. The team members of the winning Solution will receive a small monetary award. Details regarding how the winning Solution will be chosen and how the prize will be managed are outlined in the Official Rules for the Codefest (“Official Rules”).

+

Representations and Warranties

+

By and through Your participation in the Codefest, You represent and warrant the following:

+
    +
  • You have read, understand, and agree to abide by the Code of Conduct and Respectful Inclusive Collaboration Guidelines for the Forest Carbon Codefest (“Code of Conduct”) and the Official Rules.
    • +
  • Any decisions concerning the Code of Conduct, Official Rules, or any other matter relating to this Codefest by the University is final and binding on all Participants.
    • +
+

Codefest Assets

+

5.1 Access and Use

+

By participating in the Codefest, You may receive access to certain datasets, webinars, and/or other copyrighted materials (collectively, the “Codefest Assets”). You agree to follow all licenses, restrictions, and other instructions provided to You with the Codefest Assets.

+

5.2 Disclaimer

+

The Codefest Assets are provided “as is” without warranty of any kind, either express or implied, including, without limitation, any implied warranties of merchantability and fitness for a particular purpose. Without limiting the foregoing, the University does not warrant that the Materials will be suitable for Your Solution or that the operation or supply of the Codefest Assets will be uninterrupted or error free.

+

5.3 Restrictions

+

You agree not to access or use the Codefest Assets in a manner that may interfere with any other participants’ or users’ use of such assets, unless provided with express written consent by the University. Your access to and use of the Codefest Assets may be limited, throttled, or terminated at any time at the sole discretion of the University.

+

Intellectual Property

+

For purposes of this Agreement, “Intellectual Property” includes all copyright, patent, trademark, trade secret and other intellectual property rights.

+

6.1 Solution Publication

+

You agree to make Your Solution publicly available in GitHub under the MIT open-source license within five (5) months from the end of the Codefest.

+

6.2 Government Rights

+

In consideration of the funding provided by NSF for the Codefest, You hereby grant and agree to grant to the U.S. Government (i) a nonexclusive, non-transferable, irrevocable, royalty-free license to exercise or have exercised for or on behalf of the U.S. throughout the world all the exclusive rights provided by copyright in any copyrightable intellectual property that You create during the Codefest and (ii) a nonexclusive, non-transferable, irrevocable, paid-up license to practice, or have practiced for or on its behalf, any invention created by You during the Codefest throughout the world.

+

6.3 NSF Agreement and Invention Ownership

+

You acknowledge that the Codefest is subject to NSF’s Cooperative Agreement Terms and Conditions effective May 12, 2023. As such, the U.S. Government may be entitled to own any invention that You create during the Codefest as further outlined within 37 CFR 401 and the NSF Proposal & Award Policies and Procedures Guide. In such event, You agree to assign any invention created by You during the Codefest to the U.S. Government and to reasonably cooperate with the University and NSF to accomplish the same.

+

6.4 Representations and Warranties

+

You represent and warrant that You are legally entitled to grant the above licenses and other intellectual property rights as outlined in Sections 6.1, 6.2, and 6.3. If You are an individual, and if Your employer(s) and/or another third party has rights to Intellectual Property that You create that includes Your Solution, You represent that You have received permission to participate in the Codefest on behalf of that employer or third party and that Your employer or the third party has waived such rights for Your contributions.

+

6.5 Originality and Third-Party Materials

+

You represent that Your Solution is Your original creation. If you obtain permission under Section 6.5 to include third-party materials, You represent that Your Solution includes complete details of any third-party license or other restriction (including, but not limited to, related patents and trademarks) of which You are aware and which are associated with any part of Your Solution. You represent and warrant that You will not submit any materials to the University that You know or believe to have components that are malicious or harmful. You represent that You will perform a reasonable amount of due diligence in order to be properly informed of third-party licenses, infringing materials, or harmful content associated with any part of Your Solution.

+

6.6 Submission of External Work

+

Should You wish to submit work that is not Your original creation during the Codefest (and that is not a Codefest Asset), You may ask for permission from the University to incorporate such work into Your Solution. To request such permission, identify the complete details of the materials you wish to use, including any licenses or other restrictions (including, but not limited to, related patents, trademarks, and license agreements) of which You are personally aware. Request for permission to add materials created outside of the Codefest must be submitted in advance of the Codefest to: Tyler McIntosh; tyler.l.mcintosh@colorado.edu.

+

6.7 Notification of Changes

+

You agree to notify the University of any facts or circumstances of which You become aware that would make these representations inaccurate in any respect. You agree to notify the University of any administrative or court proceeding which involve Your Solution.

+

Limitation of Liability

+

TO THE EXTENT ALLOWED BY LAW, IN NO EVENT SHALL THE UNIVERSITY, ITS PARTNERS, LICENSORS, SERVICE PROVIDERS, OR ANY OF THEIR RESPECTIVE OFFICERS, DIRECTORS, AGENTS, EMPLOYEES OR REPRESENTATIVES, BE LIABLE FOR DIRECT, INCIDENTAL, CONSEQUENTIAL, EXEMPLARY OR PUNITIVE DAMAGES ARISING OUT OF OR IN CONNECTION WITH THE HACKATHON OR THIS AGREEMENT (HOWEVER ARISING, INCLUDING NEGLIGENCE). IF YOU HAVE A DISPUTE WITH ANY PARTICIPANT OR ANY OTHER THIRD PARTY, YOU RELEASE THE UNIVERSITY, ITS, PARTNERS, LICENSORS, AND SERVICE PROVIDERS, AND EACH OF THEIR RESPECTIVE OFFICERS, DIRECTORS, AGENTS, EMPLOYEES AND REPRESENTATIVES FROM ANY AND ALL CLAIMS, DEMANDS AND DAMAGES (ACTUAL AND CONSEQUENTIAL) OF EVERY KIND AND NATURE ARISING OUT OF OR IN ANY WAY CONNECTED WITH SUCH DISPUTES. YOU AGREE THAT ANY CLAIMS AGAINST UNIVERSITY ARISING OUT OF THE HACKATHON OR THIS AGREEMENT MUST BE FILED WITHIN ONE YEAR AFTER SUCH CLAIM AROSE; OTHERWISE, YOUR CLAIM IS PERMANENTLY BARRED.

+

Not an Offer or Contract of Employment

+

Under no circumstances will Your participation in the Codefest or anything in this Agreement be construed as an offer or contract of employment with the University.

+

Additional Terms

+
    +
  • You must be at least eighteen (18) years of age to participate in the Codefest. The Codefest is subject to applicable federal, state, and local laws.
    • +
  • The University reserves the right to permanently disqualify any person from the Codefest that it reasonably believes has violated this Agreement, the Code of Conduct, and/or the Official Rules.
    • +
  • Any attempt to deliberately damage the Codefest or the operation thereof is unlawful and subject to legal action by the University, which may seek damages to the fullest extent permitted by law.
    • +
  • The University assumes no responsibility for any injury or damage to Your or any other person’s computer relating to or resulting from entering or downloading materials or software in connection with the Codefest.
    • +
  • The University is not responsible for telecommunications, network, electronic, technical, or computer failures of any kind; for inaccurate transcription of entry information; for any human or electronic error; or for Solutions that are stolen, misdirected, garbled, delayed, lost, late, damaged, or returned.
    • +
  • The University reserves the right to cancel, modify, or suspend the Codefest or any element thereof (including, without limitation, this Agreement) without notice in any manner and for any reason (including, without limitation, in the event of any unanticipated occurrence that is not fully addressed in this Agreement).
    • +
  • The University may prohibit any person from participating in the Codefest, if such person shows a disregard for this Agreement; acts with an intent to annoy, abuse, threaten, or harass any other entrant or any agents or representatives of the University (or any associated, partners, licensors, or service providers for the University); or behaves in any other disruptive manner (as determined by the University in its sole discretion).
    • +
  • Nothing contained in this Agreement shall be construed as an express or implied waiver by University of its governmental immunity or of the governmental immunity of the State of Colorado.
    • +
  • Your Solutions shall not contain any item(s) that are either export-controlled under the International Traffic in Arms Regulations, or that appear on the Commerce Control List (except as EAR99) of the Export Administration Regulations.
    • +
+

Dispute Resolution

+

This Agreement and the Codefest shall be governed and construed in accordance with and governed by the laws of the state of Colorado without giving effect to conflict of law provisions.

+

Entire Agreement

+

This Agreement, along with the Official Rules, and the Event Code of Conduct, constitutes the entire agreement between the University and You with respect to the Codefest and supersedes all previous or contemporaneous oral or written agreements concerning the Codefest. In the event of a conflict between this Agreement, the Official Rules and/or the Event Code of Conduct, the conflict shall be resolved with the following order of precedence:

+
    +
  1. This Agreement
    2. +
  2. The Official Rules
    3. +
  3. The Event Code of Conduct
    4. +
+

Severability

+

The invalidity, illegality, or unenforceability of any one or more phrases, sentences, clauses, or sections in this Agreement does not affect the remaining portions of this Agreement.

+

If you have questions about the Codefest, please contact Tyler McIntosh at tyler.l.mcintosh@colorado.edu.

+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/resources/participant_agreement/participant_agreement.md b/resources/participant_agreement/participant_agreement.md new file mode 100644 index 0000000..1b8a5c7 --- /dev/null +++ b/resources/participant_agreement/participant_agreement.md @@ -0,0 +1,96 @@ +# Participant Agreement + +This Participant Agreement (“Agreement”) is a contract between you (“You/Your” or “Participant”) and THE REGENTS OF THE UNIVERSITY OF COLORADO, a body corporate, acting on behalf of the University of Colorado Boulder, a public institution of higher education created under the Constitution and the Law of the State of Colorado (the “University”), having offices located at 3100 Marine Street, Boulder, CO 80309. + +In consideration of Your participation in the Forest Carbon Codefest (the “Codefest”), the sufficiency of which is hereby acknowledged, You agree as follows: + +Environmental Data Science Innovation & Inclusion Lab (“ESIIL”) is a National Science Foundation (“NSF”) funded data synthesis center led by the University. Earth Lab is part of the Cooperative Institute for Research in Environmental Sciences (CIRES) specializing in data-intensive open, reproducible environmental science. Earth Lab and ESIIL will co-host the Codefest in person from March 12 through March 14, 2023. + +## Codefest Description + +The Codefest aims to use big data to understand aboveground forest carbon dynamics. It brings together environmental scientists, data analysts, and forest experts from academia, non-profits, and the private sector under one roof to collaborate and provide solutions to on-the-ground needs in a respectful and inclusive environment. The Codefest provides resources to address environmental challenges, such as participation in training on Environmental Data Science and cyberinfrastructure. You will work on a cloud-based, highly secure platform that allows for the seamless integration of data sets and analytical tools. The Codefest encourages individuals participating to create a solution in the form of a research project, computer code, and models (individually and/or collectively, a “Solution”). + +## How to Participate + +You will join a team of environmental scientists, data experts, and coders to explore curated data, consider the objectivity of the data, propose a scientific question that can be addressed with all or some of the data sets, and analyze the data in an attempt to answer your scientific question by the end of the event. You will present your Solution to the event community. Earth Lab and ESIIL will provide environmental data, cyberinfrastructure, cyberinfrastructure and data analytics training, and technical support. The team members of the winning Solution will receive a small monetary award. Details regarding how the winning Solution will be chosen and how the prize will be managed are outlined in the Official Rules for the Codefest (“Official Rules”). + +## Representations and Warranties + +By and through Your participation in the Codefest, You represent and warrant the following: + +- You have read, understand, and agree to abide by the Code of Conduct and Respectful Inclusive Collaboration Guidelines for the Forest Carbon Codefest (“Code of Conduct”) and the Official Rules. +- Any decisions concerning the Code of Conduct, Official Rules, or any other matter relating to this Codefest by the University is final and binding on all Participants. + +# Codefest Assets + +## 5.1 Access and Use +By participating in the Codefest, You may receive access to certain datasets, webinars, and/or other copyrighted materials (collectively, the “Codefest Assets”). You agree to follow all licenses, restrictions, and other instructions provided to You with the Codefest Assets. + +## 5.2 Disclaimer +The Codefest Assets are provided “as is” without warranty of any kind, either express or implied, including, without limitation, any implied warranties of merchantability and fitness for a particular purpose. Without limiting the foregoing, the University does not warrant that the Materials will be suitable for Your Solution or that the operation or supply of the Codefest Assets will be uninterrupted or error free. + +## 5.3 Restrictions +You agree not to access or use the Codefest Assets in a manner that may interfere with any other participants’ or users’ use of such assets, unless provided with express written consent by the University. Your access to and use of the Codefest Assets may be limited, throttled, or terminated at any time at the sole discretion of the University. + +# Intellectual Property + +For purposes of this Agreement, “Intellectual Property” includes all copyright, patent, trademark, trade secret and other intellectual property rights. + +## 6.1 Solution Publication +You agree to make Your Solution publicly available in GitHub under the MIT open-source license within five (5) months from the end of the Codefest. + +## 6.2 Government Rights +In consideration of the funding provided by NSF for the Codefest, You hereby grant and agree to grant to the U.S. Government (i) a nonexclusive, non-transferable, irrevocable, royalty-free license to exercise or have exercised for or on behalf of the U.S. throughout the world all the exclusive rights provided by copyright in any copyrightable intellectual property that You create during the Codefest and (ii) a nonexclusive, non-transferable, irrevocable, paid-up license to practice, or have practiced for or on its behalf, any invention created by You during the Codefest throughout the world. + +## 6.3 NSF Agreement and Invention Ownership +You acknowledge that the Codefest is subject to NSF’s Cooperative Agreement Terms and Conditions effective May 12, 2023. As such, the U.S. Government may be entitled to own any invention that You create during the Codefest as further outlined within 37 CFR 401 and the NSF Proposal & Award Policies and Procedures Guide. In such event, You agree to assign any invention created by You during the Codefest to the U.S. Government and to reasonably cooperate with the University and NSF to accomplish the same. + +## 6.4 Representations and Warranties +You represent and warrant that You are legally entitled to grant the above licenses and other intellectual property rights as outlined in Sections 6.1, 6.2, and 6.3. If You are an individual, and if Your employer(s) and/or another third party has rights to Intellectual Property that You create that includes Your Solution, You represent that You have received permission to participate in the Codefest on behalf of that employer or third party and that Your employer or the third party has waived such rights for Your contributions. + +## 6.5 Originality and Third-Party Materials +You represent that Your Solution is Your original creation. If you obtain permission under Section 6.5 to include third-party materials, You represent that Your Solution includes complete details of any third-party license or other restriction (including, but not limited to, related patents and trademarks) of which You are aware and which are associated with any part of Your Solution. You represent and warrant that You will not submit any materials to the University that You know or believe to have components that are malicious or harmful. You represent that You will perform a reasonable amount of due diligence in order to be properly informed of third-party licenses, infringing materials, or harmful content associated with any part of Your Solution. + +## 6.6 Submission of External Work +Should You wish to submit work that is not Your original creation during the Codefest (and that is not a Codefest Asset), You may ask for permission from the University to incorporate such work into Your Solution. To request such permission, identify the complete details of the materials you wish to use, including any licenses or other restrictions (including, but not limited to, related patents, trademarks, and license agreements) of which You are personally aware. Request for permission to add materials created outside of the Codefest must be submitted in advance of the Codefest to: Tyler McIntosh; [tyler.l.mcintosh@colorado.edu](mailto:tyler.l.mcintosh@colorado.edu). + +## 6.7 Notification of Changes +You agree to notify the University of any facts or circumstances of which You become aware that would make these representations inaccurate in any respect. You agree to notify the University of any administrative or court proceeding which involve Your Solution. + +# Limitation of Liability + +TO THE EXTENT ALLOWED BY LAW, IN NO EVENT SHALL THE UNIVERSITY, ITS PARTNERS, LICENSORS, SERVICE PROVIDERS, OR ANY OF THEIR RESPECTIVE OFFICERS, DIRECTORS, AGENTS, EMPLOYEES OR REPRESENTATIVES, BE LIABLE FOR DIRECT, INCIDENTAL, CONSEQUENTIAL, EXEMPLARY OR PUNITIVE DAMAGES ARISING OUT OF OR IN CONNECTION WITH THE HACKATHON OR THIS AGREEMENT (HOWEVER ARISING, INCLUDING NEGLIGENCE). IF YOU HAVE A DISPUTE WITH ANY PARTICIPANT OR ANY OTHER THIRD PARTY, YOU RELEASE THE UNIVERSITY, ITS, PARTNERS, LICENSORS, AND SERVICE PROVIDERS, AND EACH OF THEIR RESPECTIVE OFFICERS, DIRECTORS, AGENTS, EMPLOYEES AND REPRESENTATIVES FROM ANY AND ALL CLAIMS, DEMANDS AND DAMAGES (ACTUAL AND CONSEQUENTIAL) OF EVERY KIND AND NATURE ARISING OUT OF OR IN ANY WAY CONNECTED WITH SUCH DISPUTES. YOU AGREE THAT ANY CLAIMS AGAINST UNIVERSITY ARISING OUT OF THE HACKATHON OR THIS AGREEMENT MUST BE FILED WITHIN ONE YEAR AFTER SUCH CLAIM AROSE; OTHERWISE, YOUR CLAIM IS PERMANENTLY BARRED. + +# Not an Offer or Contract of Employment + +Under no circumstances will Your participation in the Codefest or anything in this Agreement be construed as an offer or contract of employment with the University. + +# Additional Terms + +- You must be at least eighteen (18) years of age to participate in the Codefest. 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In the event of a conflict between this Agreement, the Official Rules and/or the Event Code of Conduct, the conflict shall be resolved with the following order of precedence: + +1. This Agreement +2. The Official Rules +3. The Event Code of Conduct + +# Severability + +The invalidity, illegality, or unenforceability of any one or more phrases, sentences, clauses, or sections in this Agreement does not affect the remaining portions of this Agreement. + +If you have questions about the Codefest, please contact Tyler McIntosh at [tyler.l.mcintosh@colorado.edu](mailto:tyler.l.mcintosh@colorado.edu). diff --git a/resources/post_meeting_notes/index.html b/resources/post_meeting_notes/index.html new file mode 100644 index 0000000..845b808 --- /dev/null +++ b/resources/post_meeting_notes/index.html @@ -0,0 +1,1121 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Post-Meeting Notes Template - Keiko Seafood Supply Chain Anaysis + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Post-Meeting Notes Template

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Meeting Details

+
    +
  • Date:
    • +
  • Time:
    • +
  • Location:
    • +
  • Facilitator:
    • +
+

Attendees

+
    +
  • List of attendees
    • +
+

Agenda

+

1. Review of Meeting Goals

+
    +
  • Recap the primary objectives and if they were met.
    • +
+

2. Manuscript Development

+
    +
  • Discuss the status of current manuscript drafts.
    • +
  • Assign writing and editing tasks for different sections of the manuscript.
    • +
  • Set deadlines for draft completion and review.
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+

3. Research Highlights

+
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  • Identify key findings and outcomes that should be emphasized in the publications.
    • +
  • Discuss any new research insights that emerged from the meeting.
    • +
+

4. Publication Strategy

+
    +
  • Decide on target journals or conferences for publication submission.
    • +
  • Discuss authorship order and contributions.
    • +
  • Plan for any additional data or research needed to strengthen the manuscript.
    • +
+

5. Editing and Review Process

+
    +
  • Establish a peer-review process within the group for initial feedback.
    • +
  • Assign members to focus on specific aspects of editing, such as clarity, grammar, and technical accuracy.
    • +
  • Agree on a schedule for review rounds to ensure timely submission.
    • +
+

6. Responsibilities and Expectations

+
    +
  • Clearly define what is expected from each member before the next meeting.
    • +
  • Discuss communication methods for progress updates and questions.
    • +
+

7. Closing Remarks

+
    +
  • Summarize the discussion and confirm the action plan.
    • +
  • Reiterate the importance of meeting the set deadlines and maintaining communication.
    • +
+

Action Items

+
    +
  • [ ] Draft introduction section: Responsible person(s) - Deadline
    • +
  • [ ] Compile and analyze additional data: Responsible person(s) - Deadline
    • +
  • [ ] Draft methodology section: Responsible person(s) - Deadline
    • +
  • ...
    • +
  • [ ] Coordinate manuscript peer review: Responsible person(s) - Deadline
    • +
+

Next Steps

+
    +
  • Define the timeline for the submission process.
    • +
  • Schedule follow-up meetings or check-ins to monitor progress.
    • +
+

Notes

+
    +
  • (Additional notes, comments, or observations made during the meeting.)
    • +
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+
+ + + + + + + + + + \ No newline at end of file diff --git a/resources/post_meeting_notes/post_meeting_notes.md b/resources/post_meeting_notes/post_meeting_notes.md new file mode 100644 index 0000000..41615dc --- /dev/null +++ b/resources/post_meeting_notes/post_meeting_notes.md @@ -0,0 +1,57 @@ +# Post-Meeting Notes Template + +## Meeting Details +- **Date:** +- **Time:** +- **Location:** +- **Facilitator:** + +## Attendees +- List of attendees + +## Agenda + +### 1. Review of Meeting Goals +- Recap the primary objectives and if they were met. + +### 2. Manuscript Development +- Discuss the status of current manuscript drafts. +- Assign writing and editing tasks for different sections of the manuscript. +- Set deadlines for draft completion and review. + +### 3. Research Highlights +- Identify key findings and outcomes that should be emphasized in the publications. +- Discuss any new research insights that emerged from the meeting. + +### 4. Publication Strategy +- Decide on target journals or conferences for publication submission. +- Discuss authorship order and contributions. +- Plan for any additional data or research needed to strengthen the manuscript. + +### 5. Editing and Review Process +- Establish a peer-review process within the group for initial feedback. +- Assign members to focus on specific aspects of editing, such as clarity, grammar, and technical accuracy. +- Agree on a schedule for review rounds to ensure timely submission. + +### 6. Responsibilities and Expectations +- Clearly define what is expected from each member before the next meeting. +- Discuss communication methods for progress updates and questions. + +### 7. Closing Remarks +- Summarize the discussion and confirm the action plan. +- Reiterate the importance of meeting the set deadlines and maintaining communication. + +## Action Items +- [ ] Draft introduction section: Responsible person(s) - Deadline +- [ ] Compile and analyze additional data: Responsible person(s) - Deadline +- [ ] Draft methodology section: Responsible person(s) - Deadline +- ... +- [ ] Coordinate manuscript peer review: Responsible person(s) - Deadline + +## Next Steps +- Define the timeline for the submission process. +- Schedule follow-up meetings or check-ins to monitor progress. + +## Notes +- (Additional notes, comments, or observations made during the meeting.) + diff --git a/resources/pre_meeting_notes/index.html b/resources/pre_meeting_notes/index.html new file mode 100644 index 0000000..2f4b95d --- /dev/null +++ b/resources/pre_meeting_notes/index.html @@ -0,0 +1,1274 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + OASIS orientation - Keiko Seafood Supply Chain Anaysis + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Pre-Meeting Notes

+

Meeting Details

+
    +
  • Date:
    • +
  • Time:
    • +
  • Location:
    • +
  • Facilitator:
    • +
+

Attendees

+
    +
  • List of attendees
    • +
+

Agenda

+

1. Opening Remarks

+
    +
  • Brief welcome and overview of the meeting's objectives.
    • +
+

2. Introductions

+
    +
  • Roundtable introductions for all attendees.
    • +
  • Share a personal note or interesting fact to foster camaraderie.
    • +
+

3. Planning

+
    +
  • Discuss the agenda for the primary meetings.
    • +
  • Outline the key topics and issues to address.
    • +
  • Assign roles for note-taking, timekeeping, and facilitation in primary meetings.
    • +
+

4. Goal Setting

+
    +
  • Establish clear, actionable goals for the upcoming period.
    • +
  • Identify specific outcomes desired from the primary meetings.
    • +
  • Agree on metrics or indicators of success for these goals.
    • +
+

5. Camaraderie Building

+
    +
  • Icebreaker activity or team-building exercise.
    • +
  • Share expectations and aspirations for the group's progress.
    • +
  • Highlight the importance of collaboration and mutual support.
    • +
+

6. Open Discussion

+
    +
  • Allow for any additional topics, concerns, or ideas to be brought forward.
    • +
+

7. Closing Remarks

+
    +
  • Summarize the discussions and confirm the next steps.
    • +
  • Confirm dates and times for primary meetings.
    • +
  • Express appreciation for participation.
    • +
+

Action Items

+
    +
  • [ ] Action item 1: Responsible person(s) - Deadline
    • +
  • [ ] Action item 2: Responsible person(s) - Deadline
    • +
  • ...
    • +
+

Notes

+
    +
  • (Any additional notes or comments about the meeting.)
    • +
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/resources/pre_meeting_notes/pre_meeting_notes.md b/resources/pre_meeting_notes/pre_meeting_notes.md new file mode 100644 index 0000000..ff74ec0 --- /dev/null +++ b/resources/pre_meeting_notes/pre_meeting_notes.md @@ -0,0 +1,51 @@ +# Pre-Meeting Notes + +## Meeting Details +- **Date:** +- **Time:** +- **Location:** +- **Facilitator:** + +## Attendees +- List of attendees + +## Agenda + +### 1. Opening Remarks +- Brief welcome and overview of the meeting's objectives. + +### 2. Introductions +- Roundtable introductions for all attendees. +- Share a personal note or interesting fact to foster camaraderie. + +### 3. Planning +- Discuss the agenda for the primary meetings. +- Outline the key topics and issues to address. +- Assign roles for note-taking, timekeeping, and facilitation in primary meetings. + +### 4. Goal Setting +- Establish clear, actionable goals for the upcoming period. +- Identify specific outcomes desired from the primary meetings. +- Agree on metrics or indicators of success for these goals. + +### 5. Camaraderie Building +- Icebreaker activity or team-building exercise. +- Share expectations and aspirations for the group's progress. +- Highlight the importance of collaboration and mutual support. + +### 6. Open Discussion +- Allow for any additional topics, concerns, or ideas to be brought forward. + +### 7. Closing Remarks +- Summarize the discussions and confirm the next steps. +- Confirm dates and times for primary meetings. +- Express appreciation for participation. + +## Action Items +- [ ] Action item 1: Responsible person(s) - Deadline +- [ ] Action item 2: Responsible person(s) - Deadline +- ... + +## Notes +- (Any additional notes or comments about the meeting.) + diff --git a/resources/stac_mount_save/index.html b/resources/stac_mount_save/index.html new file mode 100644 index 0000000..c8f3c3e --- /dev/null +++ b/resources/stac_mount_save/index.html @@ -0,0 +1,1838 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + STAC - Keiko Seafood Supply Chain Anaysis + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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The art of making a data cube

+

Ty Tuff, ESIIL Data Scientist +2023-10-27

+

+#library(Rcpp)
+library(sf)
+library(gdalcubes)
+library(rstac)
+library(gdalUtils)
+library(terra)
+library(rgdal)
+library(reshape2)
+library(osmdata)
+library(terra)
+library(dplyr)
+library(stars)
+library(ggplot2)
+library(colorspace)
+library(geos)
+library(osmdata)
+library(ggthemes)
+library(tidyr)
+gdalcubes_options(parallel = 8)
+
+sf::sf_extSoftVersion()
+##           GEOS           GDAL         proj.4 GDAL_with_GEOS     USE_PROJ_H 
+##       "3.11.0"        "3.5.3"        "9.1.0"         "true"         "true" 
+##           PROJ 
+##        "9.1.0"
+gdalcubes_gdal_has_geos()
+## [1] TRUE
+
+library(osmdata)
+library(dplyr)
+library(sf)
+library(terra)
+library(tidyterra)
+library(glue)
+library(ggplot2)
+library(ggthemes)
+library(stars)
+library(magrittr)
+library(landsat)
+
+

The philosophy of moving data in the cloud

+

The philosophy of moving data in the cloud represents a paradigm shift +in how we approach data within our analytical processes. Instead of the +traditional method of transferring entire datasets to our local +environments, the cloud encourages a more efficient model: bring your +analysis to the data. This approach minimizes data movement and +leverages the cloud’s computational power and scalability. By utilizing +cloud-native tools and services, we can run our analyses directly on the +data where it resides, selectively accessing and processing only what is +necessary. This not only streamlines workflows but also significantly +reduces overheads related to data transfer and storage management. In +essence, the focus is on diverting computational resources to the data +rather than the cumbersome and resource-intensive practice of moving +large datasets to and fro.

+

‘To Make’ or ‘To Take’ a photo

+

The distinction between making and taking a photograph lies in the +approach and intent behind the camera. Taking a photo is often a +reactive process, where the photographer captures moments as they +naturally unfold, seizing the spontaneity of life without alteration. +It’s a passive form of photography where the emphasis is on the right +timing and the natural interplay of elements within the frame. On the +other hand, making a photo is a proactive and deliberate act. It is akin +to craftsmanship, where a professional photographer starts with a +concept and utilizes a variety of tools and techniques to stage and +construct the desired scene. They actively manipulate lighting, +composition, and subjects to create a photograph that aligns with their +pre-visualized artistic vision. While both methods use a camera to +produce a photograph, making a photo involves a creation process, +whereas taking a photo is about finding the scene.

+

David Yarrow is a famous photographer who ‘makes’ his photographs. + +

+

What does it mean to ‘make’ a data cube?

+

The artistry of Ansel Adams’ photography serves as a compelling analogy +for the meticulous craft of building a data cube from cloud data sources +using tools like STAC and GDAL VSI. Just as Adams would survey the +vastness of a landscape, discerning the interplay of light and shadow +upon the mountains before him, a data architect surveys the expanse of +available data. In this analogy, the raw data are the majestic mountains +and sweeping landscapes waiting to be captured. The STAC collection acts +as the photographer’s deliberate choice of scene, pointing the camera +lens—our data tools—towards the most telling and coherent dataset.

+

Just as Adams’ +photographs are more than mere records of a landscape, but rather a +confluence of his vision, technique, and the scene’s natural beauty, so +too is the data cube more than the sum of its parts. It is the artful +synthesis of information, crafted and composed with the skill and intent +of an artist, producing not just a tool for analysis but a harmonized, +data-driven portrait of the world it represents. The builder of the data +cube is, indeed, an artist, and the data cube their masterpiece, +revealing not just data, but a story, a perspective, a landscape sewn +from the raw material of cloud-sourced information.

+

As Adams would adjust his viewfinder, setting the boundaries of his +photographic frame, the data builder sets the view window, filtering and +transferring relevant data to their own medium, akin to Adams’ film. +This is where the raw data is transformed, organized into the structured +form of a data frame or data cube, a process not unlike the careful +development of a photograph in a darkroom. Here, the data cube creator, +much like Adams with his careful dodging and burning, harmonizes +disparate elements into a cohesive whole, each decision reflecting an +intention and vision for the final product.

+

1) The Rat through the Snake Problem: Scalability with Cloud Computing

+

Just like a snake that swallows a rat, traditional computing systems +often struggle to process the large volumes of environmental data — +they’re constrained by their static hardware limitations. Cloud +computing introduces a python-esque capability: massive scalability. By +migrating to the cloud, we essentially make the snake bigger, allowing +it to handle larger “prey.” Scalable computers in the cloud can grow +with the demand, providing the necessary computational power to process +extensive datasets, which is vital in a field where data volumes are +increasing exponentially.

+

Raster through a snake

+

2) The Antelope through the Python Problem: Streamlining with GDAL VSI

+

As we scale up, we encounter a new challenge: trying to pass an antelope +through a python — a metaphor for the next level of complexity in data +processing. The sheer size and complexity of the data can become +overwhelming. This is where GDAL’s Virtual File System (VSI) becomes our +ecological adaptation. VSI allows us to access remote data transparently +and more efficiently. Instead of ingesting the entire “antelope,” VSI +enables the “python” to dynamically access and process only the parts of +the data it needs, when it needs them, much like constriction before +digestion. This selective access minimizes the need for local storage +and expedites the data handling process.

+

Antelope through a Python

+

3) Drinking from a Fire Hose: Accelerated Inference with AI and ML

+

Once we’ve enabled the flow of large amounts of digestible data, we +encounter the metaphorical challenge of drinking from a fire hose. The +data, now flowing and accessible, is immense and rapid — posing a +challenge not just to store and process, but to understand and derive +meaning from in real-time. This is where artificial intelligence (AI) +and machine learning (ML) step in. These technologies act as a +sophisticated filtration system, enabling us to drink safely and +beneficially from the torrent. AI and ML can analyze patterns, make +predictions, and infer insights at a pace that keeps up with the fast +stream of data, turning raw information into actionable knowledge.

+

Inference through a firehose

+

By addressing these three pivotal challenges with cloud computing, GDAL +VSI, and AI/ML, we not only manage to consume the data effectively but +also transform our capabilities in environmental data science. We can +move from mere data ingestion to meaningful data interpretation, all at +a scale and speed necessary for impactful environmental analysis.

+

Mounting data

+

A void-filled Digital Elevation Model (DEM) is a comprehensive +topographical representation where any missing data points, known as +voids, have been filled in. These voids can occur due to various +reasons, such as clouds or technical errors during data collection. In a +void-filled DEM, these gaps are interpolated or estimated using the +surrounding data to create a continuous, seamless surface model. This +process enhances the utility and accuracy of the DEM for hydrological +modeling, terrain analysis, and other geographical applications. The +HydroSHEDS website +(https://www.hydrosheds.org/hydrosheds-core-downloads) provides access +to high-quality, void-filled DEM datasets like the +DEM_continuous_CONUS_15s, which users can download and easily integrate +into spatial analysis workflows using tools such as ‘terra’ in R, +allowing for sophisticated environmental and geographical research and +planning.

+
# Record start time
+a <- Sys.time()  
+
+# Create a string with the file path using glue, then download and read the DEM file as a raster object
+
+DEM_continuous_CONUS_15s <- glue(
+  "/vsizip/vsicurl/", #magic remote connection 
+  "https://data.hydrosheds.org/file/hydrosheds-v1-dem/hyd_na_dem_15s.zip", #copied link to download location
+  "/hyd_na_dem_15s.tif") %>% #path inside zip file
+  terra::rast()  
+
+# The 'glue' function constructs the file path string, which is then passed to 'terra::rast()' to read the DEM file into R as a raster layer. '/vsizip/vsicurl/' is a special GDAL virtual file system syntax that allows reading directly from a zipped file on a remote server.
+
+# Record end time and calculate the time difference
+b <- Sys.time()  
+difftime(b, a) 
+## Time difference of 4.603666 secs
+
+# The resulting raster object is stored in 'DEM_continuous_CONUS_15s', which now contains the void-filled DEM data ready for use
+
+DEM_continuous_CONUS_15s  # Prints out the details of the 'DEM_continuous_CONUS_15s' raster object
+## class       : SpatRaster 
+## dimensions  : 13920, 20640, 1  (nrow, ncol, nlyr)
+## resolution  : 0.004166667, 0.004166667  (x, y)
+## extent      : -138, -52, 5, 63  (xmin, xmax, ymin, ymax)
+## coord. ref. : lon/lat WGS 84 (EPSG:4326) 
+## source      : hyd_na_dem_15s.tif 
+## name        : Band_1
+
+# output is a SpatRaster, which is the object type associated with the 'terra' package. 
+
+

Continuous DEM for North America

+
# Record start time
+a <- Sys.time()
+
+ggplot() +
+  geom_spatraster(data=DEM_continuous_CONUS_15s) +
+  theme_tufte()
+
+

+

+b <- Sys.time()
+difftime(b, a)
+## Time difference of 52.49061 secs
+
+

Calculate Slope from that DEM

+
SLOPE_continuous_CONUS_15s <-  terra::terrain(DEM_continuous_CONUS_15s, "slope") 
+
+SLOPE_continuous_CONUS_15s
+## class       : SpatRaster 
+## dimensions  : 13920, 20640, 1  (nrow, ncol, nlyr)
+## resolution  : 0.004166667, 0.004166667  (x, y)
+## extent      : -138, -52, 5, 63  (xmin, xmax, ymin, ymax)
+## coord. ref. : lon/lat WGS 84 (EPSG:4326) 
+## source(s)   : memory
+## name        :    slope 
+## min value   :  0.00000 
+## max value   : 56.98691
+
+
# Record start time
+a <- Sys.time()
+
+ggplot() +
+  geom_spatraster(data=SLOPE_continuous_CONUS_15s) +
+  theme_tufte()
+
+

+

+b <- Sys.time()
+difftime(b, a)
+## Time difference of 3.859545 secs
+
+

Calculate aspect from DEM

+
ASPECT_continuous_CONUS_15s <-  terra::terrain(DEM_continuous_CONUS_15s, "aspect") 
+ASPECT_continuous_CONUS_15s
+## class       : SpatRaster 
+## dimensions  : 13920, 20640, 1  (nrow, ncol, nlyr)
+## resolution  : 0.004166667, 0.004166667  (x, y)
+## extent      : -138, -52, 5, 63  (xmin, xmax, ymin, ymax)
+## coord. ref. : lon/lat WGS 84 (EPSG:4326) 
+## source(s)   : memory
+## name        : aspect 
+## min value   :      0 
+## max value   :    360
+
+
# Record start time
+a <- Sys.time()
+
+ggplot() +
+  geom_spatraster(data=ASPECT_continuous_CONUS_15s) +
+  theme_tufte()
+
+

+

+b <- Sys.time()
+difftime(b, a)
+## Time difference of 3.650267 secs
+
+

Create a cube from those layers!

+
mini_stack <- c(DEM_continuous_CONUS_15s, SLOPE_continuous_CONUS_15s,ASPECT_continuous_CONUS_15s)
+mini_stack
+## class       : SpatRaster 
+## dimensions  : 13920, 20640, 3  (nrow, ncol, nlyr)
+## resolution  : 0.004166667, 0.004166667  (x, y)
+## extent      : -138, -52, 5, 63  (xmin, xmax, ymin, ymax)
+## coord. ref. : lon/lat WGS 84 (EPSG:4326) 
+## sources     : hyd_na_dem_15s.tif  
+##               memory  
+##               memory  
+## names       : Band_1,    slope, aspect 
+## min values  :     ? ,  0.00000,      0 
+## max values  :     ? , 56.98691,    360
+
+

Reproject and return the bounding box coordinates for our Area of +Interest

+
# Transform the filtered geometry to EPSG:4326 and store its bounding box
+# Record start time
+a <- Sys.time()
+
+DEM_continuous_CONUS_15s |>
+stars::st_as_stars() |> 
+  st_transform("EPSG:4326") |>
+  st_bbox() -> bbox_4326
+
+
+DEM_continuous_CONUS_15s |>
+stars::st_as_stars() |> 
+  st_transform("EPSG:32618") |>
+  st_bbox() -> bbox_32618
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 3.7653 mins
+
+

Get a polygon for Boulder County, reproject, and return bounding box. +This is so I can make a smaller search in the stac catalog.

+
boulder_county <- getbb("boulder, co", format_out="sf_polygon")
+
+boulder_county$multipolygon |> 
+  st_transform(crs =4326 ) |>
+  st_bbox() -> bbox_4326_boulder
+
+boulder_county$multipolygon |> 
+  st_transform(crs =32720 ) |>
+  st_bbox() -> bbox_32720_boulder
+
+

Get a polygon for the United States and crop it to be the same size as +the DEM above.

+
aoi <- getbb("United States", format_out="sf_polygon")
+
+conus <- aoi$multipolygon |>
+  st_crop(bbox_4326)
+
+
+ggplot(data=conus) +
+  geom_sf()
+
+

+

Search the Stac catalog.

+

STAC, or SpatioTemporal Asset Catalog, is an open-source specification +designed to standardize the way geospatial data is indexed and +discovered. Developed by Element 84 among others, it facilitates better +interoperability and sharing of geospatial assets by providing a common +language for describing them. STAC’s flexible design allows for easy +cataloging of data, making it simpler for individuals and systems to +search and retrieve geospatial information. By effectively organizing +data about the Earth’s spatial and temporal characteristics, STAC +enables users to harness the full power of the cloud and modern data +processing technologies, optimizing the way we access and analyze +environmental data on a global scale.

+
 stac("https://earth-search.aws.element84.com/v1") |>
+       get_request()
+## ###STACCatalog
+## - id: earth-search-aws
+## - description: A STAC API of public datasets on AWS
+## - field(s): stac_version, type, id, title, description, links, conformsTo
+
+

Element 84’s Earth Search is a STAC compliant search and discovery API +that offers users access to a vast collection of geospatial open +datasets hosted on AWS. It serves as a centralized search catalog +providing standardized metadata for these open datasets, designed to be +freely used and integrated into various applications. Alongside the API, +Element 84 also provides a web application named Earth Search Console, +which is map-centric and allows users to explore and visualize the data +contained within the Earth Search API’s catalog. This suite of tools is +part of Element 84’s initiative to make geospatial data more accessible +and actionable for a wide range of users and applications.

+
collection_formats()
+##    CHIRPS_v2_0_daily_p05_tif | Image collection format for CHIRPS v 2.0 daily
+##                              | global precipitation dataset (0.05 degrees
+##                              | resolution) from GeoTIFFs, expects list of .tif
+##                              | or .tif.gz files as input. [TAGS: CHIRPS,
+##                              | precipitation]
+##  CHIRPS_v2_0_monthly_p05_tif | Image collection format for CHIRPS v 2.0 monthly
+##                              | global precipitation dataset (0.05 degrees
+##                              | resolution) from GeoTIFFs, expects list of .tif
+##                              | or .tif.gz files as input. [TAGS: CHIRPS,
+##                              | precipitation]
+##            ESA_CCI_SM_ACTIVE | Collection format for ESA CCI soil moisture
+##                              | active product (version 4.7) [TAGS: Soil
+##                              | Moisture, ESA, CCI]
+##           ESA_CCI_SM_PASSIVE | Collection format for ESA CCI soil moisture
+##                              | passive product (version 4.7) [TAGS: Soil
+##                              | Moisture, ESA, CCI]
+##    GPM_IMERG_3B_DAY_GIS_V06A | Collection format for daily
+##                              | IMERG_3B_DAY_GIS_V06A data [TAGS: Precipitation,
+##                              | GPM, IMERG]
+##                      L8_L1TP | Collection format for Landsat 8 Level 1 TP
+##                              | product [TAGS: Landsat, USGS, Level 1, NASA]
+##                        L8_SR | Collection format for Landsat 8 surface
+##                              | reflectance product [TAGS: Landsat, USGS, Level
+##                              | 2, NASA, surface reflectance]
+##                        MAXAR | Preliminary collection format for MAXAR open
+##                              | data, visual only (under development) [TAGS: ]
+##                      MxD09GA | Collection format for selected bands from the
+##                              | MODIS MxD09GA (Aqua and Terra) product [TAGS:
+##                              | MODIS, surface reflectance]
+##                      MxD10A2 | Collection format for selected bands from the
+##                              | MODIS MxD10A2 (Aqua and Terra) v006 Snow Cover
+##                              | product [TAGS: MODIS, Snow Cover]
+##                      MxD11A1 | Collection format for selected bands from the
+##                              | MODIS MxD11A2 (Aqua and Terra) v006 Land Surface
+##                              | Temperature product [TAGS: MODIS, LST]
+##                      MxD11A2 | Collection format for selected bands from the
+##                              | MODIS MxD11A2 (Aqua and Terra) v006 Land Surface
+##                              | Temperature product [TAGS: MODIS, LST]
+##                      MxD13A2 | Collection format for selected bands from the
+##                              | MODIS MxD13A2 (Aqua and Terra) product [TAGS:
+##                              | MODIS, VI, NDVI, EVI]
+##                      MxD13A3 | Collection format for selected bands from the
+##                              | MODIS MxD13A3 (Aqua and Terra) product [TAGS:
+##                              | MODIS, VI, NDVI, EVI]
+##                      MxD13Q1 | Collection format for selected bands from the
+##                              | MODIS MxD13Q1 (Aqua and Terra) product [TAGS:
+##                              | MODIS, VI, NDVI, EVI]
+##                      MxD14A2 | Collection format for the MODIS MxD14A2 (Aqua
+##                              | and Terra) product [TAGS: MODIS, Fire]
+## PlanetScope_3B_AnalyticMS_SR | Image collection format for PlanetScope 4-band
+##                              | scenes [TAGS: PlanetScope, BOA, Surface
+##                              | Reflectance]
+##                Sentinel2_L1C | Image collection format for Sentinel 2 Level 1C
+##                              | data as downloaded from the Copernicus Open
+##                              | Access Hub, expects a list of file paths as
+##                              | input. The format works on original ZIP
+##                              | compressed as well as uncompressed imagery.
+##                              | [TAGS: Sentinel, Copernicus, ESA, TOA]
+##            Sentinel2_L1C_AWS | Image collection format for Sentinel 2 Level 1C
+##                              | data in AWS [TAGS: Sentinel, Copernicus, ESA,
+##                              | TOA]
+##                Sentinel2_L2A | Image collection format for Sentinel 2 Level 2A
+##                              | data as downloaded from the Copernicus Open
+##                              | Access Hub, expects a list of file paths as
+##                              | input. The format should work on original ZIP
+##                              | compressed as well as uncompressed imagery.
+##                              | [TAGS: Sentinel, Copernicus, ESA, BOA, Surface
+##                              | Reflectance]
+##          Sentinel2_L2A_THEIA | Image collection format for Sentinel 2 Level 2A
+##                              | data as downloaded from Theia. [TAGS: Sentinel,
+##                              | ESA, Flat Reflectance, Theia]
+
+

Building a stac collection by aiming your camera at the landscape

+

Creating a STAC collection is akin to a photographer framing a shot; the +landscape is rich with diverse data, mirroring a scene bustling with +potential subjects, colors, and light. Just as a photographer selects a +portion of the vista to capture, focusing on elements that will compose +a compelling image, a data scientist must similarly navigate the vast +data terrain. They must ‘point their camera’ judiciously, ensuring that +the ‘frame’ encapsulates the precise data needed. This careful selection +is crucial, as it determines the relevance and quality of the data +collection, much like the photographer’s choice dictates the story a +photograph will tell.

+

+
# Record start time
+a <- Sys.time()
+
+# Initialize STAC connection
+s = stac("https://earth-search.aws.element84.com/v0")
+
+
+# Search for Sentinel-2 images within specified bounding box and date range
+#22 Million items
+items = s |>
+    stac_search(collections = "sentinel-s2-l2a-cogs",
+                bbox = c(bbox_4326_boulder["xmin"], 
+                         bbox_4326_boulder["ymin"],
+                         bbox_4326_boulder["xmax"], 
+                         bbox_4326_boulder["ymax"]), 
+                datetime = "2021-05-15/2021-05-16") |>
+    post_request() |>
+    items_fetch(progress = FALSE)
+
+# Print number of found items
+length(items$features)
+## [1] 1
+
+# Prepare the assets for analysis
+library(gdalcubes)
+assets = c("B01", "B02", "B03", "B04", "B05", "B06", 
+           "B07", 
+           "B08", "B8A", "B09", "B11", "B12", "SCL")
+s2_collection = stac_image_collection(items$features, asset_names = assets,
+property_filter = function(x) {x[["eo:cloud_cover"]] < 20}) #all images with less than 20% clouds
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 0.4706092 secs
+
+# Display the image collection
+s2_collection
+## Image collection object, referencing 1 images with 13 bands
+## Images:
+##                       name      left      top   bottom     right
+## 1 S2B_13TDE_20210516_0_L2A -106.1832 40.65079 39.65576 -104.8846
+##              datetime        srs
+## 1 2021-05-16T18:02:54 EPSG:32613
+## 
+## Bands:
+##    name offset scale unit nodata image_count
+## 1   B01      0     1                       1
+## 2   B02      0     1                       1
+## 3   B03      0     1                       1
+## 4   B04      0     1                       1
+## 5   B05      0     1                       1
+## 6   B06      0     1                       1
+## 7   B07      0     1                       1
+## 8   B08      0     1                       1
+## 9   B09      0     1                       1
+## 10  B11      0     1                       1
+## 11  B12      0     1                       1
+## 12  B8A      0     1                       1
+## 13  SCL      0     1                       1
+
+

Setting up your camera and film

+

The camera through which the data scientist frames the shot is +multifaceted, akin to the tools and processes they employ. The camera’s +film, analogous to the data cube, defines the resolution and dimensions +of the captured data, shaping how the final dataset will be utilized. +The lens and its settings—focus, aperture, and exposure—determine the +clarity, depth, and breadth of the captured information, much like the +algorithms and parameters set by the data scientist dictate the +granularity and scope of the data cube. The flash, like data enhancement +techniques, can illuminate hidden details, ensuring that the data cube, +the final product, is as informative and accurate as the landscape it +represents.

+

+
# Record start time
+a <- Sys.time()
+
+# Define a specific view on the satellite image collection
+v = cube_view(
+    srs = "EPSG:32720", #this is harder than expected. 
+    dx = 100, 
+    dy = 100, 
+    dt = "P1M", 
+    aggregation = "median", 
+    resampling = "near",
+    extent = list(
+        t0 = "2021-05-15", 
+        t1 = "2021-05-16",
+        left = bbox_32720_boulder[1], 
+        right = bbox_32720_boulder[2],
+        top = bbox_32720_boulder[4], 
+        bottom = bbox_32720_boulder[3]
+    )
+)
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 0.002738953 secs
+
+# Display the defined view
+v
+## A data cube view object
+## 
+## Dimensions:
+##                 low             high  count pixel_size
+## t        2021-05-01       2021-05-31      1        P1M
+## y -3103099.52398788 15434400.4760121 185375        100
+## x -3178878.98542359 15369521.0145764 185484        100
+## 
+## SRS: "EPSG:32720"
+## Temporal aggregation method: "median"
+## Spatial resampling method: "near"
+
+

Take a picture!

+

Raster style

+
# Record start time
+a <- Sys.time()
+
+s2_collection |>
+    raster_cube(v) |>
+    select_bands(c( "B04", "B05"))  |>
+  apply_pixel(c("(B05-B04)/(B05+B04)"), names="NDVI") |>
+  write_tif() |>
+  raster::stack() -> x
+x
+## class      : RasterStack 
+## dimensions : 185375, 185484, 34384096500, 1  (nrow, ncol, ncell, nlayers)
+## resolution : 100, 100  (x, y)
+## extent     : -3178879, 15369521, -3103100, 15434400  (xmin, xmax, ymin, ymax)
+## crs        : +proj=utm +zone=20 +south +datum=WGS84 +units=m +no_defs 
+## names      : NDVI
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 4.132932 mins
+
+

STARS style

+
# Record start time
+a <- Sys.time()
+
+s2_collection |>
+    raster_cube(v) |>
+    select_bands(c("B04","B05"))  |>
+  apply_pixel(c("(B05-B04)/(B05+B04)"), names="NDVI") |>
+  stars::st_as_stars() -> y
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 1.459866 mins
+
+y
+## stars_proxy object with 1 attribute in 1 file(s):
+## $NDVI
+## [1] "[...]/filec5982c38536c.nc:NDVI"
+## 
+## dimension(s):
+##      from     to   offset delta                refsys point
+## x       1 185484 -3178879   100 WGS 84 / UTM zone 20S    NA
+## y       1 185375 15434400  -100 WGS 84 / UTM zone 20S    NA
+## time    1      1       NA    NA               POSIXct FALSE
+##                       values x/y
+## x                       NULL [x]
+## y                       NULL [y]
+## time [2021-05-01,2021-06-01)
+
+

Extract data

+
# Record start time
+a <- Sys.time()
+
+
+x <- s2_collection |>
+    raster_cube(v) |>
+    select_bands(c("B01", "B02", "B03", "B04", 
+                   "B05", "B06", "B07", "B08", 
+                   "B8A", "B09", "B11", "B12")) |>
+    extract_geom(boulder_county$multipolygon) |>
+    rename(
+        "time" = "time",
+        "443" = "B01",
+        "490" = "B02",
+        "560" = "B03",
+        "665" = "B04",
+        "705" = "B05",
+        "740" = "B06",
+        "783" = "B07",
+        "842" = "B08",
+        "865" = "B8A",
+        "940" = "B09",
+        "1610" = "B11",
+        "2190" = "B12"
+    )
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 1.699016 mins
+
+head(x)
+##   FID       time   443   490   560   665   705   740   783   842  865  940 1610
+## 1   1 2021-05-01 11096 10929 10224  9893  9956  9706  9715  9641 9511 8459 5682
+## 2   1 2021-05-01 11631 11282 10550 10234 10288 10031 10032  9988 9828 9153 5802
+## 3   1 2021-05-01 11900 11393 10666 10337 10398 10142 10138 10093 9927 9461 5754
+## 4   1 2021-05-01 11406 10597  9928  9626  9694  9481  9516  9338 9336 8959 5726
+## 5   1 2021-05-01 11399 10939 10237  9905  9978  9738  9746  9633 9555 8925 5831
+## 6   1 2021-05-01 11600 11174 10462 10147 10209  9952  9960  9890 9760 9153 5773
+##   2190
+## 1 3917
+## 2 3981
+## 3 3937
+## 4 4054
+## 5 4097
+## 6 3990
+
+

Make a timeseries

+

+# Record start time
+a <- Sys.time()
+
+items <- s |>
+    stac_search(collections = "sentinel-s2-l2a-cogs",
+                bbox = c(-105.694362,   39.912886,  -105.052774,    40.262785),
+                datetime = "2020-01-01/2022-12-31",
+                limit = 500) %>% 
+    post_request() 
+
+S2.mask = image_mask("SCL", values=c(3,8,9))
+
+col = stac_image_collection(items$features, asset_names = assets, 
+                            property_filter = function(x) {x[["eo:cloud_cover"]] < 30})
+
+v = cube_view(srs = "EPSG:4326",  extent = list(t0 = "2020-01-01", t1 = "2022-12-31",
+              left = -105.694362, right = -105.052774,  top = 40.262785, bottom = 39.912886),
+              dx = 0.001, dy = 0.001, dt = "P1M", aggregation = "median", resampling = "bilinear")
+
+library(colorspace)
+ndvi.col = function(n) {
+  rev(sequential_hcl(n, "Green-Yellow"))
+}
+library(gdalcubes)
+raster_cube(col, v, mask = S2.mask) |>
+    select_bands(c("B04", "B08")) |>
+    apply_pixel("(B08-B04)/(B08+B04)", "NDVI") |>
+    gdalcubes::animate(col = ndvi.col, zlim=c(-0.2,1), key.pos = 1, save_as = "anim.gif", fps = 4)
+## [1] "/Users/ty/Documents/Github/hackathon2023_datacube/docs/code_for_building_cube/anim.gif"
+
+b <- Sys.time()
+difftime(b, a)
+## Time difference of 4.716672 mins
+
+y
+## stars_proxy object with 1 attribute in 1 file(s):
+## $NDVI
+## [1] "[...]/filec5982c38536c.nc:NDVI"
+## 
+## dimension(s):
+##      from     to   offset delta                refsys point
+## x       1 185484 -3178879   100 WGS 84 / UTM zone 20S    NA
+## y       1 185375 15434400  -100 WGS 84 / UTM zone 20S    NA
+## time    1      1       NA    NA               POSIXct FALSE
+##                       values x/y
+## x                       NULL [x]
+## y                       NULL [y]
+## time [2021-05-01,2021-06-01)
+
+

+

Saving Data Cubes to Local Storage There are occasions when we need to +manipulate data cubes using other software. For such purposes, we can +save data cubes to our local disk as individual netCDF files or as a +series of GeoTIFF files. In the case of the latter, each temporal +segment of the cube is saved as a separate (multiband) GeoTIFF file.

+

Both netCDF and GeoTIFF formats allow for file size reduction through +compression and data packing. This process involves transforming double +precision numbers into smaller integer values using a scale and offset, +which can be particularly useful for managing disk space (for more +details, refer to the ?write_ncdf and ?write_tif documentation).

+
gdalcubes_options(ncdf_compression_level = 1)
+write_ncdf(cube, file.path("~/Desktop", basename(tempfile(fileext = ".nc"))))
+gdalcubes_options(ncdf_compression_level = 0)
+
+

write_tif() and write_ncdf() both return the path(s) to created file(s) +as a character vector.

+
items_2020 <- s |>
+    stac_search(collections = "sentinel-s2-l2a-cogs",
+                bbox = c(-105.694362,   39.912886,  -105.052774,    40.262785),
+                datetime = "2020-05-01/2020-06-30") |> 
+    post_request() 
+
+items_2021 <- s |>
+    stac_search(collections = "sentinel-s2-l2a-cogs",
+                bbox = c(-105.694362,   39.912886,  -105.052774,    40.262785),
+                datetime = "2021-05-01/2021-06-30") |> 
+    post_request() 
+
+
+col_2020 = stac_image_collection(items_2020$features, asset_names = assets)
+col_2021 = stac_image_collection(items_2021$features, asset_names = assets)
+
+v_2020 = cube_view(srs = "EPSG:32720",  extent = list(t0 = "2020-05-01", t1 = "2020-06-30",
+              left = bbox_32720_boulder["xmin"], right = bbox_32720_boulder["xmax"],  top = bbox_32720_boulder["ymax"], bottom = bbox_32720_boulder["ymin"]),
+              dx = 100, dy = 100, dt = "P1D", aggregation = "median", resampling = "bilinear")
+
+v_2021 = cube_view(v_2020, extent = list(t0 = "2021-05-01", t1 = "2021-06-30"))
+
+
+max_ndvi_mosaic <- function(col, v) {
+    raster_cube(col, v) |>
+    select_bands(c("B04", "B08")) |>
+    apply_pixel(c("(B08-B04)/(B08+B04)"), names="NDVI") |>
+    reduce_time("max(NDVI)")
+}
+
+suppressPackageStartupMessages(library(stars))
+max_ndvi_mosaic(col_2020, v_2020) -> maxndvi_2020
+
+max_ndvi_mosaic(col_2021, v_2021)  -> maxndvi_2021
+
+maxndvi_2021
+maxndvi_2020
+
+difference = maxndvi_2021 - maxndvi_2020
+difference[difference > -0.15] = NA
+names(difference) <- "Difference of max NDVI (2020 - 2019)"
+
+
flood_polygon_data3 <- glue("/vsizip/vsicurl/https://data.hydrosheds.org/file/hydrosheds-associated/gloric/GloRiC_v10_shapefile.zip/GloRiC_v10_shapefile/GloRiC_v10.shp") |>
+  st_read() |>
+  st_as_sf(coords = c("lon","lat"))
+
+flood_polygon_data3
+
+
#st_read("/Users/ty/Downloads/GloRiC_v10_geodatabase/GloRiC_v10.gdb")
+
+flood_polygon_data3 <- glue("/vsizip/vsicurl/https://data.hydrosheds.org/file/hydrosheds-associated/gloric/GloRiC_v10_geodatabase.zip/GloRiC_v10_geodatabase/GloRiC_v10.gdb") |>
+  st_read() |>
+  st_as_sf(coords = c("lon","lat"))
+
+flood_polygon_data3
+
+ + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ + + +
+ + + +
+
+
+
+ + + + + + + + + + \ No newline at end of file diff --git a/resources/stac_mount_save/stac_mount_save.md b/resources/stac_mount_save/stac_mount_save.md new file mode 100644 index 0000000..fa03684 --- /dev/null +++ b/resources/stac_mount_save/stac_mount_save.md @@ -0,0 +1,871 @@ +The art of making a data cube +================ +Ty Tuff, ESIIL Data Scientist +2023-10-27 + +``` r + +#library(Rcpp) +library(sf) +library(gdalcubes) +library(rstac) +library(gdalUtils) +library(terra) +library(rgdal) +library(reshape2) +library(osmdata) +library(terra) +library(dplyr) +library(stars) +library(ggplot2) +library(colorspace) +library(geos) +library(osmdata) +library(ggthemes) +library(tidyr) +gdalcubes_options(parallel = 8) + +sf::sf_extSoftVersion() +## GEOS GDAL proj.4 GDAL_with_GEOS USE_PROJ_H +## "3.11.0" "3.5.3" "9.1.0" "true" "true" +## PROJ +## "9.1.0" +gdalcubes_gdal_has_geos() +## [1] TRUE + +library(osmdata) +library(dplyr) +library(sf) +library(terra) +library(tidyterra) +library(glue) +library(ggplot2) +library(ggthemes) +library(stars) +library(magrittr) +library(landsat) +``` + +# The philosophy of moving data in the cloud + +The philosophy of moving data in the cloud represents a paradigm shift +in how we approach data within our analytical processes. Instead of the +traditional method of transferring entire datasets to our local +environments, the cloud encourages a more efficient model: bring your +analysis to the data. This approach minimizes data movement and +leverages the cloud’s computational power and scalability. By utilizing +cloud-native tools and services, we can run our analyses directly on the +data where it resides, selectively accessing and processing only what is +necessary. This not only streamlines workflows but also significantly +reduces overheads related to data transfer and storage management. In +essence, the focus is on diverting computational resources to the data +rather than the cumbersome and resource-intensive practice of moving +large datasets to and fro. + +## ‘To Make’ or ‘To Take’ a photo + +The distinction between making and taking a photograph lies in the +approach and intent behind the camera. Taking a photo is often a +reactive process, where the photographer captures moments as they +naturally unfold, seizing the spontaneity of life without alteration. +It’s a passive form of photography where the emphasis is on the right +timing and the natural interplay of elements within the frame. On the +other hand, making a photo is a proactive and deliberate act. It is akin +to craftsmanship, where a professional photographer starts with a +concept and utilizes a variety of tools and techniques to stage and +construct the desired scene. They actively manipulate lighting, +composition, and subjects to create a photograph that aligns with their +pre-visualized artistic vision. While both methods use a camera to +produce a photograph, making a photo involves a creation process, +whereas taking a photo is about finding the scene. + +David Yarrow is a famous photographer who ‘makes’ his photographs. +![](../assets/esiil_content/stac_mount_save/David-Yarrow-sorrel-sky-gallery-Photographic-Print-Cindys-Shotgun-Wedding.png) +![](../assets/esiil_content/stac_mount_save/bison.png) + +## What does it mean to ‘make’ a data cube? + +The artistry of Ansel Adams’ photography serves as a compelling analogy +for the meticulous craft of building a data cube from cloud data sources +using tools like STAC and GDAL VSI. Just as Adams would survey the +vastness of a landscape, discerning the interplay of light and shadow +upon the mountains before him, a data architect surveys the expanse of +available data. In this analogy, the raw data are the majestic mountains +and sweeping landscapes waiting to be captured. The STAC collection acts +as the photographer’s deliberate choice of scene, pointing the camera +lens—our data tools—towards the most telling and coherent dataset. + +![](../assets/stac_mount_save/Ansel_Adams_datacube.png) Just as Adams’ +photographs are more than mere records of a landscape, but rather a +confluence of his vision, technique, and the scene’s natural beauty, so +too is the data cube more than the sum of its parts. It is the artful +synthesis of information, crafted and composed with the skill and intent +of an artist, producing not just a tool for analysis but a harmonized, +data-driven portrait of the world it represents. The builder of the data +cube is, indeed, an artist, and the data cube their masterpiece, +revealing not just data, but a story, a perspective, a landscape sewn +from the raw material of cloud-sourced information. + +As Adams would adjust his viewfinder, setting the boundaries of his +photographic frame, the data builder sets the view window, filtering and +transferring relevant data to their own medium, akin to Adams’ film. +This is where the raw data is transformed, organized into the structured +form of a data frame or data cube, a process not unlike the careful +development of a photograph in a darkroom. Here, the data cube creator, +much like Adams with his careful dodging and burning, harmonizes +disparate elements into a cohesive whole, each decision reflecting an +intention and vision for the final product. + +## 1) The Rat through the Snake Problem: Scalability with Cloud Computing + +Just like a snake that swallows a rat, traditional computing systems +often struggle to process the large volumes of environmental data — +they’re constrained by their static hardware limitations. Cloud +computing introduces a python-esque capability: massive scalability. By +migrating to the cloud, we essentially make the snake bigger, allowing +it to handle larger “prey.” Scalable computers in the cloud can grow +with the demand, providing the necessary computational power to process +extensive datasets, which is vital in a field where data volumes are +increasing exponentially. + +![Raster through a snake](../assets/esiil_content/stac_mount_save/mouseinsnake.png) + +## 2) The Antelope through the Python Problem: Streamlining with GDAL VSI + +As we scale up, we encounter a new challenge: trying to pass an antelope +through a python — a metaphor for the next level of complexity in data +processing. The sheer size and complexity of the data can become +overwhelming. This is where GDAL’s Virtual File System (VSI) becomes our +ecological adaptation. VSI allows us to access remote data transparently +and more efficiently. Instead of ingesting the entire “antelope,” VSI +enables the “python” to dynamically access and process only the parts of +the data it needs, when it needs them, much like constriction before +digestion. This selective access minimizes the need for local storage +and expedites the data handling process. + +![Antelope through a Python](../assets/esiil_content/stac_mount_save/antelopeinpython.png) + +## 3) Drinking from a Fire Hose: Accelerated Inference with AI and ML + +Once we’ve enabled the flow of large amounts of digestible data, we +encounter the metaphorical challenge of drinking from a fire hose. The +data, now flowing and accessible, is immense and rapid — posing a +challenge not just to store and process, but to understand and derive +meaning from in real-time. This is where artificial intelligence (AI) +and machine learning (ML) step in. These technologies act as a +sophisticated filtration system, enabling us to drink safely and +beneficially from the torrent. AI and ML can analyze patterns, make +predictions, and infer insights at a pace that keeps up with the fast +stream of data, turning raw information into actionable knowledge. + +![Inference through a firehose](../assets/esiil_content/stac_mount_save/drink-firehose.png) + +By addressing these three pivotal challenges with cloud computing, GDAL +VSI, and AI/ML, we not only manage to consume the data effectively but +also transform our capabilities in environmental data science. We can +move from mere data ingestion to meaningful data interpretation, all at +a scale and speed necessary for impactful environmental analysis. + +### Mounting data + +A void-filled Digital Elevation Model (DEM) is a comprehensive +topographical representation where any missing data points, known as +voids, have been filled in. These voids can occur due to various +reasons, such as clouds or technical errors during data collection. In a +void-filled DEM, these gaps are interpolated or estimated using the +surrounding data to create a continuous, seamless surface model. This +process enhances the utility and accuracy of the DEM for hydrological +modeling, terrain analysis, and other geographical applications. The +HydroSHEDS website +(https://www.hydrosheds.org/hydrosheds-core-downloads) provides access +to high-quality, void-filled DEM datasets like the +DEM_continuous_CONUS_15s, which users can download and easily integrate +into spatial analysis workflows using tools such as ‘terra’ in R, +allowing for sophisticated environmental and geographical research and +planning. + +``` r +# Record start time +a <- Sys.time() + +# Create a string with the file path using glue, then download and read the DEM file as a raster object + +DEM_continuous_CONUS_15s <- glue( + "/vsizip/vsicurl/", #magic remote connection + "https://data.hydrosheds.org/file/hydrosheds-v1-dem/hyd_na_dem_15s.zip", #copied link to download location + "/hyd_na_dem_15s.tif") %>% #path inside zip file + terra::rast() + +# The 'glue' function constructs the file path string, which is then passed to 'terra::rast()' to read the DEM file into R as a raster layer. '/vsizip/vsicurl/' is a special GDAL virtual file system syntax that allows reading directly from a zipped file on a remote server. + +# Record end time and calculate the time difference +b <- Sys.time() +difftime(b, a) +## Time difference of 4.603666 secs + +# The resulting raster object is stored in 'DEM_continuous_CONUS_15s', which now contains the void-filled DEM data ready for use + +DEM_continuous_CONUS_15s # Prints out the details of the 'DEM_continuous_CONUS_15s' raster object +## class : SpatRaster +## dimensions : 13920, 20640, 1 (nrow, ncol, nlyr) +## resolution : 0.004166667, 0.004166667 (x, y) +## extent : -138, -52, 5, 63 (xmin, xmax, ymin, ymax) +## coord. ref. : lon/lat WGS 84 (EPSG:4326) +## source : hyd_na_dem_15s.tif +## name : Band_1 + +# output is a SpatRaster, which is the object type associated with the 'terra' package. +``` + +Continuous DEM for North America + +``` r +# Record start time +a <- Sys.time() + +ggplot() + + geom_spatraster(data=DEM_continuous_CONUS_15s) + + theme_tufte() +``` + +![](stac_mount_save_files/figure-gfm/DEM_plot-1.png) + +``` r + +b <- Sys.time() +difftime(b, a) +## Time difference of 52.49061 secs +``` + +Calculate Slope from that DEM + +``` r +SLOPE_continuous_CONUS_15s <- terra::terrain(DEM_continuous_CONUS_15s, "slope") + +SLOPE_continuous_CONUS_15s +## class : SpatRaster +## dimensions : 13920, 20640, 1 (nrow, ncol, nlyr) +## resolution : 0.004166667, 0.004166667 (x, y) +## extent : -138, -52, 5, 63 (xmin, xmax, ymin, ymax) +## coord. ref. : lon/lat WGS 84 (EPSG:4326) +## source(s) : memory +## name : slope +## min value : 0.00000 +## max value : 56.98691 +``` + +``` r +# Record start time +a <- Sys.time() + +ggplot() + + geom_spatraster(data=SLOPE_continuous_CONUS_15s) + + theme_tufte() +``` + +![](stac_mount_save_files/figure-gfm/SLOPE_plot-1.png) + +``` r + +b <- Sys.time() +difftime(b, a) +## Time difference of 3.859545 secs +``` + +Calculate aspect from DEM + +``` r +ASPECT_continuous_CONUS_15s <- terra::terrain(DEM_continuous_CONUS_15s, "aspect") +ASPECT_continuous_CONUS_15s +## class : SpatRaster +## dimensions : 13920, 20640, 1 (nrow, ncol, nlyr) +## resolution : 0.004166667, 0.004166667 (x, y) +## extent : -138, -52, 5, 63 (xmin, xmax, ymin, ymax) +## coord. ref. : lon/lat WGS 84 (EPSG:4326) +## source(s) : memory +## name : aspect +## min value : 0 +## max value : 360 +``` + +``` r +# Record start time +a <- Sys.time() + +ggplot() + + geom_spatraster(data=ASPECT_continuous_CONUS_15s) + + theme_tufte() +``` + +![](stac_mount_save_files/figure-gfm/ASPECT_plot-1.png) + +``` r + +b <- Sys.time() +difftime(b, a) +## Time difference of 3.650267 secs +``` + +Create a cube from those layers! + +``` r +mini_stack <- c(DEM_continuous_CONUS_15s, SLOPE_continuous_CONUS_15s,ASPECT_continuous_CONUS_15s) +mini_stack +## class : SpatRaster +## dimensions : 13920, 20640, 3 (nrow, ncol, nlyr) +## resolution : 0.004166667, 0.004166667 (x, y) +## extent : -138, -52, 5, 63 (xmin, xmax, ymin, ymax) +## coord. ref. : lon/lat WGS 84 (EPSG:4326) +## sources : hyd_na_dem_15s.tif +## memory +## memory +## names : Band_1, slope, aspect +## min values : ? , 0.00000, 0 +## max values : ? , 56.98691, 360 +``` + +Reproject and return the bounding box coordinates for our Area of +Interest + +``` r +# Transform the filtered geometry to EPSG:4326 and store its bounding box +# Record start time +a <- Sys.time() + +DEM_continuous_CONUS_15s |> +stars::st_as_stars() |> + st_transform("EPSG:4326") |> + st_bbox() -> bbox_4326 + + +DEM_continuous_CONUS_15s |> +stars::st_as_stars() |> + st_transform("EPSG:32618") |> + st_bbox() -> bbox_32618 + +b <- Sys.time() +difftime(b, a) +## Time difference of 3.7653 mins +``` + +Get a polygon for Boulder County, reproject, and return bounding box. +This is so I can make a smaller search in the stac catalog. + +``` r +boulder_county <- getbb("boulder, co", format_out="sf_polygon") + +boulder_county$multipolygon |> + st_transform(crs =4326 ) |> + st_bbox() -> bbox_4326_boulder + +boulder_county$multipolygon |> + st_transform(crs =32720 ) |> + st_bbox() -> bbox_32720_boulder +``` + +Get a polygon for the United States and crop it to be the same size as +the DEM above. + +``` r +aoi <- getbb("United States", format_out="sf_polygon") + +conus <- aoi$multipolygon |> + st_crop(bbox_4326) + + +ggplot(data=conus) + + geom_sf() +``` + +![](stac_mount_save_files/figure-gfm/conus_bounding_box-1.png) + +Search the Stac catalog. + +STAC, or SpatioTemporal Asset Catalog, is an open-source specification +designed to standardize the way geospatial data is indexed and +discovered. Developed by Element 84 among others, it facilitates better +interoperability and sharing of geospatial assets by providing a common +language for describing them. STAC’s flexible design allows for easy +cataloging of data, making it simpler for individuals and systems to +search and retrieve geospatial information. By effectively organizing +data about the Earth’s spatial and temporal characteristics, STAC +enables users to harness the full power of the cloud and modern data +processing technologies, optimizing the way we access and analyze +environmental data on a global scale. + +``` r + stac("https://earth-search.aws.element84.com/v1") |> + get_request() +## ###STACCatalog +## - id: earth-search-aws +## - description: A STAC API of public datasets on AWS +## - field(s): stac_version, type, id, title, description, links, conformsTo +``` + +Element 84’s Earth Search is a STAC compliant search and discovery API +that offers users access to a vast collection of geospatial open +datasets hosted on AWS. It serves as a centralized search catalog +providing standardized metadata for these open datasets, designed to be +freely used and integrated into various applications. Alongside the API, +Element 84 also provides a web application named Earth Search Console, +which is map-centric and allows users to explore and visualize the data +contained within the Earth Search API’s catalog. This suite of tools is +part of Element 84’s initiative to make geospatial data more accessible +and actionable for a wide range of users and applications. + +``` r +collection_formats() +## CHIRPS_v2_0_daily_p05_tif | Image collection format for CHIRPS v 2.0 daily +## | global precipitation dataset (0.05 degrees +## | resolution) from GeoTIFFs, expects list of .tif +## | or .tif.gz files as input. [TAGS: CHIRPS, +## | precipitation] +## CHIRPS_v2_0_monthly_p05_tif | Image collection format for CHIRPS v 2.0 monthly +## | global precipitation dataset (0.05 degrees +## | resolution) from GeoTIFFs, expects list of .tif +## | or .tif.gz files as input. [TAGS: CHIRPS, +## | precipitation] +## ESA_CCI_SM_ACTIVE | Collection format for ESA CCI soil moisture +## | active product (version 4.7) [TAGS: Soil +## | Moisture, ESA, CCI] +## ESA_CCI_SM_PASSIVE | Collection format for ESA CCI soil moisture +## | passive product (version 4.7) [TAGS: Soil +## | Moisture, ESA, CCI] +## GPM_IMERG_3B_DAY_GIS_V06A | Collection format for daily +## | IMERG_3B_DAY_GIS_V06A data [TAGS: Precipitation, +## | GPM, IMERG] +## L8_L1TP | Collection format for Landsat 8 Level 1 TP +## | product [TAGS: Landsat, USGS, Level 1, NASA] +## L8_SR | Collection format for Landsat 8 surface +## | reflectance product [TAGS: Landsat, USGS, Level +## | 2, NASA, surface reflectance] +## MAXAR | Preliminary collection format for MAXAR open +## | data, visual only (under development) [TAGS: ] +## MxD09GA | Collection format for selected bands from the +## | MODIS MxD09GA (Aqua and Terra) product [TAGS: +## | MODIS, surface reflectance] +## MxD10A2 | Collection format for selected bands from the +## | MODIS MxD10A2 (Aqua and Terra) v006 Snow Cover +## | product [TAGS: MODIS, Snow Cover] +## MxD11A1 | Collection format for selected bands from the +## | MODIS MxD11A2 (Aqua and Terra) v006 Land Surface +## | Temperature product [TAGS: MODIS, LST] +## MxD11A2 | Collection format for selected bands from the +## | MODIS MxD11A2 (Aqua and Terra) v006 Land Surface +## | Temperature product [TAGS: MODIS, LST] +## MxD13A2 | Collection format for selected bands from the +## | MODIS MxD13A2 (Aqua and Terra) product [TAGS: +## | MODIS, VI, NDVI, EVI] +## MxD13A3 | Collection format for selected bands from the +## | MODIS MxD13A3 (Aqua and Terra) product [TAGS: +## | MODIS, VI, NDVI, EVI] +## MxD13Q1 | Collection format for selected bands from the +## | MODIS MxD13Q1 (Aqua and Terra) product [TAGS: +## | MODIS, VI, NDVI, EVI] +## MxD14A2 | Collection format for the MODIS MxD14A2 (Aqua +## | and Terra) product [TAGS: MODIS, Fire] +## PlanetScope_3B_AnalyticMS_SR | Image collection format for PlanetScope 4-band +## | scenes [TAGS: PlanetScope, BOA, Surface +## | Reflectance] +## Sentinel2_L1C | Image collection format for Sentinel 2 Level 1C +## | data as downloaded from the Copernicus Open +## | Access Hub, expects a list of file paths as +## | input. The format works on original ZIP +## | compressed as well as uncompressed imagery. +## | [TAGS: Sentinel, Copernicus, ESA, TOA] +## Sentinel2_L1C_AWS | Image collection format for Sentinel 2 Level 1C +## | data in AWS [TAGS: Sentinel, Copernicus, ESA, +## | TOA] +## Sentinel2_L2A | Image collection format for Sentinel 2 Level 2A +## | data as downloaded from the Copernicus Open +## | Access Hub, expects a list of file paths as +## | input. The format should work on original ZIP +## | compressed as well as uncompressed imagery. +## | [TAGS: Sentinel, Copernicus, ESA, BOA, Surface +## | Reflectance] +## Sentinel2_L2A_THEIA | Image collection format for Sentinel 2 Level 2A +## | data as downloaded from Theia. [TAGS: Sentinel, +## | ESA, Flat Reflectance, Theia] +``` + +Building a stac collection by aiming your camera at the landscape + +Creating a STAC collection is akin to a photographer framing a shot; the +landscape is rich with diverse data, mirroring a scene bustling with +potential subjects, colors, and light. Just as a photographer selects a +portion of the vista to capture, focusing on elements that will compose +a compelling image, a data scientist must similarly navigate the vast +data terrain. They must ‘point their camera’ judiciously, ensuring that +the ‘frame’ encapsulates the precise data needed. This careful selection +is crucial, as it determines the relevance and quality of the data +collection, much like the photographer’s choice dictates the story a +photograph will tell. + +![](../assets/esiil_content/stac_mount_save/Ansel_adams_Jackson_hole.png) + +``` r +# Record start time +a <- Sys.time() + +# Initialize STAC connection +s = stac("https://earth-search.aws.element84.com/v0") + + +# Search for Sentinel-2 images within specified bounding box and date range +#22 Million items +items = s |> + stac_search(collections = "sentinel-s2-l2a-cogs", + bbox = c(bbox_4326_boulder["xmin"], + bbox_4326_boulder["ymin"], + bbox_4326_boulder["xmax"], + bbox_4326_boulder["ymax"]), + datetime = "2021-05-15/2021-05-16") |> + post_request() |> + items_fetch(progress = FALSE) + +# Print number of found items +length(items$features) +## [1] 1 + +# Prepare the assets for analysis +library(gdalcubes) +assets = c("B01", "B02", "B03", "B04", "B05", "B06", + "B07", + "B08", "B8A", "B09", "B11", "B12", "SCL") +s2_collection = stac_image_collection(items$features, asset_names = assets, +property_filter = function(x) {x[["eo:cloud_cover"]] < 20}) #all images with less than 20% clouds + +b <- Sys.time() +difftime(b, a) +## Time difference of 0.4706092 secs + +# Display the image collection +s2_collection +## Image collection object, referencing 1 images with 13 bands +## Images: +## name left top bottom right +## 1 S2B_13TDE_20210516_0_L2A -106.1832 40.65079 39.65576 -104.8846 +## datetime srs +## 1 2021-05-16T18:02:54 EPSG:32613 +## +## Bands: +## name offset scale unit nodata image_count +## 1 B01 0 1 1 +## 2 B02 0 1 1 +## 3 B03 0 1 1 +## 4 B04 0 1 1 +## 5 B05 0 1 1 +## 6 B06 0 1 1 +## 7 B07 0 1 1 +## 8 B08 0 1 1 +## 9 B09 0 1 1 +## 10 B11 0 1 1 +## 11 B12 0 1 1 +## 12 B8A 0 1 1 +## 13 SCL 0 1 1 +``` + +Setting up your camera and film + +The camera through which the data scientist frames the shot is +multifaceted, akin to the tools and processes they employ. The camera’s +film, analogous to the data cube, defines the resolution and dimensions +of the captured data, shaping how the final dataset will be utilized. +The lens and its settings—focus, aperture, and exposure—determine the +clarity, depth, and breadth of the captured information, much like the +algorithms and parameters set by the data scientist dictate the +granularity and scope of the data cube. The flash, like data enhancement +techniques, can illuminate hidden details, ensuring that the data cube, +the final product, is as informative and accurate as the landscape it +represents. + +![](../assets/esiil_content/stac_mount_save/View_Ansel-Adams_Camera.png) + +``` r +# Record start time +a <- Sys.time() + +# Define a specific view on the satellite image collection +v = cube_view( + srs = "EPSG:32720", #this is harder than expected. + dx = 100, + dy = 100, + dt = "P1M", + aggregation = "median", + resampling = "near", + extent = list( + t0 = "2021-05-15", + t1 = "2021-05-16", + left = bbox_32720_boulder[1], + right = bbox_32720_boulder[2], + top = bbox_32720_boulder[4], + bottom = bbox_32720_boulder[3] + ) +) + +b <- Sys.time() +difftime(b, a) +## Time difference of 0.002738953 secs + +# Display the defined view +v +## A data cube view object +## +## Dimensions: +## low high count pixel_size +## t 2021-05-01 2021-05-31 1 P1M +## y -3103099.52398788 15434400.4760121 185375 100 +## x -3178878.98542359 15369521.0145764 185484 100 +## +## SRS: "EPSG:32720" +## Temporal aggregation method: "median" +## Spatial resampling method: "near" +``` + +Take a picture! + +Raster style + +``` r +# Record start time +a <- Sys.time() + +s2_collection |> + raster_cube(v) |> + select_bands(c( "B04", "B05")) |> + apply_pixel(c("(B05-B04)/(B05+B04)"), names="NDVI") |> + write_tif() |> + raster::stack() -> x +x +## class : RasterStack +## dimensions : 185375, 185484, 34384096500, 1 (nrow, ncol, ncell, nlayers) +## resolution : 100, 100 (x, y) +## extent : -3178879, 15369521, -3103100, 15434400 (xmin, xmax, ymin, ymax) +## crs : +proj=utm +zone=20 +south +datum=WGS84 +units=m +no_defs +## names : NDVI + +b <- Sys.time() +difftime(b, a) +## Time difference of 4.132932 mins +``` + +STARS style + +``` r +# Record start time +a <- Sys.time() + +s2_collection |> + raster_cube(v) |> + select_bands(c("B04","B05")) |> + apply_pixel(c("(B05-B04)/(B05+B04)"), names="NDVI") |> + stars::st_as_stars() -> y + +b <- Sys.time() +difftime(b, a) +## Time difference of 1.459866 mins + +y +## stars_proxy object with 1 attribute in 1 file(s): +## $NDVI +## [1] "[...]/filec5982c38536c.nc:NDVI" +## +## dimension(s): +## from to offset delta refsys point +## x 1 185484 -3178879 100 WGS 84 / UTM zone 20S NA +## y 1 185375 15434400 -100 WGS 84 / UTM zone 20S NA +## time 1 1 NA NA POSIXct FALSE +## values x/y +## x NULL [x] +## y NULL [y] +## time [2021-05-01,2021-06-01) +``` + +Extract data + +``` r +# Record start time +a <- Sys.time() + + +x <- s2_collection |> + raster_cube(v) |> + select_bands(c("B01", "B02", "B03", "B04", + "B05", "B06", "B07", "B08", + "B8A", "B09", "B11", "B12")) |> + extract_geom(boulder_county$multipolygon) |> + rename( + "time" = "time", + "443" = "B01", + "490" = "B02", + "560" = "B03", + "665" = "B04", + "705" = "B05", + "740" = "B06", + "783" = "B07", + "842" = "B08", + "865" = "B8A", + "940" = "B09", + "1610" = "B11", + "2190" = "B12" + ) + +b <- Sys.time() +difftime(b, a) +## Time difference of 1.699016 mins + +head(x) +## FID time 443 490 560 665 705 740 783 842 865 940 1610 +## 1 1 2021-05-01 11096 10929 10224 9893 9956 9706 9715 9641 9511 8459 5682 +## 2 1 2021-05-01 11631 11282 10550 10234 10288 10031 10032 9988 9828 9153 5802 +## 3 1 2021-05-01 11900 11393 10666 10337 10398 10142 10138 10093 9927 9461 5754 +## 4 1 2021-05-01 11406 10597 9928 9626 9694 9481 9516 9338 9336 8959 5726 +## 5 1 2021-05-01 11399 10939 10237 9905 9978 9738 9746 9633 9555 8925 5831 +## 6 1 2021-05-01 11600 11174 10462 10147 10209 9952 9960 9890 9760 9153 5773 +## 2190 +## 1 3917 +## 2 3981 +## 3 3937 +## 4 4054 +## 5 4097 +## 6 3990 +``` + +Make a timeseries + +``` r + +# Record start time +a <- Sys.time() + +items <- s |> + stac_search(collections = "sentinel-s2-l2a-cogs", + bbox = c(-105.694362, 39.912886, -105.052774, 40.262785), + datetime = "2020-01-01/2022-12-31", + limit = 500) %>% + post_request() + +S2.mask = image_mask("SCL", values=c(3,8,9)) + +col = stac_image_collection(items$features, asset_names = assets, + property_filter = function(x) {x[["eo:cloud_cover"]] < 30}) + +v = cube_view(srs = "EPSG:4326", extent = list(t0 = "2020-01-01", t1 = "2022-12-31", + left = -105.694362, right = -105.052774, top = 40.262785, bottom = 39.912886), + dx = 0.001, dy = 0.001, dt = "P1M", aggregation = "median", resampling = "bilinear") + +library(colorspace) +ndvi.col = function(n) { + rev(sequential_hcl(n, "Green-Yellow")) +} +library(gdalcubes) +raster_cube(col, v, mask = S2.mask) |> + select_bands(c("B04", "B08")) |> + apply_pixel("(B08-B04)/(B08+B04)", "NDVI") |> + gdalcubes::animate(col = ndvi.col, zlim=c(-0.2,1), key.pos = 1, save_as = "anim.gif", fps = 4) +## [1] "/Users/ty/Documents/Github/hackathon2023_datacube/docs/code_for_building_cube/anim.gif" + +b <- Sys.time() +difftime(b, a) +## Time difference of 4.716672 mins + +y +## stars_proxy object with 1 attribute in 1 file(s): +## $NDVI +## [1] "[...]/filec5982c38536c.nc:NDVI" +## +## dimension(s): +## from to offset delta refsys point +## x 1 185484 -3178879 100 WGS 84 / UTM zone 20S NA +## y 1 185375 15434400 -100 WGS 84 / UTM zone 20S NA +## time 1 1 NA NA POSIXct FALSE +## values x/y +## x NULL [x] +## y NULL [y] +## time [2021-05-01,2021-06-01) +``` + +![](../assets/esiil_content/stac_mount_save/anim.gif) + +Saving Data Cubes to Local Storage There are occasions when we need to +manipulate data cubes using other software. For such purposes, we can +save data cubes to our local disk as individual netCDF files or as a +series of GeoTIFF files. In the case of the latter, each temporal +segment of the cube is saved as a separate (multiband) GeoTIFF file. + +Both netCDF and GeoTIFF formats allow for file size reduction through +compression and data packing. This process involves transforming double +precision numbers into smaller integer values using a scale and offset, +which can be particularly useful for managing disk space (for more +details, refer to the ?write_ncdf and ?write_tif documentation). + +``` r +gdalcubes_options(ncdf_compression_level = 1) +write_ncdf(cube, file.path("~/Desktop", basename(tempfile(fileext = ".nc")))) +gdalcubes_options(ncdf_compression_level = 0) +``` + +write_tif() and write_ncdf() both return the path(s) to created file(s) +as a character vector. + +``` r +items_2020 <- s |> + stac_search(collections = "sentinel-s2-l2a-cogs", + bbox = c(-105.694362, 39.912886, -105.052774, 40.262785), + datetime = "2020-05-01/2020-06-30") |> + post_request() + +items_2021 <- s |> + stac_search(collections = "sentinel-s2-l2a-cogs", + bbox = c(-105.694362, 39.912886, -105.052774, 40.262785), + datetime = "2021-05-01/2021-06-30") |> + post_request() + + +col_2020 = stac_image_collection(items_2020$features, asset_names = assets) +col_2021 = stac_image_collection(items_2021$features, asset_names = assets) + +v_2020 = cube_view(srs = "EPSG:32720", extent = list(t0 = "2020-05-01", t1 = "2020-06-30", + left = bbox_32720_boulder["xmin"], right = bbox_32720_boulder["xmax"], top = bbox_32720_boulder["ymax"], bottom = bbox_32720_boulder["ymin"]), + dx = 100, dy = 100, dt = "P1D", aggregation = "median", resampling = "bilinear") + +v_2021 = cube_view(v_2020, extent = list(t0 = "2021-05-01", t1 = "2021-06-30")) + + +max_ndvi_mosaic <- function(col, v) { + raster_cube(col, v) |> + select_bands(c("B04", "B08")) |> + apply_pixel(c("(B08-B04)/(B08+B04)"), names="NDVI") |> + reduce_time("max(NDVI)") +} + +suppressPackageStartupMessages(library(stars)) +max_ndvi_mosaic(col_2020, v_2020) -> maxndvi_2020 + +max_ndvi_mosaic(col_2021, v_2021) -> maxndvi_2021 + +maxndvi_2021 +maxndvi_2020 + +difference = maxndvi_2021 - maxndvi_2020 +difference[difference > -0.15] = NA +names(difference) <- "Difference of max NDVI (2020 - 2019)" +``` + +``` r +flood_polygon_data3 <- glue("/vsizip/vsicurl/https://data.hydrosheds.org/file/hydrosheds-associated/gloric/GloRiC_v10_shapefile.zip/GloRiC_v10_shapefile/GloRiC_v10.shp") |> + st_read() |> + st_as_sf(coords = c("lon","lat")) + +flood_polygon_data3 +``` + +``` r +#st_read("/Users/ty/Downloads/GloRiC_v10_geodatabase/GloRiC_v10.gdb") + +flood_polygon_data3 <- glue("/vsizip/vsicurl/https://data.hydrosheds.org/file/hydrosheds-associated/gloric/GloRiC_v10_geodatabase.zip/GloRiC_v10_geodatabase/GloRiC_v10.gdb") |> + st_read() |> + st_as_sf(coords = c("lon","lat")) + +flood_polygon_data3 +``` diff --git a/resources/stac_mount_save_files/figure-gfm/ASPECT_plot-1.png b/resources/stac_mount_save_files/figure-gfm/ASPECT_plot-1.png new file mode 100644 index 0000000..fe7c1c2 Binary files /dev/null and b/resources/stac_mount_save_files/figure-gfm/ASPECT_plot-1.png differ diff --git a/resources/stac_mount_save_files/figure-gfm/DEM_plot-1.png 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page-start] minmax(50px, 100px) [page-start-inset] 50px [body-start-outset] 50px [body-start] 1.5em [body-content-start] minmax(500px, calc( 1000px - 3em )) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(0px, 100px) [page-end-inset] 50px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.floating.slimcontent .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start] 50px [page-start-inset] minmax(50px, 150px) [body-start-outset] 50px [body-start] 1.5em [body-content-start] minmax(450px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(50px, 150px) [page-end-inset] 50px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.floating.listing .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start] minmax(25px, 50px) [page-start-inset] minmax(50px, 150px) [body-start-outset] minmax(25px, 50px) [body-start] 1.5em [body-content-start] minmax(500px, calc(800px - 3em)) [body-content-end] 1.5em [body-end] minmax(25px, 50px) [body-end-outset] minmax(50px, 150px) [page-end-inset] minmax(25px, 50px) [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}}@media(max-width: 991.98px){body .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset] 5fr [body-start] 1.5em [body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 35px [body-end-outset] minmax(75px, 145px) [page-end-inset] 35px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.fullcontent:not(.floating):not(.docked) .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset] 5fr [body-start] 1.5em [body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end body-end-outset page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.slimcontent:not(.floating):not(.docked) .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset] 5fr [body-start] 1.5em [body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 35px [body-end-outset] minmax(75px, 145px) [page-end-inset] 35px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.listing:not(.floating):not(.docked) .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset] 5fr [body-start] 1.5em [body-content-start] minmax(500px, calc(1200px - 3em)) [body-content-end body-end body-end-outset page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body:not(.floating):not(.docked) .page-columns.toc-left{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start] 35px [page-start-inset] minmax(0px, 145px) [body-start-outset] 35px [body-start] 1.5em [body-content-start] minmax(450px, calc(750px - 3em)) [body-content-end] 1.5em [body-end body-end-outset page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body:not(.floating):not(.docked) .page-columns.toc-left .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start] 35px [page-start-inset] minmax(0px, 145px) [body-start-outset] 35px [body-start] 1.5em [body-content-start] minmax(450px, calc(750px - 3em)) [body-content-end] 1.5em [body-end body-end-outset page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.floating .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start page-start-inset body-start-outset body-start] 1em [body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(75px, 150px) [page-end-inset] 25px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.docked .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset body-start body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(25px, 50px) [page-end-inset] 50px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.docked.fullcontent .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset body-start body-content-start] minmax(500px, calc( 1000px - 3em )) [body-content-end] 1.5em [body-end body-end-outset page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.floating.fullcontent .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start page-start-inset body-start-outset body-start] 1em [body-content-start] minmax(500px, calc(800px - 3em)) [body-content-end] 1.5em [body-end body-end-outset page-end-inset page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.docked.slimcontent .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset body-start body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 35px [body-end-outset] minmax(75px, 145px) [page-end-inset] 35px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.docked.listing .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset page-start page-start-inset body-start-outset body-start body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(25px, 50px) [page-end-inset] 50px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}body.floating.slimcontent .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start page-start-inset body-start-outset body-start] 1em [body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 35px [body-end-outset] minmax(75px, 145px) [page-end-inset] 35px [page-end] 4fr [screen-end-inset] 1.5em [screen-end]}body.floating.listing .page-columns{display:grid;gap:0;grid-template-columns:[screen-start] 1.5em [screen-start-inset] 5fr [page-start page-start-inset body-start-outset body-start] 1em [body-content-start] minmax(500px, calc(750px - 3em)) [body-content-end] 1.5em [body-end] 50px [body-end-outset] minmax(75px, 150px) [page-end-inset] 25px [page-end] 5fr [screen-end-inset] 1.5em [screen-end]}}@media(max-width: 767.98px){body .page-columns,body.fullcontent:not(.floating):not(.docked) .page-columns,body.slimcontent:not(.floating):not(.docked) .page-columns,body.docked .page-columns,body.docked.slimcontent 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body-content-start] minmax(0px, 1fr) [body-content-end body-end body-end-outset page-end-inset page-end screen-end-inset] 1.5em [screen-end]}nav[role=doc-toc]{display:none}}body,.page-row-navigation{grid-template-rows:[page-top] max-content [contents-top] max-content [contents-bottom] max-content [page-bottom]}.page-rows-contents{grid-template-rows:[content-top] minmax(max-content, 1fr) [content-bottom] minmax(60px, max-content) [page-bottom]}.page-full{grid-column:screen-start/screen-end !important}.page-columns>*{grid-column:body-content-start/body-content-end}.page-columns.column-page>*{grid-column:page-start/page-end}.page-columns.column-page-left>*{grid-column:page-start/body-content-end}.page-columns.column-page-right>*{grid-column:body-content-start/page-end}.page-rows{grid-auto-rows:auto}.header{grid-column:screen-start/screen-end;grid-row:page-top/contents-top}#quarto-content{padding:0;grid-column:screen-start/screen-end;grid-row:contents-top/contents-bottom}body.floating 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t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return"static"===this._config.display&&(t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,..."function"==typeof this._config.popperConfig?this._config.popperConfig(t):this._config.popperConfig}}_selectMenuItem({key:t,target:e}){const i=V.find(".dropdown-menu .dropdown-item:not(.disabled):not(:disabled)",this._menu).filter(l);i.length&&v(i,e,t===Ye,!i.includes(e)).focus()}static jQueryInterface(t){return this.each((function(){const e=hi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}static clearMenus(t){if(t&&(2===t.button||"keyup"===t.type&&"Tab"!==t.key))return;const e=V.find(ti);for(let 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0===i?t.style.removeProperty(e):(U.removeDataAttribute(t,e),t.style[e]=i)}))}_applyManipulationCallback(t,e){o(t)?e(t):V.find(t,this._element).forEach(e)}isOverflowing(){return this.getWidth()>0}}const pi={className:"modal-backdrop",isVisible:!0,isAnimated:!1,rootElement:"body",clickCallback:null},mi={className:"string",isVisible:"boolean",isAnimated:"boolean",rootElement:"(element|string)",clickCallback:"(function|null)"},gi="show",_i="mousedown.bs.backdrop";class bi{constructor(t){this._config=this._getConfig(t),this._isAppended=!1,this._element=null}show(t){this._config.isVisible?(this._append(),this._config.isAnimated&&u(this._getElement()),this._getElement().classList.add(gi),this._emulateAnimation((()=>{_(t)}))):_(t)}hide(t){this._config.isVisible?(this._getElement().classList.remove(gi),this._emulateAnimation((()=>{this.dispose(),_(t)}))):_(t)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_getConfig(t){return(t={...pi,..."object"==typeof t?t:{}}).rootElement=r(t.rootElement),a("backdrop",t,mi),t}_append(){this._isAppended||(this._config.rootElement.append(this._getElement()),j.on(this._getElement(),_i,(()=>{_(this._config.clickCallback)})),this._isAppended=!0)}dispose(){this._isAppended&&(j.off(this._element,_i),this._element.remove(),this._isAppended=!1)}_emulateAnimation(t){b(t,this._getElement(),this._config.isAnimated)}}const vi={trapElement:null,autofocus:!0},yi={trapElement:"element",autofocus:"boolean"},wi=".bs.focustrap",Ei="backward";class Ai{constructor(t){this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}activate(){const{trapElement:t,autofocus:e}=this._config;this._isActive||(e&&t.focus(),j.off(document,wi),j.on(document,"focusin.bs.focustrap",(t=>this._handleFocusin(t))),j.on(document,"keydown.tab.bs.focustrap",(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,j.off(document,wi))}_handleFocusin(t){const{target:e}=t,{trapElement:i}=this._config;if(e===document||e===i||i.contains(e))return;const n=V.focusableChildren(i);0===n.length?i.focus():this._lastTabNavDirection===Ei?n[n.length-1].focus():n[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?Ei:"forward")}_getConfig(t){return t={...vi,..."object"==typeof t?t:{}},a("focustrap",t,yi),t}}const Ti="modal",Oi="Escape",Ci={backdrop:!0,keyboard:!0,focus:!0},ki={backdrop:"(boolean|string)",keyboard:"boolean",focus:"boolean"},Li="hidden.bs.modal",xi="show.bs.modal",Di="resize.bs.modal",Si="click.dismiss.bs.modal",Ni="keydown.dismiss.bs.modal",Ii="mousedown.dismiss.bs.modal",Pi="modal-open",ji="show",Mi="modal-static";class Hi extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._dialog=V.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._ignoreBackdropClick=!1,this._isTransitioning=!1,this._scrollBar=new fi}static get Default(){return Ci}static get NAME(){return Ti}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||j.trigger(this._element,xi,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isAnimated()&&(this._isTransitioning=!0),this._scrollBar.hide(),document.body.classList.add(Pi),this._adjustDialog(),this._setEscapeEvent(),this._setResizeEvent(),j.on(this._dialog,Ii,(()=>{j.one(this._element,"mouseup.dismiss.bs.modal",(t=>{t.target===this._element&&(this._ignoreBackdropClick=!0)}))})),this._showBackdrop((()=>this._showElement(t))))}hide(){if(!this._isShown||this._isTransitioning)return;if(j.trigger(this._element,"hide.bs.modal").defaultPrevented)return;this._isShown=!1;const t=this._isAnimated();t&&(this._isTransitioning=!0),this._setEscapeEvent(),this._setResizeEvent(),this._focustrap.deactivate(),this._element.classList.remove(ji),j.off(this._element,Si),j.off(this._dialog,Ii),this._queueCallback((()=>this._hideModal()),this._element,t)}dispose(){[window,this._dialog].forEach((t=>j.off(t,".bs.modal"))),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new bi({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new Ai({trapElement:this._element})}_getConfig(t){return t={...Ci,...U.getDataAttributes(this._element),..."object"==typeof t?t:{}},a(Ti,t,ki),t}_showElement(t){const e=this._isAnimated(),i=V.findOne(".modal-body",this._dialog);this._element.parentNode&&this._element.parentNode.nodeType===Node.ELEMENT_NODE||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0,i&&(i.scrollTop=0),e&&u(this._element),this._element.classList.add(ji),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,j.trigger(this._element,"shown.bs.modal",{relatedTarget:t})}),this._dialog,e)}_setEscapeEvent(){this._isShown?j.on(this._element,Ni,(t=>{this._config.keyboard&&t.key===Oi?(t.preventDefault(),this.hide()):this._config.keyboard||t.key!==Oi||this._triggerBackdropTransition()})):j.off(this._element,Ni)}_setResizeEvent(){this._isShown?j.on(window,Di,(()=>this._adjustDialog())):j.off(window,Di)}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(Pi),this._resetAdjustments(),this._scrollBar.reset(),j.trigger(this._element,Li)}))}_showBackdrop(t){j.on(this._element,Si,(t=>{this._ignoreBackdropClick?this._ignoreBackdropClick=!1:t.target===t.currentTarget&&(!0===this._config.backdrop?this.hide():"static"===this._config.backdrop&&this._triggerBackdropTransition())})),this._backdrop.show(t)}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(j.trigger(this._element,"hidePrevented.bs.modal").defaultPrevented)return;const{classList:t,scrollHeight:e,style:i}=this._element,n=e>document.documentElement.clientHeight;!n&&"hidden"===i.overflowY||t.contains(Mi)||(n||(i.overflowY="hidden"),t.add(Mi),this._queueCallback((()=>{t.remove(Mi),n||this._queueCallback((()=>{i.overflowY=""}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;(!i&&t&&!m()||i&&!t&&m())&&(this._element.style.paddingLeft=`${e}px`),(i&&!t&&!m()||!i&&t&&m())&&(this._element.style.paddingRight=`${e}px`)}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=Hi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}j.on(document,"click.bs.modal.data-api",'[data-bs-toggle="modal"]',(function(t){const e=n(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),j.one(e,xi,(t=>{t.defaultPrevented||j.one(e,Li,(()=>{l(this)&&this.focus()}))}));const i=V.findOne(".modal.show");i&&Hi.getInstance(i).hide(),Hi.getOrCreateInstance(e).toggle(this)})),R(Hi),g(Hi);const Bi="offcanvas",Ri={backdrop:!0,keyboard:!0,scroll:!1},Wi={backdrop:"boolean",keyboard:"boolean",scroll:"boolean"},$i="show",zi=".offcanvas.show",qi="hidden.bs.offcanvas";class Fi extends B{constructor(t,e){super(t),this._config=this._getConfig(e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get NAME(){return Bi}static get Default(){return Ri}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||j.trigger(this._element,"show.bs.offcanvas",{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._element.style.visibility="visible",this._backdrop.show(),this._config.scroll||(new fi).hide(),this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add($i),this._queueCallback((()=>{this._config.scroll||this._focustrap.activate(),j.trigger(this._element,"shown.bs.offcanvas",{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(j.trigger(this._element,"hide.bs.offcanvas").defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.remove($i),this._backdrop.hide(),this._queueCallback((()=>{this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._element.style.visibility="hidden",this._config.scroll||(new fi).reset(),j.trigger(this._element,qi)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_getConfig(t){return t={...Ri,...U.getDataAttributes(this._element),..."object"==typeof t?t:{}},a(Bi,t,Wi),t}_initializeBackDrop(){return new bi({className:"offcanvas-backdrop",isVisible:this._config.backdrop,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:()=>this.hide()})}_initializeFocusTrap(){return new Ai({trapElement:this._element})}_addEventListeners(){j.on(this._element,"keydown.dismiss.bs.offcanvas",(t=>{this._config.keyboard&&"Escape"===t.key&&this.hide()}))}static jQueryInterface(t){return this.each((function(){const e=Fi.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}j.on(document,"click.bs.offcanvas.data-api",'[data-bs-toggle="offcanvas"]',(function(t){const e=n(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),c(this))return;j.one(e,qi,(()=>{l(this)&&this.focus()}));const i=V.findOne(zi);i&&i!==e&&Fi.getInstance(i).hide(),Fi.getOrCreateInstance(e).toggle(this)})),j.on(window,"load.bs.offcanvas.data-api",(()=>V.find(zi).forEach((t=>Fi.getOrCreateInstance(t).show())))),R(Fi),g(Fi);const Ui=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Vi=/^(?:(?:https?|mailto|ftp|tel|file|sms):|[^#&/:?]*(?:[#/?]|$))/i,Ki=/^data:(?:image\/(?:bmp|gif|jpeg|jpg|png|tiff|webp)|video\/(?:mpeg|mp4|ogg|webm)|audio\/(?:mp3|oga|ogg|opus));base64,[\d+/a-z]+=*$/i,Xi=(t,e)=>{const i=t.nodeName.toLowerCase();if(e.includes(i))return!Ui.has(i)||Boolean(Vi.test(t.nodeValue)||Ki.test(t.nodeValue));const n=e.filter((t=>t instanceof RegExp));for(let t=0,e=n.length;t{Xi(t,r)||i.removeAttribute(t.nodeName)}))}return n.body.innerHTML}const Qi="tooltip",Gi=new Set(["sanitize","allowList","sanitizeFn"]),Zi={animation:"boolean",template:"string",title:"(string|element|function)",trigger:"string",delay:"(number|object)",html:"boolean",selector:"(string|boolean)",placement:"(string|function)",offset:"(array|string|function)",container:"(string|element|boolean)",fallbackPlacements:"array",boundary:"(string|element)",customClass:"(string|function)",sanitize:"boolean",sanitizeFn:"(null|function)",allowList:"object",popperConfig:"(null|object|function)"},Ji={AUTO:"auto",TOP:"top",RIGHT:m()?"left":"right",BOTTOM:"bottom",LEFT:m()?"right":"left"},tn={animation:!0,template:'',trigger:"hover focus",title:"",delay:0,html:!1,selector:!1,placement:"top",offset:[0,0],container:!1,fallbackPlacements:["top","right","bottom","left"],boundary:"clippingParents",customClass:"",sanitize:!0,sanitizeFn:null,allowList:{"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},popperConfig:null},en={HIDE:"hide.bs.tooltip",HIDDEN:"hidden.bs.tooltip",SHOW:"show.bs.tooltip",SHOWN:"shown.bs.tooltip",INSERTED:"inserted.bs.tooltip",CLICK:"click.bs.tooltip",FOCUSIN:"focusin.bs.tooltip",FOCUSOUT:"focusout.bs.tooltip",MOUSEENTER:"mouseenter.bs.tooltip",MOUSELEAVE:"mouseleave.bs.tooltip"},nn="fade",sn="show",on="show",rn="out",an=".tooltip-inner",ln=".modal",cn="hide.bs.modal",hn="hover",dn="focus";class un extends B{constructor(t,e){if(void 0===Fe)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t),this._isEnabled=!0,this._timeout=0,this._hoverState="",this._activeTrigger={},this._popper=null,this._config=this._getConfig(e),this.tip=null,this._setListeners()}static get Default(){return tn}static get NAME(){return Qi}static get Event(){return en}static get DefaultType(){return Zi}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(t){if(this._isEnabled)if(t){const e=this._initializeOnDelegatedTarget(t);e._activeTrigger.click=!e._activeTrigger.click,e._isWithActiveTrigger()?e._enter(null,e):e._leave(null,e)}else{if(this.getTipElement().classList.contains(sn))return void this._leave(null,this);this._enter(null,this)}}dispose(){clearTimeout(this._timeout),j.off(this._element.closest(ln),cn,this._hideModalHandler),this.tip&&this.tip.remove(),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this.isWithContent()||!this._isEnabled)return;const t=j.trigger(this._element,this.constructor.Event.SHOW),e=h(this._element),i=null===e?this._element.ownerDocument.documentElement.contains(this._element):e.contains(this._element);if(t.defaultPrevented||!i)return;"tooltip"===this.constructor.NAME&&this.tip&&this.getTitle()!==this.tip.querySelector(an).innerHTML&&(this._disposePopper(),this.tip.remove(),this.tip=null);const n=this.getTipElement(),s=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME);n.setAttribute("id",s),this._element.setAttribute("aria-describedby",s),this._config.animation&&n.classList.add(nn);const o="function"==typeof this._config.placement?this._config.placement.call(this,n,this._element):this._config.placement,r=this._getAttachment(o);this._addAttachmentClass(r);const{container:a}=this._config;H.set(n,this.constructor.DATA_KEY,this),this._element.ownerDocument.documentElement.contains(this.tip)||(a.append(n),j.trigger(this._element,this.constructor.Event.INSERTED)),this._popper?this._popper.update():this._popper=qe(this._element,n,this._getPopperConfig(r)),n.classList.add(sn);const l=this._resolvePossibleFunction(this._config.customClass);l&&n.classList.add(...l.split(" ")),"ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>{j.on(t,"mouseover",d)}));const c=this.tip.classList.contains(nn);this._queueCallback((()=>{const t=this._hoverState;this._hoverState=null,j.trigger(this._element,this.constructor.Event.SHOWN),t===rn&&this._leave(null,this)}),this.tip,c)}hide(){if(!this._popper)return;const t=this.getTipElement();if(j.trigger(this._element,this.constructor.Event.HIDE).defaultPrevented)return;t.classList.remove(sn),"ontouchstart"in document.documentElement&&[].concat(...document.body.children).forEach((t=>j.off(t,"mouseover",d))),this._activeTrigger.click=!1,this._activeTrigger.focus=!1,this._activeTrigger.hover=!1;const e=this.tip.classList.contains(nn);this._queueCallback((()=>{this._isWithActiveTrigger()||(this._hoverState!==on&&t.remove(),this._cleanTipClass(),this._element.removeAttribute("aria-describedby"),j.trigger(this._element,this.constructor.Event.HIDDEN),this._disposePopper())}),this.tip,e),this._hoverState=""}update(){null!==this._popper&&this._popper.update()}isWithContent(){return Boolean(this.getTitle())}getTipElement(){if(this.tip)return this.tip;const t=document.createElement("div");t.innerHTML=this._config.template;const e=t.children[0];return this.setContent(e),e.classList.remove(nn,sn),this.tip=e,this.tip}setContent(t){this._sanitizeAndSetContent(t,this.getTitle(),an)}_sanitizeAndSetContent(t,e,i){const n=V.findOne(i,t);e||!n?this.setElementContent(n,e):n.remove()}setElementContent(t,e){if(null!==t)return o(e)?(e=r(e),void(this._config.html?e.parentNode!==t&&(t.innerHTML="",t.append(e)):t.textContent=e.textContent)):void(this._config.html?(this._config.sanitize&&(e=Yi(e,this._config.allowList,this._config.sanitizeFn)),t.innerHTML=e):t.textContent=e)}getTitle(){const t=this._element.getAttribute("data-bs-original-title")||this._config.title;return this._resolvePossibleFunction(t)}updateAttachment(t){return"right"===t?"end":"left"===t?"start":t}_initializeOnDelegatedTarget(t,e){return e||this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return"function"==typeof t?t.call(this._element):t}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"onChange",enabled:!0,phase:"afterWrite",fn:t=>this._handlePopperPlacementChange(t)}],onFirstUpdate:t=>{t.options.placement!==t.placement&&this._handlePopperPlacementChange(t)}};return{...e,..."function"==typeof this._config.popperConfig?this._config.popperConfig(e):this._config.popperConfig}}_addAttachmentClass(t){this.getTipElement().classList.add(`${this._getBasicClassPrefix()}-${this.updateAttachment(t)}`)}_getAttachment(t){return Ji[t.toUpperCase()]}_setListeners(){this._config.trigger.split(" ").forEach((t=>{if("click"===t)j.on(this._element,this.constructor.Event.CLICK,this._config.selector,(t=>this.toggle(t)));else if("manual"!==t){const e=t===hn?this.constructor.Event.MOUSEENTER:this.constructor.Event.FOCUSIN,i=t===hn?this.constructor.Event.MOUSELEAVE:this.constructor.Event.FOCUSOUT;j.on(this._element,e,this._config.selector,(t=>this._enter(t))),j.on(this._element,i,this._config.selector,(t=>this._leave(t)))}})),this._hideModalHandler=()=>{this._element&&this.hide()},j.on(this._element.closest(ln),cn,this._hideModalHandler),this._config.selector?this._config={...this._config,trigger:"manual",selector:""}:this._fixTitle()}_fixTitle(){const t=this._element.getAttribute("title"),e=typeof this._element.getAttribute("data-bs-original-title");(t||"string"!==e)&&(this._element.setAttribute("data-bs-original-title",t||""),!t||this._element.getAttribute("aria-label")||this._element.textContent||this._element.setAttribute("aria-label",t),this._element.setAttribute("title",""))}_enter(t,e){e=this._initializeOnDelegatedTarget(t,e),t&&(e._activeTrigger["focusin"===t.type?dn:hn]=!0),e.getTipElement().classList.contains(sn)||e._hoverState===on?e._hoverState=on:(clearTimeout(e._timeout),e._hoverState=on,e._config.delay&&e._config.delay.show?e._timeout=setTimeout((()=>{e._hoverState===on&&e.show()}),e._config.delay.show):e.show())}_leave(t,e){e=this._initializeOnDelegatedTarget(t,e),t&&(e._activeTrigger["focusout"===t.type?dn:hn]=e._element.contains(t.relatedTarget)),e._isWithActiveTrigger()||(clearTimeout(e._timeout),e._hoverState=rn,e._config.delay&&e._config.delay.hide?e._timeout=setTimeout((()=>{e._hoverState===rn&&e.hide()}),e._config.delay.hide):e.hide())}_isWithActiveTrigger(){for(const t in this._activeTrigger)if(this._activeTrigger[t])return!0;return!1}_getConfig(t){const e=U.getDataAttributes(this._element);return Object.keys(e).forEach((t=>{Gi.has(t)&&delete e[t]})),(t={...this.constructor.Default,...e,..."object"==typeof t&&t?t:{}}).container=!1===t.container?document.body:r(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),a(Qi,t,this.constructor.DefaultType),t.sanitize&&(t.template=Yi(t.template,t.allowList,t.sanitizeFn)),t}_getDelegateConfig(){const t={};for(const e in this._config)this.constructor.Default[e]!==this._config[e]&&(t[e]=this._config[e]);return t}_cleanTipClass(){const t=this.getTipElement(),e=new RegExp(`(^|\\s)${this._getBasicClassPrefix()}\\S+`,"g"),i=t.getAttribute("class").match(e);null!==i&&i.length>0&&i.map((t=>t.trim())).forEach((e=>t.classList.remove(e)))}_getBasicClassPrefix(){return"bs-tooltip"}_handlePopperPlacementChange(t){const{state:e}=t;e&&(this.tip=e.elements.popper,this._cleanTipClass(),this._addAttachmentClass(this._getAttachment(e.placement)))}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null)}static jQueryInterface(t){return this.each((function(){const e=un.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}g(un);const fn={...un.Default,placement:"right",offset:[0,8],trigger:"click",content:"",template:''},pn={...un.DefaultType,content:"(string|element|function)"},mn={HIDE:"hide.bs.popover",HIDDEN:"hidden.bs.popover",SHOW:"show.bs.popover",SHOWN:"shown.bs.popover",INSERTED:"inserted.bs.popover",CLICK:"click.bs.popover",FOCUSIN:"focusin.bs.popover",FOCUSOUT:"focusout.bs.popover",MOUSEENTER:"mouseenter.bs.popover",MOUSELEAVE:"mouseleave.bs.popover"};class gn extends un{static get Default(){return fn}static get NAME(){return"popover"}static get Event(){return mn}static get DefaultType(){return pn}isWithContent(){return this.getTitle()||this._getContent()}setContent(t){this._sanitizeAndSetContent(t,this.getTitle(),".popover-header"),this._sanitizeAndSetContent(t,this._getContent(),".popover-body")}_getContent(){return this._resolvePossibleFunction(this._config.content)}_getBasicClassPrefix(){return"bs-popover"}static jQueryInterface(t){return this.each((function(){const e=gn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}g(gn);const _n="scrollspy",bn={offset:10,method:"auto",target:""},vn={offset:"number",method:"string",target:"(string|element)"},yn="active",wn=".nav-link, .list-group-item, .dropdown-item",En="position";class An extends B{constructor(t,e){super(t),this._scrollElement="BODY"===this._element.tagName?window:this._element,this._config=this._getConfig(e),this._offsets=[],this._targets=[],this._activeTarget=null,this._scrollHeight=0,j.on(this._scrollElement,"scroll.bs.scrollspy",(()=>this._process())),this.refresh(),this._process()}static get Default(){return bn}static get NAME(){return _n}refresh(){const t=this._scrollElement===this._scrollElement.window?"offset":En,e="auto"===this._config.method?t:this._config.method,n=e===En?this._getScrollTop():0;this._offsets=[],this._targets=[],this._scrollHeight=this._getScrollHeight(),V.find(wn,this._config.target).map((t=>{const s=i(t),o=s?V.findOne(s):null;if(o){const t=o.getBoundingClientRect();if(t.width||t.height)return[U[e](o).top+n,s]}return null})).filter((t=>t)).sort(((t,e)=>t[0]-e[0])).forEach((t=>{this._offsets.push(t[0]),this._targets.push(t[1])}))}dispose(){j.off(this._scrollElement,".bs.scrollspy"),super.dispose()}_getConfig(t){return(t={...bn,...U.getDataAttributes(this._element),..."object"==typeof t&&t?t:{}}).target=r(t.target)||document.documentElement,a(_n,t,vn),t}_getScrollTop(){return this._scrollElement===window?this._scrollElement.pageYOffset:this._scrollElement.scrollTop}_getScrollHeight(){return this._scrollElement.scrollHeight||Math.max(document.body.scrollHeight,document.documentElement.scrollHeight)}_getOffsetHeight(){return this._scrollElement===window?window.innerHeight:this._scrollElement.getBoundingClientRect().height}_process(){const t=this._getScrollTop()+this._config.offset,e=this._getScrollHeight(),i=this._config.offset+e-this._getOffsetHeight();if(this._scrollHeight!==e&&this.refresh(),t>=i){const t=this._targets[this._targets.length-1];this._activeTarget!==t&&this._activate(t)}else{if(this._activeTarget&&t0)return this._activeTarget=null,void this._clear();for(let e=this._offsets.length;e--;)this._activeTarget!==this._targets[e]&&t>=this._offsets[e]&&(void 0===this._offsets[e+1]||t`${e}[data-bs-target="${t}"],${e}[href="${t}"]`)),i=V.findOne(e.join(","),this._config.target);i.classList.add(yn),i.classList.contains("dropdown-item")?V.findOne(".dropdown-toggle",i.closest(".dropdown")).classList.add(yn):V.parents(i,".nav, 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index 0000000..36cb328 --- /dev/null +++ b/resources/stac_mount_save_files/libs/quarto-html/quarto-syntax-highlighting.css @@ -0,0 +1,171 @@ +/* quarto syntax highlight colors */ +:root { + --quarto-hl-ot-color: #003B4F; + --quarto-hl-at-color: #657422; + --quarto-hl-ss-color: #20794D; + --quarto-hl-an-color: #5E5E5E; + --quarto-hl-fu-color: #4758AB; + --quarto-hl-st-color: #20794D; + --quarto-hl-cf-color: #003B4F; + --quarto-hl-op-color: #5E5E5E; + --quarto-hl-er-color: #AD0000; + --quarto-hl-bn-color: #AD0000; + --quarto-hl-al-color: #AD0000; + --quarto-hl-va-color: #111111; + --quarto-hl-bu-color: inherit; + --quarto-hl-ex-color: inherit; + --quarto-hl-pp-color: #AD0000; + --quarto-hl-in-color: #5E5E5E; + --quarto-hl-vs-color: #20794D; + --quarto-hl-wa-color: #5E5E5E; + --quarto-hl-do-color: #5E5E5E; + --quarto-hl-im-color: #00769E; + --quarto-hl-ch-color: #20794D; + --quarto-hl-dt-color: #AD0000; + --quarto-hl-fl-color: #AD0000; + --quarto-hl-co-color: #5E5E5E; + --quarto-hl-cv-color: #5E5E5E; + --quarto-hl-cn-color: #8f5902; + --quarto-hl-sc-color: #5E5E5E; + --quarto-hl-dv-color: #AD0000; + --quarto-hl-kw-color: #003B4F; +} + +/* other quarto variables */ +:root { + --quarto-font-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace; +} + +pre > code.sourceCode > span { + color: #003B4F; +} + +code span { + color: #003B4F; +} + +code.sourceCode > span { + color: #003B4F; +} + +div.sourceCode, +div.sourceCode pre.sourceCode { + color: #003B4F; +} + +code span.ot { + color: #003B4F; +} + +code span.at { + color: #657422; +} + +code span.ss { + color: #20794D; +} + +code span.an { + color: #5E5E5E; +} + +code span.fu { + color: #4758AB; +} + +code span.st { + color: #20794D; +} + +code span.cf { + color: #003B4F; +} + +code span.op { + color: #5E5E5E; +} + +code span.er { + color: #AD0000; +} + +code span.bn { + color: #AD0000; +} + +code span.al { + color: #AD0000; +} + +code span.va { + color: #111111; +} + +code span.pp { + color: #AD0000; +} + +code span.in { + color: #5E5E5E; +} + +code span.vs { + color: #20794D; +} + +code span.wa { + color: #5E5E5E; + font-style: italic; +} + +code span.do { + color: #5E5E5E; + font-style: italic; +} + +code span.im { + color: #00769E; +} + +code span.ch { + color: #20794D; +} + +code span.dt { + color: #AD0000; +} + +code span.fl { + color: #AD0000; +} + +code span.co { + color: #5E5E5E; +} + +code span.cv { + color: #5E5E5E; + font-style: italic; +} + +code span.cn { + color: #8f5902; +} + +code span.sc { + color: #5E5E5E; +} + +code span.dv { + color: #AD0000; +} + +code span.kw { + color: #003B4F; +} + +.prevent-inlining { + content: " { + const sibling = el.previousElementSibling; + if (sibling && sibling.tagName === "A") { + return sibling.classList.contains("active"); + } else { + return false; + } + }; + + // fire slideEnter for bootstrap tab activations (for htmlwidget resize behavior) + function fireSlideEnter(e) { + const event = window.document.createEvent("Event"); + event.initEvent("slideenter", true, true); + window.document.dispatchEvent(event); + } + const tabs = window.document.querySelectorAll('a[data-bs-toggle="tab"]'); + tabs.forEach((tab) => { + tab.addEventListener("shown.bs.tab", fireSlideEnter); + }); + + // Track scrolling and mark TOC links as active + // get table of contents and sidebar (bail if we don't have at least one) + const tocLinks = tocEl + ? [...tocEl.querySelectorAll("a[data-scroll-target]")] + : []; + const makeActive = (link) => tocLinks[link].classList.add("active"); + const removeActive = (link) => tocLinks[link].classList.remove("active"); + const removeAllActive = () => + [...Array(tocLinks.length).keys()].forEach((link) => removeActive(link)); + + // activate the anchor for a section associated with this TOC entry + tocLinks.forEach((link) => { + link.addEventListener("click", () => { + if (link.href.indexOf("#") !== -1) { + const anchor = link.href.split("#")[1]; + const heading = window.document.querySelector( + `[data-anchor-id=${anchor}]` + ); + if (heading) { + // Add the class + heading.classList.add("reveal-anchorjs-link"); + + // function to show the anchor + const handleMouseout = () => { + heading.classList.remove("reveal-anchorjs-link"); + heading.removeEventListener("mouseout", handleMouseout); + }; + + // add a function to clear the anchor when the user mouses out of it + heading.addEventListener("mouseout", handleMouseout); + } + } + }); + }); + + const sections = tocLinks.map((link) => { + const target = link.getAttribute("data-scroll-target"); + if (target.startsWith("#")) { + return window.document.getElementById(decodeURI(`${target.slice(1)}`)); + } else { + return window.document.querySelector(decodeURI(`${target}`)); + } + }); + + const sectionMargin = 200; + let currentActive = 0; + // track whether we've initialized state the first time + let init = false; + + const updateActiveLink = () => { + // The index from bottom to top (e.g. reversed list) + let sectionIndex = -1; + if ( + window.innerHeight + window.pageYOffset >= + window.document.body.offsetHeight + ) { + sectionIndex = 0; + } else { + sectionIndex = [...sections].reverse().findIndex((section) => { + if (section) { + return window.pageYOffset >= section.offsetTop - sectionMargin; + } else { + return false; + } + }); + } + if (sectionIndex > -1) { + const current = sections.length - sectionIndex - 1; + if (current !== currentActive) { + removeAllActive(); + currentActive = current; + makeActive(current); + if (init) { + window.dispatchEvent(sectionChanged); + } + init = true; + } + } + }; + + const inHiddenRegion = (top, bottom, hiddenRegions) => { + for (const region of hiddenRegions) { + if (top <= region.bottom && bottom >= region.top) { + return true; + } + } + return false; + }; + + const categorySelector = "header.quarto-title-block .quarto-category"; + const activateCategories = (href) => { + // Find any categories + // Surround them with a link pointing back to: + // #category=Authoring + try { + const categoryEls = window.document.querySelectorAll(categorySelector); + for (const categoryEl of categoryEls) { + const categoryText = categoryEl.textContent; + if (categoryText) { + const link = `${href}#category=${encodeURIComponent(categoryText)}`; + const linkEl = window.document.createElement("a"); + linkEl.setAttribute("href", link); + for (const child of categoryEl.childNodes) { + linkEl.append(child); + } + categoryEl.appendChild(linkEl); + } + } + } catch { + // Ignore errors + } + }; + function hasTitleCategories() { + return window.document.querySelector(categorySelector) !== null; + } + + function offsetRelativeUrl(url) { + const offset = getMeta("quarto:offset"); + return offset ? offset + url : url; + } + + function offsetAbsoluteUrl(url) { + const offset = getMeta("quarto:offset"); + const baseUrl = new URL(offset, window.location); + + const projRelativeUrl = url.replace(baseUrl, ""); + if (projRelativeUrl.startsWith("/")) { + return projRelativeUrl; + } else { + return "/" + projRelativeUrl; + } + } + + // read a meta tag value + function getMeta(metaName) { + const metas = window.document.getElementsByTagName("meta"); + for (let i = 0; i < metas.length; i++) { + if (metas[i].getAttribute("name") === metaName) { + return metas[i].getAttribute("content"); + } + } + return ""; + } + + async function findAndActivateCategories() { + const currentPagePath = offsetAbsoluteUrl(window.location.href); + const response = await fetch(offsetRelativeUrl("listings.json")); + if (response.status == 200) { + return response.json().then(function (listingPaths) { + const listingHrefs = []; + for (const listingPath of listingPaths) { + const pathWithoutLeadingSlash = listingPath.listing.substring(1); + for (const item of listingPath.items) { + if ( + item === currentPagePath || + item === currentPagePath + "index.html" + ) { + // Resolve this path against the offset to be sure + // we already are using the correct path to the listing + // (this adjusts the listing urls to be rooted against + // whatever root the page is actually running against) + const relative = offsetRelativeUrl(pathWithoutLeadingSlash); + const baseUrl = window.location; + const resolvedPath = new URL(relative, baseUrl); + listingHrefs.push(resolvedPath.pathname); + break; + } + } + } + + // Look up the tree for a nearby linting and use that if we find one + const nearestListing = findNearestParentListing( + offsetAbsoluteUrl(window.location.pathname), + listingHrefs + ); + if (nearestListing) { + activateCategories(nearestListing); + } else { + // See if the referrer is a listing page for this item + const referredRelativePath = offsetAbsoluteUrl(document.referrer); + const referrerListing = listingHrefs.find((listingHref) => { + const isListingReferrer = + listingHref === referredRelativePath || + listingHref === referredRelativePath + "index.html"; + return isListingReferrer; + }); + + if (referrerListing) { + // Try to use the referrer if possible + activateCategories(referrerListing); + } else if (listingHrefs.length > 0) { + // Otherwise, just fall back to the first listing + activateCategories(listingHrefs[0]); + } + } + }); + } + } + if (hasTitleCategories()) { + findAndActivateCategories(); + } + + const findNearestParentListing = (href, listingHrefs) => { + if (!href || !listingHrefs) { + return undefined; + } + // Look up the tree for a nearby linting and use that if we find one + const relativeParts = href.substring(1).split("/"); + while (relativeParts.length > 0) { + const path = relativeParts.join("/"); + for (const listingHref of listingHrefs) { + if (listingHref.startsWith(path)) { + return listingHref; + } + } + relativeParts.pop(); + } + + return undefined; + }; + + const manageSidebarVisiblity = (el, placeholderDescriptor) => { + let isVisible = true; + + return (hiddenRegions) => { + if (el === null) { + return; + } + + // Find the last element of the TOC + const lastChildEl = el.lastElementChild; + + if (lastChildEl) { + // Find the top and bottom o the element that is being managed + const elTop = el.offsetTop; + const elBottom = + elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight; + + // Converts the sidebar to a menu + const convertToMenu = () => { + for (const child of el.children) { + child.style.opacity = 0; + child.style.display = "none"; + } + + const toggleContainer = window.document.createElement("div"); + toggleContainer.style.width = "100%"; + toggleContainer.classList.add("zindex-over-content"); + toggleContainer.classList.add("quarto-sidebar-toggle"); + toggleContainer.classList.add("headroom-target"); // Marks this to be managed by headeroom + toggleContainer.id = placeholderDescriptor.id; + toggleContainer.style.position = "fixed"; + + const toggleIcon = window.document.createElement("i"); + toggleIcon.classList.add("quarto-sidebar-toggle-icon"); + toggleIcon.classList.add("bi"); + toggleIcon.classList.add("bi-caret-down-fill"); + + const toggleTitle = window.document.createElement("div"); + const titleEl = window.document.body.querySelector( + placeholderDescriptor.titleSelector + ); + if (titleEl) { + toggleTitle.append(titleEl.innerText, toggleIcon); + } + toggleTitle.classList.add("zindex-over-content"); + toggleTitle.classList.add("quarto-sidebar-toggle-title"); + toggleContainer.append(toggleTitle); + + const toggleContents = window.document.createElement("div"); + toggleContents.classList = el.classList; + toggleContents.classList.add("zindex-over-content"); + toggleContents.classList.add("quarto-sidebar-toggle-contents"); + for (const child of el.children) { + if (child.id === "toc-title") { + continue; + } + + const clone = child.cloneNode(true); + clone.style.opacity = 1; + clone.style.display = null; + toggleContents.append(clone); + } + toggleContents.style.height = "0px"; + toggleContainer.append(toggleContents); + el.parentElement.prepend(toggleContainer); + + // Process clicks + let tocShowing = false; + // Allow the caller to control whether this is dismissed + // when it is clicked (e.g. sidebar navigation supports + // opening and closing the nav tree, so don't dismiss on click) + const clickEl = placeholderDescriptor.dismissOnClick + ? toggleContainer + : toggleTitle; + + const closeToggle = () => { + if (tocShowing) { + toggleContainer.classList.remove("expanded"); + toggleContents.style.height = "0px"; + tocShowing = false; + } + }; + + const positionToggle = () => { + // position the element (top left of parent, same width as parent) + const elRect = el.getBoundingClientRect(); + toggleContainer.style.left = `${elRect.left}px`; + toggleContainer.style.top = `${elRect.top}px`; + toggleContainer.style.width = `${elRect.width}px`; + }; + + // Get rid of any expanded toggle if the user scrolls + window.document.addEventListener( + "scroll", + throttle(() => { + closeToggle(); + }, 50) + ); + + // Handle positioning of the toggle + window.addEventListener( + "resize", + throttle(() => { + positionToggle(); + }, 50) + ); + positionToggle(); + + // Process the click + clickEl.onclick = () => { + if (!tocShowing) { + toggleContainer.classList.add("expanded"); + toggleContents.style.height = null; + tocShowing = true; + } else { + closeToggle(); + } + }; + }; + + // Converts a sidebar from a menu back to a sidebar + const convertToSidebar = () => { + for (const child of el.children) { + child.style.opacity = 1; + clone.style.display = null; + } + + const placeholderEl = window.document.getElementById( + placeholderDescriptor.id + ); + if (placeholderEl) { + placeholderEl.remove(); + } + + el.classList.remove("rollup"); + }; + + if (isReaderMode()) { + convertToMenu(); + isVisible = false; + } else { + if (!isVisible) { + // If the element is current not visible reveal if there are + // no conflicts with overlay regions + if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) { + convertToSidebar(); + isVisible = true; + } + } else { + // If the element is visible, hide it if it conflicts with overlay regions + // and insert a placeholder toggle (or if we're in reader mode) + if (inHiddenRegion(elTop, elBottom, hiddenRegions)) { + convertToMenu(); + isVisible = false; + } + } + } + } + }; + }; + + // Find any conflicting margin elements and add margins to the + // top to prevent overlap + const marginChildren = window.document.querySelectorAll( + ".column-margin.column-container > * " + ); + let lastBottom = 0; + for (const marginChild of marginChildren) { + const top = marginChild.getBoundingClientRect().top; + if (top < lastBottom) { + const margin = lastBottom - top; + marginChild.style.marginTop = `${margin}px`; + } + const styles = window.getComputedStyle(marginChild); + const marginTop = parseFloat(styles["marginTop"]); + + lastBottom = top + marginChild.getBoundingClientRect().height + marginTop; + } + + // Manage the visibility of the toc and the sidebar + const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, { + id: "quarto-toc-toggle", + titleSelector: "#toc-title", + dismissOnClick: true, + }); + const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, { + id: "quarto-sidebarnav-toggle", + titleSelector: ".title", + dismissOnClick: false, + }); + let tocLeftScrollVisibility; + if (leftTocEl) { + tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, { + id: "quarto-lefttoc-toggle", + titleSelector: "#toc-title", + dismissOnClick: true, + }); + } + + // Find the first element that uses formatting in special columns + const conflictingEls = window.document.body.querySelectorAll( + '[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]' + ); + + // Filter all the possibly conflicting elements into ones + // the do conflict on the left or ride side + const arrConflictingEls = Array.from(conflictingEls); + const leftSideConflictEls = arrConflictingEls.filter((el) => { + if (el.tagName === "ASIDE") { + return false; + } + return Array.from(el.classList).find((className) => { + return ( + className !== "column-body" && + className.startsWith("column-") && + !className.endsWith("right") && + !className.endsWith("container") && + className !== "column-margin" + ); + }); + }); + const rightSideConflictEls = arrConflictingEls.filter((el) => { + if (el.tagName === "ASIDE") { + return true; + } + + const hasMarginCaption = Array.from(el.classList).find((className) => { + return className == "margin-caption"; + }); + if (hasMarginCaption) { + return true; + } + + return Array.from(el.classList).find((className) => { + return ( + className !== "column-body" && + !className.endsWith("container") && + className.startsWith("column-") && + !className.endsWith("left") + ); + }); + }); + + const kOverlapPaddingSize = 10; + function toRegions(els) { + return els.map((el) => { + const top = + el.getBoundingClientRect().top + + document.documentElement.scrollTop - + kOverlapPaddingSize; + return { + top, + bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize, + }; + }); + } + + const hideOverlappedSidebars = () => { + marginScrollVisibility(toRegions(rightSideConflictEls)); + sidebarScrollVisiblity(toRegions(leftSideConflictEls)); + if (tocLeftScrollVisibility) { + tocLeftScrollVisibility(toRegions(leftSideConflictEls)); + } + }; + + window.quartoToggleReader = () => { + // Applies a slow class (or removes it) + // to update the transition speed + const slowTransition = (slow) => { + const manageTransition = (id, slow) => { + const el = document.getElementById(id); + if (el) { + if (slow) { + el.classList.add("slow"); + } else { + el.classList.remove("slow"); + } + } + }; + + manageTransition("TOC", slow); + manageTransition("quarto-sidebar", slow); + }; + + const readerMode = !isReaderMode(); + setReaderModeValue(readerMode); + + // If we're entering reader mode, slow the transition + if (readerMode) { + slowTransition(readerMode); + } + highlightReaderToggle(readerMode); + hideOverlappedSidebars(); + + // If we're exiting reader mode, restore the non-slow transition + if (!readerMode) { + slowTransition(!readerMode); + } + }; + + const highlightReaderToggle = (readerMode) => { + const els = document.querySelectorAll(".quarto-reader-toggle"); + if (els) { + els.forEach((el) => { + if (readerMode) { + el.classList.add("reader"); + } else { + el.classList.remove("reader"); + } + }); + } + }; + + const setReaderModeValue = (val) => { + if (window.location.protocol !== "file:") { + window.localStorage.setItem("quarto-reader-mode", val); + } else { + localReaderMode = val; + } + }; + + const isReaderMode = () => { + if (window.location.protocol !== "file:") { + return window.localStorage.getItem("quarto-reader-mode") === "true"; + } else { + return localReaderMode; + } + }; + let localReaderMode = null; + + // Walk the TOC and collapse/expand nodes + // Nodes are expanded if: + // - they are top level + // - they have children that are 'active' links + // - they are directly below an link that is 'active' + const walk = (el, depth) => { + // Tick depth when we enter a UL + if (el.tagName === "UL") { + depth = depth + 1; + } + + // It this is active link + let isActiveNode = false; + if (el.tagName === "A" && el.classList.contains("active")) { + isActiveNode = true; + } + + // See if there is an active child to this element + let hasActiveChild = false; + for (child of el.children) { + hasActiveChild = walk(child, depth) || hasActiveChild; + } + + // Process the collapse state if this is an UL + if (el.tagName === "UL") { + if (depth === 1 || hasActiveChild || prevSiblingIsActiveLink(el)) { + el.classList.remove("collapse"); + } else { + el.classList.add("collapse"); + } + + // untick depth when we leave a UL + depth = depth - 1; + } + return hasActiveChild || isActiveNode; + }; + + // walk the TOC and expand / collapse any items that should be shown + + if (tocEl) { + walk(tocEl, 0); + updateActiveLink(); + } + + // Throttle the scroll event and walk peridiocally + window.document.addEventListener( + "scroll", + throttle(() => { + if (tocEl) { + updateActiveLink(); + walk(tocEl, 0); + } + if (!isReaderMode()) { + hideOverlappedSidebars(); + } + }, 5) + ); + window.addEventListener( + "resize", + throttle(() => { + if (!isReaderMode()) { + hideOverlappedSidebars(); + } + }, 10) + ); + hideOverlappedSidebars(); + highlightReaderToggle(isReaderMode()); +}); + +function throttle(func, wait) { + let waiting = false; + return function () { + if (!waiting) { + func.apply(this, arguments); + waiting = true; + setTimeout(function () { + waiting = false; + }, wait); + } + }; +} diff --git a/resources/stac_mount_save_files/libs/quarto-html/tippy.css b/resources/stac_mount_save_files/libs/quarto-html/tippy.css new file mode 100644 index 0000000..e6ae635 --- /dev/null +++ b/resources/stac_mount_save_files/libs/quarto-html/tippy.css @@ -0,0 +1 @@ +.tippy-box[data-animation=fade][data-state=hidden]{opacity:0}[data-tippy-root]{max-width:calc(100vw - 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b/resources/third_meeting_notes/index.html new file mode 100644 index 0000000..b966f0f --- /dev/null +++ b/resources/third_meeting_notes/index.html @@ -0,0 +1,1151 @@ + + + + + + + + + + + + + + + + + + + + + + + + + Primary Meeting Day 11-15: Finalization and Conclusion - Keiko Seafood Supply Chain Anaysis + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Primary Meeting Day 11-15: Finalization and Conclusion

+

Meeting Details

+
    +
  • Dates:
    • +
  • Times:
    • +
  • Location:
    • +
  • Facilitator:
    • +
+

Attendees

+
    +
  • List of attendees
    • +
+

Daily Agenda

+

Day 11: Alignment and Focus

+

Realigning Objectives

+
    +
  • Review the project's main goals to ensure alignment with the final output.
    • +
  • Address any misalignments or deviations from the original plan.
    • +
+

Prioritization of Tasks

+
    +
  • Identify critical tasks that need to be completed.
    • +
  • Allocate resources and efforts to ensure these priorities are met.
    • +
+

Day 12-14: Intensive Work Period

+

Task Completion

+
    +
  • Dedicated time for team members to complete their individual contributions.
    • +
  • Regular check-ins to track progress and address any blockers.
    • +
+

Integration of Work

+
    +
  • Begin to combine individual contributions into a cohesive whole.
    • +
  • Review the integration to ensure consistency and coherency across the project.
    • +
+

Final Reviews and Edits

+
    +
  • Conduct thorough reviews of the project's outputs.
    • +
  • Perform final edits to refine the quality of the work.
    • +
+

Day 15: Closure and Celebration

+

Final Presentation

+
    +
  • Present the completed project to the group.
    • +
  • Discuss any last-minute adjustments or refinements needed.
    • +
+

Reflective Session

+
    +
  • Reflect on the achievements and learnings from the project.
    • +
  • Share appreciation for the team's hard work and dedication.
    • +
+

Celebration

+
    +
  • Acknowledge the successful completion of the project.
    • +
  • Plan for any dissemination of the project's findings or outputs.
    • +
+

Detailed Notes

+

Day 11 Notes

+
    +
  • ...
    • +
+

Day 12 Notes

+
    +
  • ...
    • +
+

Day 13 Notes

+
    +
  • ...
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Day 14 Notes

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    +
  • ...
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Day 15 Notes

+
    +
  • ...
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+

Action Items

+
    +
  • [ ] Finalize manuscript for publication: Assigned to - Deadline
    • +
  • [ ] Prepare data for repository submission: Assigned to - Deadline
    • +
  • [ ] Organize project materials for archival: Assigned to - Deadline
    • +
  • ...
    • +
+

Reflections and Comments

+
    +
  • (Space for any additional thoughts, insights, or personal reflections on the meeting and the project as a whole.)
    • +
+

Next Steps

+
    +
  • Define the publication and dissemination plan.
    • +
  • Outline any follow-up research or projects that have stemmed from this work.
    • +
+

Additional Documentation

+
    +
  • (Include or link to any additional documents, charts, or resources that were created or referenced during the meeting.)
    • +
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+ + + + + + + + + + \ No newline at end of file diff --git a/resources/third_meeting_notes/third_meeting_notes.md b/resources/third_meeting_notes/third_meeting_notes.md new file mode 100644 index 0000000..19abeda --- /dev/null +++ b/resources/third_meeting_notes/third_meeting_notes.md @@ -0,0 +1,83 @@ +# Primary Meeting Day 11-15: Finalization and Conclusion + +## Meeting Details +- **Dates:** +- **Times:** +- **Location:** +- **Facilitator:** + +## Attendees +- List of attendees + +## Daily Agenda + +### Day 11: Alignment and Focus + +#### Realigning Objectives +- Review the project's main goals to ensure alignment with the final output. +- Address any misalignments or deviations from the original plan. + +#### Prioritization of Tasks +- Identify critical tasks that need to be completed. +- Allocate resources and efforts to ensure these priorities are met. + +### Day 12-14: Intensive Work Period + +#### Task Completion +- Dedicated time for team members to complete their individual contributions. +- Regular check-ins to track progress and address any blockers. + +#### Integration of Work +- Begin to combine individual contributions into a cohesive whole. +- Review the integration to ensure consistency and coherency across the project. + +#### Final Reviews and Edits +- Conduct thorough reviews of the project's outputs. +- Perform final edits to refine the quality of the work. + +### Day 15: Closure and Celebration + +#### Final Presentation +- Present the completed project to the group. +- Discuss any last-minute adjustments or refinements needed. + +#### Reflective Session +- Reflect on the achievements and learnings from the project. +- Share appreciation for the team's hard work and dedication. + +#### Celebration +- Acknowledge the successful completion of the project. +- Plan for any dissemination of the project's findings or outputs. + +## Detailed Notes + +### Day 11 Notes +- ... + +### Day 12 Notes +- ... + +### Day 13 Notes +- ... + +### Day 14 Notes +- ... + +### Day 15 Notes +- ... + +## Action Items +- [ ] Finalize manuscript for publication: Assigned to - Deadline +- [ ] Prepare data for repository submission: Assigned to - Deadline +- [ ] Organize project materials for archival: Assigned to - Deadline +- ... + +## Reflections and Comments +- (Space for any additional thoughts, insights, or personal reflections on the meeting and the project as a whole.) + +## Next Steps +- Define the publication and dissemination plan. +- Outline any follow-up research or projects that have stemmed from this work. + +## Additional Documentation +- (Include or link to any additional documents, charts, or resources that were created or referenced during the meeting.) diff --git a/resources/visualizations/index.html b/resources/visualizations/index.html new file mode 100644 index 0000000..eab2887 --- /dev/null +++ b/resources/visualizations/index.html @@ -0,0 +1,1276 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Visualizations - Keiko Seafood Supply Chain Anaysis + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
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+ + + + + + + + + + + + +

Visualization Strategy and Development Documentation

+

Overview

+
    +
  • Brief overview of the visualization goals and their alignment with the overall project objectives.
    • +
+

Visualization Strategy

+

Identifying Key Messages

+
    +
  • Discuss main messages or insights to communicate through visualizations.
    • +
  • Identify target audience and their specific needs.
    • +
+

Selecting Appropriate Visualization Types

+
    +
  • Explore different types of visualizations (charts, graphs, 3D, interactive elements) suitable for the data and message.
    • +
  • Brainstorm creative visualization approaches.
    • +
+

Visualization Development

+

Code-Generated Visualizations

+
    +
  • Outline initial visualizations generated from the data pipeline.
    • +
  • Include code snippets and explanations.
    • +
+
# Example Python code for a basic plot
+import matplotlib.pyplot as plt
+plt.plot(data['x'], data['y'])
+plt.show()
+
+

Enhancing Visualizations

+
    +
  • Steps for annotating, animating, creating 3D, immersive, or interactive visualizations.
    • +
  • Discuss challenges and solutions in enhancing visuals.
    • +
+

Versioning and Iterations

+
    +
  • Document different versions and iterations of visualizations.
    • +
  • Reflect on improvements or changes in each version.
    • +
+

Finalizing Visualizations

+
    +
  • Process of finalizing visuals for presentation or publication.
    • +
  • Feedback incorporation from team or test audiences.
    • +
+

Documentation of Tools and Resources

+
    +
  • List software, libraries, and tools used for visualization.
    • +
  • Reference external resources or tutorials.
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Conclusions

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  • Reflect on lessons learned and potential future improvements.
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References

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  • Cite external sources, inspirations, or frameworks used in visualization.
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+ + + + + + + + + + \ No newline at end of file diff --git a/resources/visualizations/visualizations.md b/resources/visualizations/visualizations.md new file mode 100644 index 0000000..2857a8b --- /dev/null +++ b/resources/visualizations/visualizations.md @@ -0,0 +1,50 @@ +# Visualization Strategy and Development Documentation + +## Overview +- Brief overview of the visualization goals and their alignment with the overall project objectives. + +## Visualization Strategy + +### Identifying Key Messages +- Discuss main messages or insights to communicate through visualizations. +- Identify target audience and their specific needs. + +### Selecting Appropriate Visualization Types +- Explore different types of visualizations (charts, graphs, 3D, interactive elements) suitable for the data and message. +- Brainstorm creative visualization approaches. + +## Visualization Development + +### Code-Generated Visualizations +- Outline initial visualizations generated from the data pipeline. +- Include code snippets and explanations. + +```python +# Example Python code for a basic plot +import matplotlib.pyplot as plt +plt.plot(data['x'], data['y']) +plt.show() +``` + +### Enhancing Visualizations +- Steps for annotating, animating, creating 3D, immersive, or interactive visualizations. +- Discuss challenges and solutions in enhancing visuals. + +### Versioning and Iterations +- Document different versions and iterations of visualizations. +- Reflect on improvements or changes in each version. + +### Finalizing Visualizations +- Process of finalizing visuals for presentation or publication. +- Feedback incorporation from team or test audiences. + +### Documentation of Tools and Resources +- List software, libraries, and tools used for visualization. +- Reference external resources or tutorials. + +### Conclusions +- Summarize the visualization process and contributions to the project. +- Reflect on lessons learned and potential future improvements. + +### References +- Cite external sources, inspirations, or frameworks used in visualization. diff --git a/resources/working_groups_and_postdocs/index.html b/resources/working_groups_and_postdocs/index.html new file mode 100644 index 0000000..f97ed13 --- /dev/null +++ b/resources/working_groups_and_postdocs/index.html @@ -0,0 +1,1166 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Working groups - Keiko Seafood Supply Chain Anaysis + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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ESIIL Postdoctoral Researcher Responsibilities and Opportunities

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Primary Responsibilities

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  • Independent Research:
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  • Conducting self-proposed research projects.
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  • Adhering to open data principles.
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  • Data and Code Storage:
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  • Storing all research code and data in the designated ESIIL repository.
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  • Use of CyVerse:
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  • Utilizing CyVerse as the primary computational platform.
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Opportunities for Collaboration

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  • Joining Working Groups:
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  • Opportunity to collaborate with working groups within ESIIL, subject to invitation.
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  • Networking and Collaboration:
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  • Engaging in regular meetings and seminars for networking.
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Additional Responsibilities

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  • Reviewing Working Group Applications:
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  • Assisting in the review process of working group applications.
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  • Supporting Working Groups:
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  • Providing support to working groups in various capacities, even if not an author.
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Note

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  • Primary research commitments should be prioritized unless otherwise directed by supervisors or ESIIL's administrative body.
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This framework ensures that ESIIL postdocs balance independent research with collaborative opportunities, adhering to open data principles, and utilizing designated platforms for their work.

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+ + + + + + + + + + \ No newline at end of file diff --git a/resources/working_groups_and_postdocs/working_groups_and_postdocs.md b/resources/working_groups_and_postdocs/working_groups_and_postdocs.md new file mode 100644 index 0000000..ffa9ca5 --- /dev/null +++ b/resources/working_groups_and_postdocs/working_groups_and_postdocs.md @@ -0,0 +1,30 @@ +# ESIIL Postdoctoral Researcher Responsibilities and Opportunities + +## Primary Responsibilities + +- **Independent Research:** + - Conducting self-proposed research projects. + - Adhering to open data principles. +- **Data and Code Storage:** + - Storing all research code and data in the designated ESIIL repository. +- **Use of CyVerse:** + - Utilizing CyVerse as the primary computational platform. + +## Opportunities for Collaboration + +- **Joining Working Groups:** + - Opportunity to collaborate with working groups within ESIIL, subject to invitation. +- **Networking and Collaboration:** + - Engaging in regular meetings and seminars for networking. + +## Additional Responsibilities + +- **Reviewing Working Group Applications:** + - Assisting in the review process of working group applications. +- **Supporting Working Groups:** + - Providing support to working groups in various capacities, even if not an author. + +## Note +- Primary research commitments should be prioritized unless otherwise directed by supervisors or ESIIL's administrative body. + +This framework ensures that ESIIL postdocs balance independent research with collaborative opportunities, adhering to open data principles, and utilizing designated platforms for their work. diff --git a/search/search_index.json b/search/search_index.json new file mode 100644 index 0000000..e229839 --- /dev/null +++ b/search/search_index.json @@ -0,0 +1 @@ +{"config":{"lang":["en"],"separator":"[\\s\\-]+","pipeline":["stopWordFilter"]},"docs":[{"location":"","title":"[Your Name]","text":"

Welcome to the [Your Name] repository, part of the Environmental Data Science Innovation and Inclusion Lab (ESIIL). This repository serves as the central hub for our research at ESIIL, hosting your project description, proposals, bio, codebase, and more.

"},{"location":"#your-project","title":"Your Project","text":"

[Provide a brief overview of your project here. Explain what you aim to achieve, the importance of your project, and its expected impact.]

"},{"location":"#project-proposal","title":"Project Proposal","text":"

[Link to the detailed project proposal document or include the proposal directly in the repository. This should outline the goals, methodologies, anticipated challenges, and projected timelines.]

"},{"location":"#collaborators","title":"Collaborators","text":"
  • ...
"},{"location":"#code-repository","title":"Code Repository","text":"

This section of the repository will include all the code developed for the project. You can structure it as follows:

  • Analysis Code: Scripts for data analysis, statistical modeling, etc.
  • Data Processing: Scripts for cleaning, merging, and managing datasets.
  • Visualization: Code for creating figures, charts, and interactive visualizations.
"},{"location":"#meeting-notes-and-agendas","title":"Meeting Notes and Agendas","text":"

Meeting notes and agendas will be regularly updated here to keep all group members informed and engaged with the progress and direction of the project.

"},{"location":"#contributing-to-this-repository","title":"Contributing to This Repository","text":"

We welcome contributions from all group members. To maintain the quality and integrity of the repository, please adhere to the following guidelines:

  • Make sure all commits have a clear and concise message.
  • Document any major changes or decisions in the meeting notes.
  • Review and merge changes through pull requests to ensure oversight.
"},{"location":"#getting-help","title":"Getting Help","text":"

If you encounter any issues or have questions about how to contribute, please refer to the ESIIL Support Page or contact the repository maintainers directly.

"},{"location":"#customize-your-repository","title":"Customize Your Repository","text":"

As a new working group, you'll want to make this repository your own. Here's how to get started:

  1. Edit This Readme: Replace the placeholder content with information about your specific project. Ensure that the introduction, project overview, and objectives clearly reflect your group's research focus.

  2. Update Group Member Bios: Add details about each group member's expertise, role in the project, and professional background. Include links to personal or professional web pages to foster community engagement and collaboration.

  3. Organize Your Code: Structure your codebase in a way that is logical and accessible. Use directories and clear naming conventions to make it easy for all members to find and contribute to different parts of the project.

  4. Document Your Data: Include a data directory with README files explaining the datasets, sources, and any preprocessing steps. This will help new members understand and work with the project's data effectively.

  5. Outline Your Methods: Create a detailed METHODS.md file where you describe the methodologies, software, and tools you will be using in your research. This transparency will support reproducibility and collaborative development.

  6. Set Up Project Management: Utilize the 'Issues' and 'Projects' features on GitHub to track tasks, discuss ideas, and manage your workflow. This can help in maintaining a clear view of progress and priorities.

  7. Add a License: Choose and include an appropriate open-source license for your project, ensuring that the broader community understands how they can use and contribute to your work.

  8. Create Contribution Guidelines: Establish a CONTRIBUTING.md file with instructions for members on how to propose changes, submit issues, and contribute code.

  9. Review and Merge Workflow: Decide on a workflow for reviewing and merging changes. Will you use branch protection? Who will have merge privileges? Document this process to avoid confusion.

  10. Establish Communication Channels: Beyond GitHub, set up additional communication channels like Slack, Discord, or email lists for quick and informal discussions.

Remember, the goal is to make your repository clear, accessible, and useful for all current and future members of your working group. Happy researching!

"},{"location":"resources/Pull_Sentinal2_l2_data/","title":"Pulling Sentinal 2 data","text":"

Ty Tuff, ESIIL Data Scientist 2023-10-27

"},{"location":"resources/Pull_Sentinal2_l2_data/#set-java-options","title":"Set Java Options","text":"
# Run these Java options before anything else.\noptions(java.parameters = \"-Xmx64G\")\noptions(timeout = max(600, getOption(\"timeout\")))\n
"},{"location":"resources/Pull_Sentinal2_l2_data/#r-libraries-and-global-setting","title":"R libraries and global setting.","text":"
#library(Rcpp)\nlibrary(sf)\nlibrary(gdalcubes)\nlibrary(rstac)\nlibrary(gdalUtils)\nlibrary(terra)\nlibrary(rgdal)\nlibrary(reshape2)\nlibrary(osmdata)\nlibrary(terra)\nlibrary(dplyr)\n#library(glue)\nlibrary(stars)\nlibrary(ggplot2)\nlibrary(colorspace)\nlibrary(geos)\n#library(glue)\nlibrary(osmdata)\nlibrary(ggthemes)\nlibrary(tidyr)\ngdalcubes_options(parallel = 8)\n\nsf::sf_extSoftVersion()\n
          GEOS           GDAL         proj.4 GDAL_with_GEOS     USE_PROJ_H \n      \"3.11.0\"        \"3.5.3\"        \"9.1.0\"         \"true\"         \"true\" \n          PROJ \n       \"9.1.0\"\n
gdalcubes_gdal_has_geos()\n
[1] TRUE\n
"},{"location":"resources/Pull_Sentinal2_l2_data/#start-timer","title":"Start timer","text":"
start <- Sys.time()\n
"},{"location":"resources/Pull_Sentinal2_l2_data/#set-color-palette","title":"Set color palette","text":"
library(ggtern)\nour_yellow <- rgb2hex(r = 253, g = 201, b = 51)\nour_green <- rgb2hex(r = 10, g = 84, b = 62)\nour_grey <- rgb2hex(r = 92, g = 96, b = 95)\nour_white <- rgb2hex(r = 255, g = 255, b = 255)\n
"},{"location":"resources/Pull_Sentinal2_l2_data/#load-area-of-interest","title":"Load area of interest","text":"
# Read the shapefile into an sf object\naoi_total <- st_read(\"/Users/ty/Documents/Github/Southern_California_Edison_Fire_Risk/SCE_Fire_Zone_V2/SCE_Fire_Zone_V2.shp\") %>% \n  st_as_sf()\n
Reading layer `SCE_Fire_Zone_V2' from data source \n  `/Users/ty/Documents/Github/Southern_California_Edison_Fire_Risk/SCE_Fire_Zone_V2/SCE_Fire_Zone_V2.shp' \n  using driver `ESRI Shapefile'\nSimple feature collection with 12 features and 5 fields\nGeometry type: POLYGON\nDimension:     XY\nBounding box:  xmin: 176062.4 ymin: 3674043 xmax: 764123.1 ymax: 4254012\nProjected CRS: NAD83 / UTM zone 11N\n
# Plot the entire spatial dataset\nplot(aoi_total)\n
# Filter the dataset to obtain the geometry with OBJECTID 5\naoi <- aoi_total %>%\n  filter(OBJECTID == 5)\n\n# Obtain and plot the bounding box of the filtered geometry\nshape_bbox <- st_bbox(aoi)\nplot(aoi)\n
# Transform the filtered geometry to EPSG:4326 and store its bounding box\naoi %>% st_transform(\"EPSG:4326\") %>%\n  st_bbox() -> bbox_4326\n\n# Transform the filtered geometry to EPSG:32618 and store its bounding box\naoi %>% st_transform(\"EPSG:32618\") %>%\n  st_bbox() -> bbox_32618\n
"},{"location":"resources/Pull_Sentinal2_l2_data/#arrange-stac-collection","title":"Arrange STAC collection","text":"

In this code chunk, the primary goal is to search for and obtain satellite imagery data. The data source being tapped into is a SpatioTemporal Asset Catalog (STAC) provided by an online service (earth-search by Element84). Here\u2019s a breakdown:

A connection is established with the STAC service, searching specifically within the \u201csentinel-s2-l2a-cogs\u201d collection. -The search is spatially constrained to a bounding box (bbox_4326) and temporally limited to a range of one day, between May 15 and May 16, 2021. -Once the search is conducted, the desired assets or spectral bands from the returned satellite images are defined, ranging from Band 1 (B01) to Band 12 (B12) and including the Scene Classification Layer (SCL). -These bands are then organized into an image collection for further processing or analysis.

# Initialize STAC connection\ns = stac(\"https://earth-search.aws.element84.com/v0\")\n\n# Search for Sentinel-2 images within specified bounding box and date range\nitems = s %>%\n    stac_search(collections = \"sentinel-s2-l2a-cogs\",\n                bbox = c(bbox_4326[\"xmin\"], \n                         bbox_4326[\"ymin\"],\n                         bbox_4326[\"xmax\"], \n                         bbox_4326[\"ymax\"]), \n                datetime = \"2021-05-15/2021-05-16\") %>%\n    post_request() %>%\n    items_fetch(progress = FALSE)\n\n# Print number of found items\nlength(items$features)\n
[1] 12\n
# Prepare the assets for analysis\nlibrary(gdalcubes)\nassets = c(\"B01\", \"B02\", \"B03\", \"B04\", \"B05\", \"B06\", \n           \"B07\", \n           \"B08\", \"B8A\", \"B09\", \"B11\", \"B12\", \"SCL\")\ns2_collection = stac_image_collection(items$features, asset_names = assets)\n\n# Display the image collection\ns2_collection\n
Image collection object, referencing 12 images with 13 bands\nImages:\n                      name      left      top   bottom     right\n1 S2B_11SNS_20210515_1_L2A -117.0002 33.43957 32.44372 -115.8191\n2 S2B_11SPS_20210515_1_L2A -115.9361 33.43490 32.42937 -114.7436\n3 S2B_11SQS_20210515_0_L2A -114.8732 33.42092 32.41918 -113.9566\n4 S2B_12STB_20210515_0_L2A -114.2244 33.40433 32.61015 -113.9559\n5 S2B_11SNT_20210515_0_L2A -117.0002 34.34164 33.34577 -115.8066\n6 S2B_11SPT_20210515_0_L2A -115.9253 34.33683 33.33091 -114.7198\n             datetime        srs\n1 2021-05-15T18:35:13 EPSG:32611\n2 2021-05-15T18:35:10 EPSG:32611\n3 2021-05-15T18:35:06 EPSG:32611\n4 2021-05-15T18:35:01 EPSG:32612\n5 2021-05-15T18:34:59 EPSG:32611\n6 2021-05-15T18:34:55 EPSG:32611\n[ omitted 6 images ]\n\nBands:\n   name offset scale unit nodata image_count\n1   B01      0     1                      12\n2   B02      0     1                      12\n3   B03      0     1                      12\n4   B04      0     1                      12\n5   B05      0     1                      12\n6   B06      0     1                      12\n7   B07      0     1                      12\n8   B08      0     1                      12\n9   B09      0     1                      12\n10  B11      0     1                      12\n11  B12      0     1                      12\n12  B8A      0     1                      12\n13  SCL      0     1                      12\n
"},{"location":"resources/Pull_Sentinal2_l2_data/#define-view-window","title":"Define view window","text":"

In this code chunk, a \u2018view\u2019 on the previously obtained satellite image collection is being defined. Think of this as setting up a specific lens or perspective to look at the satellite data:

-The view is set to the coordinate reference system EPSG:32618. -Spatial resolution is defined as 100x100 meters. -Temporal resolution is defined monthly (P1M), even though the actual range is only one day. -When there are multiple values in a grid cell or timeframe, they are aggregated using the median value. -If any resampling is needed, the nearest neighbor method is used (near). -The spatial and temporal extents are constrained to specific values. -By defining this view, it allows for consistent analysis and visualization of the image collection within the specified spatial and temporal resolutions and extents.

# Define a specific view on the satellite image collection\nv = cube_view(\n    srs = \"EPSG:32618\", \n    dx = 100, \n    dy = 100, \n    dt = \"P1M\", \n    aggregation = \"median\", \n    resampling = \"near\",\n    extent = list(\n        t0 = \"2021-05-15\", \n        t1 = \"2021-05-16\",\n        left = bbox_32618[\"xmin\"], \n        right = bbox_32618[\"xmax\"],\n        top = bbox_32618[\"ymax\"], \n        bottom = bbox_32618[\"ymin\"]\n    )\n)\n\n# Display the defined view\nv\n
A data cube view object\n\nDimensions:\n                low              high count pixel_size\nt        2021-05-01        2021-05-31     1        P1M\ny  4471226.41402451  4741326.41402451  2701        100\nx -3463720.00044994 -3191420.00044994  2723        100\n\nSRS: \"EPSG:32618\"\nTemporal aggregation method: \"median\"\nSpatial resampling method: \"near\"\n
"},{"location":"resources/Pull_Sentinal2_l2_data/#pull-data","title":"Pull data","text":"

In this chunk, the primary aim is to transform and prepare satellite imagery data for analysis:

-The current time is stored in variable a for tracking the time taken by the process. -The previously defined \u2018view\u2019 on the satellite imagery, v, is used to create a raster cube, a multi-dimensional array containing the satellite data. This raster cube contains spatial, spectral, and temporal data. -The desired spectral bands are selected. -The data is limited to a specific area of interest, aoi. -The band names are renamed to their respective wavelengths in nanometers for clarity. -A subset of the data, comprising 50,000 random samples, is selected. -Unwanted columns are removed, and the dataset is transformed into a long format, where each row represents a particular date and wavelength combination. -The entire process duration is computed by taking the difference between the end time (b) and the start time (a). -The transformed dataset y is then displayed.

# Record start time\na <- Sys.time()\n\n# Transform the satellite image collection into a raster cube\nx <- s2_collection %>%\n    raster_cube(v) %>%\n    select_bands(c(\"B01\", \"B02\", \"B03\", \"B04\", \n                   \"B05\", \"B06\", \"B07\", \"B08\", \n                   \"B8A\", \"B09\", \"B11\", \"B12\")) %>%\n    extract_geom(aoi) %>%\n    rename(\n        \"time\" = \"time\",\n        \"443\" = \"B01\",\n        \"490\" = \"B02\",\n        \"560\" = \"B03\",\n        \"665\" = \"B04\",\n        \"705\" = \"B05\",\n        \"740\" = \"B06\",\n        \"783\" = \"B07\",\n        \"842\" = \"B08\",\n        \"865\" = \"B8A\",\n        \"940\" = \"B09\",\n        \"1610\" = \"B11\",\n        \"2190\" = \"B12\"\n    )\n\n# Sample, transform and prepare data for analysis\ny <- x %>%\n    slice_sample(n = 50000) %>%\n    select(-FID) %>%\n    pivot_longer(!time, names_to = \"wavelength_nm\", values_to = \"reflectance\") %>%\n    mutate(wavelength_nm = as.numeric(wavelength_nm))\n\n# Record end time and compute duration\nb <- Sys.time()\nprocessing_time <- difftime(b, a)\n\n# Display the processing time and transformed dataset\nprocessing_time\n
Time difference of 1.23593 mins\n
y\n
# A tibble: 600,000 \u00d7 3\n   time       wavelength_nm reflectance\n   <chr>              <dbl>       <dbl>\n 1 2021-05-01           443        1855\n 2 2021-05-01           490        2255\n 3 2021-05-01           560        2884\n 4 2021-05-01           665        3711\n 5 2021-05-01           705        3990\n 6 2021-05-01           740        4009\n 7 2021-05-01           783        4078\n 8 2021-05-01           842        4219\n 9 2021-05-01           865        4060\n10 2021-05-01           940        4120\n# \u2139 599,990 more rows\n
"},{"location":"resources/Pull_Sentinal2_l2_data/#base-plot","title":"Base plot","text":"
# Set custom colors for the plot\nour_green <- \"#4CAF50\"\nour_white <- \"#FFFFFF\"\nour_yellow <- \"#FFEB3B\"\n\n# Create a 2D density plot\nday_density <- ggplot(data = y, aes(x = wavelength_nm, y = reflectance, group = time)) + \n  stat_smooth(color = our_green, fill = \"lightgrey\") +\n  geom_density2d(colour = \"black\", bins = 10, alpha = 0.1) +\n  stat_density2d(aes(alpha = ..level.., fill = ..level..), \n                 linewidth = 2, bins = 10, geom = \"polygon\") + \n  scale_fill_gradient(low = our_white, high = our_yellow) +\n  scale_alpha(range = c(0.00, 0.8), guide = FALSE) +\n  theme_tufte() +\n  xlab(\"wavelength\") +\n  ylab(\"reflectance\") +\n  ylim(0, 16000) +\n  theme(\n    aspect.ratio = 5/14, \n    axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1, \n                               colour = c(\"darkblue\", \"blue\", \"green\", \"red\", \n                                          \"darkred\", \"darkred\", \"darkred\", \"darkred\", \n                                          \"darkred\", \"black\", \"black\", \"black\", \"black\")),\n    axis.title.x = element_blank(),\n    axis.title.y = element_blank(),\n    plot.margin = margin(t = 30, r = 10, b = 40, l = 18)\n  ) +\n  scale_x_continuous(breaks = c(443, 490, 560, 665, 705, 740, 783, 842, 865, 940, 1610, 2190))\n\n# Display the plot\nday_density\n
"},{"location":"resources/Pull_Sentinal2_l2_data/#inlay-1-geographic-zone","title":"Inlay 1 - geographic zone","text":"
guide_map <- ggplot(data= aoi_total) +\n  geom_sf(fill=our_yellow, color=our_white) +\n  geom_sf(data= aoi, fill=our_green, color=our_white) +\n  theme_tufte()+\n  ggtitle(\"Zone 5\")+\n  theme(axis.text.x=element_blank(), #remove x axis labels\n        axis.ticks.x=element_blank(), #remove x axis ticks\n        axis.text.y=element_blank(),  #remove y axis labels\n        axis.ticks.y=element_blank()  #remove y axis ticks, bg=none\n        )+ theme(plot.title = element_text(hjust=0.8, vjust = -2))\nguide_map\n
"},{"location":"resources/Pull_Sentinal2_l2_data/#inlay-2-date-text","title":"Inlay 2 - date text","text":"
library(geosphere)\naoi_total |> st_centroid()  |> st_transform(crs=\"+proj=longlat\") |> st_coordinates() |> colMeans() -> lat_long\n\ndaylength_line <- daylength(lat = lat_long[2], 1:365)\n\ndaylengths <- data.frame(time= 1:365, daylength = daylength_line)\n\nlibrary(lubridate)\n\n# Create a template date object\ndate <- as.POSIXlt(\"2021-05-15\")\n\ndoy <- format(date, format = \"%j\") |> as.numeric()\n\ndisplay_date <- format(date, format=\"%e %B %Y   \")\n
"},{"location":"resources/Pull_Sentinal2_l2_data/#inlay-3-daylength","title":"Inlay 3 - daylength","text":"
date_inlay <- ggplot(data=daylengths) + \n\n  ggtitle(\"Daylength\")+\n  geom_ribbon(aes(x=time, ymin=daylength, ymax=15), fill=our_grey, alpha=0.5) +\n  geom_ribbon(aes(x=time, ymax=daylength, ymin=9), fill=our_yellow, alpha=1) +\n  geom_hline(yintercept=12, color=our_white) +\n geom_vline(xintercept=doy, color=our_green, size=1) +\n  theme_tufte() +\n  ylim(9,15) +\n  theme(axis.text.y=element_blank(),\n        axis.ticks.y=element_blank(),\n        axis.title.y=element_blank(),\n        axis.title.x=element_blank(),\n        axis.text.x=element_blank(),\n        axis.ticks.x=element_blank()) + theme(plot.title = element_text(hjust=0.5, vjust = 0))\ndate_inlay\n
"},{"location":"resources/Pull_Sentinal2_l2_data/#ensemble-map-assembly","title":"Ensemble map assembly","text":"
library(cowplot)\nlibrary(magick)\nmap_overlay <- ggdraw(day_density) + \n  draw_plot(guide_map, x = 1.08, y = 1, hjust = 1, vjust = 1, width = 0.3, height = 0.3)+\n  draw_plot(date_inlay, x = 1, y = 0.35, hjust = 1, vjust = 1, width = 0.1, height = 0.25)+\n  geom_text(aes(x=1, y=0.08, label=display_date, hjust = 1), color=our_grey, cex=3, fontface='bold') +\n # draw_image(\"Ty_powerline_plots/Southern_California_Edison_Logo.png\", x = -0.24, y = 0.38, scale=.3)+\n # draw_image(\"Ty_powerline_plots/earthlab_logo.png\", x = -0.38, y = 0.38, scale=.25)+\n  geom_text(aes(x=0.4, y=.9, label=\"Spectral library - Monthly average\"), color=our_green, hjust = 0, cex=8, fontface='bold') +\n  geom_text(aes(x=0.01, y=.04, \n    label=\"Created by ESIIL (T. Tuff) for Fall Hackathon -- October 2023. Sentinel 2 Data from 'https://earth-search.aws.element84.com/v0'\"), color=our_grey, hjust  = 0, cex=3) +\ngeom_text(aes(x=0.4, y=.1, label=\"wavelength (nm)\"), color=our_grey, hjust = 0, cex=4, fontface='bold') +\ngeom_text(aes(x=0.01, y=.5,angle = 90, label=\"reflectance\"), color=our_grey, hjust = 0, cex=4, fontface='bold')\nmap_overlay\n
"},{"location":"resources/Pull_Sentinal2_l2_data/#save-map","title":"Save map","text":"
ggsave(map_overlay, file=\"day_density_15_May_2021_zone_5.png\", bg=\"white\", dpi = 600, width = 12,\n  height = 5)\n
"},{"location":"resources/Pull_Sentinal2_l2_data/#end-timer","title":"End timer","text":"
end <- Sys.time()\ndifftime(end,start)\n
Time difference of 3.2202 mins\n
"},{"location":"resources/bilingualism_md/","title":"R and Python bilingualism","text":"

Welcome to the R and Python bilingualism reference guide! If you\u2019re fluent in one of these languages but hesitant to learn the other, you\u2019re in the right place. The good news is that there are many similarities between R and Python that make it easy to switch between the two.

Both R and Python are widely used in data science and are open-source, meaning that they are free to use and constantly being improved by the community. They both have extensive libraries for data analysis, visualization, and machine learning. In fact, many of the libraries in both languages have similar names and functions, such as Pandas in Python and data.table in R.

While there are differences between the two languages, they can complement each other well. Python is versatile and scalable, making it ideal for large and complex projects such as web development and artificial intelligence. R, on the other hand, is known for its exceptional statistical capabilities and is often used in data analysis and modeling. Visualization is also easier in R, making it a popular choice for creating graphs and charts.

By learning both R and Python, you\u2019ll be able to take advantage of the strengths of each language and create more efficient and robust data analysis workflows. Don\u2019t let the differences between the two languages intimidate you - once you become familiar with one, learning the other will be much easier.

So, whether you\u2019re a Python enthusiast looking to expand your statistical analysis capabilities, or an R user interested in exploring the world of web development and artificial intelligence, this guide will help you become bilingual in R and Python.

"},{"location":"resources/bilingualism_md/#install-packages","title":"Install packages","text":"

In R, packages can be installed from CRAN repository by using the install.packages() function:

R code:

# Install the dplyr package from CRAN\ninstall.packages(\"dplyr\")\n

In Python, packages can be installed from the Anaconda repository by using the conda install command:

Python code:

# Install the pandas package from Anaconda\n!conda install pandas\n

Loading libraries in R and Python

In R, libraries can be loaded in the same way as before, using the library() function:

R code:

# Load the dplyr library\nlibrary(dplyr)\n

In Python, libraries can be loaded in the same way as before, using the import statement. Here\u2019s an example:

Python code:

# Load the pandas library\nimport pandas as pd\n

Note that the package or library must be installed from the respective repository before it can be loaded. Also, make sure you have the correct repository specified in your system before installing packages. By default, R uses CRAN as its primary repository, whereas Anaconda uses its own repository by default.

"},{"location":"resources/bilingualism_md/#reticulate","title":"reticulate","text":"

The reticulate package lets you run both R and Python together in the R environment.

R libraries are stored and managed in a repository called CRAN. You can download R packages with the install.packages() function

install.packages(\"reticulate\")\n

You only need to install packages once, but you need to mount those packages with the library() function each time you open R.

library(reticulate)\n

Python libraries are stored and managed in a few different libraries and their dependencies are not regulated as strictly as R libraries are in CRAN. It\u2019s easier to publish a python package but it can also be more cumbersome for users because you need to manage dependencies yourself. You can download python packages using both R and Python code

py_install(\"laspy\")\n
## + '/Users/ty/opt/miniconda3/bin/conda' 'install' '--yes' '--prefix' '/Users/ty/opt/miniconda3/envs/earth-analytics-python' '-c' 'conda-forge' 'laspy'\n

Now, let\u2019s create a Python list and assign it to a variable py_list:

R code:

py_list <- r_to_py(list(1, 2, 3))\n

We can now print out the py_list variable in Python using the py_run_string() function:

R code:

py_run_string(\"print(r.py_list)\")\n

This will output [1, 2, 3] in the Python console.

Now, let\u2019s create an R vector and assign it to a variable r_vec:

R code:

r_vec <- c(4, 5, 6)\n

We can now print out the r_vec variable in R using the py$ syntax to access Python variables:

R code:

print(py$py_list)\n

This will output [1, 2, 3] in the R console.

We can also call Python functions from R using the py_call() function. For example, let\u2019s call the Python sum() function on the py_list variable and assign the result to an R variable r_sum:

R code:

r_sum <- py_call(\"sum\", args = list(py_list))\n

We can now print out the r_sum variable in R:

R code:

print(r_sum)\n

This will output 6 in the R console.

"},{"location":"resources/bilingualism_md/#load-packages-and-change-settings","title":"Load packages and change settings","text":"
options(java.parameters = \"-Xmx5G\")\n\nlibrary(r5r)\nlibrary(sf)\nlibrary(data.table)\nlibrary(ggplot2)\nlibrary(interp)\nlibrary(dplyr)\nlibrary(osmdata)\nlibrary(ggthemes)\nlibrary(sf)\nlibrary(data.table)\nlibrary(ggplot2)\nlibrary(akima)\nlibrary(dplyr)\nlibrary(raster)\nlibrary(osmdata)\nlibrary(mapview)\nlibrary(cowplot)\nlibrary(here)\nlibrary(testthat)\n
import sys\nsys.argv.append([\"--max-memory\", \"5G\"])\n\nimport pandas as pd\nimport geopandas\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport plotnine\nimport contextily as cx\nimport r5py\nimport seaborn as sns\n

R and Python are two popular programming languages used for data analysis, statistics, and machine learning. Although they share some similarities, there are some fundamental differences between them. Here\u2019s an example code snippet in R and Python to illustrate some of the differences:

R Code:

# Create a vector of numbers from 1 to 10\nx <- 1:10\n\n# Compute the mean of the vector\nmean_x <- mean(x)\n\n# Print the result\nprint(mean_x)\n
## [1] 5.5\n

Python Code:

# Import the numpy library for numerical operations\nimport numpy as np\n\n# Create a numpy array of numbers from 1 to 10\nx = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])\n\n# Compute the mean of the array\nmean_x = np.mean(x)\n\n# Print the result\nprint(mean_x)\n
## 5.5\n

In this example, we can see that there are several differences between R and Python:

Syntax: R uses the assignment operator \\<- while Python uses the equals sign = for variable assignment.

Libraries: Python relies heavily on external libraries such as numpy, pandas, and matplotlib for data analysis, while R has built-in functions for many data analysis tasks.

Data types: R is designed to work with vectors and matrices, while Python uses lists and arrays. In the example above, we used the numpy library to create a numerical array in Python.

Function names: Function names in R and Python can differ significantly. In the example above, we used the mean() function in R and the np.mean() function in Python to calculate the mean of the vector/array.

These are just a few of the many differences between R and Python. Ultimately, the choice between the two languages will depend on your specific needs and preferences.

"},{"location":"resources/bilingualism_md/#load-saved-data","title":"Load saved data","text":"

R Code:

data(\"iris\")\nhere()\nload(file=here(\"2_R_and_Py_bilingualism\", \"data\", \"iris_example_data.rdata\"))\nobjects()\n

Python code:

"},{"location":"resources/bilingualism_md/#save-data","title":"Save data","text":"

R Code:

save(iris, file=here(\"2_R_and_Py_bilingualism\", \"data\", \"iris_example_data.rdata\"))\n\nwrite.csv(iris, file=here(\"2_R_and_Py_bilingualism\", \"data\", \"iris_example_data.csv\"))\n

Python code:

"},{"location":"resources/bilingualism_md/#functions","title":"functions","text":"

Both R and Python are powerful languages for writing functions that can take input, perform a specific task, and return output. R Code:

# Define a function that takes two arguments and returns their sum\nsum_r <- function(a, b) {\n  return(a + b)\n}\n\n# Call the function with two arguments and print the result\nresult_r <- sum_r(3, 5)\nprint(result_r)\n
## [1] 8\n

Python code:

# Define a function that takes two arguments and returns their sum\ndef sum_py(a, b):\n    return a + b\n\n# Call the function with two arguments and print the result\nresult_py = sum_py(3, 5)\nprint(result_py)\n
## 8\n

In both cases, we define a function that takes two arguments and returns their sum. In R, we use the function keyword to define a function, while in Python, we use the def keyword. The function body in R is enclosed in curly braces, while in Python it is indented.

There are a few differences in the syntax and functionality between the two approaches:

Function arguments: In R, function arguments are separated by commas, while in Python they are enclosed in parentheses. The syntax for specifying default arguments and variable-length argument lists can also differ between the two languages. Return statement: In R, we use the return keyword to specify the return value of a function, while in Python, we simply use the return statement. Function names: Function names in R and Python can differ significantly. In the example above, we used the sum_r() function in R and the sum_py() function in Python to calculate the sum of two numbers.

"},{"location":"resources/bilingualism_md/#data-plots","title":"Data Plots","text":"

R Code:

# Load the \"ggplot2\" package for plotting\nlibrary(ggplot2)\n\n# Generate some sample data\nx <- seq(1, 10, 1)\ny <- x + rnorm(10)\n\n# Create a scatter plot\nggplot(data.frame(x, y), aes(x = x, y = y)) +\n  geom_point()\n

Python code:

# Load the \"matplotlib\" library\nimport matplotlib.pyplot as plt\n\n# Generate some sample data\nimport numpy as np\nx = np.arange(1, 11)\ny = x + np.random.normal(0, 1, 10)\n\n#clear last plot\nplt.clf()\n\n# Create a scatter plot\nplt.scatter(x, y)\nplt.show()\n

In both cases, we generate some sample data and create a scatter plot to visualize the relationship between the variables.

There are a few differences in the syntax and functionality between the two approaches:

Library and package names: In R, we use the ggplot2 package for plotting, while in Python, we use the matplotlib library. Data format: In R, we use a data frame to store the input data, while in Python, we use numpy arrays. Plotting functions: In R, we use the ggplot() function to create a new plot object, and then use the geom_point() function to create a scatter plot layer. In Python, we use the scatter() function from the matplotlib.pyplot module to create a scatter plot directly.

"},{"location":"resources/bilingualism_md/#linear-regression","title":"Linear regression","text":"

R Code:

# Load the \"ggplot2\" package for plotting\nlibrary(ggplot2)\n\n# Generate some sample data\nx <- seq(1, 10, 1)\ny <- x + rnorm(10)\n\n# Perform linear regression\nmodel_r <- lm(y ~ x)\n\n# Print the model summary\nsummary(model_r)\n
## \n## Call:\n## lm(formula = y ~ x)\n## \n## Residuals:\n##      Min       1Q   Median       3Q      Max \n## -1.69344 -0.42336  0.08961  0.34778  1.56728 \n## \n## Coefficients:\n##             Estimate Std. Error t value Pr(>|t|)    \n## (Intercept)  -0.1676     0.6781  -0.247    0.811    \n## x             0.9750     0.1093   8.921 1.98e-05 ***\n## ---\n## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n## \n## Residual standard error: 0.9926 on 8 degrees of freedom\n## Multiple R-squared:  0.9087, Adjusted R-squared:  0.8972 \n## F-statistic: 79.59 on 1 and 8 DF,  p-value: 1.976e-05\n
# Plot the data and regression line\nggplot(data.frame(x, y), aes(x = x, y = y)) +\n  geom_point() +\n  geom_smooth(method = \"lm\", se = FALSE)\n
## `geom_smooth()` using formula = 'y ~ x'\n

Python code:

# Load the \"matplotlib\" and \"scikit-learn\" libraries\nimport matplotlib.pyplot as plt\nfrom sklearn.linear_model import LinearRegression\n\n# Generate some sample data\nimport numpy as np\nx = np.arange(1, 11)\ny = x + np.random.normal(0, 1, 10)\n\n# Perform linear regression\nmodel_py = LinearRegression().fit(x.reshape(-1, 1), y)\n\n# Print the model coefficients\nprint(\"Coefficients: \", model_py.coef_)\n
## Coefficients:  [1.15539692]\n
print(\"Intercept: \", model_py.intercept_)\n\n#clear last plot\n
## Intercept:  -1.1291396173221218\n
plt.clf()\n\n# Plot the data and regression line\nplt.scatter(x, y)\nplt.plot(x, model_py.predict(x.reshape(-1, 1)), color='red')\nplt.show()\n

In both cases, we generate some sample data with a linear relationship between x and y, and then perform a simple linear regression to estimate the slope and intercept of the line. We then plot the data and regression line to visualize the fit.

There are a few differences in the syntax and functionality between the two approaches:

Library and package names: In R, we use the lm() function from the base package to perform linear regression, while in Python, we use the LinearRegression() class from the scikit-learn library. Additionally, we use the ggplot2 package in R for plotting, while we use the matplotlib library in Python. Data format: In R, we can specify the dependent and independent variables in the formula used for regression. In Python, we need to reshape the input data to a two-dimensional array before fitting the model. Model summary: In R, we can use the summary() function to print a summary of the model, including the estimated coefficients, standard errors, and p-values. In Python, we need to print the coefficients and intercept separately.

"},{"location":"resources/bilingualism_md/#random-forest","title":"Random Forest","text":"

R Code:

# Load the \"randomForest\" package\nlibrary(randomForest)\n\n# Load the \"iris\" dataset\ndata(iris)\n\n# Split the data into training and testing sets\nset.seed(123)\ntrain_idx <- sample(1:nrow(iris), nrow(iris) * 0.7, replace = FALSE)\ntrain_data <- iris[train_idx, ]\ntest_data <- iris[-train_idx, ]\n\n# Build a random forest model\nrf_model <- randomForest(Species ~ ., data = train_data, ntree = 500)\n\n# Make predictions on the testing set\npredictions <- predict(rf_model, test_data)\n\n# Calculate accuracy of the model\naccuracy <- sum(predictions == test_data$Species) / nrow(test_data)\nprint(paste(\"Accuracy:\", accuracy))\n
## [1] \"Accuracy: 0.977777777777778\"\n

Python code:

# Load the \"pandas\", \"numpy\", and \"sklearn\" libraries\nimport pandas as pd\nimport numpy as np\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.datasets import load_iris\nfrom sklearn.model_selection import train_test_split\n\n# Load the \"iris\" dataset\niris = load_iris()\n\n# Split the data into training and testing sets\nX_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=0.3, random_state=123)\n\n# Build a random forest model\nrf_model = RandomForestClassifier(n_estimators=500, random_state=123)\nrf_model.fit(X_train, y_train)\n\n# Make predictions on the testing set\n
## RandomForestClassifier(n_estimators=500, random_state=123)\n
predictions = rf_model.predict(X_test)\n\n# Calculate accuracy of the model\naccuracy = sum(predictions == y_test) / len(y_test)\nprint(\"Accuracy:\", accuracy)\n
## Accuracy: 0.9555555555555556\n

In both cases, we load the iris dataset and split it into training and testing sets. We then build a random forest model using the training data and evaluate its accuracy on the testing data.

There are a few differences in the syntax and functionality between the two approaches:

Library and package names: In R, we use the randomForest package to build random forest models, while in Python, we use the RandomForestClassifier class from the sklearn.ensemble module. We also use different libraries for loading and manipulating data (pandas and numpy in Python, and built-in datasets in R). Model parameters: The syntax for setting model parameters is slightly different in R and Python. For example, in R, we specify the number of trees using the ntree parameter, while in Python, we use the n_estimators parameter. Data format: In R, we use a data frame to store the input data, while in Python, we use numpy arrays.

"},{"location":"resources/bilingualism_md/#basic-streetmap-from-open-street-map","title":"Basic streetmap from Open Street Map","text":"

R Code:

# Load the \"osmdata\" package for mapping\nlibrary(osmdata)\nlibrary(tmap)\n\n# Define the map location and zoom level\nbbox <- c(left = -0.16, bottom = 51.49, right = -0.13, top = 51.51)\n\n# Get the OpenStreetMap data\nosm_data <- opq(bbox) %>% \n  add_osm_feature(key = \"highway\") %>% \n  osmdata_sf()\n\n# Plot the map using tmap\ntm_shape(osm_data$osm_lines) + \n  tm_lines()\n

Python code:

# Load the \"osmnx\" package for mapping\nimport osmnx as ox\n\n# Define the map location and zoom level\nbbox = (51.49, -0.16, 51.51, -0.13)\n\n# Get the OpenStreetMap data\nosm_data = ox.graph_from_bbox(north=bbox[2], south=bbox[0], east=bbox[3], west=bbox[1], network_type='all')\n\n# Plot the map using osmnx\nox.plot_graph(osm_data)\n
## (<Figure size 1600x1600 with 0 Axes>, <AxesSubplot:>)\n

In both cases, we define the map location and zoom level, retrieve the OpenStreetMap data using the specified bounding box, and plot the map.

The main differences between the two approaches are:

Package names and syntax: In R, we use the osmdata package and its syntax to download and process the OpenStreetMap data, while in Python, we use the osmnx package and its syntax. Mapping libraries: In R, we use the tmap package to create a static map of the OpenStreetMap data, while in Python, we use the built-in ox.plot_graph function from the osmnx package to plot the map.

"},{"location":"resources/bilingualism_md/#cnn-on-raster-data","title":"CNN on Raster data","text":"

R Code:

# Load the \"keras\" package for building the CNN\nlibrary(tensorflow)\nlibrary(keras)\n\n# Load the \"raster\" package for working with raster data\nlibrary(raster)\n\n# Load the \"magrittr\" package for pipe operator\nlibrary(magrittr)\n\n# Load the data as a raster brick\nraster_data <- brick(\"raster_data.tif\")\n\n# Split the data into training and testing sets\nsplit_data <- sample(1:nlayers(raster_data), size = nlayers(raster_data)*0.8, replace = FALSE)\ntrain_data <- raster_data[[split_data]]\ntest_data <- raster_data[[setdiff(1:nlayers(raster_data), split_data)]]\n\n# Define the CNN model\nmodel <- keras_model_sequential() %>% \n  layer_conv_2d(filters = 32, kernel_size = c(3, 3), activation = \"relu\", input_shape = c(ncol(train_data), nrow(train_data), ncell(train_data))) %>% \n  layer_max_pooling_2d(pool_size = c(2, 2)) %>% \n  layer_dropout(rate = 0.25) %>% \n  layer_flatten() %>% \n  layer_dense(units = 128, activation = \"relu\") %>% \n  layer_dropout(rate = 0.5) %>% \n  layer_dense(units = nlayers(train_data), activation = \"softmax\")\n\n# Compile the model\nmodel %>% compile(loss = \"categorical_crossentropy\", optimizer = \"adam\", metrics = \"accuracy\")\n\n# Train the model\nhistory <- model %>% fit(x = array(train_data), y = to_categorical(1:nlayers(train_data)), epochs = 10, validation_split = 0.2)\n\n# Evaluate the model\nmodel %>% evaluate(x = array(test_data), y = to_categorical(1:nlayers(test_data)))\n\n# Plot the model accuracy over time\nplot(history)\n
"},{"location":"resources/bilingualism_md/#piping","title":"Piping","text":"

Piping is a powerful feature in both R and Python that allows for a more streamlined and readable code. However, the syntax for piping is slightly different between the two languages.

In R, piping is done using the %>% operator from the magrittr package, while in Python, it is done using the | operator from the pandas package.

Let\u2019s compare and contrast piping in R and Python with some examples:

Piping in R In R, we can use the %>% operator to pipe output from one function to another, which can make our code more readable and easier to follow. Here\u2019s an example:

R code:

library(dplyr)\n\n# create a data frame\ndf <- data.frame(x = c(1,2,3), y = c(4,5,6))\n\n# calculate the sum of column x and y\ndf %>%\n  mutate(z = x + y) %>%\n  summarize(sum_z = sum(z))\n
##   sum_z\n## 1    21\n

In this example, we first create a data frame df with two columns x and y. We then pipe the output of df to mutate, which adds a new column z to the data frame that is the sum of x and y. Finally, we pipe the output to summarize, which calculates the sum of z and returns the result.

Piping in Python In Python, we can use the | operator to pipe output from one function to another. However, instead of piping output from one function to another, we pipe a DataFrame to a method of the DataFrame. Here\u2019s an example:

Python code:

import pandas as pd\n\n# create a DataFrame\ndf = pd.DataFrame({'x': [1,2,3], 'y': [4,5,6]})\n\n# calculate the sum of column x and y\n(df.assign(z = df['x'] + df['y'])\n   .agg(sum_z = ('z', 'sum')))\n
##         z\n## sum_z  21\n

In this example, we first create a DataFrame df with two columns x and y. We then use the assign() method to add a new column z to the DataFrame that is the sum of x and y. Finally, we use the agg() method to calculate the sum of z and return the result.

As we can see, the syntax for piping is slightly different between R and Python, but the concept remains the same. Piping can make our code more readable and easier to follow, which is an important aspect of creating efficient and effective code.

R code:

library(dplyr)\nlibrary(ggplot2)\n\niris %>%\n  filter(Species == \"setosa\") %>%\n  group_by(Sepal.Width) %>%\n  summarise(mean.Petal.Length = mean(Petal.Length)) %>%\n  mutate(Sepal.Width = as.factor(Sepal.Width)) %>%\n  ggplot(aes(x = Sepal.Width, y = mean.Petal.Length)) +\n  geom_bar(stat = \"identity\", fill = \"dodgerblue\") +\n  labs(title = \"Mean Petal Length of Setosa by Sepal Width\",\n       x = \"Sepal Width\",\n       y = \"Mean Petal Length\")\n

In this example, we start with the iris dataset and filter it to only include rows where the Species column is \u201csetosa\u201d. We then group the remaining rows by the Sepal.Width column and calculate the mean Petal.Length for each group. Next, we convert Sepal.Width to a factor variable to ensure that it is treated as a categorical variable in the visualization. Finally, we create a bar plot using ggplot2, with Sepal.Width on the x-axis and mean.Petal.Length on the y-axis. The resulting plot shows the mean petal length of setosa flowers for each sepal width category.

Python code:

import pandas as pd\n\n# Load the iris dataset and pipe it into the next function\n( pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data\", header=None, names=['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'class'])\n\n  # Select columns and pivot the dataset\n  .loc[:, ['sepal_length', 'sepal_width', 'petal_length']]\n  .melt(var_name='variable', value_name='value')\n\n  # Group by variable and calculate mean\n  .groupby('variable', as_index=False)\n  .mean()\n\n  # Filter for mean greater than 3.5 and sort by descending mean\n  .query('value > 3.5')\n  .sort_values('value', ascending=False)\n)\n
##        variable     value\n## 1  sepal_length  5.843333\n## 0  petal_length  3.758667\n
"},{"location":"resources/bilingualism_md/#for-loops","title":"for loops","text":"

Here is an example of a for loop in R:

R code

# Create a vector of numbers\nnumbers <- c(1, 2, 3, 4, 5)\n\n# Use a for loop to print out each number in the vector\nfor (i in numbers) {\n  print(i)\n}\n
## [1] 1\n## [1] 2\n## [1] 3\n## [1] 4\n## [1] 5\n

In this example, the for loop iterates over each element in the numbers vector, assigning the current element to the variable i. The print(i) statement is then executed for each iteration, outputting the value of i.

Here is the equivalent example in Python:

Python code

# Create a list of numbers\nnumbers = [1, 2, 3, 4, 5]\n\n# Use a for loop to print out each number in the list\nfor i in numbers:\n  print(i)\n
## 1\n## 2\n## 3\n## 4\n## 5\n

In Python, the for loop iterates over each element in the numbers list, assigning the current element to the variable i. The print(i) statement is then executed for each iteration, outputting the value of i.

Both languages also support nested for loops, which can be used to perform iterations over multiple dimensions, such as looping through a 2D array.

"},{"location":"resources/bilingualism_md/#parallel","title":"Parallel","text":"

Parallel computing is a technique used to execute multiple computational tasks simultaneously, which can significantly reduce the time required to complete a task. Both R and Python have built-in support for parallel computing, although the approaches are slightly different. In this answer, we will compare and contrast the parallel computing capabilities of R and Python, and provide working examples in code.

Parallel computing in R In R, there are several packages that support parallel computing, such as parallel, foreach, and doParallel. The parallel package provides basic functionality for parallel computing, while foreach and doParallel provide higher-level abstractions that make it easier to write parallel code.

Here is an example of using the foreach package to execute a loop in parallel:

R code:

library(foreach)\nlibrary(doParallel)\n\n# Set up a parallel backend with 4 workers\ncl <- makeCluster(4)\nregisterDoParallel(cl)\n\n# Define a function to apply in parallel\nmyfunc <- function(x) {\n  # some computation here\n  return(x^2)\n}\n\n# Generate some data\nmydata <- 1:1000\n\n# Apply the function to the data in parallel\nresult <- foreach(i = mydata) %dopar% {\n  myfunc(i)\n}\n\n# Stop the cluster\nstopCluster(cl)\n

In this example, we use the makeCluster() function to set up a cluster with 4 workers, and the registerDoParallel() function to register the cluster as the parallel backend for foreach. We then define a function myfunc() that takes an input x and returns x^2. We generate some data mydata and use foreach to apply myfunc() to each element of mydata in parallel, using the %dopar% operator.

R Tidyverse parallel

In R Tidyverse, we can use the furrr package for parallel computing. Here\u2019s an example of using furrr to parallelize a map function:

R Tidy code:

library(tidyverse)\nlibrary(furrr)\n\n# Generate a list of numbers\nnumbers <- 1:10\n\n# Use the future_map function from furrr to parallelize the map function\nplan(multisession)\nsquares <- future_map(numbers, function(x) x^2)\n

In this example, we first load the Tidyverse and furrr libraries. We then generate a list of numbers from 1 to 10. We then use the plan function to set the parallelization strategy to \u201cmultisession\u201d, which will use multiple CPU cores to execute the code. Finally, we use the future_map function from furrr to apply the function x^2 to each number in the list in parallel.

Parallel computing in Python In Python, the standard library includes the multiprocessing module, which provides basic support for parallel computing. Additionally, there are several third-party packages that provide higher-level abstractions, such as joblib and dask.

Here is an example of using the multiprocessing module to execute a loop in parallel:

Python code:

def square(x):\n    return x**2\n\nfrom multiprocessing import Pool\n\n# Generate a list of numbers\nnumbers = list(range(1, 11))\n\n# Use the map function and a pool of workers to parallelize the square function\nwith Pool() as pool:\n    squares = pool.map(square, numbers)\n\nprint(squares)\n

In this example, we define a function myfunc() that takes an input x and returns x^2. We generate some data mydata and use the Pool class from the multiprocessing module to set up a pool of 4 workers. We then use the map() method of the Pool class to apply myfunc() to each element of mydata in parallel.

Comparison and contrast Both R and Python have built-in support for parallel computing, with similar basic functionality for creating and managing parallel processes. However, the higher-level abstractions differ between the two languages. In R, the foreach package provides a high-level interface that makes it easy to write parallel code, while in Python, the multiprocessing module provides a basic interface that can be extended using third-party packages like joblib and dask.

Additionally, Python has better support for distributed computing using frameworks like Apache Spark, while R has better support for shared-memory parallelism using tools like data.table and ff.

"},{"location":"resources/bilingualism_md/#data-wrangling","title":"Data wrangling","text":"

Data wrangling is an important part of any data analysis project, and both R and Python provide tools and libraries for performing this task. In this answer, we will compare and contrast data wrangling in R\u2019s tidyverse and Python\u2019s pandas library, with working examples in code.

Data Wrangling in R Tidyverse

The tidyverse is a collection of R packages designed for data science, and it includes several packages that are useful for data wrangling. One of the most popular packages is dplyr, which provides a grammar of data manipulation for data frames.

Here is an example of using dplyr to filter, mutate, and summarize a data frame:

R code

library(dplyr)\n\n# Load data\ndata(mtcars)\n\n# Filter for cars with more than 100 horsepower\nmtcars %>%\n  filter(hp > 100) %>%\n  # Add a new column with fuel efficiency in km per liter\n  mutate(kmpl = 0.425 * mpg) %>%\n  # Group by number of cylinders and summarize\n  group_by(cyl) %>%\n  summarize(mean_hp = mean(hp),\n            mean_kmpl = mean(kmpl))\n
## # A tibble: 3 \u00d7 3\n##     cyl mean_hp mean_kmpl\n##   <dbl>   <dbl>     <dbl>\n## 1     4    111      11.0 \n## 2     6    122.      8.39\n## 3     8    209.      6.42\n

In this example, we first filter the mtcars data frame to only include cars with more than 100 horsepower. We then use mutate to create a new column with fuel efficiency in kilometers per liter. Finally, we group the data by the number of cylinders and calculate the mean horsepower and fuel efficiency.

Data Wrangling in Python Pandas

Pandas is a popular library for data manipulation in Python. It provides a data frame object similar to R\u2019s data frames, along with a wide range of functions for data wrangling.

Here is an example of using pandas to filter, transform, and group a data frame:

Python code:

import pandas as pd\n\n# Load data\nmtcars = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/mtcars.csv')\n\n# Filter for cars with more than 100 horsepower\nfiltered_mtcars = mtcars[mtcars['hp'] > 100]\n\n# Add a new column with fuel efficiency in km per liter\nfiltered_mtcars['kmpl'] = 0.425 * filtered_mtcars['mpg']\n\n# Group by number of cylinders and calculate mean horsepower and fuel efficiency\ngrouped_mtcars = filtered_mtcars.groupby('cyl').agg({'hp': 'mean',\n                                                     'kmpl': 'mean'})\n

In this example, we first load the mtcars data from a CSV file. We then filter the data to only include cars with more than 100 horsepower, using boolean indexing. We use the assign function to create a new column with fuel efficiency in kilometers per liter. Finally, we group the data by the number of cylinders and calculate the mean horsepower and fuel efficiency.

Comparison

Overall, both R\u2019s tidyverse and Python\u2019s pandas provide similar functionality for data wrangling. Both allow for filtering, transforming, and aggregating data frames. The syntax for performing these operations is slightly different between the two languages, with R using the %>% operator for chaining operations and Python using method chaining or the apply family of functions.

One key difference between the two languages is that R\u2019s tidyverse provides a consistent grammar for data manipulation across its various packages, making it easier to learn and use. However, Python\u2019s pandas library has a larger developer community and is more versatile for use in other applications, such as web development or machine learning.

In conclusion, both R and Python provide powerful tools for data wrangling, and the choice between the two ultimately depends on the specific needs of the user and their familiarity

"},{"location":"resources/bilingualism_md/#data-from-api","title":"Data from API","text":"

Retrieving data from an API is a common task in both R and Python. Here are examples of how to retrieve data from an API in both languages:

Python

To retrieve data from an API in Python, we can use the requests library. Here\u2019s an example of how to retrieve weather data from the OpenWeatherMap API:

Python code:

import requests\n\nurl = 'https://api.openweathermap.org/data/2.5/weather?q=London,uk&appid=API_KEY'\n\nresponse = requests.get(url)\n\ndata = response.json()\n\nprint(data)\n

This code retrieves the current weather data for London from the OpenWeatherMap API. We first construct the API URL with the location and API key, then use the requests.get() function to make a request to the API. We then extract the JSON data from the response using the .json() method and print the resulting data.

R

In R, we can use the httr package to retrieve data from an API. Here\u2019s an example of how to retrieve weather data from the OpenWeatherMap API in R:

R code:

library(httr)\n\nurl <- 'https://api.openweathermap.org/data/2.5/weather?q=London,uk&appid=API_KEY'\n\nresponse <- GET(url)\n\ndata <- content(response, 'text')\n\nprint(data)\n

This code is similar to the Python code above. We first load the httr library, then construct the API URL and use the GET() function to make a request to the API. We then extract the data from the response using the content() function and print the resulting data.

Retrieving Data from an API in R Tidyverse In R Tidyverse, we can use the httr and jsonlite packages to retrieve and process data from an API.

R code:

# Load required packages\nlibrary(httr)\nlibrary(jsonlite)\n\n# Define API endpoint\nendpoint <- \"https://jsonplaceholder.typicode.com/posts\"\n\n# Retrieve data from API\nresponse <- GET(endpoint)\n\n# Extract content from response\ncontent <- content(response, \"text\")\n\n# Convert content to JSON\njson <- fromJSON(content)\n\n# Convert JSON to a data frame\ndf <- as.data.frame(json)\n

In the above example, we use the GET() function from the httr package to retrieve data from an API endpoint, and the content() function to extract the content of the response. We then use the fromJSON() function from the jsonlite package to convert the JSON content to a list, and the as.data.frame() function to convert the list to a data frame.

Retrieving Data from an API in Python In Python, we can use the requests library to retrieve data from an API, and the json library to process the JSON data.

Python code:

# Load required libraries\nimport requests\nimport json\n\n# Define API endpoint\nendpoint = \"https://jsonplaceholder.typicode.com/posts\"\n\n# Retrieve data from API\nresponse = requests.get(endpoint)\n\n# Extract content from response\ncontent = response.content\n\n# Convert content to JSON\njson_data = json.loads(content)\n\n# Convert JSON to a list of dictionaries\ndata = [dict(row) for row in json_data]\n

In the above example, we use the get() function from the requests library to retrieve data from an API endpoint, and the content attribute to extract the content of the response. We then use the loads() function from the json library to convert the JSON content to a list of dictionaries.

Comparison Both R Tidyverse and Python provide powerful tools for retrieving and processing data from an API. In terms of syntax, the two languages are somewhat similar. In both cases, we use a library to retrieve data from the API, extract the content of the response, and then process the JSON data. However, there are some differences in the specific functions and methods used. For example, in R Tidyverse, we use the content() function to extract the content of the response, whereas in Python, we use the content attribute. Additionally, in R Tidyverse, we use the fromJSON() function to convert the JSON data to a list, whereas in Python, we use the loads() function.

"},{"location":"resources/bilingualism_md/#census-data","title":"Census data","text":"

Retrieving USA census data in R, R Tidy, and Python can be done using different packages and libraries. Here are some working examples in code for each language:

R:

To retrieve census data in R, we can use the tidycensus package. Here\u2019s an example of how to retrieve the total population for the state of California:

R code:

library(tidycensus)\nlibrary(tidyverse)\n\n# Set your Census API key\ncensus_api_key(\"your_api_key\")\n\n# Get the total population for the state of California\nca_pop <- get_acs(\n  geography = \"state\",\n  variables = \"B01003_001\",\n  state = \"CA\"\n) %>% \n  rename(total_population = estimate) %>% \n  select(total_population)\n\n# View the result\nca_pop\n

R Tidy:

To retrieve census data in R Tidy, we can also use the tidycensus package. Here\u2019s an example of how to retrieve the total population for the state of California using pipes and dplyr functions:

R tidy code:

library(tidycensus)\nlibrary(tidyverse)\n\n# Set your Census API key\ncensus_api_key(\"your_api_key\")\n\n# Get the total population for the state of California\nca_pop <- get_acs(\n  geography = \"state\",\n  variables = \"B01003_001\",\n  state = \"CA\"\n) %>% \n  rename(total_population = estimate) %>% \n  select(total_population)\n\n# View the result\nca_pop\n

Python:

To retrieve census data in Python, we can use the census library. Here\u2019s an example of how to retrieve the total population for the state of California:

Python code:

from census import Census\nfrom us import states\nimport pandas as pd\n\n# Set your Census API key\nc = Census(\"your_api_key\")\n\n# Get the total population for the state of California\nca_pop = c.acs5.state((\"B01003_001\"), states.CA.fips, year=2019)\n\n# Convert the result to a Pandas DataFrame\nca_pop_df = pd.DataFrame(ca_pop)\n\n# Rename the column\nca_pop_df = ca_pop_df.rename(columns={\"B01003_001E\": \"total_population\"})\n\n# Select only the total population column\nca_pop_df = ca_pop_df[[\"total_population\"]]\n\n# View the result\nca_pop_df\n
"},{"location":"resources/bilingualism_md/#lidar-data","title":"Lidar data","text":"

To find Lidar data in R and Python, you typically need to start by identifying sources of Lidar data and then accessing them using appropriate packages and functions. Here are some examples of how to find Lidar data in R and Python:

R:

Identify sources of Lidar data: The USGS National Map Viewer provides access to Lidar data for the United States. You can also find Lidar data on state and local government websites, as well as on commercial data providers\u2019 websites. Access the data: You can use the lidR package in R to download and read Lidar data in the LAS format. For example, the following code downloads and reads Lidar data for a specific area:

R code:

library(lidR)\n\n# Download Lidar data\nLASfile <- system.file(\"extdata\", \"Megaplot.laz\", package=\"lidR\")\nlidar <- readLAS(LASfile)\n\n# Visualize the data\nplot(lidar)\n

Python:

Identify sources of Lidar data: The USGS 3DEP program provides access to Lidar data for the United States. You can also find Lidar data on state and local government websites, as well as on commercial data providers\u2019 websites. Access the data: You can use the pylastools package in Python to download and read Lidar data in the LAS format. For example, the following code downloads and reads Lidar data for a specific area:

Python code:

py_install(\"requests\")\npy_install(\"pylas\")\npy_install(\"laspy\")\n
import requests\nfrom pylas import read\nimport laspy\nimport numpy as np\n\n# Download Lidar data\nurl = \"https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_CA_SanFrancisco_2016_LAS_2018.zip\"\nlasfile = \"USGS_LPC_CA_SanFrancisco_2016_LAS_2018.las\"\nr = requests.get(url, allow_redirects=True)\nopen(lasfile, 'wb').write(r.content)\n\n# Read the data\nlidar = read(lasfile)\n\n# Visualize the data\nlaspy.plot.plot(lidar)\n
"},{"location":"resources/bilingualism_md/#data-for-black-lives","title":"Data for black lives","text":"

Data for Black Lives (https://d4bl.org/) is a movement that uses data science to create measurable change in the lives of Black people. While the Data for Black Lives website provides resources, reports, articles, and datasets related to racial equity, it doesn\u2019t provide a direct API for downloading data.

Instead, you can access the Data for Black Lives GitHub repository (https://github.com/Data4BlackLives) to find datasets and resources to work with. In this example, we\u2019ll use a sample dataset available at https://github.com/Data4BlackLives/covid-19/tree/master/data. The dataset \u201cCOVID19_race_data.csv\u201d contains COVID-19 race-related data.

R: In R, we\u2019ll use the \u2018readr\u2019 and \u2018dplyr\u2019 packages to read, process, and analyze the dataset.

R code:

# Install and load necessary libraries\n\nlibrary(readr)\nlibrary(dplyr)\n\n# Read the CSV file\nurl <- \"https://raw.githubusercontent.com/Data4BlackLives/covid-19/master/data/COVID19_race_data.csv\"\ndata <- read_csv(url)\n\n# Basic information about the dataset\nprint(dim(data))\nprint(head(data))\n\n# Example analysis: calculate the mean of 'cases_total' by 'state'\ndata %>%\n  group_by(state) %>%\n  summarize(mean_cases_total = mean(cases_total, na.rm = TRUE)) %>%\n  arrange(desc(mean_cases_total))\n

Python: In Python, we\u2019ll use the \u2018pandas\u2019 library to read, process, and analyze the dataset.

Python code:

import pandas as pd\n\n# Read the CSV file\nurl = \"https://raw.githubusercontent.com/Data4BlackLives/covid-19/master/data/COVID19_race_data.csv\"\ndata = pd.read_csv(url)\n\n# Basic information about the dataset\nprint(data.shape)\nprint(data.head())\n\n# Example analysis: calculate the mean of 'cases_total' by 'state'\nmean_cases_total = data.groupby(\"state\")[\"cases_total\"].mean().sort_values(ascending=False)\nprint(mean_cases_total)\n

In conclusion, both R and Python provide powerful libraries and tools for downloading, processing, and analyzing datasets, such as those found in the Data for Black Lives repository. The \u2018readr\u2019 and \u2018dplyr\u2019 libraries in R offer a simple and intuitive way to read and manipulate data, while the \u2018pandas\u2019 library in Python offers similar functionality with a different syntax. Depending on your preferred programming language and environment, both options can be effective in working with social justice datasets.

"},{"location":"resources/bilingualism_md/#propublica-congress-api","title":"Propublica Congress API","text":"

The ProPublica Congress API provides information about the U.S. Congress members and their voting records. In this example, we\u2019ll fetch data about the current Senate members and calculate the number of members in each party.

R: In R, we\u2019ll use the \u2018httr\u2019 and \u2018jsonlite\u2019 packages to fetch and process data from the ProPublica Congress API.

R code:

# load necessary libraries\nlibrary(httr)\nlibrary(jsonlite)\n\n# Replace 'your_api_key' with your ProPublica API key\n\n#\n\n# Fetch data about the current Senate members\nurl <- \"https://api.propublica.org/congress/v1/117/senate/members.json\"\nresponse <- GET(url, add_headers(`X-API-Key` = api_key))\n\n# Check if the request was successful\nif (http_status(response)$category == \"Success\") {\n  data <- content(response, \"parsed\")\n  members <- data$results[[1]]$members\n\n  # Calculate the number of members in each party\n  party_counts <- table(sapply(members, function(x) x$party))\n  print(party_counts)\n} else {\n  print(http_status(response)$message)\n}\n
## \n##  D  I ID  R \n## 49  1  2 51\n

Python: In Python, we\u2019ll use the \u2018requests\u2019 library to fetch data from the ProPublica Congress API and \u2018pandas\u2019 library to process the data.

python code:

# Install necessary libraries\n\nimport requests\nimport pandas as pd\n\n# Replace 'your_api_key' with your ProPublica API key\napi_key = \"your_api_key\"\nheaders = {\"X-API-Key\": api_key}\n\n# Fetch data about the current Senate members\nurl = \"https://api.propublica.org/congress/v1/117/senate/members.json\"\nresponse = requests.get(url, headers=headers)\n\n# Check if the request was successful\nif response.status_code == 200:\n    data = response.json()\n    members = data[\"results\"][0][\"members\"]\n\n    # Calculate the number of members in each party\n    party_counts = pd.DataFrame(members)[\"party\"].value_counts()\n    print(party_counts)\nelse:\n    print(f\"Error: {response.status_code}\")\n

In conclusion, both R and Python offer efficient ways to fetch and process data from APIs like the ProPublica Congress API. The \u2018httr\u2019 and \u2018jsonlite\u2019 libraries in R provide a straightforward way to make HTTP requests and parse JSON data, while the \u2018requests\u2019 library in Python offers similar functionality. The \u2018pandas\u2019 library in Python can be used for data manipulation and analysis, and R provides built-in functions like table() for aggregating data. Depending on your preferred programming language and environment, both options can be effective for working with the ProPublica Congress API.

"},{"location":"resources/bilingualism_md/#nonprofit-explorer-api-by-propublica","title":"Nonprofit Explorer API by ProPublica","text":"

The Nonprofit Explorer API by ProPublica provides data on tax-exempt organizations in the United States. In this example, we\u2019ll search for organizations with the keyword \u201ceducation\u201d and analyze the results.

R: In R, we\u2019ll use the \u2018httr\u2019 and \u2018jsonlite\u2019 packages to fetch and process data from the Nonprofit Explorer API.

R code:

# Install and load necessary libraries\nlibrary(httr)\nlibrary(jsonlite)\n\n# Fetch data for organizations with the keyword \"education\"\nurl <- \"https://projects.propublica.org/nonprofits/api/v2/search.json?q=education\"\nresponse <- GET(url)\n\n# Check if the request was successful\nif (http_status(response)$category == \"Success\") {\n  data <- content(response, \"parsed\")\n  organizations <- data$organizations\n\n  # Count the number of organizations per state\n  state_counts <- table(sapply(organizations, function(x) x$state))\n  print(state_counts)\n} else {\n  print(http_status(response)$message)\n}\n
## \n##      AZ      CA      CO      DC      FL      GA      HI      IL Indiana      LA \n##       3      22       6       5       3       2       1       2       1       1 \n##      MD      MI      MN      MO      MP      MS      NC      NE      NJ      NM \n##       1       2       5       3       1       1       2       2       2       1 \n##      NY      OH      OK  Oregon      PA      TX      UT      VA      WA      WV \n##       1       5       1       2       2      12       1       4       3       1 \n##      ZZ \n##       2\n

Python: In Python, we\u2019ll use the \u2018requests\u2019 library to fetch data from the Nonprofit Explorer API and \u2018pandas\u2019 library to process the data.

Python code:

# Install necessary libraries\nimport requests\nimport pandas as pd\n\n# Fetch data for organizations with the keyword \"education\"\nurl = \"https://projects.propublica.org/nonprofits/api/v2/search.json?q=education\"\nresponse = requests.get(url)\n\n# Check if the request was successful\nif response.status_code == 200:\n    data = response.json()\n    organizations = data[\"organizations\"]\n\n    # Count the number of organizations per state\n    state_counts = pd.DataFrame(organizations)[\"state\"].value_counts()\n    print(state_counts)\nelse:\n    print(f\"Error: {response.status_code}\")\n
## CA         22\n## TX         12\n## CO          6\n## MN          5\n## OH          5\n## DC          5\n## VA          4\n## AZ          3\n## WA          3\n## MO          3\n## FL          3\n## IL          2\n## GA          2\n## NC          2\n## MI          2\n## Oregon      2\n## NE          2\n## ZZ          2\n## PA          2\n## NJ          2\n## HI          1\n## MS          1\n## NY          1\n## Indiana     1\n## NM          1\n## LA          1\n## UT          1\n## MD          1\n## MP          1\n## WV          1\n## OK          1\n## Name: state, dtype: int64\n

In conclusion, both R and Python offer efficient ways to fetch and process data from APIs like the Nonprofit Explorer API. The \u2018httr\u2019 and \u2018jsonlite\u2019 libraries in R provide a straightforward way to make HTTP requests and parse JSON data, while the \u2018requests\u2019 library in Python offers similar functionality. The \u2018pandas\u2019 library in Python can be used for data manipulation and analysis, and R provides built-in functions like table() for aggregating data. Depending on your preferred programming language and environment, both options can be effective for working with the Nonprofit Explorer API.

"},{"location":"resources/bilingualism_md/#campaign-finance-api-by-propublica","title":"Campaign Finance API by ProPublica","text":"

The Campaign Finance API by the Federal Election Commission (FEC) provides data on campaign finance in U.S. federal elections. In this example, we\u2019ll fetch data about individual contributions for the 2020 election cycle and analyze the results.

R: In R, we\u2019ll use the \u2018httr\u2019 and \u2018jsonlite\u2019 packages to fetch and process data from the Campaign Finance API.

R code:

# Install and load necessary libraries\nlibrary(httr)\nlibrary(jsonlite)\n\n# Fetch data about individual contributions for the 2020 election cycle\nurl <- \"https://api.open.fec.gov/v1/schedules/schedule_a/?api_key='OGwpkX7tH5Jihs1qQcisKfVAMddJzmzouWKtKoby'&two_year_transaction_period=2020&sort_hide_null=false&sort_null_only=false&per_page=20&page=1\"\nresponse <- GET(url)\n\n# Check if the request was successful\nif (http_status(response)$category == \"Success\") {\n  data <- content(response, \"parsed\")\n  contributions <- data$results\n\n  # Calculate the total contributions per state\n  state_totals <- aggregate(contributions$contributor_state, by = list(contributions$contributor_state), FUN = sum)\n  colnames(state_totals) <- c(\"State\", \"Total_Contributions\")\n  print(state_totals)\n} else {\n  print(http_status(response)$message)\n}\n
## [1] \"Client error: (403) Forbidden\"\n

Python: In Python, we\u2019ll use the \u2018requests\u2019 library to fetch data from the Campaign Finance API and \u2018pandas\u2019 library to process the data.

Python code:

# Install necessary libraries\n\nimport requests\nimport pandas as pd\n\n# Fetch data about individual contributions for the 2020 election cycle\nurl = \"https://api.open.fec.gov/v1/schedules/schedule_a/?api_key=your_api_key&two_year_transaction_period=2020&sort_hide_null=false&sort_null_only=false&per_page=20&page=1\"\nresponse = requests.get(url)\n\n# Check if the request was successful\nif response.status_code == 200:\n    data = response.json()\n    contributions = data[\"results\"]\n\n    # Calculate the total contributions per state\n    df = pd.DataFrame(contributions)\n    state_totals = df.groupby(\"contributor_state\")[\"contribution_receipt_amount\"].sum()\n    print(state_totals)\nelse:\n    print(f\"Error: {response.status_code}\")\n
## Error: 403\n

In conclusion, both R and Python offer efficient ways to fetch and process data from APIs like the Campaign Finance API. The \u2018httr\u2019 and \u2018jsonlite\u2019 libraries in R provide a straightforward way to make HTTP requests and parse JSON data, while the \u2018requests\u2019 library in Python offers similar functionality. The \u2018pandas\u2019 library in Python can be used for data manipulation and analysis, and R provides built-in functions like aggregate() for aggregating data. Depending on your preferred programming language and environment, both options can be effective for working with the Campaign Finance API.

Note: Remember to replace your_api_key with your actual FEC API key in the code examples above.

"},{"location":"resources/bilingualism_md/#historic-redlining","title":"Historic Redlining","text":"

Historic redlining data refers to data from the Home Owners\u2019 Loan Corporation (HOLC) that created residential security maps in the 1930s, which contributed to racial segregation and disinvestment in minority neighborhoods. One popular source for this data is the Mapping Inequality project (https://dsl.richmond.edu/panorama/redlining/).

In this example, we\u2019ll download historic redlining data for Philadelphia in the form of a GeoJSON file and analyze the data in R and Python.

R: In R, we\u2019ll use the \u2018sf\u2019 and \u2018dplyr\u2019 packages to read and process the GeoJSON data.

R code:

# Install and load necessary libraries\nlibrary(sf)\nlibrary(dplyr)\n\n# Download historic redlining data for Philadelphia\nurl <- \"https://dsl.richmond.edu/panorama/redlining/static/downloads/geojson/PAPhiladelphia1937.geojson\"\nphilly_geojson <- read_sf(url)\n\n# Count the number of areas per HOLC grade\ngrade_counts <- philly_geojson %>%\n  group_by(holc_grade) %>%\n  summarize(count = n())\n\nplot(grade_counts)\n

Python: In Python, we\u2019ll use the \u2018geopandas\u2019 library to read and process the GeoJSON data.

Python code:

# Install necessary libraries\n\n\nimport geopandas as gpd\n\n# Download historic redlining data for Philadelphia\nurl = \"https://dsl.richmond.edu/panorama/redlining/static/downloads/geojson/PAPhiladelphia1937.geojson\"\nphilly_geojson = gpd.read_file(url)\n\n# Count the number of areas per HOLC grade\ngrade_counts = philly_geojson[\"holc_grade\"].value_counts()\nprint(grade_counts)\n
## B    28\n## D    26\n## C    18\n## A    10\n## Name: holc_grade, dtype: int64\n

In conclusion, both R and Python offer efficient ways to download and process historic redlining data in the form of GeoJSON files. The \u2018sf\u2019 package in R provides a simple way to read and manipulate spatial data, while the \u2018geopandas\u2019 library in Python offers similar functionality. The \u2018dplyr\u2019 package in R can be used for data manipulation and analysis, and Python\u2019s built-in functions like value_counts() can be used for aggregating data. Depending on your preferred programming language and environment, both options can be effective for working with historic redlining data.

"},{"location":"resources/bilingualism_md/#american-indian-and-alaska-native-areas-aiannh","title":"American Indian and Alaska Native Areas (AIANNH)","text":"

In this example, we\u2019ll download and analyze the American Indian and Alaska Native Areas (AIANNH) TIGER/Line Shapefile from the U.S. Census Bureau. We\u2019ll download the data for the year 2020, and analyze the number of AIANNH per congressional district

R: In R, we\u2019ll use the \u2018sf\u2019 and \u2018dplyr\u2019 packages to read and process the Shapefile data.

R code:

# Install and load necessary libraries\nlibrary(sf)\nlibrary(dplyr)\n\n# Download historic redlining data for Philadelphia\nurl <- \"https://www2.census.gov/geo/tiger/TIGER2020/AIANNH/tl_2020_us_aiannh.zip\"\ntemp_file <- tempfile(fileext = \".zip\")\ndownload.file(url, temp_file, mode = \"wb\")\nunzip(temp_file, exdir = tempdir())\n\n# Read the Shapefile\nshapefile_path <- file.path(tempdir(), \"tl_2020_us_aiannh.shp\")\naiannh <- read_sf(shapefile_path)\n\n# Count the number of AIANNH per congressional district\nstate_counts <- aiannh %>%\n  group_by(LSAD) %>%\n  summarize(count = n())\n\nprint(state_counts[order(-state_counts$count),])\n
## Simple feature collection with 26 features and 2 fields\n## Geometry type: GEOMETRY\n## Dimension:     XY\n## Bounding box:  xmin: -174.236 ymin: 18.91069 xmax: -67.03552 ymax: 71.34019\n## Geodetic CRS:  NAD83\n## # A tibble: 26 \u00d7 3\n##    LSAD  count                                                          geometry\n##    <chr> <int>                                                <MULTIPOLYGON [\u00b0]>\n##  1 79      221 (((-166.5331 65.33918, -166.5331 65.33906, -166.533 65.33699, -1\u2026\n##  2 86      206 (((-83.38811 35.46645, -83.38342 35.46596, -83.38316 35.46593, -\u2026\n##  3 OT      155 (((-92.32972 47.81374, -92.3297 47.81305, -92.32967 47.81196, -9\u2026\n##  4 78       75 (((-155.729 20.02457, -155.7288 20.02428, -155.7288 20.02427, -1\u2026\n##  5 85       46 (((-122.3355 37.95215, -122.3354 37.95206, -122.3352 37.95199, -\u2026\n##  6 92       35 (((-93.01356 31.56287, -93.01354 31.56251, -93.01316 31.56019, -\u2026\n##  7 88       25 (((-97.35299 36.908, -97.35291 36.90801, -97.35287 36.908, -97.3\u2026\n##  8 96       19 (((-116.48 32.63814, -116.48 32.63718, -116.4794 32.63716, -116.\u2026\n##  9 84       16 (((-105.5937 36.40379, -105.5937 36.40324, -105.5937 36.40251, -\u2026\n## 10 89       11 (((-95.91705 41.28037, -95.91653 41.28036, -95.91653 41.28125, -\u2026\n## # \u2139 16 more rows\n

Python: In Python, we\u2019ll use the \u2018geopandas\u2019 library to read and process the Shapefile data.

Python code:

import geopandas as gpd\nimport pandas as pd\nimport requests\nimport zipfile\nimport os\nfrom io import BytesIO\n\n# Download historic redlining data for Philadelphia\nurl = \"https://www2.census.gov/geo/tiger/TIGER2020/AIANNH/tl_2020_us_aiannh.zip\"\nresponse = requests.get(url)\nzip_file = zipfile.ZipFile(BytesIO(response.content))\n\n# Extract Shapefile\ntemp_dir = \"temp\"\nif not os.path.exists(temp_dir):\n    os.makedirs(temp_dir)\n\nzip_file.extractall(path=temp_dir)\nshapefile_path = os.path.join(temp_dir, \"tl_2020_us_aiannh.shp\")\n\n# Read the Shapefile\naiannh = gpd.read_file(shapefile_path)\n\n# Count the number of AIANNH per congressional district\nstate_counts = aiannh.groupby(\"LSAD\").size().reset_index(name=\"count\")\n\n# Sort by descending count\nstate_counts_sorted = state_counts.sort_values(by=\"count\", ascending=False)\n\nprint(state_counts_sorted)\n
##    LSAD  count\n## 2    79    221\n## 9    86    206\n## 25   OT    155\n## 1    78     75\n## 8    85     46\n## 15   92     35\n## 11   88     25\n## 19   96     19\n## 7    84     16\n## 12   89     11\n## 5    82      8\n## 3    80      7\n## 4    81      6\n## 21   98      5\n## 20   97      5\n## 13   90      4\n## 18   95      3\n## 6    83      3\n## 17   94      2\n## 16   93      1\n## 14   91      1\n## 10   87      1\n## 22   99      1\n## 23   9C      1\n## 24   9D      1\n## 0    00      1\n

In conclusion, both R and Python offer efficient ways to download and process AIANNH TIGER/Line Shapefile data from the U.S. Census Bureau. The \u2018sf\u2019 package in R provides a simple way to read and manipulate spatial data, while the \u2018geopandas\u2019 library in Python offers similar functionality. The \u2018dplyr\u2019 package in R can be used for data manipulation and analysis, and Python\u2019s built-in functions like value_counts() can be used for aggregating data. Depending on your preferred programming language and environment, both options can be effective for working with AIANNH data.

"},{"location":"resources/bilingualism_md/#indian-entities-recognized-and-eligible-to-receive-services-by-bia","title":"Indian Entities Recognized and Eligible To Receive Services by BIA","text":"

The Bureau of Indian Affairs (BIA) provides a PDF document containing a list of Indian Entities Recognized and Eligible To Receive Services. To analyze the data, we\u2019ll first need to extract the information from the PDF. In this example, we\u2019ll extract the names of the recognized tribes and count the number of tribes per state.

R: In R, we\u2019ll use the \u2018pdftools\u2019 package to extract text from the PDF and the \u2018stringr\u2019 package to process the text data.

R code:

# Install and load necessary libraries\nlibrary(pdftools)\nlibrary(stringr)\nlibrary(dplyr)\n\n# Download the BIA PDF\nurl <- \"https://www.govinfo.gov/content/pkg/FR-2022-01-28/pdf/2022-01789.pdf\"\ntemp_file <- tempfile(fileext = \".pdf\")\ndownload.file(url, temp_file, mode = \"wb\")\n\n# Extract text from the PDF\npdf_text <- pdf_text(temp_file)\ntribe_text <- pdf_text[4:length(pdf_text)]\n\n# Define helper functions\ntribe_state_extractor <- function(text_line) {\n  regex_pattern <- \"(.*),\\\\s+([A-Z]{2})$\"\n  tribe_state <- str_match(text_line, regex_pattern)\n  return(tribe_state)\n}\n\nis_valid_tribe_line <- function(text_line) {\n  regex_pattern <- \"^\\\\d+\\\\s+\"\n  return(!is.na(str_match(text_line, regex_pattern)))\n}\n\n# Process text data to extract tribes and states\ntribe_states <- sapply(tribe_text, tribe_state_extractor)\nvalid_lines <- sapply(tribe_text, is_valid_tribe_line)\ntribe_states <- tribe_states[valid_lines, 2:3]\n\n# Count the number of tribes per state\ntribe_data <- as.data.frame(tribe_states)\ncolnames(tribe_data) <- c(\"Tribe\", \"State\")\nstate_counts <- tribe_data %>%\n  group_by(State) %>%\n  summarise(Count = n())\n\nprint(state_counts)\n
## # A tibble: 0 \u00d7 2\n## # \u2139 2 variables: State <chr>, Count <int>\n

Python: In Python, we\u2019ll use the \u2018PyPDF2\u2019 library to extract text from the PDF and the \u2018re\u2019 module to process the text data.

Python code:

# Install necessary libraries\nimport requests\nimport PyPDF2\nimport io\nimport re\nfrom collections import Counter\n\n# Download the BIA PDF\nurl = \"https://www.bia.gov/sites/bia.gov/files/assets/public/raca/online-tribal-leaders-directory/tribal_leaders_2021-12-27.pdf\"\nresponse = requests.get(url)\n\n# Extract text from the PDF\npdf_reader = PyPDF2.PdfFileReader(io.BytesIO(response.content))\ntribe_text = [pdf_reader.getPage(i).extractText() for i in range(3, pdf_reader.numPages)]\n\n# Process text data to extract tribes and states\ntribes = [re.findall(r'^\\d+\\s+(.+),\\s+([A-Z]{2})', line) for text in tribe_text for line in text.split('\\n') if line]\ntribe_states = [state for tribe, state in tribes]\n\n# Count the number of tribes per state\nstate_counts = Counter(tribe_states)\nprint(state_counts)\n

In conclusion, both R and Python offer efficient ways to download and process the list of Indian Entities Recognized and Eligible To Receive Services from the BIA. The \u2018pdftools\u2019 package in R provides a simple way to extract text from PDF files, while the \u2018PyPDF2\u2019 library in Python offers similar functionality. The \u2018stringr\u2019 package in R and the \u2018re\u2019 module in Python can be used to process and analyze text data. Depending on your preferred programming language and environment, both options can be effective for working with BIA data.

"},{"location":"resources/bilingualism_md/#national-atlas-indian-lands-of-the-united-states-dataset","title":"National Atlas - Indian Lands of the United States dataset","text":"

In this example, we will download and analyze the National Atlas - Indian Lands of the United States dataset in both R and Python. We will read the dataset and count the number of Indian lands per state.

R: In R, we\u2019ll use the \u2018sf\u2019 package to read the Shapefile and the \u2018dplyr\u2019 package to process the data.

R code:

# Install and load necessary libraries\n\nlibrary(sf)\nlibrary(dplyr)\n\n# Download the Indian Lands dataset\nurl <- \"https://prd-tnm.s3.amazonaws.com/StagedProducts/Small-scale/data/Boundaries/indlanp010g.shp_nt00968.tar.gz\"\ntemp_file <- tempfile(fileext = \".tar.gz\")\ndownload.file(url, temp_file, mode = \"wb\")\nuntar(temp_file, exdir = tempdir())\n\n# Read the Shapefile\nshapefile_path <- file.path(tempdir(), \"indlanp010g.shp\")\nindian_lands <- read_sf(shapefile_path)\n\n# Count the number of Indian lands per state\n# state_counts <- indian_lands %>%\n#   group_by(STATE) %>%\n#   summarize(count = n())\n\nplot(indian_lands)\n
## Warning: plotting the first 9 out of 23 attributes; use max.plot = 23 to plot\n## all\n

Python: In Python, we\u2019ll use the \u2018geopandas\u2019 and \u2018pandas\u2019 libraries to read the Shapefile and process the data.

Python code:

import geopandas as gpd\nimport pandas as pd\nimport requests\nimport tarfile\nimport os\nfrom io import BytesIO\n\n# Download the Indian Lands dataset\nurl = \"https://prd-tnm.s3.amazonaws.com/StagedProducts/Small-scale/data/Boundaries/indlanp010g.shp_nt00966.tar.gz\"\nresponse = requests.get(url)\ntar_file = tarfile.open(fileobj=BytesIO(response.content), mode='r:gz')\n\n# Extract Shapefile\ntemp_dir = \"temp\"\nif not os.path.exists(temp_dir):\n    os.makedirs(temp_dir)\n\ntar_file.extractall(path=temp_dir)\nshapefile_path = os.path.join(temp_dir, \"indlanp010g.shp\")\n\n# Read the Shapefile\nindian_lands = gpd.read_file(shapefile_path)\n\n# Count the number of Indian lands per state\nstate_counts = indian_lands.groupby(\"STATE\").size().reset_index(name=\"count\")\n\nprint(state_counts)\n

Both R and Python codes download the dataset and read the Shapefile using the respective packages. They then group the data by the \u2018STATE\u2019 attribute and calculate the count of Indian lands per state.

"},{"location":"resources/citations/","title":"Citation Management and Notes Collection in Markdown","text":""},{"location":"resources/citations/#introduction","title":"Introduction","text":"

This document serves as a guide for managing citations and collecting research notes for our project. We'll use a combination of a .bib file for bibliographic references and Markdown for note-taking.

"},{"location":"resources/citations/#part-1-setting-up-your-bib-file-for-citations","title":"Part 1: Setting Up Your .bib File for Citations","text":""},{"location":"resources/citations/#creating-a-bib-file","title":"Creating a .bib File","text":"
  1. Create a new file with a .bib extension, for example, project_references.bib.
  2. Add bibliographic entries to this file. Each entry should follow the BibTeX format.
"},{"location":"resources/citations/#example-of-a-bib-entry","title":"Example of a .bib Entry","text":"

```bibtex @article{Doe2021, author = {Jane Doe and John Smith}, title = {Insights into Environmental Data Science}, journal = {Journal of Data Science}, year = {2021}, volume = {15}, number = {4}, pages = {123-145}, doi = {10.1000/jds.2021.15.4} }

"},{"location":"resources/citations/#part-2-using-citations-in-markdown","title":"Part 2: Using Citations in Markdown","text":""},{"location":"resources/citations/#citing-in-your-markdown-document","title":"Citing in Your Markdown Document","text":"
  • Refer to works in your .bib file using citation keys, like [@Doe2021].
"},{"location":"resources/citations/#converting-markdown-to-pdf-with-citations","title":"Converting Markdown to PDF with Citations","text":"
  • Use Pandoc: pandoc yourdoc.md --bibliography=project_references.bib --citeproc -o output.pdf
"},{"location":"resources/citations/#part-3-collecting-citations-and-research-notes","title":"Part 3: Collecting Citations and Research Notes","text":""},{"location":"resources/citations/#structuring-your-notes","title":"Structuring Your Notes","text":""},{"location":"resources/citations/#notes-on-doe-2021-doe2021","title":"Notes on Doe 2021 [@Doe2021]","text":"
  • Key Points:
  • Summary of the article's main arguments.

  • Notable methodologies.

  • Relevance to Our Project:

  • How this research informs our project.
  • Applicable methodologies or theories.
"},{"location":"resources/citations/#notes-on-another-article-another2021","title":"Notes on Another Article [@Another2021]","text":"
  • Key Points:

  • ...

  • Relevance to Our Project:

  • ...
"},{"location":"resources/citations/#conclusion","title":"Conclusion","text":"

This document facilitates efficient management of references and collaborative knowledge building for our project.

"},{"location":"resources/code-of-conduct/","title":"Code of Conduct and Respectful Inclusive Collaboration Guidelines","text":"

CIRES Earth Lab and Environmental Data Science Innovation & Inclusion Lab (ESIIL) are committed to building, maintaining, and fostering an inclusive, kind, collaborative, and diverse transdisciplinary environmental data science community, whose members feel welcome, supported, and safe to contribute ideas and knowledge.

The ESIIL postdoc program will follow all aspects of the ESIIL Code of Conduct (below).

All community members are responsible for creating this culture, embodying our values, welcoming diverse perspectives and ways of knowing, creating safe inclusive spaces, and conducting ethical science as guided by FAIR (Findable, Accessible, Interoperable, Reusable) and CARE (Collective Benefit, Authority to Control, Responsibility, and Ethics) principles for scientific and Indigenous data management, governance, and stewardship.

"},{"location":"resources/code-of-conduct/#our-values","title":"Our values","text":"

ESIIL\u2019s vision is grounded in the conviction that innovation and breakthroughs in environmental data science will be precipitated by a diverse, collaborative, curious, and inclusive research community empowered by open data and infrastructure, cross-sector and community partnerships, team science, and engaged learning.

As such, our core values center people through inclusion, kindness, respect, collaboration, and genuine relationships. They also center innovation, driven by collaborative, cross-sector science and synthesis, open, accessible data and tools, and fun, diverse teams. Finally, they center learning, propelled by curiosity and accessible, inclusive training, and education opportunities.

"},{"location":"resources/code-of-conduct/#when-and-how-to-use-these-guidelines","title":"When and how to use these guidelines","text":"

These guidelines outline behavior expectations for ESIIL community members. Your participation in the ESIIL network is contingent upon following these guidelines in all ESIIL activities, including, but not limited to, participating in meetings, webinars, hackathons, working groups, hosted or funded by ESIIL, as well as email lists and online forums such as GutHub, Slack, and Twitter. These guidelines have been adapted from those of the International Arctic Research Policy Committee, the Geological Society of America, the American Geophysical Union, the University Corporation for Atmospheric Research, The Carpentries, and others. We encourage other organizations to adapt these guidelines for use in their own meetings.

Note: Working groups and hackathon/codefest teams are encouraged to discuss these guidelines and what they mean to them, and will have the opportunity to add to them to specifically support and empower their team. Collaborative and behavior commitments complement data use, management, authorship, and access plans that commit to CARE and FAIR principles.

"},{"location":"resources/code-of-conduct/#behavior-agreements","title":"Behavior Agreements","text":"

ESIIL community members are expected to act professionally and respectfully in all activities, such that each person, regardless of gender, gender identity or expression, sexual orientation, disability, physical appearance, age, body size, race, religion, national origin, ethnicity, level of experience, language fluency, political affiliation, veteran status, pregnancy, country of origin, and any other characteristic protected under state or federal law, feels safe and welcome in our activities and community. We gain strength from diversity and actively seek participation from those who enhance it.

In order to garner the benefits of a diverse community and to reach the full potential of our mission and charge, ESIIL participants must be allowed to develop a sense of belonging and trust within a respectful, inclusive, and collaborative culture. Guiding behaviors that contribute to this culture include, but are not limited to:

"},{"location":"resources/code-of-conduct/#showing-respect","title":"Showing Respect","text":"

  • Listen carefully \u2013 we each bring our own styles of communication, language, and ideas, and we must do our best to accept and accommodate differences. Do not interrupt when someone is speaking and maintain an open mind when others have different ideas than yours.

  • Be present \u2013 when engaging with others, give them your full attention. If you need to respond to outside needs, please step away from the group quietly.

  • Be kind \u2013 offer positive, supportive comments and constructive feedback. Critique ideas, not people. Harassment, discrimination, bullying, aggression, including offensive comments, jokes, and imagery, are unacceptable, regardless of intent, and will not be tolerated.

  • Be punctual - adhere to the schedule provided by the organizers and avoid disruptive behavior during presentations, trainings, or working sessions.

  • Respect privacy - be mindful of the confidentiality of others. Always obtain explicit consent before recording, sharing, or using someone else\u2019s personal information, photos, or recordings.

  • Practice good digital etiquette (netiquette) when communicating online, whether in emails, messages, or social media - think before posting online and consider the potential impact on others. Do not share or distribute content generated by or involving others without their explicit consent.

"},{"location":"resources/code-of-conduct/#being-inclusive","title":"Being Inclusive","text":"

  • Create space for everyone to participate \u2013 be thoughtful about who is at the table; openly address accessibility needs, and provide multiple ways to contribute.

  • Be welcoming \u2013 ESIIL participants come from a wide range of skill levels and career stages, backgrounds, and cultures. Demonstrate that you value these different perspectives and identities through your words and actions, including through correct use of names, titles, and pronouns.

  • Be self-aware \u2013 recognize that positionality, identity, unconscious biases, and upbringing can all affect how words and behaviors are perceived. Ensure that your words and behavior make others feel welcome.

  • Commit to ongoing learning \u2013 the move toward inclusive, equitable, and just environmental data science is a collective journey. Continue to learn about and apply practices of inclusion, anti-racism, bystander intervention, and cultural sensitivity. None of us is perfect; all of us will, from time to time, fail to live up to our own high standards. Being perfect is not what matters; owning our mistakes and committing to clear and persistent efforts to grow and improve is.

"},{"location":"resources/code-of-conduct/#being-curious","title":"Being Curious","text":"

  • Check your presumptions \u2013 we each bring our own ideas and assumptions about how the world should and does work \u2013 what are yours, and how do they affect how you interact with others? How do they shape your perception of new ideas?

  • Ask questions \u2013 one of the strengths of interdisciplinary and diverse teams is that we all bring different knowledge and viewpoints; no one person is expected to know everything. So don\u2019t be afraid to ask, to learn, and to share.

  • Be bold \u2013 significant innovations don\u2019t come from incremental efforts. Be brave in proposing and testing new ideas. When things don\u2019t work, learn from the experience.

  • Invite feedback \u2013 new ideas and improvements can emerge from many places when we\u2019re open to hearing them. Check your defensiveness and listen; accept feedback as a gift toward improving our work and ourselves.

"},{"location":"resources/code-of-conduct/#being-collaborative","title":"Being Collaborative","text":"

  • Recognize that everyone is bringing something different to the table \u2013 take the time to get to know each other. Keep an open mind, encourage ideas that are different from yours, and learn from each other\u2019s expertise and experience.

  • Be accountable - great team science depends on trust, communication, respect, and delivering on your commitments. Be clear about your needs, as both a requester and a responder, realistic about your time and capacity commitments, and communicate timelines and standards in advance.

  • Make assumptions explicit and provide context wherever possible - misunderstandings are common on transdisciplinary and cross-cultural teams and can best be managed with intentionality. Check in about assumptions, and be willing to share and correct misunderstandings or mistakes when they happen. Make use of collaboration agreements, communicate clearly and avoid jargon wherever possible.

  • Respect intellectual property and Indigenous data sovereignty \u2013 ESIIL recognizes the extractive and abusive history of scientific engagement with Native peoples, and is committed to doing better. Indigenous knowledge holders are under no obligation to share their data, stories or knowledge. Their work should always be credited, and only shared with permission. Follow guidelines for authorship, Indigenous data sovereignty, and CARE principles. Acknowledge and credit the ideas and work of others.

  • Use the resources that we provide - take advantage of the cyberinfrastructure and data cube at your disposal, but do not use them for unrelated tasks, as it could disrupt the event, introduce security risks, undermine the spirit of collaboration and fair play, and erode trust within the event community.

  • Be safe - never share sensitive personal information; use strong passwords for your Cyverse and GitHub accounts and do not share them with other participants; be cautious of unsolicited emails, messages, or links; and verify online contacts. If you encounter any illegal or harmful activities online related to this event, report them to Tyler McIntosh or Susan Sullivan.

Finally, speak up if you experience or notice a dangerous situation, or someone in distress!

"},{"location":"resources/code-of-conduct/#code-of-conduct-unacceptable-behaviors","title":"Code of Conduct: Unacceptable behaviors","text":"

We adopt the full Code of Conduct of our home institution, the University of Colorado, details of which are found here. To summarize, examples of unacceptable and reportable behaviors include, but are not limited to:

  • Harassment, intimidation, or discrimination in any form
  • Physical or verbal abuse by anyone to anyone, including but not limited to a participant, member of the public, guest, member of any institution or sponsor
  • Unwelcome sexual attention or advances
  • Personal attacks directed at other guests, members, participants, etc.
  • Alarming, intimidating, threatening, or hostile comments or conduct
  • Inappropriate use of nudity and/or sexual images in public spaces or in presentations
  • Threatening or stalking anyone
  • Unauthorized use or sharing of personal or confidential information or private communication
  • Continuing interactions, including but not limited to conversations, photographies, recordings, instant messages, and emails, after being asked to stop
  • Ethical and scientific misconduct, including failing to credit contributions or respect intellectual property
  • Engaging in any illegal activities, including hacking, cheating, or unauthorized access to systems or data
  • Using the cyberinfrastructure provided by the organizers for activities unrelated to this event.
  • Other conduct which could reasonably be considered inappropriate in a professional setting.

The University of Colorado recognizes all Federal and State protected classes, which include the following: race, color, national origin, sex, pregnancy, age, marital status, disability, creed, religion, sexual orientation, gender identity, gender expression, veteran status, political affiliation or political philosophy. Mistreatment or harassment not related to protected class also has a negative impact and will be addressed by the ESIIL team.

Anyone requested to stop unacceptable behavior is expected to comply immediately.

If there is a clear violation of the code of conduct during an ESIIL event\u2014for example, a meeting is Zoom bombed or a team member is verbally abusing another participant during a workshop\u2014 ESIIL leaders, facilitators (or their designee) or campus/local police may take any action deemed necessary and appropriate, including expelling the violator, or immediate removal of the violator from any online or in-person event or platform without warning or refund. If such actions are necessary, there will be follow up with the ESIIL Diversity Equity and Inclusion (DEI) team to determine what further action is needed (see Reporting Process and Consequences below).

"},{"location":"resources/code-of-conduct/#addressing-behavior-directly","title":"Addressing Behavior Directly","text":"

For smaller incidents that might be settled with a brief conversation, you may choose to contact the person in question or set up a (video) conversation to discuss how the behavior affected you. Please use this approach only if you feel comfortable; you do not have to carry the weight of addressing these issues yourself. If you are interested in this option but unsure how to go about it, please contact the ESIIL DEI lead, Susan Sullivan, first\u2014she will have advice on how to make the conversation happen and is available to join you in a conversation as requested.

"},{"location":"resources/code-of-conduct/#reporting-process-and-consequences","title":"Reporting Process and Consequences","text":"

We take any reports of Code of Conduct violations seriously, and aim to support those who are impacted and ensure that problematic behavior doesn\u2019t happen again.

"},{"location":"resources/code-of-conduct/#making-a-report","title":"Making a Report","text":"

If you believe you\u2019re experiencing or have experienced unacceptable behavior that is counter to this code of conduct, or you are witness to this behavior happening to someone else, we encourage you to contact our DEI lead:

  • Susan Sullivan, CIRES
  • Email: susan.sullivan@colorado.edu

You may also choose to anonymously report behavior to ESIIL using this form.

The DEI team will keep reports as confidential as possible. However, as mandatory reporters, we have an obligation to report alleged protected class violations to our home institution or to law enforcement.

"},{"location":"resources/code-of-conduct/#specifically","title":"Specifically:","text":"
  • Cases of potential protected-class harassment will be reported to the CU Office of Institutional Equity and Compliance.
  • If the violation is made by a member of another institution, that information may also be shared with that member\u2019s home institution by the CU Office of Institutional Equity and Compliance under Title IX.
  • In some instances, harassment information may be shared with the National Science Foundation, who are the funding organization of ESIIL.

When we discuss incidents with people who are accused of misconduct (the respondent), we will anonymize details as much as possible to protect the privacy of the reporter and the person who was impacted (the complainant). In some cases, even when the details are anonymized, the respondent may guess at the identities of the reporter and complainants. If you have concerns about retaliation or your personal safety, please let us know (or note that in your report). We encourage you to report in any case, so that we can support you while keeping ESIIL members safe. In some cases, we are able to compile several anonymized reports into a pattern of behavior, and take action based on that pattern.

If you prefer to speak with someone who is not on the ESIIL leadership team, or who can maintain confidentiality, you may contact:

  • CU Ombuds
  • Phone: 303-492-5077 (for guidance and support navigating difficult conversations)
  • CU Office of Victim Assistance
  • Phone: 303-492-8855

If you want more information about when to report, or how to help someone who needs to report, please review the resources at Don\u2019t Ignore It.

Note: The reporting party does not need to be directly involved in a code of conduct violation incident. Please make a bystander report if you observe a potentially dangerous situation, someone in distress, or violations of these guidelines, even if the situation is not happening to you.

"},{"location":"resources/code-of-conduct/#what-happens-after-a-report-is-filed","title":"What Happens After a Report Is Filed","text":"

After a member of the ESIIL DEI team takes your report, they will (if necessary) consult with the appropriate support people at CU. The ESIIL DEI team will respond with a status update within 5 business days.

During this time, they, or members of the CU Office of Institutional Equity and Compliance, will:

  • Meet with you or review report documentation to determine what happened
  • Consult documentation of past incidents for patterns of behavior
  • Discuss appropriate response(s) to the incident
  • Connect with the appropriate offices and/or make those response(s)
  • Determine the follow-up actions for any impacted people and/or the reporter
  • Follow up with the impacted people, including connecting them with support and resources.
"},{"location":"resources/code-of-conduct/#as-a-result-of-this-process-in-minor-cases-esiil-dei-may-communicate-with-the-respondent-to","title":"As a result of this process, in minor cases ESIIL DEI may communicate with the respondent to:","text":"
  • Explain what happened and the impact of their behavior
  • Offer concrete examples of how to improve their behavior
  • Explain consequences of their behavior, or future consequences if the behavior is repeated.

For significant infractions, follow up to the report may be turned over to the CU Office of Institutional Equity and Compliance and/or campus police.

"},{"location":"resources/code-of-conduct/#possible-consequences-to-code-of-conduct-violations","title":"Possible Consequences to Code of Conduct Violations","text":"

What follows are examples of possible responses to an incident report. This list is not inclusive, and ESIIL reserves the right to take any action it deems necessary. Generally speaking, the strongest response ESIIL may take is to completely ban a user from further engagement with ESIIL activities and, as is required, report a person to the CU Office of Institutional Equity and Compliance and/or their home institution and NSF. If law enforcement should be involved, they will recommend that the complainant make that contact. Employees of CU Boulder may also be subject to consequences as determined by the institution.

In addition to the responses above, ESIIL responses may include but are not limited to the following:

  • A verbal discussion in person or via phone/Zoom followed by documentation of the conversation via email
  • Not publishing the video or slides of a talk that violated the code of conduct
  • Not allowing a speaker who violated the code of conduct to give (further) talks
  • Immediately ending any team leadership, membership, or other responsibilities and privileges that a person holds
  • Temporarily banning a person from ESIIL activities
  • Permanently banning a person from ESIIL activities
  • Nothing, if the behavior is determined to not be a code of conduct violation

Do you need more resources?

Please don\u2019t hesitate to contact the ESIIL DEI lead, Susan Sullivan, if you have questions or concerns.

The CU Office of Institutional Equity and Compliance is a resource for all of us in navigating this space. They also offer resource materials that can assist you in exploring various topics and skills here.

If you have questions about what, when or how to report, or how to help someone else with concerns, Don\u2019t Ignore It.

CU Ombud\u2019s Office: Confidential support to navigate university situations. (Most universities have these resources)

The CU Office of Victims Assistance (counseling limited to CU students/staff/faculty, though advocacy is open to everyone engaged with a CU-sponsored activity. Please look for a similar resource on your campus if you are from another institution).

National Crisis Hotlines

How are we doing?

Despite our best intentions, in some cases we may not be living up to our ideals of a positive, supportive, inclusive, respectful and collaborative community. If you feel we could do better, we welcome your feedback. Comments, suggestions and praise are also very welcome! Acknowledgment By participating in this event, you agree to abide by this code of conduct and understand the consequences of violating it. We believe that a respectful and inclusive environment benefits all participants and leads to more creative and successful outcomes. Thank you for your cooperation in making the this event a welcoming event for all. Have fun!

"},{"location":"resources/cyverse_basics/","title":"Connecting Cyverse to GitHub","text":""},{"location":"resources/cyverse_basics/#log-in-to-cyverse","title":"Log in to Cyverse","text":"
  1. Go to the Cyverse user account website https://user.cyverse.org/
  1. Click Sign up (if you do not already have an account)
  1. Head over to the Cyverse Discovery Environment https://de.cyverse.org, and log in with your new account.

You should now see the Discovery Environment:

  1. We will give you permissions to access the Hackathon app. If you haven't already, let us know that you need access
"},{"location":"resources/cyverse_basics/#open-up-an-analysis-with-the-hackathon-environment-jupyter-lab","title":"Open up an analysis with the hackathon environment (Jupyter Lab)","text":"

  1. From the Cyverse Discovery Environment, click on Apps in the left menu

  2. Select JupyterLab ESIIL

  3. Configure and launch your analysis - when choosing the disk size, make sure to choose 64GB or greater. The rest of the settings you can change to suit your computing needs:

  1. Click Go to analysis:

  2. Now you should see Jupyter Lab!

"},{"location":"resources/cyverse_basics/#set-up-your-github-credentials","title":"Set up your GitHub credentials","text":""},{"location":"resources/cyverse_basics/#if-you-would-prefer-to-follow-a-video-instead-of-a-written-outline-we-have-prepared-a-video-here","title":"If you would prefer to follow a video instead of a written outline, we have prepared a video here:","text":"

  1. From Jupyter Lab, click on the Git Extension icon on the left menu:

  2. Click Clone a Repository and Paste the link to the cyverse-utils https://github.com/CU-ESIIL/cyverse-utils.git and click Clone:

  3. You should now see the cyverse-utils folder in your directory tree (provided you haven't changed directories from the default /home/jovyan/data-store

  4. Go into the cyverse-utils folder:

  5. open up the create_github_keypair.ipynb notebook if you prefer Python or the 'create_github_keypair.R' script if you prefer R by double-clicking and then select the default 'macrosystems' kernel:

  6. Now you should see the notebook open. Click the play button at the top. You will be prompted to enter your GitHub username and email:

  1. You should now see your Public Key. Copy the WHOLE LINE including ssh-ed25519 at the beginning and the jovyan@... at the end

  2. Go to your GitHub settings page (you may need to log in to GitHub first):

  3. Select SSH and GPG keys

  4. Select New SSH key

  5. Give your key a descriptive name, paste your ENTIRE public key in the Key input box, and click Add SSH Key. You may need to re-authenticate with your password or two-factor authentication.:

  6. You should now see your new SSH key in your Authentication Keys list! Now you will be able to clone private repositories and push changes to GitHub from your Cyverse analysis!

NOTE! Your GitHub authentication is ONLY for the analysis you're working with right now. You will be able to use it as long as you want there, but once you start a new analysis you will need to go through this process again. Feel free to delete keys from old analyses that have been shut down.

"},{"location":"resources/cyverse_hacks/","title":"Transitioning Workflows to CyVerse: A Guide for ESIIL Postdocs","text":""},{"location":"resources/cyverse_hacks/#earth-lab-data-storage","title":"Earth Lab Data Storage","text":"
  • Path: /home/jovyan/data-store/iplant/home/shared/earthlab/
  • Ensure your project has a directory within the Earth Lab data storage.
"},{"location":"resources/cyverse_hacks/#setup","title":"Setup","text":"
  1. CyVerse Account:
  2. Create an account if not already owned.
  3. Contact Tyson for account upgrades after maximizing current limits.
"},{"location":"resources/cyverse_hacks/#github-connection","title":"GitHub Connection","text":"
  • Follow Elsa Culler's guide for connecting GitHub to CyVerse.
  • Select \u201cJupyterLab ESIIL\u201d and choose \u201cmacrosystems\u201d in the version dropdown.
  • Clone into /home/jovyan/data-store.
  • Clone innovation-summit-utils for SSH connection to GitHub.
  • Run conda install -c conda-forge openssh in the terminal if encountering errors.
  • GitHub authentication is session-specific.
"},{"location":"resources/cyverse_hacks/#rstudio-in-de","title":"RStudio in DE","text":"
  1. Copy your instance ID. It can be found in your analyis URL in form https://.cyverse.run/lab.
  2. Use your ID in these links:
  3. https://<id>.cyverse.run/rstudio/auth-sign-in
  4. https://<id>.cyverse.run/rstudio/
    5. "},{"location":"resources/cyverse_hacks/#package-requests","title":"Package Requests","text":"
    • List desired packages here for future container updates.
    "},{"location":"resources/cyverse_hacks/#data-transfer-to-cyverse","title":"Data Transfer to CyVerse","text":"
    • Use GoCommands for HPC/CyVerse transfers.
    • Installation:
    • Linux: (Command)
    • Windows Powershell: (Command)
    • Usage:
    • Use put for upload and get for download.
    • Ensure correct CyVerse directory path.
    "},{"location":"resources/data_analysis/","title":"Data Analysis Documentation","text":""},{"location":"resources/data_analysis/#overview","title":"Overview","text":"

    Brief overview of the data analysis goals and the analytical questions being addressed.

    "},{"location":"resources/data_analysis/#analysis-methodology","title":"Analysis Methodology","text":"

    Description of the analytical approach, methods used, and justification for the chosen techniques.

    "},{"location":"resources/data_analysis/#code-overview","title":"Code Overview","text":"

    Explanation of the structure of the analysis code, including key functions and their roles.

    "},{"location":"resources/data_analysis/#running-the-analysis","title":"Running the Analysis","text":"

    Instructions and example commands for executing the analysis scripts.

    python analysis_script.py\n
    "},{"location":"resources/data_analysis/#analysis-results","title":"Analysis Results","text":"

    Summary of key findings from the analysis, including interpretation and relevance.

    "},{"location":"resources/data_analysis/#challenges-and-solutions","title":"Challenges and Solutions","text":"

    Discussion of challenges faced during the analysis and solutions or workarounds implemented.

    "},{"location":"resources/data_analysis/#conclusions","title":"Conclusions","text":"

    Concluding remarks on the analysis, insights gained, and their potential impact.

    "},{"location":"resources/data_analysis/#future-work","title":"Future Work","text":"

    Suggestions for extending or refining the analysis and potential areas for further research.

    "},{"location":"resources/data_analysis/#references","title":"References","text":"

    Citations or references to external sources or literature used.

    "},{"location":"resources/data_processing/","title":"Data Processing Documentation","text":""},{"location":"resources/data_processing/#overview","title":"Overview","text":"

    Brief description of the data processing objectives and scope. Reminder to adhere to data ownership and usage guidelines.

    "},{"location":"resources/data_processing/#data-sources","title":"Data Sources","text":"

    List and describe data sources used, including links to cloud-optimized sources. Highlight permissions and compliance with data ownership guidelines.

    "},{"location":"resources/data_processing/#cyverse-discovery-environment","title":"CyVerse Discovery Environment","text":"

    Instructions for setting up and using the CyVerse Discovery Environment for data processing. Tips for cloud-based data access and processing.

    "},{"location":"resources/data_processing/#data-processing-steps","title":"Data Processing Steps","text":""},{"location":"resources/data_processing/#using-gdal-vsi","title":"Using GDAL VSI","text":"

    Guidance on using GDAL VSI (Virtual System Interface) for data access and processing. Example commands or scripts:

    gdal_translate /vsicurl/http://example.com/data.tif output.tif\n
    "},{"location":"resources/data_processing/#cloud-optimized-data","title":"Cloud-Optimized Data","text":"

    Advantages of using cloud-optimized data formats and processing data without downloading. Instructions for such processes.

    "},{"location":"resources/data_processing/#data-storage","title":"Data Storage","text":"

    Information on storing processed data, with guidelines for choosing between the repository and CyVerse Data Store.

    "},{"location":"resources/data_processing/#best-practices","title":"Best Practices","text":"

    Recommendations for efficient and responsible data processing in the cloud. Tips to ensure data integrity and reproducibility.

    "},{"location":"resources/data_processing/#challenges-and-troubleshooting","title":"Challenges and Troubleshooting","text":"

    Common challenges in data processing and potential solutions. Resources for troubleshooting in the CyVerse Discovery Environment.

    "},{"location":"resources/data_processing/#conclusions","title":"Conclusions","text":"

    Summary of the data processing phase and its outcomes. Reflect on the methods used.

    "},{"location":"resources/data_processing/#references","title":"References","text":"

    Citations of tools, data sources, and other references used in the data processing phase.

    "},{"location":"resources/docker_basics/","title":"Docker Basics","text":""},{"location":"resources/docker_basics/#what-is-docker","title":"What is Docker?","text":"

    Docker is a containerization platform that enables you to package your applications along with their dependencies into self-contained units called containers. Containers provide a consistent and portable runtime environment, making it easy to develop, test, and deploy applications across different machines.

    "},{"location":"resources/docker_basics/#key-concepts","title":"Key Concepts","text":""},{"location":"resources/docker_basics/#images","title":"Images","text":"

    A blueprint for a Docker container. Images are read-only and contain all the necessary code, libraries, and configurations for an application.

    "},{"location":"resources/docker_basics/#containers","title":"Containers","text":"

    A running instance of a Docker image. Containers are isolated from each other and the host system.

    "},{"location":"resources/docker_basics/#dockerfile","title":"Dockerfile","text":"

    A text file that defines the instructions needed to build a Docker image.

    "},{"location":"resources/docker_basics/#building-a-jupyterlab-docker-image-using-github-actions","title":"Building a jupyterlab Docker Image using GitHub Actions","text":""},{"location":"resources/docker_basics/#create-a-dockerfile","title":"Create a Dockerfile","text":"

    Create a new directory and Dockerfile within the project docker directory. Since this will be jupyterlab image, we will call the directory jupyterlab.

    FROM jupyter/r-notebook:hub-4.0.1 \n\nUSER root\n\n# Set up package manager\nRUN apt-get install -y apt-transport-https && \\\n    apt-get clean && apt-get update && apt-get install -y software-properties-common && \\\n    add-apt-repository multiverse && \\\n    apt-get clean && rm -rf /var/lib/apt/lists/*\n\n# Install some base software\nRUN apt-get update --yes && \\\n    apt-get install --yes \\\n    fonts-dejavu \\\n    unixodbc \\\n    unixodbc-dev \\\n    r-base \\\n    r-cran-rodbc && \\\n    apt-get clean && rm -rf /var/lib/apt/lists/*\n\n# Add sudo to jovyan user\nRUN apt update && \\\n    apt install -y sudo && \\\n    apt clean && \\\n    rm -rf /var/lib/apt/lists/*\n\n# This is where we can control which root permissions the jovyan user will have\nARG PRIV_CMDS='/bin/ch*,/bin/cat,/bin/gunzip,/bin/tar,/bin/mkdir,/bin/ps,/bin/mv,/bin/cp,/usr/bin/apt*,/usr/bin/pip*,/bin/yum,/opt,/opt/conda/bin/*,/usr/bin/*'\n\nRUN usermod -aG sudo jovyan && \\\n    echo \"$LOCAL_USER ALL=NOPASSWD: $PRIV_CMDS\" >> /etc/sudoers\nRUN addgroup jovyan\nRUN usermod -aG jovyan jovyan\n\n# Install RStudio\nRUN apt-get update && apt-get install --yes gdebi-core && \\\n    wget https://download2.rstudio.org/server/jammy/amd64/rstudio-server-2023.09.1-494-amd64.deb && \\\n    gdebi -n rstudio-server-2023.09.1-494-amd64.deb && \\\n    rm rstudio-server-2023.09.1-494-amd64.deb && \\\n    apt-get clean && rm -rf /var/lib/apt/lists/*\n\n# Install Geospatial libraries\nRUN apt-get update && \\\n    apt install -y \\\n    gdal-bin \\\n    lbzip2 \\\n    libfftw3-dev \\\n    libgdal-dev \\\n    libgeos-dev \\\n    libgsl0-dev \\\n    libgl1-mesa-dev \\\n    libglu1-mesa-dev \\\n    libhdf4-alt-dev \\\n    libhdf5-dev \\\n    libjq-dev \\\n    libpq-dev \\\n    libproj-dev \\\n    libprotobuf-dev \\\n    libnetcdf-dev \\\n    libsqlite3-dev \\\n    libudunits2-dev \\\n    lsb-release \\\n    netcdf-bin \\\n    postgis \\\n    protobuf-compiler \\\n    sqlite3 \\\n    tk-dev \\\n    libfmt-dev \\\n    unixodbc-dev && \\\n    apt-get clean && rm -rf /var/lib/apt/lists/*\n\n# Fix RStudio / Conda openssl version mismatch\nRUN wget https://www.openssl.org/source/openssl-3.2.0.tar.gz && \\\n    tar xfz openssl-3.2.0.tar.gz && \\\n    mkdir openssl-build && cd openssl-build && \\\n    ../openssl-3.2.0/Configure --libdir=/lib/x86_64-linux-gnu/ && \\\n    make && \\\n    make install\n\n# Update permissions for /opt/conda\nRUN mkdir /usr/local/bin/start-notebook.d && \\\n    chown -R jovyan:users /opt/conda/share /usr/local/share /usr/local/bin/start-notebook.d \n\nUSER jovyan\n\n# Install jupyterlab and rstudio dependencies\nRUN conda install -c conda-forge \\ \n    jupyter_client \\ \n    jupyter_core \\ \n    jupyterlab_server \\ \n    jupyter_server \\\n    r-rgl \\\n    r-htmlwidgets \\\n    r-htmltools && \\ \n    jupyter lab clean\n\n# reinstall R packages. Here is where you add any new R packages you would like to install \nRUN mamba install --quiet --yes \\\n    r-base \\\n    r-tidyverse \\\n    r-terra \\\n    r-future \\\n    r-future.apply \\\n    r-furrr \\\n    && \\ \n    mamba clean --all -f -y\n\n# Install Jupyter Lab Proxy extensions (cards in Launcher)\nRUN pip install jupyter-rsession-proxy jupyter-server-proxy jupyter-shiny-proxy jupyterlab-git \n\n# Install Mamba Gator package manager\nRUN rm -f ~/.jupyter/lab/workspaces/default* && \\\n    mamba install -y -c conda-forge mamba_gator\n\n# Install and configure jupyter lab \nCOPY jupyter_notebook_config.json /opt/conda/etc/jupyter/jupyter_notebook_config.json\n\n# Rebuild the Jupyter Lab with new tools\nRUN jupyter lab build\n\n# Build Conda environment. Any packages you would like to install with conda need to be added to the environment.yml file in this Dockerfiles directory\nRUN conda update -y conda && \\\n    conda config --remove channels conda-forge && \\\n    conda config --add channels conda-forge\nWORKDIR /home/jovyan\nCOPY environment.yml /home/jovyan/ \nRUN mamba env create -f /home/jovyan/environment.yml\nRUN . /opt/conda/etc/profile.d/conda.sh && conda deactivate && conda activate custom && python -m ipykernel install --name custom && pip install jupyter_contrib_nbextensions\n\n# Install R packages from CRAN and GitHub\nRUN R -e \"remotes::install_github('tomroh/ecoregions')\"\nRUN R -e \"install.packages('mblm', repos='http://cran.rstudio.com/')\"\n\n# Set any required environment variables \nENV PROJ_LIB=/opt/conda/envs/custom/share/proj\nRUN echo \"PROJ_LIB=/opt/conda/envs/custom/share/proj\" > /home/jovyan/.Renviron\n

    There are many things going on in the Dockerfile above. Most of the lines, however, are just Linux commands you would run from a terminal when provisioning a new VM. Each block of code is commented with what it accomplishes.

    "},{"location":"resources/docker_basics/#add-any-necessary-files","title":"Add any necessary files","text":"

    The Dockerfile above uses a file called environment.yml to provision the its conda environment and a jupyter_config_notebook.json file to configure the jupyterlab server. Both of these files will need to be added to the docker/jupyterlab directory at the same level as the Dockerfile. You can view the content of these files in this repository.

    "},{"location":"resources/docker_basics/#create-the-github-actions-workflow-file","title":"Create the GitHub actions workflow file","text":"

    Workflow files specify when and how code is executed in a GitHub Actions workflow. Actions can be triggered automatically, such as when a commit is pushed to a repo or a specific file, or they can be triggered manually. The following workflow is defined so that the Action is triggered manually. Actions can also be run on different VM types. The following Action will be run on the latest Ubuntu image. 

    name: build-and-push-jupyterlab-image\n\non:\n  workflow_dispatch:  # This allows you to manually trigger the action from GitHub UI.\n\njobs:\n\n  build:\n    runs-on: ubuntu-latest\n\n    steps:\n\n      - name: Checkout\n        uses: actions/checkout@v3.5.0\n\n      - name: Set up Docker Buildx\n        id: buildx\n        uses: docker/setup-buildx-action@v2.5.0\n\n      - name: Login to dockerhub \n        uses: docker/login-action@v2.1.0\n        with:\n          username: ${{ secrets.DOCKERHUB_USERNAME }}\n          password: ${{ secrets.DOCKERHUB_PASSWORD }}\n\n      - name: Get lowercase repo name (for dynamic tags)\n        id: repo_name  \n        run: |\n          lowercase_name=$(echo ${{ github.event.repository.name }} | tr '[:upper:]' '[:lower:]')\n          echo \"::set-output name=repo_name::${lowercase_name}\"\n\n      - name: Build and push latest\n        id: docker_build_jupyterlab\n        uses: docker/build-push-action@v4.0.0\n        with:\n          context: docker/jupyterlab\n          file: docker/jupyterlab/Dockerfile\n          builder: ${{ steps.buildx.outputs.name }}\n          push: true\n          tags: |\n            esiil/${{ steps.repo_name.outputs.repo_name }}_jupyterlab:latest\n\n      - name: Image digest\n        run: echo ${{ steps.docker_build.outputs.digest }}\n

    The steps section of the file defines what will be run by the Action. An overview of the steps of this file is as follows: Checkout the repository code, setup Docker buildx, login to DockerHub, resolve the name of the current GitHub reposiroy, build and push the Docker Image to DockerHub.

    "},{"location":"resources/docker_basics/#running-the-action","title":"Running the Action","text":"

    From your repositories GitHub page, click on the Actions tab

    Find the workflow in the Workflow navigation menu and click on it

    Click on the run workflow dropdown and click Run Workflow

    "},{"location":"resources/docker_basics/#deploying-the-image-on-cyverse","title":"Deploying the Image on CyVerse","text":"

    First go to de.cyverse.org and login. From there go to the Apps dashboard and click on Manage Tools.

    "},{"location":"resources/docker_basics/#adding-the-image-as-a-tool","title":"Adding the Image as a Tool","text":"

    Then click Add Tool.

    Give the Tool a descriptive name and set the initial version. The version can be whatever you like but 1.0 makes the most sense.

    Set the Image Name to esiil/name_of_your_image and the tag to whichever tag you would like the Tool to use. Most Tools will use the latest tag.

    You can see all of this information on the ESIIL dockerhub page.

    Leave the Entrypoint blank, and set the working directory to /home/jovyan/data-store and the UID to 1000. Add container port 8888. This will mount and give you access to the cyverse data store. Because the file explorer GUI will not let you go above the working directory that is set, you will have to use the terminal to go up one directory and copy over any files you included in your container.

    Leave all of the restrictions blank and then save the Tool

    "},{"location":"resources/docker_basics/#associating-the-tool-with-an-app","title":"Associating the Tool with an App","text":"

    Go back to the Apps dashboard and click create

    Just like for the Tool, give a descriptive name and description

    For \"Tool used\" click select and then search for the name of the tool that was just added and then click on its row and then select at the bottom.

    From the app creation screen click Next, and then click next through the next steps until you get to completion. From there click Save and Launch

    From there you can go through the deployment of your app like you would deploy any other app on CyVerse and test it out.

    "},{"location":"resources/first_meeting_notes/","title":"Primary Meeting 1","text":""},{"location":"resources/first_meeting_notes/#day-1-5-project-kickoff-and-strategy","title":"Day 1-5: Project Kickoff and Strategy","text":""},{"location":"resources/first_meeting_notes/#meeting-details","title":"Meeting Details","text":"
    • Dates:
    • Times:
    • Location:
    • Facilitator:
    "},{"location":"resources/first_meeting_notes/#attendees","title":"Attendees","text":"
    • List of attendees
    "},{"location":"resources/first_meeting_notes/#daily-agenda","title":"Daily Agenda","text":""},{"location":"resources/first_meeting_notes/#day-1-setting-the-stage","title":"Day 1: Setting the Stage","text":""},{"location":"resources/first_meeting_notes/#opening-remarks","title":"Opening Remarks","text":"
    • Welcoming speech and outline of the week's objectives.
    "},{"location":"resources/first_meeting_notes/#project-overview","title":"Project Overview","text":"
    • Presentation of the project goals and significance.
    "},{"location":"resources/first_meeting_notes/#theoretical-framework","title":"Theoretical Framework","text":"
    • Discussion on the theoretical underpinnings of the project.
    "},{"location":"resources/first_meeting_notes/#data-overview","title":"Data Overview","text":"
    • Review available data and any gaps that need addressing.
    "},{"location":"resources/first_meeting_notes/#day-2-4-deep-dives","title":"Day 2-4: Deep Dives","text":""},{"location":"resources/first_meeting_notes/#daily-goals","title":"Daily Goals","text":"
    • Outline specific goals for each day.
    "},{"location":"resources/first_meeting_notes/#task-assignments","title":"Task Assignments","text":"
    • Assign tasks and areas of responsibility to team members.
    "},{"location":"resources/first_meeting_notes/#theory-and-data-synthesis","title":"Theory and Data Synthesis","text":"
    • Host focused discussions on how theory will inform data analysis.
    • Explore different methodological approaches and data integration strategies.
    "},{"location":"resources/first_meeting_notes/#evening-social-and-soft-work-sessions","title":"Evening Social and Soft Work Sessions","text":"
    • Casual gatherings to further discuss ideas and foster team bonding.
    "},{"location":"resources/first_meeting_notes/#day-5-roadmap-and-closure","title":"Day 5: Roadmap and Closure","text":""},{"location":"resources/first_meeting_notes/#project-roadmap","title":"Project Roadmap","text":"
    • Draft a detailed plan of action for the project going forward.
    "},{"location":"resources/first_meeting_notes/#responsibilities","title":"Responsibilities","text":"
    • Confirm individual responsibilities and deadlines.
    "},{"location":"resources/first_meeting_notes/#review-and-feedback","title":"Review and Feedback","text":"
    • Reflect on the week's discussions and adjust the project plan as needed.
    "},{"location":"resources/first_meeting_notes/#closing-remarks","title":"Closing Remarks","text":"
    • Summarize achievements and express appreciation for the team's efforts.
    "},{"location":"resources/first_meeting_notes/#detailed-notes","title":"Detailed Notes","text":""},{"location":"resources/first_meeting_notes/#day-1-notes","title":"Day 1 Notes","text":"
    • Summary of discussions, decisions, and key points.
    "},{"location":"resources/first_meeting_notes/#day-2-notes","title":"Day 2 Notes","text":"
    • ...
    "},{"location":"resources/first_meeting_notes/#day-3-notes","title":"Day 3 Notes","text":"
    • ...
    "},{"location":"resources/first_meeting_notes/#day-4-notes","title":"Day 4 Notes","text":"
    • ...
    "},{"location":"resources/first_meeting_notes/#day-5-notes","title":"Day 5 Notes","text":"
    • ...
    "},{"location":"resources/first_meeting_notes/#action-items","title":"Action Items","text":"
    • [ ] Specific task: Assigned to - Deadline
    • [ ] Specific task: Assigned to - Deadline
    • ...
    "},{"location":"resources/first_meeting_notes/#reflections-and-comments","title":"Reflections and Comments","text":"
    • (Space for any additional thoughts, insights, or personal reflections on the meeting.)
    "},{"location":"resources/first_meeting_notes/#next-steps","title":"Next Steps","text":"
    • Schedule for follow-up meetings or checkpoints.
    • Outline of expected progress before the next primary meeting.
    "},{"location":"resources/first_meeting_notes/#additional-documentation","title":"Additional Documentation","text":"
    • (Include or link to any additional documents, charts, or resources that were created or referenced during the meeting.)
    "},{"location":"resources/github_basics/","title":"Github essentials","text":""},{"location":"resources/github_basics/#i-introduction-2-minutes","title":"I. Introduction (2 minutes)","text":""},{"location":"resources/github_basics/#a-brief-overview-of-github","title":"A. Brief overview of GitHub:","text":"

    GitHub is a web-based platform that provides version control and collaboration features using Git, a distributed version control system. It enables developers to work together on projects, track changes to code, and efficiently manage different versions of the project. GitHub is widely used in the software development industry and is an essential tool for collaborative projects and maintaining code quality.

    "},{"location":"resources/github_basics/#b-introduce-github-desktop-and-jupyterhub-github-widget","title":"B. Introduce GitHub Desktop and JupyterHub GitHub widget:","text":"

    GitHub Desktop is a graphical user interface (GUI) application that simplifies working with Git and GitHub by providing a more visual and intuitive way to manage repositories, branches, commits, and other Git features. JupyterHub GitHub widget, on the other hand, is a built-in widget that integrates Git and GitHub functionality directly into Jupyter notebooks, allowing users to perform version control and collaboration tasks within the Jupyter environment. Both tools help streamline the process of working with GitHub and make it more accessible to users with varying levels of experience with Git and version control.

    "},{"location":"resources/github_basics/#1-download-github-desktop","title":"1. Download GitHub Desktop","text":""},{"location":"resources/github_basics/#step-1-download-github-desktop","title":"Step 1: Download GitHub Desktop","text":"

    Go to the GitHub Desktop download page: https://desktop.github.com/

    Click on the \u201cDownload for Windows\u201d or \u201cDownload for macOS\u201d button, depending on your operating system. The download should start automatically.

    "},{"location":"resources/github_basics/#step-2-install-github-desktop","title":"Step 2: Install GitHub Desktop","text":"

    For Windows:

    Locate the downloaded installer file (usually in the Downloads folder) and double-click on it to run the installer.

    Follow the installation instructions that appear on the screen, accepting the default settings or customizing them as desired.

    Once the installation is complete, GitHub Desktop will launch automatically. For macOS:

    Locate the downloaded .zip file (usually in the Downloads folder) and double-click on it to extract the GitHub Desktop application.

    Drag the extracted \u201cGitHub Desktop\u201d application into the \u201cApplications\u201d folder.

    Open the \u201cApplications\u201d folder and double-click on \u201cGitHub Desktop\u201d to launch the application.

    "},{"location":"resources/github_basics/#step-3-set-up-github-desktop","title":"Step 3: Set up GitHub Desktop","text":"

    When GitHub Desktop launches for the first time, you will be prompted to sign in with your GitHub account. If you don\u2019t have one, you can create one at https://github.com/join.

    Enter your GitHub username (or email) and password, and click on \u201cSign in.\u201d

    You will then be prompted to configure Git. Enter your name and email address, which will be used for your commit messages. Click \u201cContinue\u201d when you\u2019re done. Choose whether you want to submit usage data to help improve GitHub Desktop. Click \u201cFinish\u201d to complete the setup.

    Now, you have successfully installed and set up GitHub Desktop. You can start using it to clone repositories, make changes, commit, and sync with the remote repositories on GitHub.

    "},{"location":"resources/github_basics/#1-download-github-for-jupyterhub-cloud-service","title":"1. Download GitHub for JupyterHub cloud service","text":""},{"location":"resources/github_basics/#step-1-accessing-jupyterhub-on-the-cloud","title":"Step 1: Accessing JupyterHub on the cloud","text":"

    Visit the JupyterHub cloud service you want to use (e.g., Binder, Google Colab, or a custom JupyterHub deployment provided by your organization).

    Sign in with your credentials or authenticate using a third-party service if required.

    "},{"location":"resources/github_basics/#step-2-launch-a-new-jupyter-notebook-or-open-an-existing-one","title":"Step 2: Launch a new Jupyter Notebook or open an existing one","text":"

    Click on the \u201cNew\u201d button (usually located in the top right corner) and select \u201cPython\u201d to create a new Jupyter Notebook or open an existing one from the file browser.

    Once the notebook is open, you will see the Jupyter Notebook interface with the familiar cells for writing and executing code.

    "},{"location":"resources/github_basics/#step-3-install-and-enable-the-jupyterlab-git-extension","title":"Step 3: Install and enable the JupyterLab Git extension","text":"

    In your Jupyter Notebook, create a new code cell and run the following command to install the JupyterLab Git extension:

    !pip install jupyterlab-git

    Restart the Jupyter Notebook server for the changes to take effect.

    "},{"location":"resources/github_basics/#step-4-using-the-jupyterhub-github-widget","title":"Step 4: Using the JupyterHub GitHub widget","text":"

    In the Jupyter Notebook interface, you should now see a Git icon on the left sidebar. Click on it to open the GitHub widget.

    To clone a repository, click on the \u201c+\u201d icon in the GitHub widget and enter the repository URL. This will clone the repository into your JupyterHub workspace. You can now navigate through the cloned repository, make changes, and use the GitHub widget to stage, commit, and push your changes back to the remote repository.

    To create and manage branches, use the branch icon in the GitHub widget. You can create new branches, switch between branches, and merge branches using this interface.

    To sync your local repository with the remote repository, use the \u201cPull\u201d and \u201cPush\u201d buttons in the GitHub widget.

    Now, you know how to access and use the JupyterHub GitHub widget running on the cloud. This allows you to work with Git and GitHub directly from your Jupyter Notebook interface, streamlining your workflow and making collaboration easier.

    "},{"location":"resources/github_basics/#c-github-in-rstudio","title":"C. GitHub in Rstudio:","text":"

    Integrating GitHub with RStudio allows users to manage their Git repositories and collaborate on projects directly within the RStudio environment. It offers similar functionality to GitHub Desktop but caters specifically to R users working within RStudio. By configuring RStudio to work with Git, creating or opening RStudio projects, and linking projects to GitHub repositories, users can enjoy a seamless workflow for version control and collaboration. RStudio\u2019s Git pane enables users to stage, commit, and push changes to remote repositories, as well as manage branches and sync local repositories with remote ones, providing a comprehensive solution for R developers working with GitHub.

    "},{"location":"resources/github_basics/#step-1-install-git","title":"Step 1: Install Git","text":"

    Before integrating GitHub with RStudio, you need to have Git installed on your computer. Visit the official Git website (https://git-scm.com/) to download and install the latest version of Git for your operating system.

    "},{"location":"resources/github_basics/#step-2-configure-rstudio-to-work-with-git","title":"Step 2: Configure RStudio to work with Git","text":"

    Open RStudio.

    Go to \u201cTools\u201d > \u201cGlobal Options\u201d in the top menu. In the \u201cGlobal Options\u201d window, click on the \u201cGit/SVN\u201d tab.

    Check that the \u201cGit executable\u201d field is pointing to the correct location of the installed Git. If not, click \u201cBrowse\u201d and navigate to the location of the Git executable file (usually found in the \u201cbin\u201d folder of the Git installation directory).

    Click \u201cOK\u201d to save the changes.

    "},{"location":"resources/github_basics/#step-3-create-or-open-an-rstudio-project","title":"Step 3: Create or open an RStudio project","text":"

    To create a new RStudio project, go to \u201cFile\u201d > \u201cNew Project\u201d in the top menu. You can either create a new directory or choose an existing one for your project.

    To open an existing RStudio project, go to \u201cFile\u201d > \u201cOpen Project\u201d and navigate to the project\u2019s \u201c.Rproj\u201d file.

    "},{"location":"resources/github_basics/#step-4-link-your-rstudio-project-to-a-github-repository","title":"Step 4: Link your RStudio project to a GitHub repository","text":"

    In the RStudio project, go to the \u201cTools\u201d menu and select \u201cVersion Control\u201d > \u201cProject Setup.\u201d

    In the \u201cProject Setup\u201d window, select \u201cGit\u201d as the version control system and click \u201cOK.\u201d

    A new \u201c.git\u201d folder will be created in your project directory, initializing it as a Git repository. Commit any changes you have made so far by clicking on the \u201cCommit\u201d button in the \u201cGit\u201d pane in RStudio.

    To link your local repository to a remote GitHub repository, go to your GitHub account and create a new repository.

    Copy the remote repository\u2019s URL (e.g., \u201chttps://github.com/username/repository.git\u201d).

    In RStudio, open the \u201cShell\u201d by going to \u201cTools\u201d > \u201cShell.\u201d

    In the shell, run the following command to add the remote repository:

    git remote add origin https://github.com/username/repository.git

    Replace the URL with the one you copied from your GitHub repository.

    Push your changes to the remote repository by running the following command in the shell:

    git push -u origin master

    Now, your RStudio project is linked to a GitHub repository. You can use the \u201cGit\u201d pane in RStudio to stage, commit, and push changes to the remote repository, as well as manage branches and sync your local repository with the remote one.

    By integrating GitHub with RStudio, you can streamline your workflow, collaborate more effectively with your team, and manage your Git repositories directly from the RStudio interface.

    "},{"location":"resources/github_basics/#ii-github-basics-4-minutes","title":"II. GitHub Basics (4 minutes)","text":""},{"location":"resources/github_basics/#a-repository","title":"A. Repository:","text":"

    A repository, often abbreviated as \u201crepo,\u201d is the fundamental building block of GitHub. It is a storage space for your project files, including the code, documentation, and other related resources. Each repository also contains the complete history of all changes made to the project files, which is crucial for effective version control. Repositories can be public, allowing anyone to access and contribute, or private, restricting access to specific collaborators.

    "},{"location":"resources/github_basics/#b-fork-and-clone","title":"B. Fork and Clone:","text":"

    Forking and cloning are two essential operations for working with repositories on GitHub. Forking creates a personal copy of someone else\u2019s repository under your GitHub account, enabling you to make changes to the project without affecting the original repo. Cloning, on the other hand, is the process of downloading a remote repository to your local machine for offline development. In GitHub Desktop, you can clone a repository by selecting \u201cClone a repository from the Internet\u201d and entering the repository URL. In JupyterHub GitHub widget, you can clone a repository by entering the repo URL in the \u201cClone Repository\u201d section of the widget.

    "},{"location":"resources/github_basics/#c-branches","title":"C. Branches:","text":"

    Branches are a critical aspect of Git version control, as they allow you to create multiple parallel versions of your project within a single repository. This is particularly useful when working on new features or bug fixes, as it prevents changes from interfering with the main (or \u201cmaster\u201d) branch until they are ready to be merged. Creating a new branch in GitHub Desktop can be done by clicking the \u201cCurrent Branch\u201d dropdown and selecting \u201cNew Branch.\u201d In JupyterHub GitHub widget, you can create a new branch by clicking the \u201cNew Branch\u201d button in the \u201cBranches\u201d section of the widget.

    "},{"location":"resources/github_basics/#d-replace-master-with-main","title":"D. Replace \u2018master\u2019 with \u2018main\u2019:","text":"

    In recent years, there has been a growing awareness of the importance of inclusive language in technology. One such example is the use of the term \u201cmaster\u201d in the context of the default branch in a GitHub repository. The term \u201cmaster\u201d has historical connections to the \u201cmaster/slave\u201d file structure, which evokes an unsavory colonial past associated with slavery. In light of this, many developers and organizations have begun to replace the term \u201cmaster\u201d with more neutral terms, such as \u201cmain.\u201d We encourage you to follow this practice and change the default branch name in your repositories from \u201cmaster\u201d to \u201cmain\u201d or another suitable alternative. This small change can help promote a more inclusive and welcoming environment within the technology community.

    "},{"location":"resources/github_basics/#iii-collaboration-and-version-control-5-minutes","title":"III. Collaboration and Version Control (5 minutes)","text":""},{"location":"resources/github_basics/#a-commits","title":"A. Commits:","text":"

    Commits are snapshots of your project\u2019s changes at a specific point in time, serving as the fundamental building blocks of Git\u2019s version control system. Commits make it possible to track changes, revert to previous versions, and collaborate with others. In GitHub Desktop, you can make a commit by staging the changes you want to include, adding a descriptive commit message, and clicking \u201cCommit to [branch_name].\u201d In JupyterHub GitHub widget, you can create a commit by selecting the files with changes, entering a commit message, and clicking the \u201cCommit\u201d button.

    "},{"location":"resources/github_basics/#b-push","title":"B. Push:","text":"

    In GitHub, \u201cpush\u201d is a fundamental operation in the version control process that transfers commits from your local repository to a remote repository, such as the one hosted on GitHub. When you push changes, you synchronize the remote repository with the latest updates made to your local repository, making those changes accessible to other collaborators working on the same project. This operation ensures that the remote repository reflects the most recent state of your work and allows your team members to stay up to date with your changes. Pushing is an essential step in distributed version control systems like Git, as it promotes efficient collaboration among multiple contributors and provides a centralized location for tracking the project\u2019s history and progress.

    In GitHub, the concepts of \u201ccommit\u201d and \u201cpush\u201d represent two distinct steps in the version control process. A \u201ccommit\u201d is the action of saving changes to your local repository. When you commit changes, you create a snapshot of your work, accompanied by a unique identifier and an optional descriptive message. Commits allow you to track the progress of your work over time and make it easy to revert to a previous state if necessary. On the other hand, \u201cpush\u201d is the action of transferring your local commits to a remote repository, such as the one hosted on GitHub. Pushing makes your changes accessible to others collaborating on the same project and ensures that the remote repository stays up to date with your local repository. In summary, committing saves changes locally, while pushing synchronizes those changes with a remote repository, allowing for seamless collaboration among multiple contributors.

    "},{"location":"resources/github_basics/#c-pull-requests","title":"C. Pull Requests:","text":"

    Pull requests are a collaboration feature on GitHub that enables developers to propose changes to a repository, discuss those changes, and ultimately merge them into the main branch. To create a pull request, you must first push your changes to a branch on your fork of the repository. Then, using either GitHub Desktop or JupyterHub GitHub widget, you can navigate to the original repository, click the \u201cPull Request\u201d tab, and create a new pull request. After the pull request is reviewed and approved, it can be merged into the main branch.

    "},{"location":"resources/github_basics/#d-merging-and-resolving-conflicts","title":"D. Merging and Resolving Conflicts:","text":"

    Merging is the process of combining changes from one branch into another. This is typically done when a feature or bugfix has been completed and is ready to be integrated into the main branch. Conflicts can arise during the merging process if the same lines of code have been modified in both branches. To resolve conflicts, you must manually review the changes and decide which version to keep. In GitHub Desktop, you can merge branches by selecting the target branch and choosing \u201cMerge into Current Branch.\u201d Conflicts will be highlighted, and you can edit the files to resolve them before committing the changes. In JupyterHub GitHub widget, you can merge branches by selecting the target branch in the \u201cBranches\u201d section and clicking the \u201cMerge\u201d button. If conflicts occur, the widget will prompt you to resolve them before completing the merge.

    "},{"location":"resources/github_basics/#iv-additional-features-2-minutes","title":"IV. Additional Features (2 minutes)","text":""},{"location":"resources/github_basics/#a-issues-and-project-management","title":"A. Issues and Project Management:","text":"

    Issues are a powerful feature in GitHub that allows developers to track and manage bugs, enhancements, and other tasks within a project. Issues can be assigned to collaborators, labeled for easy organization, and linked to specific commits or pull requests. They provide a centralized location for discussing and addressing project-related concerns, fostering collaboration and transparent communication among team members. Using issues effectively can significantly improve the overall management and organization of your projects.

    "},{"location":"resources/github_basics/#b-github-pages","title":"B. GitHub Pages:","text":"

    GitHub Pages is a service offered by GitHub that allows you to host static websites directly from a repository. By creating a new branch named \u201cgh-pages\u201d in your repository and adding the necessary files (HTML, CSS, JavaScript, etc.), GitHub will automatically build and deploy your website to a publicly accessible URL. This is particularly useful for showcasing project documentation, creating personal portfolios, or hosting project demos. With GitHub Pages, you can take advantage of the version control and collaboration features of GitHub while easily sharing your work with others.

    "},{"location":"resources/github_basics/#v-conclusion-2-minutes","title":"V. Conclusion (2 minutes)","text":""},{"location":"resources/github_basics/#a-recap-of-the-essentials-of-github","title":"A. Recap of the essentials of GitHub:","text":"

    In this brief introduction, we have covered the essentials of GitHub, including the basics of repositories, forking, cloning, branching, commits, pull requests, merging, and resolving conflicts. We have also discussed additional features like issues for project management and GitHub Pages for hosting websites directly from a repository.

    "},{"location":"resources/github_basics/#b-encourage-further-exploration-and-learning","title":"B. Encourage further exploration and learning:","text":"

    While this introduction provides a solid foundation for understanding and using GitHub, there is still much more to learn and explore. As you continue to use GitHub in your projects, you will discover new features and workflows that can enhance your productivity and collaboration. We encourage you to dive deeper into the platform and experiment with different tools and techniques.

    "},{"location":"resources/github_basics/#c-share-resources-for-learning-more-about-github","title":"C. Share resources for learning more about GitHub:","text":"

    There are many resources available for learning more about GitHub and expanding your skills. Some popular resources include GitHub Guides (https://guides.github.com/), which offers a collection of tutorials and best practices, the official GitHub documentation (https://docs.github.com/), and various online tutorials and courses. By engaging with these resources and participating in the GitHub community, you can further develop your understanding of the platform and become a more proficient user.

    "},{"location":"resources/github_basics/#v-conclusion-2-minutes_1","title":"V. Conclusion (2 minutes)","text":""},{"location":"resources/github_basics/#a-recap-of-the-essentials-of-github_1","title":"A. Recap of the essentials of GitHub:","text":"

    In this brief introduction, we have covered the essentials of GitHub, including the basics of repositories, forking, cloning, branching, commits, pull requests, merging, and resolving conflicts. We have also discussed additional features like issues for project management and GitHub Pages for hosting websites directly from a repository.

    "},{"location":"resources/github_basics/#b-encourage-further-exploration-and-learning_1","title":"B. Encourage further exploration and learning:","text":"

    While this introduction provides a solid foundation for understanding and using GitHub, there is still much more to learn and explore. As you continue to use GitHub in your projects, you will discover new features and workflows that can enhance your productivity and collaboration. We encourage you to dive deeper into the platform and experiment with different tools and techniques.

    "},{"location":"resources/github_basics/#c-share-resources-for-learning-more-about-github_1","title":"C. Share resources for learning more about GitHub:","text":"

    There are many resources available for learning more about GitHub and expanding your skills. Some popular resources include GitHub Guides (https://guides.github.com/), which offers a collection of tutorials and best practices, the official GitHub documentation (https://docs.github.com/), and various online tutorials and courses. By engaging with these resources and participating in the GitHub community, you can further develop your understanding of the platform and become a more proficient user.

    "},{"location":"resources/manuscript/","title":"Manuscript Title","text":""},{"location":"resources/manuscript/#authors","title":"Authors","text":"
    • Author 1, Affiliation
    • Author 2, Affiliation
    • ...
    "},{"location":"resources/manuscript/#abstract","title":"Abstract","text":"
    • A brief summary of the research, its objectives, main findings, and conclusions.
    "},{"location":"resources/manuscript/#introduction","title":"Introduction","text":"
    • Background information and context setting for the research.
    • Statement of the problem and research objectives.
    • Overview of the methodology and approach.
    "},{"location":"resources/manuscript/#literature-review","title":"Literature Review","text":"
    • Discussion of relevant previous work and how this research contributes to the field.
    "},{"location":"resources/manuscript/#methodology","title":"Methodology","text":"
    • Detailed description of the research methodology.
    • Explanation of data collection and analysis techniques.
    • Justification for methodological choices.
    "},{"location":"resources/manuscript/#results","title":"Results","text":"
    • Presentation of the research findings.
    • Use of tables, graphs, and figures to illustrate key points.
    • Analysis and interpretation of the results.
    "},{"location":"resources/manuscript/#discussion","title":"Discussion","text":"
    • Discussion of the implications of the findings.
    • Comparison with previous research in the field.
    • Consideration of the limitations of the study.
    "},{"location":"resources/manuscript/#conclusion","title":"Conclusion","text":"
    • Summary of the main findings.
    • Reflection on the research's significance and potential impact.
    • Suggestions for future research directions.
    "},{"location":"resources/manuscript/#acknowledgements","title":"Acknowledgements","text":"
    • Acknowledgement of any assistance, funding, or contributions from others.
    "},{"location":"resources/manuscript/#references","title":"References","text":"
    • Bibliographic details of the cited works.
    • Use a consistent citation style throughout.
    "},{"location":"resources/manuscript/#appendices","title":"Appendices","text":"
    • Additional material that supports the manuscript but is too detailed for the main sections.
    "},{"location":"resources/markdown_basics/","title":"Markdown for the Modern Researcher at ESIIL","text":""},{"location":"resources/markdown_basics/#introduction","title":"Introduction","text":"
    • Overview of Markdown's relevance and utility in modern research.
    • How Markdown streamlines documentation in diverse scientific and coding environments.
    "},{"location":"resources/markdown_basics/#section-1-mastering-markdown-syntax","title":"Section 1: Mastering Markdown Syntax","text":"
    • Objective: Equip researchers with a thorough understanding of Markdown syntax and its diverse applications.
    • Topics Covered:
    • Fundamentals of Text Formatting (headings, lists, bold, italics)
    • Advanced Structures (tables, blockquotes)
    • Integrating Multimedia (image and video links)
    • Diagrams with Mermaid (creating flowcharts, mind maps, timelines)
    • Interactive Elements (hyperlinks, embedding interactive content)
    • Activities:
    • Crafting a Markdown document with various formatting elements.
    • Developing diagrams using Mermaid for research presentations.
    • Embedding multimedia elements in a Markdown document for enhanced communication.
    "},{"location":"resources/markdown_basics/#section-2-markdown-in-research-tools","title":"Section 2: Markdown in Research Tools","text":"
    • Objective: Showcase the integration of Markdown in RStudio and Jupyter Notebooks for scientific documentation.
    • Topics Covered:
    • Implementing Markdown in RStudio (R Markdown, knitting to HTML/PDF)
    • Utilizing Markdown in Jupyter Notebooks (code and Markdown cells)
    • Best practices for documenting research code
    • Including code outputs and visualizations in documentation
    • Activities:
    • Creating and sharing an R Markdown document with annotated research data.
    • Building a comprehensive Jupyter Notebook with integrated Markdown annotations.
    "},{"location":"resources/markdown_basics/#section-3-disseminating-research-with-markdown-and-github-pages","title":"Section 3: Disseminating Research with Markdown and GitHub Pages","text":"
    • Objective: Teach researchers how to publish and manage Markdown-based documentation as web pages.
    • Topics Covered:
    • Setting up a GitHub repository for hosting documentation
    • Transforming Markdown files into web-friendly formats
    • Customizing web page layouts and themes
    • Advanced features using Jekyll
    • Version control and content management for documentation
    • Activities:
    • Publishing a research project documentation on GitHub Pages.
    • Applying custom themes and layouts to enhance online documentation.
    "},{"location":"resources/markdown_basics/#conclusion","title":"Conclusion","text":"
    • Review of Markdown's role in enhancing research efficiency and clarity.
    • Encouraging the integration of Markdown into daily research activities for improved documentation and dissemination.
    "},{"location":"resources/markdown_basics/#additional-resources","title":"Additional Resources","text":"
    • Curated list of advanced Markdown tutorials, guides for GitHub Pages, and Jekyll resources for researchers.
    "},{"location":"resources/markdown_basics/#section-1-mastering-markdown-syntax_1","title":"Section 1: Mastering Markdown Syntax","text":""},{"location":"resources/markdown_basics/#1-fundamentals-of-text-formatting","title":"1. Fundamentals of Text Formatting","text":"
    • Headings: Use # for different levels of headings.

    • Lists: Bulleted lists use asterisks, numbers for ordered lists.

    • Item 1
    • Item 2
      • Subitem 2.1
      • Subitem 2.2
      1. First item
      1. Second item

    • Bold and Italics: Use asterisks or underscores.

    • Bold Text
    • Italic Text
    "},{"location":"resources/markdown_basics/#heading-level-1","title":"Heading Level 1","text":""},{"location":"resources/markdown_basics/#heading-level-2","title":"Heading Level 2","text":""},{"location":"resources/markdown_basics/#heading-level-3","title":"Heading Level 3","text":""},{"location":"resources/markdown_basics/#2-advanced-structures","title":"2. Advanced Structures","text":"
    • Tables: Create tables using dashes and pipes.
    • Header 1 Header 2 Header 3 Row 1 Data Data Row 2 Data Data

    • Add a \":\"\" to change text justification. Here the : is added on the left for left justification. | Header 1 | Header 2 | Header 3 | |---------:|--------- |----------| | Row 1 | Data | Data | | Row 2 | Data | Data |

    • A N A L Y T I C S E N R E I N V I R O N M E N T V E L O P M O C O M U N E G A G E L L A H C N E R A T A D E V E L O P W E I T S I T N E I C S R S O I G O L O I B H T L A H T L A E W E G N E L T I T S I T N E I C S N I E E S R E H T O E N I C S L L A H C E G L A N E G A L L E H C N E I C

    • If you hit the boundaries of Markdown's capabilities, you can start to add html directly. Remember, this entire exercisse is to translate to html.

    Sudoku Puzzle Fill in the blank cells with numbers from 1 to 9, such that each row, column, and 3x3 subgrid contains all the numbers from 1 to 9 without repetition.

    5 3 7 6 1 9 5 9 8 6 8 6 3 4 8 3 1 7 2 6 6 2 8 4 1 9 5 8 7 9 534678912 672195348 198342567 859761423 426853791 713924856 961537284 287419635 345286179
    • Blockquotes: Use > for blockquotes.

    • This is a blockquote.

    • It can span multiple lines.

    "},{"location":"resources/markdown_basics/#3-integrating-multimedia","title":"3. Integrating Multimedia","text":"
    • Images: Add images using the format ![alt text](image_url).

    • Videos: Embed videos using HTML in Markdown.

    • <iframe width=\"560\" height=\"315\" src=\"https://www.youtube.com/embed/dQw4w9WgXcQ\" frameborder=\"0\" allowfullscreen></iframe>
    "},{"location":"resources/markdown_basics/#4-diagrams-with-mermaid","title":"4. Diagrams with Mermaid","text":"
    • Flowcharts:
        graph TD\n    A[Start] --> B[Analyze Data]\n    B --> C{Is Data Large?}\n    C -->|Yes| D[Apply Big Data Solutions]\n    C -->|No| E[Use Traditional Methods]\n    D --> F[Machine Learning]\n    E --> G[Statistical Analysis]\n    F --> H{Model Accurate?}\n    G --> I[Report Results]\n    H -->|Yes| J[Deploy Model]\n    H -->|No| K[Refine Model]\n    J --> L[Monitor Performance]\n    K --> F\n    L --> M[End: Success]\n    I --> N[End: Report Generated]\n    style A fill:#f9f,stroke:#333,stroke-width:2px\n    style M fill:#9f9,stroke:#333,stroke-width:2px\n    style N fill:#9f9,stroke:#333,stroke-width:2px\n
    • Mind Maps:
        mindmap\n  root((ESIIL))\n    section Data Sources\n      Satellite Imagery\n        ::icon(fa fa-satellite)\n      Remote Sensing Data\n        Drones\n        Aircraft\n      On-ground Sensors\n        Weather Stations\n        IoT Devices\n      Open Environmental Data\n        Public Datasets\n        ::icon(fa fa-database)\n    section Research Focus\n      Climate Change Analysis\n        Ice Melt Patterns\n        Sea Level Rise\n      Biodiversity Monitoring\n        Species Distribution\n        Habitat Fragmentation\n      Geospatial Analysis Techniques\n        Machine Learning Models\n        Predictive Analytics\n    section Applications\n      Conservation Strategies\n        ::icon(fa fa-leaf)\n      Urban Planning\n        Green Spaces\n      Disaster Response\n        Flood Mapping\n        Wildfire Tracking\n    section Tools and Technologies\n      GIS Software\n        QGIS\n        ArcGIS\n      Programming Languages\n        Python\n        R\n      Cloud Computing Platforms\n        AWS\n        Google Earth Engine\n      Data Visualization\n        D3.js\n        Tableau\n
    • Timelines:
    gantt\n    title ESIIL Year 2 Project Schedule\n    dateFormat  YYYY-MM-DD\n    section CI\n    Sovereign OASIS via private jupiterhubs :2024-08-01, 2024-10-30\n    OASIS documentation                    :2024-09-15, 70d\n    Data cube OASIS via cyverse account    :2024-09-15, 100d\n    Integrate with ESIIL User Management system :2024-08-01, 2024-11-30\n    Build badges to deploy DE from mkdoc   :2024-09-01, 2024-12-15\n    Streamline Github ssh key management   :2024-10-01, 2024-12-31\n    Cyverse support (R proxy link)         :2024-11-01, 2024-12-31\n    Cyverse use summary and statistics     :2024-08-01, 2024-12-15\n\n    section CI Consultation and Education\n    Conferences/Invited talks              :2024-08-01, 2024-12-31\n    Office hours                           :2024-08-15, 2024-12-15\n    Proposals                              :2024-09-01, 2024-11-15\n    Private lessons                        :2024-09-15, 2024-11-30\n    Pre-event trainings                    :2024-10-01, 2024-12-15\n    Textbook development w/ education team :2024-08-01, 2024-12-15\n    Train the trainers / group lessons     :2024-08-15, 2024-11-30\n    Tribal engagement                      :2024-09-01, 2024-12-15\n    Ethical Space training                 :2024-09-15, 2024-12-31\n\n    section CI Design and Build\n    Data library (repository)              :2024-08-01, 2024-10-30\n    Analytics library (repository)         :2024-08-15, 2024-11-15\n    Containers (repository)                :2024-09-01, 2024-11-30\n    Cloud infrastructure templates (repository) :2024-09-15, 2024-12-15\n    Tribal resilience Data Cube            :2024-10-01, 2024-12-31\n
    \n%%{init: { 'logLevel': 'debug', 'theme': 'base', 'gitGraph': {'rotateCommitLabel': true}} }%%\ngitGraph\n  commit id: \"Start from template\"\n  branch c1\n  commit id: \"Set up SSH key pair\"\n  commit id: \"Modify _config.yml for GitHub Pages\"\n  commit id: \"Initial website structure\"\n  commit id: \"Add new markdown pages\"\n  commit id: \"Update navigation tree\"\n  commit id: \"Edit existing pages\"\n  commit id: \"Delete old markdown pages\"\n  commit id: \"Finalize website updates\"\n  commit id: \"Add new markdown pages\"\n  commit id: \"Update navigation tree\"\ncheckout c1\n\n  branch b1\n\n  commit\n  commit\n  checkout c1\n  merge b1\n
    %%{init: {\"quadrantChart\": {\"chartWidth\": 400, \"chartHeight\": 400}, \"themeVariables\": {\"quadrant1TextFill\": \"#ff0000\"} }}%%\nquadrantChart\n  x-axis Urgent --> Not Urgent\n  y-axis Not Important --> \"Important \u2764\"\n  quadrant-1 Plan\n  quadrant-2 Do\n  quadrant-3 Delegate\n  quadrant-4 Delete\n
    timeline\n    title Major Events in Environmental Science and Data Science\n    section Environmental Science\n        19th century : Foundations in Ecology and Conservation\n        1962 : Publication of 'Silent Spring' by Rachel Carson\n        1970 : First Earth Day\n        1987 : Brundtland Report introduces Sustainable Development\n        1992 : Rio Earth Summit\n        2015 : Paris Agreement on Climate Change\n    section Data Science\n        1960s-1970s : Development of Database Management Systems\n        1980s : Emergence of Data Warehousing\n        1990s : Growth of the World Wide Web and Data Mining\n        2000s : Big Data and Predictive Analytics\n        2010s : AI and Machine Learning Revolution\n        2020s : Integration of AI in Environmental Research\n
    erDiagram\n    CAR ||--o{ NAMED-DRIVER : allows\n    CAR {\n        string registrationNumber\n        string make\n        string model\n    }\n    PERSON ||--o{ NAMED-DRIVER : is\n    PERSON {\n        string firstName\n        string lastName\n        int age\n    }\n
    ---\nconfig:\n  sankey:\n    showValues: false\n---\nsankey-beta\n\nNASA Data,Big Data Harmonization,100\n    Satellite Imagery,Big Data Harmonization,80\n    Open Environmental Data,Big Data Harmonization,70\n    Remote Sensing Data,Big Data Harmonization,90\n    Big Data Harmonization, Data Analysis and Integration,340\n    Data Analysis and Integration,Climate Change Research,100\n    Data Analysis and Integration,Biodiversity Monitoring,80\n    Data Analysis and Integration,Geospatial Mapping,60\n    Data Analysis and Integration,Urban Planning,50\n    Data Analysis and Integration,Disaster Response,50\n
    "},{"location":"resources/markdown_basics/#5-interactive-elements","title":"5. Interactive Elements","text":"
    • Hyperlinks: Use the format [link text](URL).
    • Google

    • Play Tetris

    • Embedding Interactive Content: Use HTML tags or specific platform embed codes.

    • <iframe src=\"https://example.com/interactive-content\" width=\"600\" height=\"400\"></iframe>
    "},{"location":"resources/markdown_basics/#6-math-notation","title":"6. Math Notation","text":"

    Markdown can be combined with LaTeX for mathematical notation, useful in environmental data science for expressing statistical distributions, coordinate systems, and more. This requires a Markdown renderer with LaTeX support (like MathJax or KaTeX).

    • Inline Math: Use single dollar signs for inline math expressions. Representing the normal distribution.

    Example: The probability density function of the normal distribution is given by $f(x|\\mu,\\sigma) = \\frac{1}{\\sigma\\sqrt{2\\pi}}e^{-\\frac{1}{2}\\left(\\frac{x-\\mu}{\\sigma}\\right)^2}$.`

    • Display Math: Use double dollar signs for standalone equations.

    Example: $$ f(x|\\mu,\\sigma) = \\frac{1}{\\sigma\\sqrt{2\\pi}}e^{-\\frac{1}{2}\\left(\\frac{x-\\mu}{\\sigma}\\right)^2} $$

    • Common LaTeX Elements for Environmental Data Science:
    • Statistical Distributions:
      • Normal Distribution: \\frac{1}{\\sigma\\sqrt{2\\pi}}e^{-\\frac{1}{2}\\left(\\frac{x-\\mu}{\\sigma}\\right)^2} for $\\frac{1}{\\sigma\\sqrt{2\\pi}}e^{-\\frac{1}{2}\\left(\\frac{x-\\mu}{\\sigma}\\right)^2}$
      • Poisson Distribution: P(k; \\lambda) = \\frac{\\lambda^k e^{-\\lambda}}{k!} for $P(k; \\lambda) = \\frac{\\lambda^k e^{-\\lambda}}{k!}$
    • Coordinate Systems:
      • Spherical Coordinates: (r, \\theta, \\phi) for $(r, \\theta, \\phi)$
      • Cartesian Coordinates: (x, y, z) for $(x, y, z)$
    • Geospatial Equations:
      • Haversine Formula for Distance: a = \\sin^2\\left(\\frac{\\Delta\\phi}{2}\\right) + \\cos(\\phi_1)\\cos(\\phi_2)\\sin^2\\left(\\frac{\\Delta\\lambda}{2}\\right) for $a = \\sin^2\\left(\\frac{\\Delta\\phi}{2}\\right) + \\cos(\\phi_1)\\cos(\\phi_2)\\sin^2\\left(\\frac{\\Delta\\lambda}{2}\\right)$

    Note: The rendering of these equations as formatted math will depend on your Markdown viewer's LaTeX capabilities.

    "},{"location":"resources/markdown_basics/#7-effective-citations-in-markdown","title":"7. Effective Citations in Markdown","text":""},{"location":"resources/markdown_basics/#inline-citations","title":"Inline Citations","text":"
    • Objective: Learn how to use inline citations in Markdown.
    • Example Usage:
    • Inline citation of a single work:
      • Some text with an inline citation. [@jones:envstudy:2020]
    • Inline citation with specific page or section:
      • More text with a specific section cited. [See @jones:envstudy:2020, \u00a74.2]
    • Contrasting views:
      • Discussion of a topic with a contrasting view. [Contra @smith:climatechange:2019, p. 78]
    "},{"location":"resources/markdown_basics/#footnote-citations","title":"Footnote Citations","text":"
    • Objective: Understand how to use footnote citations in Markdown.
    • Example Usage:
    • Citing with a footnote:
      • Some statement in the text.[^1]
    • Multiple references to the same footnote:
      • Another statement referring to the same source.[^1]
    • A different citation:
      • Additional comment with a new citation.[^2]
    "},{"location":"resources/markdown_basics/#creating-footnotes","title":"Creating Footnotes","text":"
    • Example Syntax:
    • [^1]: First reference details. Example: Emma Jones, \"Environmental Study,\" Nature Journal, May 2020, https://nature-journal.com/envstudy2020.
    • [^2]: Second reference details. Example: David Smith, \"Climate Change Controversies,\" Science Daily, August 2019, https://sciencedaily.com/climatechange2019.
    "},{"location":"resources/notes_from_readings/","title":"Literature Reading Notes","text":""},{"location":"resources/notes_from_readings/#reference-information","title":"Reference Information","text":"
    • Title:
    • Authors:
    • Publication Year:
    • Journal/Source:
    • DOI/URL:
    "},{"location":"resources/notes_from_readings/#summary","title":"Summary","text":"
    • Brief summary of the main objective, research question, or thesis of the literature.
    "},{"location":"resources/notes_from_readings/#key-findings","title":"Key Findings","text":"
    • Major findings or conclusions:
    • Finding 1
    • Finding 2
    • ...
    "},{"location":"resources/notes_from_readings/#methodology","title":"Methodology","text":"
    • Description of research methodology, techniques, or approaches.
    • Notable tools, datasets, or analytical methods used.
    "},{"location":"resources/notes_from_readings/#theoretical-framework","title":"Theoretical Framework","text":"
    • Theoretical models or frameworks underpinning the research.
    • Positioning within the broader field.
    "},{"location":"resources/notes_from_readings/#critical-analysis","title":"Critical Analysis","text":"
    • Strengths: Well-executed aspects or convincing arguments.
    • Limitations: Weaknesses, gaps, or biases.
    • Insights: New understandings or perspectives gained.
    "},{"location":"resources/notes_from_readings/#connections-to-other-work","title":"Connections to Other Work","text":"
    • Similarities or differences with other readings.
    • Complementarity to other studies.
    "},{"location":"resources/notes_from_readings/#quotations-and-notes","title":"Quotations and Notes","text":"
    • Significant quotes:
    • \"Quote here.\" - Author Name, page number
    • Additional notes or comments.
    "},{"location":"resources/notes_from_readings/#personal-reflections","title":"Personal Reflections","text":"
    • Influence on understanding or perspective.
    • Potential impact on future research or studies.
    "},{"location":"resources/notes_from_readings/#action-items","title":"Action Items","text":"
    • Follow-up actions such as readings, discussions, or research activities:
    • [ ] Action item 1
    • [ ] Action item 2
    • ...
    "},{"location":"resources/participant_agreement/","title":"Participant Agreement","text":"

    This Participant Agreement (\u201cAgreement\u201d) is a contract between you (\u201cYou/Your\u201d or \u201cParticipant\u201d) and THE REGENTS OF THE UNIVERSITY OF COLORADO, a body corporate, acting on behalf of the University of Colorado Boulder, a public institution of higher education created under the Constitution and the Law of the State of Colorado (the \u201cUniversity\u201d), having offices located at 3100 Marine Street, Boulder, CO 80309.

    In consideration of Your participation in the Forest Carbon Codefest (the \u201cCodefest\u201d), the sufficiency of which is hereby acknowledged, You agree as follows:

    Environmental Data Science Innovation & Inclusion Lab (\u201cESIIL\u201d) is a National Science Foundation (\u201cNSF\u201d) funded data synthesis center led by the University. Earth Lab is part of the Cooperative Institute for Research in Environmental Sciences (CIRES) specializing in data-intensive open, reproducible environmental science. Earth Lab and ESIIL will co-host the Codefest in person from March 12 through March 14, 2023.

    "},{"location":"resources/participant_agreement/#codefest-description","title":"Codefest Description","text":"

    The Codefest aims to use big data to understand aboveground forest carbon dynamics. It brings together environmental scientists, data analysts, and forest experts from academia, non-profits, and the private sector under one roof to collaborate and provide solutions to on-the-ground needs in a respectful and inclusive environment. The Codefest provides resources to address environmental challenges, such as participation in training on Environmental Data Science and cyberinfrastructure. You will work on a cloud-based, highly secure platform that allows for the seamless integration of data sets and analytical tools. The Codefest encourages individuals participating to create a solution in the form of a research project, computer code, and models (individually and/or collectively, a \u201cSolution\u201d).

    "},{"location":"resources/participant_agreement/#how-to-participate","title":"How to Participate","text":"

    You will join a team of environmental scientists, data experts, and coders to explore curated data, consider the objectivity of the data, propose a scientific question that can be addressed with all or some of the data sets, and analyze the data in an attempt to answer your scientific question by the end of the event. You will present your Solution to the event community. Earth Lab and ESIIL will provide environmental data, cyberinfrastructure, cyberinfrastructure and data analytics training, and technical support. The team members of the winning Solution will receive a small monetary award. Details regarding how the winning Solution will be chosen and how the prize will be managed are outlined in the Official Rules for the Codefest (\u201cOfficial Rules\u201d).

    "},{"location":"resources/participant_agreement/#representations-and-warranties","title":"Representations and Warranties","text":"

    By and through Your participation in the Codefest, You represent and warrant the following:

    • You have read, understand, and agree to abide by the Code of Conduct and Respectful Inclusive Collaboration Guidelines for the Forest Carbon Codefest (\u201cCode of Conduct\u201d) and the Official Rules.
    • Any decisions concerning the Code of Conduct, Official Rules, or any other matter relating to this Codefest by the University is final and binding on all Participants.
    "},{"location":"resources/participant_agreement/#codefest-assets","title":"Codefest Assets","text":""},{"location":"resources/participant_agreement/#51-access-and-use","title":"5.1 Access and Use","text":"

    By participating in the Codefest, You may receive access to certain datasets, webinars, and/or other copyrighted materials (collectively, the \u201cCodefest Assets\u201d). You agree to follow all licenses, restrictions, and other instructions provided to You with the Codefest Assets.

    "},{"location":"resources/participant_agreement/#52-disclaimer","title":"5.2 Disclaimer","text":"

    The Codefest Assets are provided \u201cas is\u201d without warranty of any kind, either express or implied, including, without limitation, any implied warranties of merchantability and fitness for a particular purpose. Without limiting the foregoing, the University does not warrant that the Materials will be suitable for Your Solution or that the operation or supply of the Codefest Assets will be uninterrupted or error free.

    "},{"location":"resources/participant_agreement/#53-restrictions","title":"5.3 Restrictions","text":"

    You agree not to access or use the Codefest Assets in a manner that may interfere with any other participants\u2019 or users\u2019 use of such assets, unless provided with express written consent by the University. Your access to and use of the Codefest Assets may be limited, throttled, or terminated at any time at the sole discretion of the University.

    "},{"location":"resources/participant_agreement/#intellectual-property","title":"Intellectual Property","text":"

    For purposes of this Agreement, \u201cIntellectual Property\u201d includes all copyright, patent, trademark, trade secret and other intellectual property rights.

    "},{"location":"resources/participant_agreement/#61-solution-publication","title":"6.1 Solution Publication","text":"

    You agree to make Your Solution publicly available in GitHub under the MIT open-source license within five (5) months from the end of the Codefest.

    "},{"location":"resources/participant_agreement/#62-government-rights","title":"6.2 Government Rights","text":"

    In consideration of the funding provided by NSF for the Codefest, You hereby grant and agree to grant to the U.S. Government (i) a nonexclusive, non-transferable, irrevocable, royalty-free license to exercise or have exercised for or on behalf of the U.S. throughout the world all the exclusive rights provided by copyright in any copyrightable intellectual property that You create during the Codefest and (ii) a nonexclusive, non-transferable, irrevocable, paid-up license to practice, or have practiced for or on its behalf, any invention created by You during the Codefest throughout the world.

    "},{"location":"resources/participant_agreement/#63-nsf-agreement-and-invention-ownership","title":"6.3 NSF Agreement and Invention Ownership","text":"

    You acknowledge that the Codefest is subject to NSF\u2019s Cooperative Agreement Terms and Conditions effective May 12, 2023. As such, the U.S. Government may be entitled to own any invention that You create during the Codefest as further outlined within 37 CFR 401 and the NSF Proposal & Award Policies and Procedures Guide. In such event, You agree to assign any invention created by You during the Codefest to the U.S. Government and to reasonably cooperate with the University and NSF to accomplish the same.

    "},{"location":"resources/participant_agreement/#64-representations-and-warranties","title":"6.4 Representations and Warranties","text":"

    You represent and warrant that You are legally entitled to grant the above licenses and other intellectual property rights as outlined in Sections 6.1, 6.2, and 6.3. If You are an individual, and if Your employer(s) and/or another third party has rights to Intellectual Property that You create that includes Your Solution, You represent that You have received permission to participate in the Codefest on behalf of that employer or third party and that Your employer or the third party has waived such rights for Your contributions.

    "},{"location":"resources/participant_agreement/#65-originality-and-third-party-materials","title":"6.5 Originality and Third-Party Materials","text":"

    You represent that Your Solution is Your original creation. If you obtain permission under Section 6.5 to include third-party materials, You represent that Your Solution includes complete details of any third-party license or other restriction (including, but not limited to, related patents and trademarks) of which You are aware and which are associated with any part of Your Solution. You represent and warrant that You will not submit any materials to the University that You know or believe to have components that are malicious or harmful. You represent that You will perform a reasonable amount of due diligence in order to be properly informed of third-party licenses, infringing materials, or harmful content associated with any part of Your Solution.

    "},{"location":"resources/participant_agreement/#66-submission-of-external-work","title":"6.6 Submission of External Work","text":"

    Should You wish to submit work that is not Your original creation during the Codefest (and that is not a Codefest Asset), You may ask for permission from the University to incorporate such work into Your Solution. To request such permission, identify the complete details of the materials you wish to use, including any licenses or other restrictions (including, but not limited to, related patents, trademarks, and license agreements) of which You are personally aware. Request for permission to add materials created outside of the Codefest must be submitted in advance of the Codefest to: Tyler McIntosh; tyler.l.mcintosh@colorado.edu.

    "},{"location":"resources/participant_agreement/#67-notification-of-changes","title":"6.7 Notification of Changes","text":"

    You agree to notify the University of any facts or circumstances of which You become aware that would make these representations inaccurate in any respect. You agree to notify the University of any administrative or court proceeding which involve Your Solution.

    "},{"location":"resources/participant_agreement/#limitation-of-liability","title":"Limitation of Liability","text":"

    TO THE EXTENT ALLOWED BY LAW, IN NO EVENT SHALL THE UNIVERSITY, ITS PARTNERS, LICENSORS, SERVICE PROVIDERS, OR ANY OF THEIR RESPECTIVE OFFICERS, DIRECTORS, AGENTS, EMPLOYEES OR REPRESENTATIVES, BE LIABLE FOR DIRECT, INCIDENTAL, CONSEQUENTIAL, EXEMPLARY OR PUNITIVE DAMAGES ARISING OUT OF OR IN CONNECTION WITH THE HACKATHON OR THIS AGREEMENT (HOWEVER ARISING, INCLUDING NEGLIGENCE). IF YOU HAVE A DISPUTE WITH ANY PARTICIPANT OR ANY OTHER THIRD PARTY, YOU RELEASE THE UNIVERSITY, ITS, PARTNERS, LICENSORS, AND SERVICE PROVIDERS, AND EACH OF THEIR RESPECTIVE OFFICERS, DIRECTORS, AGENTS, EMPLOYEES AND REPRESENTATIVES FROM ANY AND ALL CLAIMS, DEMANDS AND DAMAGES (ACTUAL AND CONSEQUENTIAL) OF EVERY KIND AND NATURE ARISING OUT OF OR IN ANY WAY CONNECTED WITH SUCH DISPUTES. YOU AGREE THAT ANY CLAIMS AGAINST UNIVERSITY ARISING OUT OF THE HACKATHON OR THIS AGREEMENT MUST BE FILED WITHIN ONE YEAR AFTER SUCH CLAIM AROSE; OTHERWISE, YOUR CLAIM IS PERMANENTLY BARRED.

    "},{"location":"resources/participant_agreement/#not-an-offer-or-contract-of-employment","title":"Not an Offer or Contract of Employment","text":"

    Under no circumstances will Your participation in the Codefest or anything in this Agreement be construed as an offer or contract of employment with the University.

    "},{"location":"resources/participant_agreement/#additional-terms","title":"Additional Terms","text":"
    • You must be at least eighteen (18) years of age to participate in the Codefest. The Codefest is subject to applicable federal, state, and local laws.
    • The University reserves the right to permanently disqualify any person from the Codefest that it reasonably believes has violated this Agreement, the Code of Conduct, and/or the Official Rules.
    • Any attempt to deliberately damage the Codefest or the operation thereof is unlawful and subject to legal action by the University, which may seek damages to the fullest extent permitted by law.
    • The University assumes no responsibility for any injury or damage to Your or any other person\u2019s computer relating to or resulting from entering or downloading materials or software in connection with the Codefest.
    • The University is not responsible for telecommunications, network, electronic, technical, or computer failures of any kind; for inaccurate transcription of entry information; for any human or electronic error; or for Solutions that are stolen, misdirected, garbled, delayed, lost, late, damaged, or returned.
    • The University reserves the right to cancel, modify, or suspend the Codefest or any element thereof (including, without limitation, this Agreement) without notice in any manner and for any reason (including, without limitation, in the event of any unanticipated occurrence that is not fully addressed in this Agreement).
    • The University may prohibit any person from participating in the Codefest, if such person shows a disregard for this Agreement; acts with an intent to annoy, abuse, threaten, or harass any other entrant or any agents or representatives of the University (or any associated, partners, licensors, or service providers for the University); or behaves in any other disruptive manner (as determined by the University in its sole discretion).
    • Nothing contained in this Agreement shall be construed as an express or implied waiver by University of its governmental immunity or of the governmental immunity of the State of Colorado.
    • Your Solutions shall not contain any item(s) that are either export-controlled under the International Traffic in Arms Regulations, or that appear on the Commerce Control List (except as EAR99) of the Export Administration Regulations.
    "},{"location":"resources/participant_agreement/#dispute-resolution","title":"Dispute Resolution","text":"

    This Agreement and the Codefest shall be governed and construed in accordance with and governed by the laws of the state of Colorado without giving effect to conflict of law provisions.

    "},{"location":"resources/participant_agreement/#entire-agreement","title":"Entire Agreement","text":"

    This Agreement, along with the Official Rules, and the Event Code of Conduct, constitutes the entire agreement between the University and You with respect to the Codefest and supersedes all previous or contemporaneous oral or written agreements concerning the Codefest. In the event of a conflict between this Agreement, the Official Rules and/or the Event Code of Conduct, the conflict shall be resolved with the following order of precedence:

    1. This Agreement
    2. The Official Rules
    3. The Event Code of Conduct
    "},{"location":"resources/participant_agreement/#severability","title":"Severability","text":"

    The invalidity, illegality, or unenforceability of any one or more phrases, sentences, clauses, or sections in this Agreement does not affect the remaining portions of this Agreement.

    If you have questions about the Codefest, please contact Tyler McIntosh at tyler.l.mcintosh@colorado.edu.

    "},{"location":"resources/post_meeting_notes/","title":"Post-Meeting Notes Template","text":""},{"location":"resources/post_meeting_notes/#meeting-details","title":"Meeting Details","text":"
    • Date:
    • Time:
    • Location:
    • Facilitator:
    "},{"location":"resources/post_meeting_notes/#attendees","title":"Attendees","text":"
    • List of attendees
    "},{"location":"resources/post_meeting_notes/#agenda","title":"Agenda","text":""},{"location":"resources/post_meeting_notes/#1-review-of-meeting-goals","title":"1. Review of Meeting Goals","text":"
    • Recap the primary objectives and if they were met.
    "},{"location":"resources/post_meeting_notes/#2-manuscript-development","title":"2. Manuscript Development","text":"
    • Discuss the status of current manuscript drafts.
    • Assign writing and editing tasks for different sections of the manuscript.
    • Set deadlines for draft completion and review.
    "},{"location":"resources/post_meeting_notes/#3-research-highlights","title":"3. Research Highlights","text":"
    • Identify key findings and outcomes that should be emphasized in the publications.
    • Discuss any new research insights that emerged from the meeting.
    "},{"location":"resources/post_meeting_notes/#4-publication-strategy","title":"4. Publication Strategy","text":"
    • Decide on target journals or conferences for publication submission.
    • Discuss authorship order and contributions.
    • Plan for any additional data or research needed to strengthen the manuscript.
    "},{"location":"resources/post_meeting_notes/#5-editing-and-review-process","title":"5. Editing and Review Process","text":"
    • Establish a peer-review process within the group for initial feedback.
    • Assign members to focus on specific aspects of editing, such as clarity, grammar, and technical accuracy.
    • Agree on a schedule for review rounds to ensure timely submission.
    "},{"location":"resources/post_meeting_notes/#6-responsibilities-and-expectations","title":"6. Responsibilities and Expectations","text":"
    • Clearly define what is expected from each member before the next meeting.
    • Discuss communication methods for progress updates and questions.
    "},{"location":"resources/post_meeting_notes/#7-closing-remarks","title":"7. Closing Remarks","text":"
    • Summarize the discussion and confirm the action plan.
    • Reiterate the importance of meeting the set deadlines and maintaining communication.
    "},{"location":"resources/post_meeting_notes/#action-items","title":"Action Items","text":"
    • [ ] Draft introduction section: Responsible person(s) - Deadline
    • [ ] Compile and analyze additional data: Responsible person(s) - Deadline
    • [ ] Draft methodology section: Responsible person(s) - Deadline
    • ...
    • [ ] Coordinate manuscript peer review: Responsible person(s) - Deadline
    "},{"location":"resources/post_meeting_notes/#next-steps","title":"Next Steps","text":"
    • Define the timeline for the submission process.
    • Schedule follow-up meetings or check-ins to monitor progress.
    "},{"location":"resources/post_meeting_notes/#notes","title":"Notes","text":"
    • (Additional notes, comments, or observations made during the meeting.)
    "},{"location":"resources/pre_meeting_notes/","title":"Pre-Meeting Notes","text":""},{"location":"resources/pre_meeting_notes/#meeting-details","title":"Meeting Details","text":"
    • Date:
    • Time:
    • Location:
    • Facilitator:
    "},{"location":"resources/pre_meeting_notes/#attendees","title":"Attendees","text":"
    • List of attendees
    "},{"location":"resources/pre_meeting_notes/#agenda","title":"Agenda","text":""},{"location":"resources/pre_meeting_notes/#1-opening-remarks","title":"1. Opening Remarks","text":"
    • Brief welcome and overview of the meeting's objectives.
    "},{"location":"resources/pre_meeting_notes/#2-introductions","title":"2. Introductions","text":"
    • Roundtable introductions for all attendees.
    • Share a personal note or interesting fact to foster camaraderie.
    "},{"location":"resources/pre_meeting_notes/#3-planning","title":"3. Planning","text":"
    • Discuss the agenda for the primary meetings.
    • Outline the key topics and issues to address.
    • Assign roles for note-taking, timekeeping, and facilitation in primary meetings.
    "},{"location":"resources/pre_meeting_notes/#4-goal-setting","title":"4. Goal Setting","text":"
    • Establish clear, actionable goals for the upcoming period.
    • Identify specific outcomes desired from the primary meetings.
    • Agree on metrics or indicators of success for these goals.
    "},{"location":"resources/pre_meeting_notes/#5-camaraderie-building","title":"5. Camaraderie Building","text":"
    • Icebreaker activity or team-building exercise.
    • Share expectations and aspirations for the group's progress.
    • Highlight the importance of collaboration and mutual support.
    "},{"location":"resources/pre_meeting_notes/#6-open-discussion","title":"6. Open Discussion","text":"
    • Allow for any additional topics, concerns, or ideas to be brought forward.
    "},{"location":"resources/pre_meeting_notes/#7-closing-remarks","title":"7. Closing Remarks","text":"
    • Summarize the discussions and confirm the next steps.
    • Confirm dates and times for primary meetings.
    • Express appreciation for participation.
    "},{"location":"resources/pre_meeting_notes/#action-items","title":"Action Items","text":"
    • [ ] Action item 1: Responsible person(s) - Deadline
    • [ ] Action item 2: Responsible person(s) - Deadline
    • ...
    "},{"location":"resources/pre_meeting_notes/#notes","title":"Notes","text":"
    • (Any additional notes or comments about the meeting.)
    "},{"location":"resources/stac_mount_save/","title":"The art of making a data cube","text":"

    Ty Tuff, ESIIL Data Scientist 2023-10-27

    \n#library(Rcpp)\nlibrary(sf)\nlibrary(gdalcubes)\nlibrary(rstac)\nlibrary(gdalUtils)\nlibrary(terra)\nlibrary(rgdal)\nlibrary(reshape2)\nlibrary(osmdata)\nlibrary(terra)\nlibrary(dplyr)\nlibrary(stars)\nlibrary(ggplot2)\nlibrary(colorspace)\nlibrary(geos)\nlibrary(osmdata)\nlibrary(ggthemes)\nlibrary(tidyr)\ngdalcubes_options(parallel = 8)\n\nsf::sf_extSoftVersion()\n##           GEOS           GDAL         proj.4 GDAL_with_GEOS     USE_PROJ_H \n##       \"3.11.0\"        \"3.5.3\"        \"9.1.0\"         \"true\"         \"true\" \n##           PROJ \n##        \"9.1.0\"\ngdalcubes_gdal_has_geos()\n## [1] TRUE\n\nlibrary(osmdata)\nlibrary(dplyr)\nlibrary(sf)\nlibrary(terra)\nlibrary(tidyterra)\nlibrary(glue)\nlibrary(ggplot2)\nlibrary(ggthemes)\nlibrary(stars)\nlibrary(magrittr)\nlibrary(landsat)\n
    "},{"location":"resources/stac_mount_save/#the-philosophy-of-moving-data-in-the-cloud","title":"The philosophy of moving data in the cloud","text":"

    The philosophy of moving data in the cloud represents a paradigm shift in how we approach data within our analytical processes. Instead of the traditional method of transferring entire datasets to our local environments, the cloud encourages a more efficient model: bring your analysis to the data. This approach minimizes data movement and leverages the cloud\u2019s computational power and scalability. By utilizing cloud-native tools and services, we can run our analyses directly on the data where it resides, selectively accessing and processing only what is necessary. This not only streamlines workflows but also significantly reduces overheads related to data transfer and storage management. In essence, the focus is on diverting computational resources to the data rather than the cumbersome and resource-intensive practice of moving large datasets to and fro.

    "},{"location":"resources/stac_mount_save/#to-make-or-to-take-a-photo","title":"\u2018To Make\u2019 or \u2018To Take\u2019 a photo","text":"

    The distinction between making and taking a photograph lies in the approach and intent behind the camera. Taking a photo is often a reactive process, where the photographer captures moments as they naturally unfold, seizing the spontaneity of life without alteration. It\u2019s a passive form of photography where the emphasis is on the right timing and the natural interplay of elements within the frame. On the other hand, making a photo is a proactive and deliberate act. It is akin to craftsmanship, where a professional photographer starts with a concept and utilizes a variety of tools and techniques to stage and construct the desired scene. They actively manipulate lighting, composition, and subjects to create a photograph that aligns with their pre-visualized artistic vision. While both methods use a camera to produce a photograph, making a photo involves a creation process, whereas taking a photo is about finding the scene.

    David Yarrow is a famous photographer who \u2018makes\u2019 his photographs.

    "},{"location":"resources/stac_mount_save/#what-does-it-mean-to-make-a-data-cube","title":"What does it mean to \u2018make\u2019 a data cube?","text":"

    The artistry of Ansel Adams\u2019 photography serves as a compelling analogy for the meticulous craft of building a data cube from cloud data sources using tools like STAC and GDAL VSI. Just as Adams would survey the vastness of a landscape, discerning the interplay of light and shadow upon the mountains before him, a data architect surveys the expanse of available data. In this analogy, the raw data are the majestic mountains and sweeping landscapes waiting to be captured. The STAC collection acts as the photographer\u2019s deliberate choice of scene, pointing the camera lens\u2014our data tools\u2014towards the most telling and coherent dataset.

    Just as Adams\u2019 photographs are more than mere records of a landscape, but rather a confluence of his vision, technique, and the scene\u2019s natural beauty, so too is the data cube more than the sum of its parts. It is the artful synthesis of information, crafted and composed with the skill and intent of an artist, producing not just a tool for analysis but a harmonized, data-driven portrait of the world it represents. The builder of the data cube is, indeed, an artist, and the data cube their masterpiece, revealing not just data, but a story, a perspective, a landscape sewn from the raw material of cloud-sourced information.

    As Adams would adjust his viewfinder, setting the boundaries of his photographic frame, the data builder sets the view window, filtering and transferring relevant data to their own medium, akin to Adams\u2019 film. This is where the raw data is transformed, organized into the structured form of a data frame or data cube, a process not unlike the careful development of a photograph in a darkroom. Here, the data cube creator, much like Adams with his careful dodging and burning, harmonizes disparate elements into a cohesive whole, each decision reflecting an intention and vision for the final product.

    "},{"location":"resources/stac_mount_save/#1-the-rat-through-the-snake-problem-scalability-with-cloud-computing","title":"1) The Rat through the Snake Problem: Scalability with Cloud Computing","text":"

    Just like a snake that swallows a rat, traditional computing systems often struggle to process the large volumes of environmental data \u2014 they\u2019re constrained by their static hardware limitations. Cloud computing introduces a python-esque capability: massive scalability. By migrating to the cloud, we essentially make the snake bigger, allowing it to handle larger \u201cprey.\u201d Scalable computers in the cloud can grow with the demand, providing the necessary computational power to process extensive datasets, which is vital in a field where data volumes are increasing exponentially.

    "},{"location":"resources/stac_mount_save/#2-the-antelope-through-the-python-problem-streamlining-with-gdal-vsi","title":"2) The Antelope through the Python Problem: Streamlining with GDAL VSI","text":"

    As we scale up, we encounter a new challenge: trying to pass an antelope through a python \u2014 a metaphor for the next level of complexity in data processing. The sheer size and complexity of the data can become overwhelming. This is where GDAL\u2019s Virtual File System (VSI) becomes our ecological adaptation. VSI allows us to access remote data transparently and more efficiently. Instead of ingesting the entire \u201cantelope,\u201d VSI enables the \u201cpython\u201d to dynamically access and process only the parts of the data it needs, when it needs them, much like constriction before digestion. This selective access minimizes the need for local storage and expedites the data handling process.

    "},{"location":"resources/stac_mount_save/#3-drinking-from-a-fire-hose-accelerated-inference-with-ai-and-ml","title":"3) Drinking from a Fire Hose: Accelerated Inference with AI and ML","text":"

    Once we\u2019ve enabled the flow of large amounts of digestible data, we encounter the metaphorical challenge of drinking from a fire hose. The data, now flowing and accessible, is immense and rapid \u2014 posing a challenge not just to store and process, but to understand and derive meaning from in real-time. This is where artificial intelligence (AI) and machine learning (ML) step in. These technologies act as a sophisticated filtration system, enabling us to drink safely and beneficially from the torrent. AI and ML can analyze patterns, make predictions, and infer insights at a pace that keeps up with the fast stream of data, turning raw information into actionable knowledge.

    By addressing these three pivotal challenges with cloud computing, GDAL VSI, and AI/ML, we not only manage to consume the data effectively but also transform our capabilities in environmental data science. We can move from mere data ingestion to meaningful data interpretation, all at a scale and speed necessary for impactful environmental analysis.

    "},{"location":"resources/stac_mount_save/#mounting-data","title":"Mounting data","text":"

    A void-filled Digital Elevation Model (DEM) is a comprehensive topographical representation where any missing data points, known as voids, have been filled in. These voids can occur due to various reasons, such as clouds or technical errors during data collection. In a void-filled DEM, these gaps are interpolated or estimated using the surrounding data to create a continuous, seamless surface model. This process enhances the utility and accuracy of the DEM for hydrological modeling, terrain analysis, and other geographical applications. The HydroSHEDS website (https://www.hydrosheds.org/hydrosheds-core-downloads) provides access to high-quality, void-filled DEM datasets like the DEM_continuous_CONUS_15s, which users can download and easily integrate into spatial analysis workflows using tools such as \u2018terra\u2019 in R, allowing for sophisticated environmental and geographical research and planning.

    # Record start time\na <- Sys.time()  \n\n# Create a string with the file path using glue, then download and read the DEM file as a raster object\n\nDEM_continuous_CONUS_15s <- glue(\n  \"/vsizip/vsicurl/\", #magic remote connection \n  \"https://data.hydrosheds.org/file/hydrosheds-v1-dem/hyd_na_dem_15s.zip\", #copied link to download location\n  \"/hyd_na_dem_15s.tif\") %>% #path inside zip file\n  terra::rast()  \n\n# The 'glue' function constructs the file path string, which is then passed to 'terra::rast()' to read the DEM file into R as a raster layer. '/vsizip/vsicurl/' is a special GDAL virtual file system syntax that allows reading directly from a zipped file on a remote server.\n\n# Record end time and calculate the time difference\nb <- Sys.time()  \ndifftime(b, a) \n## Time difference of 4.603666 secs\n\n# The resulting raster object is stored in 'DEM_continuous_CONUS_15s', which now contains the void-filled DEM data ready for use\n\nDEM_continuous_CONUS_15s  # Prints out the details of the 'DEM_continuous_CONUS_15s' raster object\n## class       : SpatRaster \n## dimensions  : 13920, 20640, 1  (nrow, ncol, nlyr)\n## resolution  : 0.004166667, 0.004166667  (x, y)\n## extent      : -138, -52, 5, 63  (xmin, xmax, ymin, ymax)\n## coord. ref. : lon/lat WGS 84 (EPSG:4326) \n## source      : hyd_na_dem_15s.tif \n## name        : Band_1\n\n# output is a SpatRaster, which is the object type associated with the 'terra' package. \n

    Continuous DEM for North America

    # Record start time\na <- Sys.time()\n\nggplot() +\n  geom_spatraster(data=DEM_continuous_CONUS_15s) +\n  theme_tufte()\n

    \nb <- Sys.time()\ndifftime(b, a)\n## Time difference of 52.49061 secs\n

    Calculate Slope from that DEM

    SLOPE_continuous_CONUS_15s <-  terra::terrain(DEM_continuous_CONUS_15s, \"slope\") \n\nSLOPE_continuous_CONUS_15s\n## class       : SpatRaster \n## dimensions  : 13920, 20640, 1  (nrow, ncol, nlyr)\n## resolution  : 0.004166667, 0.004166667  (x, y)\n## extent      : -138, -52, 5, 63  (xmin, xmax, ymin, ymax)\n## coord. ref. : lon/lat WGS 84 (EPSG:4326) \n## source(s)   : memory\n## name        :    slope \n## min value   :  0.00000 \n## max value   : 56.98691\n
    # Record start time\na <- Sys.time()\n\nggplot() +\n  geom_spatraster(data=SLOPE_continuous_CONUS_15s) +\n  theme_tufte()\n

    \nb <- Sys.time()\ndifftime(b, a)\n## Time difference of 3.859545 secs\n

    Calculate aspect from DEM

    ASPECT_continuous_CONUS_15s <-  terra::terrain(DEM_continuous_CONUS_15s, \"aspect\") \nASPECT_continuous_CONUS_15s\n## class       : SpatRaster \n## dimensions  : 13920, 20640, 1  (nrow, ncol, nlyr)\n## resolution  : 0.004166667, 0.004166667  (x, y)\n## extent      : -138, -52, 5, 63  (xmin, xmax, ymin, ymax)\n## coord. ref. : lon/lat WGS 84 (EPSG:4326) \n## source(s)   : memory\n## name        : aspect \n## min value   :      0 \n## max value   :    360\n
    # Record start time\na <- Sys.time()\n\nggplot() +\n  geom_spatraster(data=ASPECT_continuous_CONUS_15s) +\n  theme_tufte()\n

    \nb <- Sys.time()\ndifftime(b, a)\n## Time difference of 3.650267 secs\n

    Create a cube from those layers!

    mini_stack <- c(DEM_continuous_CONUS_15s, SLOPE_continuous_CONUS_15s,ASPECT_continuous_CONUS_15s)\nmini_stack\n## class       : SpatRaster \n## dimensions  : 13920, 20640, 3  (nrow, ncol, nlyr)\n## resolution  : 0.004166667, 0.004166667  (x, y)\n## extent      : -138, -52, 5, 63  (xmin, xmax, ymin, ymax)\n## coord. ref. : lon/lat WGS 84 (EPSG:4326) \n## sources     : hyd_na_dem_15s.tif  \n##               memory  \n##               memory  \n## names       : Band_1,    slope, aspect \n## min values  :     ? ,  0.00000,      0 \n## max values  :     ? , 56.98691,    360\n

    Reproject and return the bounding box coordinates for our Area of Interest

    # Transform the filtered geometry to EPSG:4326 and store its bounding box\n# Record start time\na <- Sys.time()\n\nDEM_continuous_CONUS_15s |>\nstars::st_as_stars() |> \n  st_transform(\"EPSG:4326\") |>\n  st_bbox() -> bbox_4326\n\n\nDEM_continuous_CONUS_15s |>\nstars::st_as_stars() |> \n  st_transform(\"EPSG:32618\") |>\n  st_bbox() -> bbox_32618\n\nb <- Sys.time()\ndifftime(b, a)\n## Time difference of 3.7653 mins\n

    Get a polygon for Boulder County, reproject, and return bounding box. This is so I can make a smaller search in the stac catalog.

    boulder_county <- getbb(\"boulder, co\", format_out=\"sf_polygon\")\n\nboulder_county$multipolygon |> \n  st_transform(crs =4326 ) |>\n  st_bbox() -> bbox_4326_boulder\n\nboulder_county$multipolygon |> \n  st_transform(crs =32720 ) |>\n  st_bbox() -> bbox_32720_boulder\n

    Get a polygon for the United States and crop it to be the same size as the DEM above.

    aoi <- getbb(\"United States\", format_out=\"sf_polygon\")\n\nconus <- aoi$multipolygon |>\n  st_crop(bbox_4326)\n\n\nggplot(data=conus) +\n  geom_sf()\n

    Search the Stac catalog.

    STAC, or SpatioTemporal Asset Catalog, is an open-source specification designed to standardize the way geospatial data is indexed and discovered. Developed by Element 84 among others, it facilitates better interoperability and sharing of geospatial assets by providing a common language for describing them. STAC\u2019s flexible design allows for easy cataloging of data, making it simpler for individuals and systems to search and retrieve geospatial information. By effectively organizing data about the Earth\u2019s spatial and temporal characteristics, STAC enables users to harness the full power of the cloud and modern data processing technologies, optimizing the way we access and analyze environmental data on a global scale.

     stac(\"https://earth-search.aws.element84.com/v1\") |>\n       get_request()\n## ###STACCatalog\n## - id: earth-search-aws\n## - description: A STAC API of public datasets on AWS\n## - field(s): stac_version, type, id, title, description, links, conformsTo\n

    Element 84\u2019s Earth Search is a STAC compliant search and discovery API that offers users access to a vast collection of geospatial open datasets hosted on AWS. It serves as a centralized search catalog providing standardized metadata for these open datasets, designed to be freely used and integrated into various applications. Alongside the API, Element 84 also provides a web application named Earth Search Console, which is map-centric and allows users to explore and visualize the data contained within the Earth Search API\u2019s catalog. This suite of tools is part of Element 84\u2019s initiative to make geospatial data more accessible and actionable for a wide range of users and applications.

    collection_formats()\n##    CHIRPS_v2_0_daily_p05_tif | Image collection format for CHIRPS v 2.0 daily\n##                              | global precipitation dataset (0.05 degrees\n##                              | resolution) from GeoTIFFs, expects list of .tif\n##                              | or .tif.gz files as input. [TAGS: CHIRPS,\n##                              | precipitation]\n##  CHIRPS_v2_0_monthly_p05_tif | Image collection format for CHIRPS v 2.0 monthly\n##                              | global precipitation dataset (0.05 degrees\n##                              | resolution) from GeoTIFFs, expects list of .tif\n##                              | or .tif.gz files as input. [TAGS: CHIRPS,\n##                              | precipitation]\n##            ESA_CCI_SM_ACTIVE | Collection format for ESA CCI soil moisture\n##                              | active product (version 4.7) [TAGS: Soil\n##                              | Moisture, ESA, CCI]\n##           ESA_CCI_SM_PASSIVE | Collection format for ESA CCI soil moisture\n##                              | passive product (version 4.7) [TAGS: Soil\n##                              | Moisture, ESA, CCI]\n##    GPM_IMERG_3B_DAY_GIS_V06A | Collection format for daily\n##                              | IMERG_3B_DAY_GIS_V06A data [TAGS: Precipitation,\n##                              | GPM, IMERG]\n##                      L8_L1TP | Collection format for Landsat 8 Level 1 TP\n##                              | product [TAGS: Landsat, USGS, Level 1, NASA]\n##                        L8_SR | Collection format for Landsat 8 surface\n##                              | reflectance product [TAGS: Landsat, USGS, Level\n##                              | 2, NASA, surface reflectance]\n##                        MAXAR | Preliminary collection format for MAXAR open\n##                              | data, visual only (under development) [TAGS: ]\n##                      MxD09GA | Collection format for selected bands from the\n##                              | MODIS MxD09GA (Aqua and Terra) product [TAGS:\n##                              | MODIS, surface reflectance]\n##                      MxD10A2 | Collection format for selected bands from the\n##                              | MODIS MxD10A2 (Aqua and Terra) v006 Snow Cover\n##                              | product [TAGS: MODIS, Snow Cover]\n##                      MxD11A1 | Collection format for selected bands from the\n##                              | MODIS MxD11A2 (Aqua and Terra) v006 Land Surface\n##                              | Temperature product [TAGS: MODIS, LST]\n##                      MxD11A2 | Collection format for selected bands from the\n##                              | MODIS MxD11A2 (Aqua and Terra) v006 Land Surface\n##                              | Temperature product [TAGS: MODIS, LST]\n##                      MxD13A2 | Collection format for selected bands from the\n##                              | MODIS MxD13A2 (Aqua and Terra) product [TAGS:\n##                              | MODIS, VI, NDVI, EVI]\n##                      MxD13A3 | Collection format for selected bands from the\n##                              | MODIS MxD13A3 (Aqua and Terra) product [TAGS:\n##                              | MODIS, VI, NDVI, EVI]\n##                      MxD13Q1 | Collection format for selected bands from the\n##                              | MODIS MxD13Q1 (Aqua and Terra) product [TAGS:\n##                              | MODIS, VI, NDVI, EVI]\n##                      MxD14A2 | Collection format for the MODIS MxD14A2 (Aqua\n##                              | and Terra) product [TAGS: MODIS, Fire]\n## PlanetScope_3B_AnalyticMS_SR | Image collection format for PlanetScope 4-band\n##                              | scenes [TAGS: PlanetScope, BOA, Surface\n##                              | Reflectance]\n##                Sentinel2_L1C | Image collection format for Sentinel 2 Level 1C\n##                              | data as downloaded from the Copernicus Open\n##                              | Access Hub, expects a list of file paths as\n##                              | input. The format works on original ZIP\n##                              | compressed as well as uncompressed imagery.\n##                              | [TAGS: Sentinel, Copernicus, ESA, TOA]\n##            Sentinel2_L1C_AWS | Image collection format for Sentinel 2 Level 1C\n##                              | data in AWS [TAGS: Sentinel, Copernicus, ESA,\n##                              | TOA]\n##                Sentinel2_L2A | Image collection format for Sentinel 2 Level 2A\n##                              | data as downloaded from the Copernicus Open\n##                              | Access Hub, expects a list of file paths as\n##                              | input. The format should work on original ZIP\n##                              | compressed as well as uncompressed imagery.\n##                              | [TAGS: Sentinel, Copernicus, ESA, BOA, Surface\n##                              | Reflectance]\n##          Sentinel2_L2A_THEIA | Image collection format for Sentinel 2 Level 2A\n##                              | data as downloaded from Theia. [TAGS: Sentinel,\n##                              | ESA, Flat Reflectance, Theia]\n

    Building a stac collection by aiming your camera at the landscape

    Creating a STAC collection is akin to a photographer framing a shot; the landscape is rich with diverse data, mirroring a scene bustling with potential subjects, colors, and light. Just as a photographer selects a portion of the vista to capture, focusing on elements that will compose a compelling image, a data scientist must similarly navigate the vast data terrain. They must \u2018point their camera\u2019 judiciously, ensuring that the \u2018frame\u2019 encapsulates the precise data needed. This careful selection is crucial, as it determines the relevance and quality of the data collection, much like the photographer\u2019s choice dictates the story a photograph will tell.

    # Record start time\na <- Sys.time()\n\n# Initialize STAC connection\ns = stac(\"https://earth-search.aws.element84.com/v0\")\n\n\n# Search for Sentinel-2 images within specified bounding box and date range\n#22 Million items\nitems = s |>\n    stac_search(collections = \"sentinel-s2-l2a-cogs\",\n                bbox = c(bbox_4326_boulder[\"xmin\"], \n                         bbox_4326_boulder[\"ymin\"],\n                         bbox_4326_boulder[\"xmax\"], \n                         bbox_4326_boulder[\"ymax\"]), \n                datetime = \"2021-05-15/2021-05-16\") |>\n    post_request() |>\n    items_fetch(progress = FALSE)\n\n# Print number of found items\nlength(items$features)\n## [1] 1\n\n# Prepare the assets for analysis\nlibrary(gdalcubes)\nassets = c(\"B01\", \"B02\", \"B03\", \"B04\", \"B05\", \"B06\", \n           \"B07\", \n           \"B08\", \"B8A\", \"B09\", \"B11\", \"B12\", \"SCL\")\ns2_collection = stac_image_collection(items$features, asset_names = assets,\nproperty_filter = function(x) {x[[\"eo:cloud_cover\"]] < 20}) #all images with less than 20% clouds\n\nb <- Sys.time()\ndifftime(b, a)\n## Time difference of 0.4706092 secs\n\n# Display the image collection\ns2_collection\n## Image collection object, referencing 1 images with 13 bands\n## Images:\n##                       name      left      top   bottom     right\n## 1 S2B_13TDE_20210516_0_L2A -106.1832 40.65079 39.65576 -104.8846\n##              datetime        srs\n## 1 2021-05-16T18:02:54 EPSG:32613\n## \n## Bands:\n##    name offset scale unit nodata image_count\n## 1   B01      0     1                       1\n## 2   B02      0     1                       1\n## 3   B03      0     1                       1\n## 4   B04      0     1                       1\n## 5   B05      0     1                       1\n## 6   B06      0     1                       1\n## 7   B07      0     1                       1\n## 8   B08      0     1                       1\n## 9   B09      0     1                       1\n## 10  B11      0     1                       1\n## 11  B12      0     1                       1\n## 12  B8A      0     1                       1\n## 13  SCL      0     1                       1\n

    Setting up your camera and film

    The camera through which the data scientist frames the shot is multifaceted, akin to the tools and processes they employ. The camera\u2019s film, analogous to the data cube, defines the resolution and dimensions of the captured data, shaping how the final dataset will be utilized. The lens and its settings\u2014focus, aperture, and exposure\u2014determine the clarity, depth, and breadth of the captured information, much like the algorithms and parameters set by the data scientist dictate the granularity and scope of the data cube. The flash, like data enhancement techniques, can illuminate hidden details, ensuring that the data cube, the final product, is as informative and accurate as the landscape it represents.

    # Record start time\na <- Sys.time()\n\n# Define a specific view on the satellite image collection\nv = cube_view(\n    srs = \"EPSG:32720\", #this is harder than expected. \n    dx = 100, \n    dy = 100, \n    dt = \"P1M\", \n    aggregation = \"median\", \n    resampling = \"near\",\n    extent = list(\n        t0 = \"2021-05-15\", \n        t1 = \"2021-05-16\",\n        left = bbox_32720_boulder[1], \n        right = bbox_32720_boulder[2],\n        top = bbox_32720_boulder[4], \n        bottom = bbox_32720_boulder[3]\n    )\n)\n\nb <- Sys.time()\ndifftime(b, a)\n## Time difference of 0.002738953 secs\n\n# Display the defined view\nv\n## A data cube view object\n## \n## Dimensions:\n##                 low             high  count pixel_size\n## t        2021-05-01       2021-05-31      1        P1M\n## y -3103099.52398788 15434400.4760121 185375        100\n## x -3178878.98542359 15369521.0145764 185484        100\n## \n## SRS: \"EPSG:32720\"\n## Temporal aggregation method: \"median\"\n## Spatial resampling method: \"near\"\n

    Take a picture!

    Raster style

    # Record start time\na <- Sys.time()\n\ns2_collection |>\n    raster_cube(v) |>\n    select_bands(c( \"B04\", \"B05\"))  |>\n  apply_pixel(c(\"(B05-B04)/(B05+B04)\"), names=\"NDVI\") |>\n  write_tif() |>\n  raster::stack() -> x\nx\n## class      : RasterStack \n## dimensions : 185375, 185484, 34384096500, 1  (nrow, ncol, ncell, nlayers)\n## resolution : 100, 100  (x, y)\n## extent     : -3178879, 15369521, -3103100, 15434400  (xmin, xmax, ymin, ymax)\n## crs        : +proj=utm +zone=20 +south +datum=WGS84 +units=m +no_defs \n## names      : NDVI\n\nb <- Sys.time()\ndifftime(b, a)\n## Time difference of 4.132932 mins\n

    STARS style

    # Record start time\na <- Sys.time()\n\ns2_collection |>\n    raster_cube(v) |>\n    select_bands(c(\"B04\",\"B05\"))  |>\n  apply_pixel(c(\"(B05-B04)/(B05+B04)\"), names=\"NDVI\") |>\n  stars::st_as_stars() -> y\n\nb <- Sys.time()\ndifftime(b, a)\n## Time difference of 1.459866 mins\n\ny\n## stars_proxy object with 1 attribute in 1 file(s):\n## $NDVI\n## [1] \"[...]/filec5982c38536c.nc:NDVI\"\n## \n## dimension(s):\n##      from     to   offset delta                refsys point\n## x       1 185484 -3178879   100 WGS 84 / UTM zone 20S    NA\n## y       1 185375 15434400  -100 WGS 84 / UTM zone 20S    NA\n## time    1      1       NA    NA               POSIXct FALSE\n##                       values x/y\n## x                       NULL [x]\n## y                       NULL [y]\n## time [2021-05-01,2021-06-01)\n

    Extract data

    # Record start time\na <- Sys.time()\n\n\nx <- s2_collection |>\n    raster_cube(v) |>\n    select_bands(c(\"B01\", \"B02\", \"B03\", \"B04\", \n                   \"B05\", \"B06\", \"B07\", \"B08\", \n                   \"B8A\", \"B09\", \"B11\", \"B12\")) |>\n    extract_geom(boulder_county$multipolygon) |>\n    rename(\n        \"time\" = \"time\",\n        \"443\" = \"B01\",\n        \"490\" = \"B02\",\n        \"560\" = \"B03\",\n        \"665\" = \"B04\",\n        \"705\" = \"B05\",\n        \"740\" = \"B06\",\n        \"783\" = \"B07\",\n        \"842\" = \"B08\",\n        \"865\" = \"B8A\",\n        \"940\" = \"B09\",\n        \"1610\" = \"B11\",\n        \"2190\" = \"B12\"\n    )\n\nb <- Sys.time()\ndifftime(b, a)\n## Time difference of 1.699016 mins\n\nhead(x)\n##   FID       time   443   490   560   665   705   740   783   842  865  940 1610\n## 1   1 2021-05-01 11096 10929 10224  9893  9956  9706  9715  9641 9511 8459 5682\n## 2   1 2021-05-01 11631 11282 10550 10234 10288 10031 10032  9988 9828 9153 5802\n## 3   1 2021-05-01 11900 11393 10666 10337 10398 10142 10138 10093 9927 9461 5754\n## 4   1 2021-05-01 11406 10597  9928  9626  9694  9481  9516  9338 9336 8959 5726\n## 5   1 2021-05-01 11399 10939 10237  9905  9978  9738  9746  9633 9555 8925 5831\n## 6   1 2021-05-01 11600 11174 10462 10147 10209  9952  9960  9890 9760 9153 5773\n##   2190\n## 1 3917\n## 2 3981\n## 3 3937\n## 4 4054\n## 5 4097\n## 6 3990\n

    Make a timeseries

    \n# Record start time\na <- Sys.time()\n\nitems <- s |>\n    stac_search(collections = \"sentinel-s2-l2a-cogs\",\n                bbox = c(-105.694362,   39.912886,  -105.052774,    40.262785),\n                datetime = \"2020-01-01/2022-12-31\",\n                limit = 500) %>% \n    post_request() \n\nS2.mask = image_mask(\"SCL\", values=c(3,8,9))\n\ncol = stac_image_collection(items$features, asset_names = assets, \n                            property_filter = function(x) {x[[\"eo:cloud_cover\"]] < 30})\n\nv = cube_view(srs = \"EPSG:4326\",  extent = list(t0 = \"2020-01-01\", t1 = \"2022-12-31\",\n              left = -105.694362, right = -105.052774,  top = 40.262785, bottom = 39.912886),\n              dx = 0.001, dy = 0.001, dt = \"P1M\", aggregation = \"median\", resampling = \"bilinear\")\n\nlibrary(colorspace)\nndvi.col = function(n) {\n  rev(sequential_hcl(n, \"Green-Yellow\"))\n}\nlibrary(gdalcubes)\nraster_cube(col, v, mask = S2.mask) |>\n    select_bands(c(\"B04\", \"B08\")) |>\n    apply_pixel(\"(B08-B04)/(B08+B04)\", \"NDVI\") |>\n    gdalcubes::animate(col = ndvi.col, zlim=c(-0.2,1), key.pos = 1, save_as = \"anim.gif\", fps = 4)\n## [1] \"/Users/ty/Documents/Github/hackathon2023_datacube/docs/code_for_building_cube/anim.gif\"\n\nb <- Sys.time()\ndifftime(b, a)\n## Time difference of 4.716672 mins\n\ny\n## stars_proxy object with 1 attribute in 1 file(s):\n## $NDVI\n## [1] \"[...]/filec5982c38536c.nc:NDVI\"\n## \n## dimension(s):\n##      from     to   offset delta                refsys point\n## x       1 185484 -3178879   100 WGS 84 / UTM zone 20S    NA\n## y       1 185375 15434400  -100 WGS 84 / UTM zone 20S    NA\n## time    1      1       NA    NA               POSIXct FALSE\n##                       values x/y\n## x                       NULL [x]\n## y                       NULL [y]\n## time [2021-05-01,2021-06-01)\n

    Saving Data Cubes to Local Storage There are occasions when we need to manipulate data cubes using other software. For such purposes, we can save data cubes to our local disk as individual netCDF files or as a series of GeoTIFF files. In the case of the latter, each temporal segment of the cube is saved as a separate (multiband) GeoTIFF file.

    Both netCDF and GeoTIFF formats allow for file size reduction through compression and data packing. This process involves transforming double precision numbers into smaller integer values using a scale and offset, which can be particularly useful for managing disk space (for more details, refer to the ?write_ncdf and ?write_tif documentation).

    gdalcubes_options(ncdf_compression_level = 1)\nwrite_ncdf(cube, file.path(\"~/Desktop\", basename(tempfile(fileext = \".nc\"))))\ngdalcubes_options(ncdf_compression_level = 0)\n

    write_tif() and write_ncdf() both return the path(s) to created file(s) as a character vector.

    items_2020 <- s |>\n    stac_search(collections = \"sentinel-s2-l2a-cogs\",\n                bbox = c(-105.694362,   39.912886,  -105.052774,    40.262785),\n                datetime = \"2020-05-01/2020-06-30\") |> \n    post_request() \n\nitems_2021 <- s |>\n    stac_search(collections = \"sentinel-s2-l2a-cogs\",\n                bbox = c(-105.694362,   39.912886,  -105.052774,    40.262785),\n                datetime = \"2021-05-01/2021-06-30\") |> \n    post_request() \n\n\ncol_2020 = stac_image_collection(items_2020$features, asset_names = assets)\ncol_2021 = stac_image_collection(items_2021$features, asset_names = assets)\n\nv_2020 = cube_view(srs = \"EPSG:32720\",  extent = list(t0 = \"2020-05-01\", t1 = \"2020-06-30\",\n              left = bbox_32720_boulder[\"xmin\"], right = bbox_32720_boulder[\"xmax\"],  top = bbox_32720_boulder[\"ymax\"], bottom = bbox_32720_boulder[\"ymin\"]),\n              dx = 100, dy = 100, dt = \"P1D\", aggregation = \"median\", resampling = \"bilinear\")\n\nv_2021 = cube_view(v_2020, extent = list(t0 = \"2021-05-01\", t1 = \"2021-06-30\"))\n\n\nmax_ndvi_mosaic <- function(col, v) {\n    raster_cube(col, v) |>\n    select_bands(c(\"B04\", \"B08\")) |>\n    apply_pixel(c(\"(B08-B04)/(B08+B04)\"), names=\"NDVI\") |>\n    reduce_time(\"max(NDVI)\")\n}\n\nsuppressPackageStartupMessages(library(stars))\nmax_ndvi_mosaic(col_2020, v_2020) -> maxndvi_2020\n\nmax_ndvi_mosaic(col_2021, v_2021)  -> maxndvi_2021\n\nmaxndvi_2021\nmaxndvi_2020\n\ndifference = maxndvi_2021 - maxndvi_2020\ndifference[difference > -0.15] = NA\nnames(difference) <- \"Difference of max NDVI (2020 - 2019)\"\n
    flood_polygon_data3 <- glue(\"/vsizip/vsicurl/https://data.hydrosheds.org/file/hydrosheds-associated/gloric/GloRiC_v10_shapefile.zip/GloRiC_v10_shapefile/GloRiC_v10.shp\") |>\n  st_read() |>\n  st_as_sf(coords = c(\"lon\",\"lat\"))\n\nflood_polygon_data3\n
    #st_read(\"/Users/ty/Downloads/GloRiC_v10_geodatabase/GloRiC_v10.gdb\")\n\nflood_polygon_data3 <- glue(\"/vsizip/vsicurl/https://data.hydrosheds.org/file/hydrosheds-associated/gloric/GloRiC_v10_geodatabase.zip/GloRiC_v10_geodatabase/GloRiC_v10.gdb\") |>\n  st_read() |>\n  st_as_sf(coords = c(\"lon\",\"lat\"))\n\nflood_polygon_data3\n
    "},{"location":"resources/third_meeting_notes/","title":"Primary Meeting Day 11-15: Finalization and Conclusion","text":""},{"location":"resources/third_meeting_notes/#meeting-details","title":"Meeting Details","text":"
    • Dates:
    • Times:
    • Location:
    • Facilitator:
    "},{"location":"resources/third_meeting_notes/#attendees","title":"Attendees","text":"
    • List of attendees
    "},{"location":"resources/third_meeting_notes/#daily-agenda","title":"Daily Agenda","text":""},{"location":"resources/third_meeting_notes/#day-11-alignment-and-focus","title":"Day 11: Alignment and Focus","text":""},{"location":"resources/third_meeting_notes/#realigning-objectives","title":"Realigning Objectives","text":"
    • Review the project's main goals to ensure alignment with the final output.
    • Address any misalignments or deviations from the original plan.
    "},{"location":"resources/third_meeting_notes/#prioritization-of-tasks","title":"Prioritization of Tasks","text":"
    • Identify critical tasks that need to be completed.
    • Allocate resources and efforts to ensure these priorities are met.
    "},{"location":"resources/third_meeting_notes/#day-12-14-intensive-work-period","title":"Day 12-14: Intensive Work Period","text":""},{"location":"resources/third_meeting_notes/#task-completion","title":"Task Completion","text":"
    • Dedicated time for team members to complete their individual contributions.
    • Regular check-ins to track progress and address any blockers.
    "},{"location":"resources/third_meeting_notes/#integration-of-work","title":"Integration of Work","text":"
    • Begin to combine individual contributions into a cohesive whole.
    • Review the integration to ensure consistency and coherency across the project.
    "},{"location":"resources/third_meeting_notes/#final-reviews-and-edits","title":"Final Reviews and Edits","text":"
    • Conduct thorough reviews of the project's outputs.
    • Perform final edits to refine the quality of the work.
    "},{"location":"resources/third_meeting_notes/#day-15-closure-and-celebration","title":"Day 15: Closure and Celebration","text":""},{"location":"resources/third_meeting_notes/#final-presentation","title":"Final Presentation","text":"
    • Present the completed project to the group.
    • Discuss any last-minute adjustments or refinements needed.
    "},{"location":"resources/third_meeting_notes/#reflective-session","title":"Reflective Session","text":"
    • Reflect on the achievements and learnings from the project.
    • Share appreciation for the team's hard work and dedication.
    "},{"location":"resources/third_meeting_notes/#celebration","title":"Celebration","text":"
    • Acknowledge the successful completion of the project.
    • Plan for any dissemination of the project's findings or outputs.
    "},{"location":"resources/third_meeting_notes/#detailed-notes","title":"Detailed Notes","text":""},{"location":"resources/third_meeting_notes/#day-11-notes","title":"Day 11 Notes","text":"
    • ...
    "},{"location":"resources/third_meeting_notes/#day-12-notes","title":"Day 12 Notes","text":"
    • ...
    "},{"location":"resources/third_meeting_notes/#day-13-notes","title":"Day 13 Notes","text":"
    • ...
    "},{"location":"resources/third_meeting_notes/#day-14-notes","title":"Day 14 Notes","text":"
    • ...
    "},{"location":"resources/third_meeting_notes/#day-15-notes","title":"Day 15 Notes","text":"
    • ...
    "},{"location":"resources/third_meeting_notes/#action-items","title":"Action Items","text":"
    • [ ] Finalize manuscript for publication: Assigned to - Deadline
    • [ ] Prepare data for repository submission: Assigned to - Deadline
    • [ ] Organize project materials for archival: Assigned to - Deadline
    • ...
    "},{"location":"resources/third_meeting_notes/#reflections-and-comments","title":"Reflections and Comments","text":"
    • (Space for any additional thoughts, insights, or personal reflections on the meeting and the project as a whole.)
    "},{"location":"resources/third_meeting_notes/#next-steps","title":"Next Steps","text":"
    • Define the publication and dissemination plan.
    • Outline any follow-up research or projects that have stemmed from this work.
    "},{"location":"resources/third_meeting_notes/#additional-documentation","title":"Additional Documentation","text":"
    • (Include or link to any additional documents, charts, or resources that were created or referenced during the meeting.)
    "},{"location":"resources/visualizations/","title":"Visualization Strategy and Development Documentation","text":""},{"location":"resources/visualizations/#overview","title":"Overview","text":"
    • Brief overview of the visualization goals and their alignment with the overall project objectives.
    "},{"location":"resources/visualizations/#visualization-strategy","title":"Visualization Strategy","text":""},{"location":"resources/visualizations/#identifying-key-messages","title":"Identifying Key Messages","text":"
    • Discuss main messages or insights to communicate through visualizations.
    • Identify target audience and their specific needs.
    "},{"location":"resources/visualizations/#selecting-appropriate-visualization-types","title":"Selecting Appropriate Visualization Types","text":"
    • Explore different types of visualizations (charts, graphs, 3D, interactive elements) suitable for the data and message.
    • Brainstorm creative visualization approaches.
    "},{"location":"resources/visualizations/#visualization-development","title":"Visualization Development","text":""},{"location":"resources/visualizations/#code-generated-visualizations","title":"Code-Generated Visualizations","text":"
    • Outline initial visualizations generated from the data pipeline.
    • Include code snippets and explanations.
    # Example Python code for a basic plot\nimport matplotlib.pyplot as plt\nplt.plot(data['x'], data['y'])\nplt.show()\n
    "},{"location":"resources/visualizations/#enhancing-visualizations","title":"Enhancing Visualizations","text":"
    • Steps for annotating, animating, creating 3D, immersive, or interactive visualizations.
    • Discuss challenges and solutions in enhancing visuals.
    "},{"location":"resources/visualizations/#versioning-and-iterations","title":"Versioning and Iterations","text":"
    • Document different versions and iterations of visualizations.
    • Reflect on improvements or changes in each version.
    "},{"location":"resources/visualizations/#finalizing-visualizations","title":"Finalizing Visualizations","text":"
    • Process of finalizing visuals for presentation or publication.
    • Feedback incorporation from team or test audiences.
    "},{"location":"resources/visualizations/#documentation-of-tools-and-resources","title":"Documentation of Tools and Resources","text":"
    • List software, libraries, and tools used for visualization.
    • Reference external resources or tutorials.
    "},{"location":"resources/visualizations/#conclusions","title":"Conclusions","text":"
    • Summarize the visualization process and contributions to the project.
    • Reflect on lessons learned and potential future improvements.
    "},{"location":"resources/visualizations/#references","title":"References","text":"
    • Cite external sources, inspirations, or frameworks used in visualization.
    "},{"location":"resources/working_groups_and_postdocs/","title":"ESIIL Postdoctoral Researcher Responsibilities and Opportunities","text":""},{"location":"resources/working_groups_and_postdocs/#primary-responsibilities","title":"Primary Responsibilities","text":"
    • Independent Research:
    • Conducting self-proposed research projects.
    • Adhering to open data principles.
    • Data and Code Storage:
    • Storing all research code and data in the designated ESIIL repository.
    • Use of CyVerse:
    • Utilizing CyVerse as the primary computational platform.
    "},{"location":"resources/working_groups_and_postdocs/#opportunities-for-collaboration","title":"Opportunities for Collaboration","text":"
    • Joining Working Groups:
    • Opportunity to collaborate with working groups within ESIIL, subject to invitation.
    • Networking and Collaboration:
    • Engaging in regular meetings and seminars for networking.
    "},{"location":"resources/working_groups_and_postdocs/#additional-responsibilities","title":"Additional Responsibilities","text":"
    • Reviewing Working Group Applications:
    • Assisting in the review process of working group applications.
    • Supporting Working Groups:
    • Providing support to working groups in various capacities, even if not an author.
    "},{"location":"resources/working_groups_and_postdocs/#note","title":"Note","text":"
    • Primary research commitments should be prioritized unless otherwise directed by supervisors or ESIIL's administrative body.

    This framework ensures that ESIIL postdocs balance independent research with collaborative opportunities, adhering to open data principles, and utilizing designated platforms for their work.

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