report_template.Rmd

---
title: "`r params$title`"
params:
  #   - Noise
  #   - Cetaceans
  #   - Pinnipeds
  #   - Cetaceans AND Noise
  #   - Pinnipeds AND Noise
  title: ''
  technology: Marine Energy (General)
  aoi_wkt: POLYGON ((-82.84218 26.44127, -81.89644 24.29934, -78.92945 24.86505, -78.89557
    26.67814, -82.84218 26.44127))
  stressors: null
  receptors: null
  stressor_receptors: null
  lit_tethys: no
  lit_ferc: no
  spatial: yes
  mgt_tethys: no
  # title: "Test Report"
  # technology: "Ocean Current"
  # aoi_wkt: "POLYGON ((-68.37953 44.857, -67.38415 43.89608, -64.21114 45.0997, -64.90587 45.89335, -68.37953 44.857))"
  # stressors: 
  # receptors:
  # stressor_receptors:
  # lit_tethys: true
  # lit_ferc: false
  # spatial: true
  # mgt_tethys: false
output:
  pdf_document:
    toc: true
    toc_depth: 4
    number_sections: true
    #keep_md: yes
    latex_engine: xelatex
  html_document:
    toc: true
    toc_depth: 4
    toc_float: true
    number_sections: true
    mathjax: null
  word_document:
    toc: true
    toc_depth: 4
    number_sections: true
    #keep_md: yes
editor_options: 
  chunk_output_type: console
always_allow_html: true
---

```{r setup, include=F}
# render("report_template.Rmd", output_file="report_template.pdf", output_format="pdf_document")
# render("report_template.Rmd", output_file="report_template.docx", output_format="word_document")
# render("report_template.Rmd", output_file="report_template.html", output_format="html_document")
knitr::opts_chunk$set(echo = F, warning = F, message = F, eval = T)
```

```{r init}
source(here::here("functions.R")) # libraries, db connection object (con)
# rmd_params <- readRDS(here("data/tmp_rmd_params.rds"))
```

# Configuration

```{r}
# params = list(technology="Cross Flow")
#tech_choices <- read_csv(here("report/data/tech_choices.csv"))
# TODO: integrate finer detail in tech_choices.csv with tags.csv
tech <- read_csv(here("data/tags.csv")) %>% 
  filter(facet == "technology") %>% 
  select(tag = item_label, tag_parent, tag_img) %>% 
  filter(tag == params$technology) %>% 
  mutate(
    img_local = map_chr(
      tag_img, 
      function(url){
        # url <- tech$tag_img
        fname         <- urltools::path(url) %>% url_decode() %>% basename()
        img_local <- file.path(here("report/data/tech_images"), fname)
        if (!file.exists(img_local))
          download.file(url, img_local)
        img_local}))

stopifnot(nrow(tech) == 1)

bullets <- function(tags, indent=1){
  glue("{strrep(' ', indent*2)}- {tags}", .trim = F) %>% 
  paste(collapse = "\n") %>% 
  cat()
}
```

## Technology: `r glue("{params$technology}")`

![](`r ifelse(knitr::is_html_output(), tech$tag_img, tech$img_local)`)

## Stressors & Receptors

* Stressors

```{r, results='asis'}
bullets(params$stressors)
```

* Receptors

```{r, results='asis'}
bullets(params$receptors)
```

* Stressor-Receptors

```{r, results='asis'}
bullets(params$stressor_receptors)
```

## Location

```{r map, dpi=150, out.width = '100%'}
#{r map, out.width = '100%', cache=F}
# params = list(aoi_wkt = "POLYGON ((-67.06819 44.99416, -67.1857 44.94707, -67.21651 44.88058, -67.15834 44.78871, -67.04385 44.81789, -66.91015 44.86279, -67.06819 44.99416))")

if (is.null(params$aoi_wkt) || str_trim(params$aoi_wkt) == ""){
  cat("Please draw a Location to include a map here.")
} else {
    
  aoi_sf <- tibble(
    geometry = params$aoi_wkt) %>%
    st_as_sf(wkt = "geometry", crs=4326)

  if (knitr::is_html_output()){
    # TODO: inset map showing larger area
    m <- leaflet(
      options = leafletOptions(
        zoomControl = F,
        attributionControl = F)) %>%
      addProviderTiles(providers$Esri.OceanBasemap) %>%
      addPolygons(data = aoi_sf)
    m
  } else {
    
    
    # OLD (slow):
    #   m_png <- tempfile(fileext = ".png")
    #   mapshot(m, file = m_png)
    #   include_graphics(m_png)
    # NEW: https://github.com/dkahle/ggmap/issues/160 ...
    
    bb <- st_bbox(aoi_sf) %>% as.vector()
    bb_m <- 0.15
    bb_x <- expand_range(c(bb[1], bb[3]), bb_m)
    bb_y <- expand_range(c(bb[2], bb[4]), bb_m)
    bb <- c(bb_x[1], bb_y[1], bb_x[2], bb_y[2])
    
    # Convert to 3857
    aoi_3857 <- st_transform(aoi_sf, 3857)
    
    bkmap <- get_map(location = bb, source = "stamen")
    
    # Define a function to fix the bbox to be in EPSG:3857
    ggmap_bbox <- function(map) {
      if (!inherits(map, "ggmap")) stop("map must be a ggmap object")
      # Extract the bounding box (in lat/lon) from the ggmap to a numeric vector, 
      # and set the names to what sf::st_bbox expects:
      map_bbox <- setNames(unlist(attr(map, "bb")), 
                           c("ymin", "xmin", "ymax", "xmax"))
      
      # Coonvert the bbox to an sf polygon, transform it to 3857, 
      # and convert back to a bbox (convoluted, but it works)
      bbox_3857 <- st_bbox(st_transform(st_as_sfc(st_bbox(map_bbox, crs = 4326)), 3857))
      
      # Overwrite the bbox of the ggmap object with the transformed coordinates 
      attr(map, "bb")$ll.lat <- bbox_3857["ymin"]
      attr(map, "bb")$ll.lon <- bbox_3857["xmin"]
      attr(map, "bb")$ur.lat <- bbox_3857["ymax"]
      attr(map, "bb")$ur.lon <- bbox_3857["xmax"]
      map
    }
    
    # Use the function:
    bkmap <- ggmap_bbox(bkmap)
    
    ggmap(bkmap) + 
      coord_sf(crs = st_crs(3857)) + # force the ggplot2 map to be in 3857
      geom_sf(data = aoi_3857, inherit.aes = F, fill="red", alpha=.5)
  }
}
```

# Literature

## Stressors

Stressors are potentially harmful environmental effects from technology for marine renewable energy.

```{r stressors, results='asis'}
# params = list(stressors = c("Noise", "EMF"))
if (params$lit_tethys & !is.null(params$stressors))
  knit_tethys_literature_from_tags(params$stressors)
```

## Receptors

Receptors are species, habitats and human activities of environmental concern.

```{r receptors, results='asis'}
# params = list(receptors = c("Marine Mammals", "Fish"))
if (params$lit_tethys & !is.null(params$receptors))
  knit_tethys_literature_from_tags(params$receptors)
```

## Stressor-Receptors

```{r stressor_receptors, results='asis'}
# params = list(stressor_receptors = c("Marine Mammals AND Noise", "Fish AND EMF"))
if (params$lit_tethys & !is.null(params$stressor_receptors))
  knit_tethys_literature_from_tags(params$stressor_receptors)
```

# Spatial

Spatial data of Receptors are extracted for the Location from datasets harvested predominantly from [MarineCadastre.gov](https://MarineCadastre.gov).

```{r, results='asis'}
# datasets_gsheet2db ----
# datasets_marinecadastre.gov.csv - Google Sheet
#   edit online: https://docs.google.com/spreadsheets/d/1MMVqPr39R5gAyZdY2iJIkkIdYqgEBJYQeGqDk1z-RKQ/edit#gid=0
# datasets_gsheet2db()

# params = list(
#   receptors = c("Marine Mammals", "Fish"),
#   aoi_wkt = "POLYGON ((-67.06819 44.99416, -67.1857 44.94707, -67.21651 44.88058, -67.15834 44.78871, -67.04385 44.81789, -66.91015 44.86279, -67.06819 44.99416))")

if (params$spatial & !is.null(params$receptors)){
  datasets <- tbl(con, "datasets") %>% 
    collect() %>%
    replace_na(list(buffer_km = 0)) %>% 
    select(-notes, -issues) %>% 
    separate_rows(tags, sep = ";") %>% 
    rename(tag = tags) %>% 
    filter(
      tag %in% params$receptors) %>% 
    arrange(tag, title)
  
  lapply(1:nrow(datasets), function(i_datasets) {
    knit_expand('_spatial-tag-dataset.Rmd') }) %>% 
    knit_child(text = unlist(.), quiet = T) %>% 
    cat(sep = '\n\n')
}
```