Release 6.2 (#81)

* black + isort

* add .git-blame-ignore-revs

* add ci to dev branch

* add citation file

* move to pyproject toml
delete setup.py

* Update CITATION.cff

Co-authored-by: Mike Taves <mwtoews@gmail.com>

* fix #75

* up version

---------

Co-authored-by: Mike Taves <mwtoews@gmail.com>

.git-blame-ignore-revs

@@ -0,0 +1,2 @@
+# Migrate code style to black
+998b86fc128e35f1506e3d4facb169c558679bde

.github/workflows/ci.yml

@@ -5,9 +5,11 @@ on:
  push:
  branches:
  - master
+ - dev
  pull_request:
  branches:
  - master
+ - dev
 
 jobs:
  test:

CITATION.cff

@@ -0,0 +1,25 @@
+cff-version: 1.2.0
+message: "If you use this software, please cite it as below."
+authors:
+ - family-names: "Bakker"
+ given-names: "Mark"
+ orcid: "https://orcid.org/0000-0002-5629-2861"
+title: "TimML"
+url: "https://github.com/mbakker7/timml"
+
+preferred-citation:
+ type: article
+ authors:
+ - family-names: "Bakker"
+ given-names: "Mark"
+ orcid: "https://orcid.org/0000-0002-5629-2861"
+ - family-names: "Strack" 
+ given-names: "Otto D.L."
+ doi: "10.1016/S0022-1694(02)00319-0"
+ journal: "Journal of Hydrology"
+ title: "Analytic elements for multiaquifer flow"
+ volume: 271
+ number: 1
+ start: 119
+ end: 129
+ year: 2003

notebooks/benchmarking_besselaes.ipynb

@@ -24,7 +24,7 @@
  "import pandas as pd\n",
  "\n",
  "import matplotlib as mpl\n",
- "import matplotlib.pyplot as plt\n"
+ "import matplotlib.pyplot as plt"
  ]
  },
  {
@@ -72,7 +72,7 @@
  "def ctxt(val):\n",
  " bg = cmap(norm(val))\n",
  " c = \"White\" if np.mean(bg[:3]) < 0.4 else \"Black\"\n",
- " return f\"color: {c}\"\n"
+ " return f\"color: {c}\""
  ]
  },
  {
@@ -144,7 +144,7 @@
  " ls2 = timml.HeadLineSinkString(ml, xy=xy2, hls=hls2, layers=0)\n",
  " ls3 = timml.HeadLineSinkString(ml, xy=xy3, hls=hls3, layers=0)\n",
  " ls4 = timml.HeadLineSinkString(ml, xy=xy4, hls=hls4, layers=0)\n",
- " \n",
+ "\n",
  " return ml"
  ]
  },
@@ -179,31 +179,29 @@
  "print(timml.bessel.bessel) # print module name to check if switch works\n",
  "\n",
  "for nproc in df_ls.index:\n",
- " \n",
  " ml = model1()\n",
- " \n",
+ "\n",
  " if nproc == 0:\n",
  " t_n = %timeit -o ml.solve(silent=True)\n",
  " else:\n",
  " t_n = %timeit -o ml.solve_mp(nproc=nproc, silent=True)\n",
- " \n",
+ "\n",
  " df_ls.loc[nproc, \"numba\"] = t_n.average\n",
  "\n",
  "# %%\n",
  "# Fortran\n",
- "timml.bessel.set_bessel_method(method=\"fortran\") \n",
+ "timml.bessel.set_bessel_method(method=\"fortran\")\n",
  "print(timml.bessel.bessel) # print module name to check if switch works\n",
  "\n",
  "for nproc in df_ls.index:\n",
- "\n",
  " ml = model1()\n",
  "\n",
  " if nproc == 0:\n",
  " t_f = %timeit -o ml.solve(silent=True)\n",
  " else:\n",
  " t_f = %timeit -o ml.solve_mp(nproc=nproc, silent=True)\n",
- " \n",
- " df_ls.loc[nproc, \"fortran\"] = t_f.average\n"
+ "\n",
+ " df_ls.loc[nproc, \"fortran\"] = t_f.average"
  ]
  },
  {
@@ -308,7 +306,7 @@
  "norm = mpl.colors.LogNorm(vmin=50, vmax=100)\n",
  "\n",
  "df_ls.index.name = \"nproc\"\n",
- "(df_ls * 1e3).style.applymap(cbg).applymap(ctxt)\n"
+ "(df_ls * 1e3).style.applymap(cbg).applymap(ctxt)"
  ]
  },
  {
@@ -471,15 +469,45 @@
  " layers = np.arange(np.sum(z_dw <= ml.aq.zaqbot))\n",
  " last_lay_dw = layers[-1]\n",
  "\n",
- " inhom = timml.BuildingPit(ml, xy, kaq=kh_arr, z=z[1:], topboundary=\"conf\", \n",
- " c=c[1:], order=4, ndeg=3, layers=layers)\n",
+ " inhom = timml.BuildingPit(\n",
+ " ml,\n",
+ " xy,\n",
+ " kaq=kh_arr,\n",
+ " z=z[1:],\n",
+ " topboundary=\"conf\",\n",
+ " c=c[1:],\n",
+ " order=4,\n",
+ " ndeg=3,\n",
+ " layers=layers,\n",
+ " )\n",
  "\n",
- " timml.HeadLineSink(ml, x1=-l/2+offset, y1=b/2-offset, x2=l/2-offset, y2=b/2-offset, hls=h_bem, \n",
- " layers=np.arange(last_lay_dw+1))\n",
- " timml.HeadLineSink(ml, x1=-l/2+offset, y1=0, x2=l/2-offset, y2=0, hls=h_bem, \n",
- " layers=np.arange(last_lay_dw+1))\n",
- " timml.HeadLineSink(ml, x1=-l/2+offset, y1=-b/2+offset, x2=l/2-offset, y2=-b/2+offset, hls=h_bem, \n",
- " layers=np.arange(last_lay_dw+1))\n",
+ " timml.HeadLineSink(\n",
+ " ml,\n",
+ " x1=-l / 2 + offset,\n",
+ " y1=b / 2 - offset,\n",
+ " x2=l / 2 - offset,\n",
+ " y2=b / 2 - offset,\n",
+ " hls=h_bem,\n",
+ " layers=np.arange(last_lay_dw + 1),\n",
+ " )\n",
+ " timml.HeadLineSink(\n",
+ " ml,\n",
+ " x1=-l / 2 + offset,\n",
+ " y1=0,\n",
+ " x2=l / 2 - offset,\n",
+ " y2=0,\n",
+ " hls=h_bem,\n",
+ " layers=np.arange(last_lay_dw + 1),\n",
+ " )\n",
+ " timml.HeadLineSink(\n",
+ " ml,\n",
+ " x1=-l / 2 + offset,\n",
+ " y1=-b / 2 + offset,\n",
+ " x2=l / 2 - offset,\n",
+ " y2=-b / 2 + offset,\n",
+ " hls=h_bem,\n",
+ " layers=np.arange(last_lay_dw + 1),\n",
+ " )\n",
  "\n",
  " return ml"
  ]
@@ -511,33 +539,31 @@
  "source": [
  "df_bp = pd.DataFrame(index=nproc_list, columns=[\"numba\", \"fortran\"])\n",
  "\n",
- "timml.bessel.set_bessel_method(method=\"numba\") \n",
+ "timml.bessel.set_bessel_method(method=\"numba\")\n",
  "print(timml.bessel.bessel)\n",
  "\n",
  "for nproc in df_bp.index:\n",
- "\n",
  " ml = model2()\n",
  "\n",
  " if nproc == 0:\n",
  " t_n = %timeit -o ml.solve(silent=True)\n",
  " else:\n",
  " t_n = %timeit -o ml.solve_mp(nproc=nproc, silent=True)\n",
- " \n",
+ "\n",
  " df_bp.loc[nproc, \"numba\"] = t_n.average\n",
  "\n",
  "timml.bessel.set_bessel_method(method=\"fortran\")\n",
  "print(timml.bessel.bessel)\n",
  "\n",
  "for nproc in df_bp.index:\n",
- "\n",
  " ml = model2()\n",
- " \n",
+ "\n",
  " if nproc == 0:\n",
  " t_f = %timeit -o ml.solve(silent=True)\n",
  " else:\n",
  " t_f = %timeit -o ml.solve_mp(nproc=nproc, silent=True)\n",
- " \n",
- " df_bp.loc[nproc, \"fortran\"] = t_f.average\n"
+ "\n",
+ " df_bp.loc[nproc, \"fortran\"] = t_f.average"
  ]
  },
  {
@@ -770,15 +796,48 @@
  "source": [
  "def model3():\n",
  " ml = timml.ModelMaq(kaq=[10, 20], z=[20, 0, -10, -30], c=[4000])\n",
- " xy1 = [(0, 600), (-100, 400), (-100, 200), (100, 100), (300, 100), (500, 100),\n",
- " (700, 300), (700, 500), (600, 700), (400, 700), (200, 600)]\n",
- " p1 = timml.PolygonInhomMaq(ml, xy=xy1, \n",
- " kaq=[2, 80], z=[20, 0, -10, -30], c=[500], \n",
- " topboundary='conf', order=4, ndeg=2)\n",
- " xy2 = [(0, 600), (200, 600), (400, 700), (400, 900), (200, 1100), (0, 1000), (-100, 800)]\n",
- " p2 = timml.PolygonInhomMaq(ml, xy=xy2, \n",
- " kaq=[2, 8], z=[20, 0, -10, -30], c=[50], \n",
- " topboundary='conf', order=4, ndeg=2)\n",
+ " xy1 = [\n",
+ " (0, 600),\n",
+ " (-100, 400),\n",
+ " (-100, 200),\n",
+ " (100, 100),\n",
+ " (300, 100),\n",
+ " (500, 100),\n",
+ " (700, 300),\n",
+ " (700, 500),\n",
+ " (600, 700),\n",
+ " (400, 700),\n",
+ " (200, 600),\n",
+ " ]\n",
+ " p1 = timml.PolygonInhomMaq(\n",
+ " ml,\n",
+ " xy=xy1,\n",
+ " kaq=[2, 80],\n",
+ " z=[20, 0, -10, -30],\n",
+ " c=[500],\n",
+ " topboundary=\"conf\",\n",
+ " order=4,\n",
+ " ndeg=2,\n",
+ " )\n",
+ " xy2 = [\n",
+ " (0, 600),\n",
+ " (200, 600),\n",
+ " (400, 700),\n",
+ " (400, 900),\n",
+ " (200, 1100),\n",
+ " (0, 1000),\n",
+ " (-100, 800),\n",
+ " ]\n",
+ " p2 = timml.PolygonInhomMaq(\n",
+ " ml,\n",
+ " xy=xy2,\n",
+ " kaq=[2, 8],\n",
+ " z=[20, 0, -10, -30],\n",
+ " c=[50],\n",
+ " topboundary=\"conf\",\n",
+ " order=4,\n",
+ " ndeg=2,\n",
+ " )\n",
  " rf = timml.Constant(ml, xr=1000, yr=0, hr=40)\n",
  " uf = timml.Uflow(ml, slope=0.002, angle=-45)\n",
  " w = timml.Well(ml, xw=400, yw=400, Qw=500, rw=0.2, layers=0)\n",
@@ -812,33 +871,31 @@
  "source": [
  "df = pd.DataFrame(index=nproc_list, columns=[\"numba\", \"fortran\"])\n",
  "\n",
- "timml.bessel.set_bessel_method(method=\"numba\") \n",
+ "timml.bessel.set_bessel_method(method=\"numba\")\n",
  "print(timml.bessel.bessel)\n",
  "\n",
  "for nproc in df.index:\n",
- "\n",
  " ml = model3()\n",
  "\n",
  " if nproc == 0:\n",
  " t_n = %timeit -o ml.solve(silent=True)\n",
  " else:\n",
  " t_n = %timeit -o ml.solve_mp(nproc=nproc, silent=True)\n",
- " \n",
+ "\n",
  " df.loc[nproc, \"numba\"] = t_n.average\n",
  "\n",
- "timml.bessel.set_bessel_method(method=\"fortran\") \n",
+ "timml.bessel.set_bessel_method(method=\"fortran\")\n",
  "print(timml.bessel.bessel)\n",
  "\n",
  "for nproc in df.index:\n",
- "\n",
  " ml = model3()\n",
- " \n",
+ "\n",
  " if nproc == 0:\n",
  " t_f = %timeit -o ml.solve(silent=True)\n",
  " else:\n",
  " t_f = %timeit -o ml.solve_mp(nproc=nproc, silent=True)\n",
- " \n",
- " df.loc[nproc, \"fortran\"] = t_f.average\n"
+ "\n",
+ " df.loc[nproc, \"fortran\"] = t_f.average"
  ]
  },
  {

notebooks/circareasink_example.ipynb

@@ -67,9 +67,9 @@
  "for i in range(len(x)):\n",
  " qx[i], qy = ml.disvec(x[i], 1e-6)\n",
  "plt.plot(x, qx)\n",
- "qxb = N * np.pi * R ** 2 / (2 * np.pi * R)\n",
- "plt.axhline(qxb, color='r', ls='--')\n",
- "plt.axhline(-qxb, color='r', ls='--');"
+ "qxb = N * np.pi * R**2 / (2 * np.pi * R)\n",
+ "plt.axhline(qxb, color=\"r\", ls=\"--\")\n",
+ "plt.axhline(-qxb, color=\"r\", ls=\"--\");"
  ]
  },
  {
@@ -101,7 +101,7 @@
  "source": [
  "N = 0.001\n",
  "R = 100\n",
- "Q = N * np.pi * R ** 2\n",
+ "Q = N * np.pi * R**2\n",
  "ml = tml.ModelMaq(kaq=5, z=[10, 0])\n",
  "ca = tml.CircAreaSink(ml, xc=-200, yc=0, R=100, N=0.001)\n",
  "w = tml.Well(ml, 200, 0, Qw=Q, rw=0.1)\n",
@@ -140,7 +140,7 @@
  "source": [
  "N = 0.001\n",
  "R = 100\n",
- "Q = N * np.pi * R ** 2\n",
+ "Q = N * np.pi * R**2\n",
  "ml = tml.ModelMaq(kaq=5, z=[10, 0])\n",
  "ca = tml.CircAreaSink(ml, xc=-200, yc=0, R=100, N=0.001)\n",
  "w = tml.Well(ml, 200, 0, Qw=Q, rw=0.1)\n",
@@ -184,15 +184,15 @@
  "source": [
  "N = 0.001\n",
  "R = 100\n",
- "Q = N * np.pi * R ** 2\n",
+ "Q = N * np.pi * R**2\n",
  "ml = tml.ModelMaq(kaq=[5, 20], z=[20, 12, 10, 0], c=[1000])\n",
  "ca = tml.CircAreaSink(ml, xc=0, yc=0, R=100, N=0.001)\n",
  "w = tml.Well(ml, 0, 0, Qw=Q, rw=0.1, layers=1)\n",
  "rf = tml.Constant(ml, 1000, 0, 0)\n",
  "ml.solve()\n",
  "x = np.linspace(-200, 200, 100)\n",
  "h = ml.headalongline(x, 0)\n",
- "plt.plot(x, h[0]);\n",
+ "plt.plot(x, h[0])\n",
  "plt.plot(x, h[1]);"
  ]
  },
@@ -215,7 +215,7 @@
  "source": [
  "x = np.linspace(-1000, 1000, 101)\n",
  "h = ml.headalongline(x, 0)\n",
- "plt.plot(x, h[0]);\n",
+ "plt.plot(x, h[0])\n",
  "plt.plot(x, h[1]);"
  ]
  },

notebooks/circular_buildingpit.ipynb

@@ -39,7 +39,7 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "R = 100.0 # radius of building pit"
+ "R = 100.0  # radius of building pit"
  ]
  },
  {
@@ -346,16 +346,16 @@
  "Qr = disrvec(r) * 2 * np.pi * r\n",
  "plt.figure(figsize=(10, 3))\n",
  "plt.subplot(121)\n",
- "plt.plot(r, h, label='head with wall')\n",
- "plt.plot(r, head_nowall(r), '--', label='head no wall')\n",
- "plt.xlabel('r (m)')\n",
- "plt.ylabel('head (m)')\n",
+ "plt.plot(r, h, label=\"head with wall\")\n",
+ "plt.plot(r, head_nowall(r), \"--\", label=\"head no wall\")\n",
+ "plt.xlabel(\"r (m)\")\n",
+ "plt.ylabel(\"head (m)\")\n",
  "plt.grid()\n",
  "plt.legend()\n",
  "plt.subplot(122)\n",
  "plt.plot(r, Qr)\n",
- "plt.xlabel('r (m)')\n",
- "plt.ylabel('$Q_r$ (m$^2$/d)')\n",
+ "plt.xlabel(\"r (m)\")\n",
+ "plt.ylabel(\"$Q_r$ (m$^2$/d)\")\n",
  "plt.grid()\n",
  "plt.tight_layout()"
  ]