run pre-commits

Author: ocefpaf

docs/conf.py

@@ -114,7 +114,7 @@
         "relations.html",  # needs 'show_related': True theme option to display
         "searchbox.html",
         "donate.html",
-    ]
+    ],
 }
 
 
@@ -151,7 +151,7 @@
         "windrose Documentation",
         "Lionel Roubeyrie \\& Sebastien Celles",
         "manual",
-    )
+    ),
 ]
 
 
@@ -176,7 +176,7 @@
         "windrose",
         "One line description of project.",
         "Miscellaneous",
-    )
+    ),
 ]
 
 

notebooks/usage.ipynb

@@ -125,15 +125,15 @@
    "metadata": {},
    "source": [
     "After that, you can have a look at the computed values used to plot the\n",
-    "windrose with the ``ax._info`` dictionary : \n",
+    "windrose with the `ax._info` dictionary :\n",
     "\n",
-    "- ``ax._info['bins']`` :\n",
+    "- `ax._info['bins']` :\n",
     "  list of bins (limits) used for wind speeds. If not set in the call, bins\n",
-    "  will be set to 6 parts between wind speed min and max. \n",
-    "- ``ax._info['dir']`` : list of directions \"boundaries\" used to compute the\n",
+    "  will be set to 6 parts between wind speed min and max.\n",
+    "- `ax._info['dir']` : list of directions \"boundaries\" used to compute the\n",
     "  distribution by wind direction sector. This can be set by the nsector\n",
-    "  parameter (see below). \n",
-    "- ``ax._info['table']`` : the resulting table of\n",
+    "  parameter (see below).\n",
+    "- `ax._info['table']` : the resulting table of\n",
     "  the computation. It's a 2D histogram, where each line represents a wind\n",
     "  speed class, and each column represents a wind direction class.\n",
     "\n",
@@ -171,14 +171,22 @@
     "\n",
     "plt.bar(np.arange(16), wd_freq, align=\"center\")\n",
     "xlabels = (\n",
-    "    \"N\", \"\",\n",
-    "    \"N-E\", \"\",\n",
-    "    \"E\", \"\",\n",
-    "    \"S-E\", \"\",\n",
-    "    \"S\", \"\",\n",
-    "    \"S-O\", \"\",\n",
-    "    \"O\", \"\",\n",
-    "    \"N-O\", \"\",\n",
+    "    \"N\",\n",
+    "    \"\",\n",
+    "    \"N-E\",\n",
+    "    \"\",\n",
+    "    \"E\",\n",
+    "    \"\",\n",
+    "    \"S-E\",\n",
+    "    \"\",\n",
+    "    \"S\",\n",
+    "    \"\",\n",
+    "    \"S-O\",\n",
+    "    \"\",\n",
+    "    \"O\",\n",
+    "    \"\",\n",
+    "    \"N-O\",\n",
+    "    \"\",\n",
     ")\n",
     "xticks = np.arange(16)\n",
     "plt.gca().set_xticks(xticks)\n",
@@ -192,45 +200,45 @@
     "In addition of all the standard pyplot parameters, you can pass special\n",
     "parameters to control the windrose production. For the stacked histogram\n",
     "windrose, calling help(ax.bar) will give :\n",
-    "``bar(self, direction, var, **kwargs)`` method of\n",
-    "``windrose.WindroseAxes`` instance Plot a windrose in bar mode. For each\n",
+    "`bar(self, direction, var, **kwargs)` method of\n",
+    "`windrose.WindroseAxes` instance Plot a windrose in bar mode. For each\n",
     "var bins and for each sector, a colored bar will be draw on the axes.\n",
     "\n",
     "Mandatory:\n",
     "\n",
-    "- ``direction`` : 1D array - directions the wind blows from, North centred\n",
-    "- ``var`` : 1D array - values of the variable to compute. Typically the wind speeds\n",
+    "- `direction` : 1D array - directions the wind blows from, North centred\n",
+    "- `var` : 1D array - values of the variable to compute. Typically the wind speeds\n",
     "\n",
-    "Optional: \n",
+    "Optional:\n",
     "\n",
-    "- ``nsector`` : integer - number of sectors used to compute\n",
+    "- `nsector` : integer - number of sectors used to compute\n",
     "  the windrose table. If not set, nsectors=16, then each sector will be\n",
     "  360/16=22.5°, and the resulting computed table will be aligned with the\n",
     "  cardinals points.\n",
-    "- ``bins`` : 1D array or integer - number of bins, or a\n",
+    "- `bins` : 1D array or integer - number of bins, or a\n",
     "  sequence of bins variable. If not set, bins=6 between min(var) and\n",
     "  max(var).\n",
-    "- ``blowto`` : bool. If True, the windrose will be pi rotated,\n",
-    "  to show where the wind blow to (useful for pollutant rose). \n",
-    "- ``colors`` : string or tuple - one string color (``'k'`` or\n",
-    "  ``'black'``), in this case all bins will be plotted in this color; a\n",
+    "- `blowto` : bool. If True, the windrose will be pi rotated,\n",
+    "  to show where the wind blow to (useful for pollutant rose).\n",
+    "- `colors` : string or tuple - one string color (`'k'` or\n",
+    "  `'black'`), in this case all bins will be plotted in this color; a\n",
     "  tuple of matplotlib color args (string, float, rgb, etc), different\n",
-    "  levels will be plotted in different colors in the order specified. \n",
-    "- ``cmap`` : a cm Colormap instance from ``matplotlib.cm``. - if\n",
-    "  ``cmap == None`` and ``colors == None``, a default Colormap is used. \n",
-    "- ``edgecolor`` : string - The string color each edge bar will be plotted.\n",
-    "  Default : no edgecolor \n",
-    "- ``opening`` : float - between 0.0 and 1.0, to\n",
-    "  control the space between each sector (1.0 for no space) \n",
-    "- ``mean_values`` : Bool - specify wind speed statistics with\n",
+    "  levels will be plotted in different colors in the order specified.\n",
+    "- `cmap` : a cm Colormap instance from `matplotlib.cm`. - if\n",
+    "  `cmap == None` and `colors == None`, a default Colormap is used.\n",
+    "- `edgecolor` : string - The string color each edge bar will be plotted.\n",
+    "  Default : no edgecolor\n",
+    "- `opening` : float - between 0.0 and 1.0, to\n",
+    "  control the space between each sector (1.0 for no space)\n",
+    "- `mean_values` : Bool - specify wind speed statistics with\n",
     "  direction=specific mean wind speeds. If this flag is specified, var is\n",
     "  expected to be an array of mean wind speeds corresponding to each entry\n",
-    "  in ``direction``. These are used to generate a distribution of wind\n",
-    "  speeds assuming the distribution is Weibull with shape factor = 2. \n",
-    "- ``weibull_factors`` : Bool - specify wind speed statistics with\n",
+    "  in `direction`. These are used to generate a distribution of wind\n",
+    "  speeds assuming the distribution is Weibull with shape factor = 2.\n",
+    "- `weibull_factors` : Bool - specify wind speed statistics with\n",
     "  direction=specific weibull scale and shape factors. If this flag is\n",
-    "  specified, var is expected to be of the form [[7,2], ...., [7.5,1.9]]\n",
-    "  where var[i][0] is the weibull scale factor and var[i][1] is the shape\n",
+    "  specified, var is expected to be of the form \\[\\[7,2\\], ...., \\[7.5,1.9\\]\\]\n",
+    "  where var\\[i\\]\\[0\\] is the weibull scale factor and var\\[i\\]\\[1\\] is the shape\n",
     "  factor"
    ]
   },
@@ -268,7 +276,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "print(params)"
+    "print(f\"{params=}\")"
    ]
   },
   {
@@ -371,17 +379,20 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from windrose import WindroseAxes, plot_windrose\n",
-    "import seaborn as sns\n",
-    "from matplotlib import pyplot as plt\n",
     "import numpy as np\n",
     "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "from matplotlib import pyplot as plt\n",
     "\n",
-    "wind_data = pd.DataFrame({\n",
-    "    'ws': np.random.random(1200) * 6,\n",
-    "    'wd': np.random.random(1200) * 360,\n",
-    "    'month': np.repeat(range(1, 13), 100),\n",
-    "})\n",
+    "from windrose import WindroseAxes, plot_windrose\n",
+    "\n",
+    "wind_data = pd.DataFrame(\n",
+    "    {\n",
+    "        \"ws\": np.random.random(1200) * 6,\n",
+    "        \"wd\": np.random.random(1200) * 360,\n",
+    "        \"month\": np.repeat(range(1, 13), 100),\n",
+    "    }\n",
+    ")\n",
     "\n",
     "\n",
     "def plot_windrose_subplots(data, *, direction, var, color=None, **kwargs):\n",
@@ -390,39 +401,42 @@
     "    ax = WindroseAxes.from_ax(ax=ax)\n",
     "    plot_windrose(direction_or_df=data[direction], var=data[var], ax=ax, **kwargs)\n",
     "\n",
+    "\n",
     "# this creates the raw subplot structure with a subplot per value in month.\n",
     "g = sns.FacetGrid(\n",
     "    data=wind_data,\n",
     "    # the column name for each level a subplot should be created\n",
-    "    col='month',\n",
+    "    col=\"month\",\n",
     "    # place a maximum of 3 plots per row\n",
     "    col_wrap=3,\n",
-    "    subplot_kws={'projection': 'windrose'},\n",
+    "    subplot_kws={\"projection\": \"windrose\"},\n",
     "    sharex=False,\n",
     "    sharey=False,\n",
     "    despine=False,\n",
-    "    height=3.5\n",
+    "    height=3.5,\n",
     ")\n",
     "\n",
     "g.map_dataframe(\n",
     "    plot_windrose_subplots,\n",
-    "    direction='wd',\n",
-    "    var='ws',\n",
+    "    direction=\"wd\",\n",
+    "    var=\"ws\",\n",
     "    normed=True,\n",
     "    # manually set bins, so they match for each subplot\n",
     "    bins=(0.1, 1, 2, 3, 4, 5),\n",
     "    calm_limit=0.1,\n",
-    "    kind='bar'\n",
+    "    kind=\"bar\",\n",
     ")\n",
     "\n",
     "# make the subplots easier to compare, by having the same y-axis range\n",
     "y_ticks = range(0, 17, 4)\n",
     "for ax in g.axes:\n",
-    "    ax.set_legend(title='$m \\cdot s^{-1}$', bbox_to_anchor=(1.15, -.1), loc='lower right')\n",
+    "    ax.set_legend(\n",
+    "        title=\"$m \\cdot s^{-1}$\", bbox_to_anchor=(1.15, -0.1), loc=\"lower right\"\n",
+    "    )\n",
     "    ax.set_rgrids(y_ticks, y_ticks)\n",
     "\n",
     "# adjust the spacing between the subplots to have sufficient space between plots\n",
-    "plt.subplots_adjust(wspace=-.2)"
+    "plt.subplots_adjust(wspace=-0.2)"
    ]
   },
   {
@@ -437,8 +451,8 @@
    "metadata": {},
    "source": [
     "Instead of using object oriented approach like previously shown, some\n",
-    "\"shortcut\" functions have been defined: ``wrbox``, ``wrbar``,\n",
-    "``wrcontour``, ``wrcontourf``, ``wrpdf``. See [unit tests](https://github.com/python-windrose/windrose/blob/master/tests/test_windrose.py)."
+    "\"shortcut\" functions have been defined: `wrbox`, `wrbar`,\n",
+    "`wrcontour`, `wrcontourf`, `wrpdf`. See [unit tests](https://github.com/python-windrose/windrose/blob/master/tests/test_windrose.py)."
    ]
   },
   {
@@ -453,7 +467,7 @@
    "metadata": {},
    "source": [
     "windrose not only supports Numpy arrays. It also supports also Pandas\n",
-    "DataFrame. ``plot_windrose`` function provides most of plotting features\n",
+    "DataFrame. `plot_windrose` function provides most of plotting features\n",
     "previously shown."
    ]
   },
@@ -465,8 +479,6 @@
    "source": [
     "import pandas as pd\n",
     "\n",
-    "from windrose import plot_windrose\n",
-    "\n",
     "N = 500\n",
     "ws = np.random.random(N) * 6\n",
     "wd = np.random.random(N) * 360\n",
@@ -480,18 +492,18 @@
    "source": [
     "Mandatory:\n",
     "\n",
-    "- ``df``: Pandas DataFrame with ``DateTimeIndex`` as index\n",
-    "  and at least 2 columns (``'speed'`` and ``'direction'``).\n",
+    "- `df`: Pandas DataFrame with `DateTimeIndex` as index\n",
+    "  and at least 2 columns (`'speed'` and `'direction'`).\n",
     "\n",
-    "Optional: \n",
+    "Optional:\n",
     "\n",
-    "- ``kind`` : kind of plot (might be either, ``'contour'``, ``'contourf'``, ``'bar'``, ``'box'``, ``'pdf'``)\n",
-    "- ``var_name`` : name of var column name ; default value is ``VAR_DEFAULT='speed'``\n",
-    "- ``direction_name`` : name of direction column name ; default value is\n",
-    "  ``DIR_DEFAULT='direction'``\n",
-    "- ``clean_flag`` : cleanup data flag (remove\n",
-    "  data points with ``NaN``, ``var=0``) before plotting ; default value is\n",
-    "  ``True``."
+    "- `kind` : kind of plot (might be either, `'contour'`, `'contourf'`, `'bar'`, `'box'`, `'pdf'`)\n",
+    "- `var_name` : name of var column name ; default value is `VAR_DEFAULT='speed'`\n",
+    "- `direction_name` : name of direction column name ; default value is\n",
+    "  `DIR_DEFAULT='direction'`\n",
+    "- `clean_flag` : cleanup data flag (remove\n",
+    "  data points with `NaN`, `var=0`) before plotting ; default value is\n",
+    "  `True`."
    ]
   },
   {
@@ -500,7 +512,6 @@
    "source": [
     "## Video export\n",
     "\n",
-    "\n",
     "A video of plots can be exported. A playlist of videos is [available here](https://www.youtube.com/playlist?list=PLE9hIvV5BUzsQ4EPBDnJucgmmZ85D_b-W), see:\n",
     "\n",
     "[![Video1](http://img.youtube.com/vi/0u2RxtGgEFo/0.jpg)](https://www.youtube.com/watch?v=0u2RxtGgEFo)\n",
@@ -539,7 +550,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,

notebooks/windrose_sample_poitiers_csv.ipynb

@@ -161,7 +161,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,

samples/example_animate.py

@@ -1,5 +1,4 @@
 #!/usr/bin/env python
-# -*- coding: utf-8 -*-
 
 """
 This sample need to be improve to provide
@@ -143,12 +142,12 @@ def main(
 
     # Create a video writer (ffmpeg can create MPEG files)
     FFMpegWriter = matplotlib.animation.writers["ffmpeg"]
-    metadata = dict(
-        title="windrose",
-        artist="windrose",
-        comment="""Made with windrose
+    metadata = {
+        "title": "windrose",
+        "artist": "windrose",
+        "comment": """Made with windrose
 http://www.github.com/scls19fr/windrose""",
-    )
+    }
     writer = FFMpegWriter(fps=fps, metadata=metadata)
 
     dt_start_process = datetime.datetime.now()
@@ -159,10 +158,10 @@ def main(
                 dt1 = df.index[0]
                 dt2 = df.index[-1]
                 td = dt2 - dt1
-                msg = """  Slide %s/%s
-    From %s
-      to %s
-      td %s""" % (
+                msg = """  Slide {}/{}
+    From {}
+      to {}
+      td {}""".format(
                     i + 1,
                     Nslides,
                     dt1,
@@ -175,13 +174,12 @@ def main(
                 td_remaining = (now - dt_start_process) / (i + 1) * remaining
                 logger.info(
                     """    Expected
-    time: %s
-  end at: %s
-"""
-                    % (td_remaining, now + td_remaining)
+    time: {}
+  end at: {}
+""".format(td_remaining, now + td_remaining)
                 )
 
-                title = "  From %s\n    to %s" % (dt1, dt2)
+                title = f"  From {dt1}\n    to {dt2}"
 
                 try:
                     ax = WindroseAxes.from_ax(