minor fixes and changes (#530)

* minor fixes and changes

* reinstate fix

Author: OnnoEbbens

.gitignore

@@ -156,3 +156,5 @@ tests/data/mfoutput/*
 docs/examples/*/
 !docs/examples/data/
 !docs/examples/data/chloride_hbossche.nc
+
+docs/data_sources/*

docs/examples/09_schoonhoven.ipynb

@@ -93,7 +93,7 @@
     "if not os.path.isfile(fname_bgt):\n",
     "    raise (\n",
     "        Exception(\n",
-    "            f\"{fname_bgt} not found. Please run notebook 02_surface_water.ipynb first\"\n",
+    "            f\"{fname_bgt} not found. Please run notebook 02_surface_water.ipynb in the 'data_sources' directory first\"\n",
     "        )\n",
     "    )\n",
     "bgt = gpd.read_file(fname_bgt)"
@@ -857,8 +857,22 @@
   }
  ],
  "metadata": {
+  "kernelspec": {
+   "display_name": "venv",
+   "language": "python",
+   "name": "python3"
+  },
   "language_info": {
-   "name": "python"
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.10"
   }
  },
  "nbformat": 4,

docs/utilities/13_plot_methods.ipynb

@@ -77,7 +77,14 @@
    "source": [
     "model_name = \"Schoonhoven\"\n",
     "model_ws = os.path.join(\"..\", \"data_sources\", \"schoonhoven\")\n",
-    "ds = xr.open_dataset(os.path.join(model_ws, f\"{model_name}.nc\"))\n",
+    "fname_nc = os.path.join(model_ws, f\"{model_name}.nc\")\n",
+    "if not os.path.isfile(fname_nc):\n",
+    "    raise (\n",
+    "        Exception(\n",
+    "            f\"{fname_nc} not found. Please run notebook 09_schoonhoven.ipynb in the 'examples' directory first\"\n",
+    "        )\n",
+    "    )\n",
+    "ds = xr.open_dataset(fname_nc)\n",
     "\n",
     "# add calculated heads\n",
     "ds[\"head\"] = nlmod.gwf.get_heads_da(ds)\n",
@@ -228,6 +235,7 @@
     "    cmap(i)\n",
     "    for i in np.linspace(0, int((len(df) - 1) * cmap.N / len(df)), len(df), dtype=int)\n",
     "]\n",
+    "df['tubecolor'] = 'white'\n",
     "gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(df.x, df.y))\n",
     "\n",
     "# plot cross section\n",
@@ -241,7 +249,8 @@
     "    df,\n",
     "    legend=True,\n",
     "    max_dist=max_dist,\n",
-    "    filter_kwargs={'alpha':0.5, 'zorder':10},\n",
+    "    filter_patch_kwargs={'alpha':0.5, 'zorder':10},\n",
+    "    filter_rect_kwargs={'alpha':0.5, 'zorder':10},\n",
     "    tubeline_kwargs={'alpha':0.5},\n",
     "    legend_kwds={\"loc\": (0, 1), \"frameon\": False, \"ncol\": 7},\n",
     ")\n",
@@ -359,8 +368,22 @@
   }
  ],
  "metadata": {
+  "kernelspec": {
+   "display_name": "venv",
+   "language": "python",
+   "name": "python3"
+  },
   "language_info": {
-   "name": "python"
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.10"
   }
  },
  "nbformat": 4,

docs/workflows/03_aggregating_surface_water.ipynb

@@ -69,7 +69,7 @@
     "if not os.path.isfile(fname_bgt):\n",
     "    raise (\n",
     "        Exception(\n",
-    "            f\"{fname_bgt} not found. Please run notebook 02_surface_water.ipynb first\"\n",
+    "            f\"{fname_bgt} not found. Please run notebook 02_surface_water.ipynb in the 'data_sources' directory first\"\n",
     "        )\n",
     "    )\n",
     "bgt = gpd.read_file(fname_bgt)"
@@ -635,8 +635,22 @@
   }
  ],
  "metadata": {
+  "kernelspec": {
+   "display_name": "venv",
+   "language": "python",
+   "name": "python3"
+  },
   "language_info": {
-   "name": "python"
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.10"
   }
  },
  "nbformat": 4,

nlmod/plot/dcs.py

@@ -515,7 +515,8 @@ def plot_wells(
         legend_kwds=None,
         max_dist=None,
         sort_by_dist=True,
-        filter_kwargs=None,
+        filter_patch_kwargs=None,
+        filter_rect_kwargs=None,
         tubeline_kwargs=None,
     ):
         """plot filter screens in cross section from a DataFrame
@@ -561,9 +562,14 @@ def plot_wells(
             by default None
         sort_by_dist : bool, optional
             if True the values are sorted by distance along the cross section line.
-        filter_kwargs : None, optional
+        filter_patch_kwargs : None, optional
             additional keyword arguments passed to the PatchCollection of the
-            filters.
+            filters. These keyword arguments are typically for how the rectangles
+            appear in the plot.
+        filter_rect_kwargs : None, optional
+            additional keyword arguments passed to the Rectangle shape of the
+            filters. These keyword arguments are typically for how the rectangles
+            appear in the legend.
         tubeline_kwargs : None, optional
             additional keyword arguments passed to the tube line plot.
         **kwargs
@@ -625,8 +631,10 @@ def plot_wells(
                     df[parname] = color
 
         # parse filter and tube kwargs
-        if filter_kwargs is None:
-            filter_kwargs = {}
+        if filter_patch_kwargs is None:
+            filter_patch_kwargs = {}
+        if filter_rect_kwargs is None:
+            filter_rect_kwargs = {}
         if tubeline_kwargs is None:
             tubeline_kwargs = {}
 
@@ -676,10 +684,10 @@ def plot_wells(
                 (left, bottom_left_y),
                 filter_width,
                 height,
-                linewidth=linewidth,
                 facecolor=row["filtercolor_face"],
                 edgecolor=row["filtercolor_edge"],
                 label=name,
+                **filter_rect_kwargs,
             )
             rectangles.append(rect)
             legend_handles[name] = rect
@@ -689,7 +697,7 @@ def plot_wells(
             rectangles,
             facecolors=df["filtercolor_face"],
             edgecolors=df["filtercolor_edge"],
-            **filter_kwargs,
+            **filter_patch_kwargs,
         )
         self.ax.add_collection(patch_collection)