Improve output

docs/examples/02_surface_water.ipynb

@@ -223,7 +223,7 @@
    "metadata": {},
    "source": [
     "#### Save the data to use in other notebooks as well\n",
-    "We save the bgt-data to a geojson file, so we can use the data in other notebooks with surface water as well"
+    "We save the bgt-data to a GeoPackage file, so we can use the data in other notebooks with surface water as well"
    ]
   },
   {
@@ -233,8 +233,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fname_bgt = os.path.join(cachedir, \"bgt.geojson\")\n",
-    "bgt.to_file(fname_bgt, driver=\"GeoJSON\")"
+    "fname_bgt = os.path.join(cachedir, \"bgt.gpkg\")\n",
+    "bgt.to_file(fname_bgt)"
    ]
   },
   {
@@ -787,14 +787,6 @@
     "cbar = fig.colorbar(qm, shrink=1.0)\n",
     "cbar.set_label(\"head [m NAP]\")"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6e5833d6",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

docs/examples/09_schoonhoven.ipynb

@@ -91,7 +91,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fname_bgt = os.path.join(cachedir, \"bgt.geojson\")\n",
+    "fname_bgt = os.path.join(cachedir, \"bgt.gpkg\")\n",
     "if not os.path.isfile(fname_bgt):\n",
     "    raise (\n",
     "        Exception(\n",
@@ -207,7 +207,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "refinement_features = [(bgt[bgt[\"bronhouder\"] == \"L0002\"], 2)]\n",
+    "refinement_features = [(bgt[bgt[\"bronhouder\"] == \"L0002\"].dissolve().boundary, 2)]\n",
     "ds = nlmod.grid.refine(ds, refinement_features=refinement_features)"
    ]
   },
@@ -503,7 +503,7 @@
     "    colorbar_label=\"head [m NAP]\",\n",
     "    title=\"mean head\",\n",
     ")\n",
-    "bgt.plot(ax=pc.axes, edgecolor=\"k\", facecolor=\"none\");"
+    "bgt.dissolve().plot(ax=pc.axes, edgecolor=\"k\", facecolor=\"none\");"
    ]
   },
   {
@@ -745,7 +745,7 @@
     "line = ax.add_collection(lc)\n",
     "nlmod.plot.colorbar_inside(line, label=\"Travel time (years)\")\n",
     "\n",
-    "bgt.plot(ax=ax, edgecolor=\"k\", facecolor=\"none\")"
+    "bgt.dissolve().plot(ax=ax, edgecolor=\"k\", facecolor=\"none\")"
    ]
   },
   {

docs/examples/11_grid_rotation.ipynb

@@ -165,17 +165,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "bgt = nlmod.gwf.surface_water.get_gdf(ds)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e023dbca",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "bgt.plot()"
+    "bgt = nlmod.read.bgt.get_bgt(extent)\n",
+    "bgt = nlmod.gwf.surface_water.add_stages_from_waterboards(bgt, extent=extent)\n",
+    "bgt = nlmod.grid.gdf_to_grid(bgt, ds).set_index(\"cellid\")"
    ]
   },
   {

docs/examples/14_stromingen_example.ipynb

@@ -106,7 +106,7 @@
     "# wells = nlmod.read.get_wells(extent)  # no well data is available just yet\n",
     "\n",
     "# surface water features and levels\n",
-    "fname_bgt = os.path.join(cachedir, \"bgt.geojson\")\n",
+    "fname_bgt = os.path.join(cachedir, \"bgt.gpkg\")\n",
     "if not os.path.isfile(fname_bgt):\n",
     "    raise (\n",
     "        Exception(\n",

docs/examples/15_geotop.ipynb

@@ -40,7 +40,7 @@
    "outputs": [],
    "source": [
     "# Define an extent and a line from southwest to northeast through this extent\n",
-    "extent = [95000.0, 105000.0, 494000.0, 500000.0]\n",
+    "extent = [100000.0, 105000.0, 499800.0, 500000.0]\n",
     "line = LineString([(extent[0], extent[2]), (extent[1], extent[3])])"
    ]
   },
@@ -386,13 +386,13 @@
     "var = \"kh\"\n",
     "norm = matplotlib.colors.Normalize(0.0, 40.0)\n",
     "\n",
-    "f, axes = nlmod.plot.get_map(extent, ncols=2)\n",
+    "f, axes = nlmod.plot.get_map(extent, nrows=2, figsize=20)\n",
     "pc = nlmod.plot.data_array(regis[var].loc[layer], ax=axes[0], norm=norm)\n",
     "nlmod.plot.colorbar_inside(pc, bounds=[0.02, 0.05, 0.02, 0.9], ax=axes[0])\n",
     "nlmod.plot.title_inside(\"REGIS\", ax=axes[0])\n",
     "pc = nlmod.plot.data_array(regis[f\"{var}_gt\"].loc[layer], ax=axes[1], norm=norm)\n",
     "nlmod.plot.title_inside(\"GeoTOP\", ax=axes[1])\n",
-    "nlmod.plot.colorbar_inside(pc, bounds=[0.02, 0.05, 0.02, 0.9], ax=axes[1])"
+    "nlmod.plot.colorbar_inside(pc, bounds=[0.02, 0.05, 0.02, 0.9], ax=axes[1]);"
    ]
   },
   {

docs/examples/16_groundwater_transport.ipynb

@@ -67,7 +67,7 @@
     "start_time = \"2010-1-1\"\n",
     "starting_head = 1.0\n",
     "\n",
-    "municipalities = nlmod.read.boundaries.get_municipalities(extent=extent_hbossche)"
+    "municipalities = nlmod.read.administrative.get_municipalities(extent=extent_hbossche)"
    ]
   },
   {
@@ -600,14 +600,8 @@
   }
  ],
  "metadata": {
-  "kernelspec": {
-   "display_name": "artesia",
-   "language": "python",
-   "name": "python3"
-  },
   "language_info": {
-   "name": "python",
-   "version": "3.10.12"
+   "name": "python"
   }
  },
  "nbformat": 4,

docs/examples/17_unsaturated_zone_flow.ipynb

@@ -66,8 +66,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "model_name = \"test_uzf\"\n",
-    "model_ws = os.path.join(\"data\", model_name)\n",
+    "model_name = model_ws = \"model17\"\n",
     "figdir, cachedir = nlmod.util.get_model_dirs(model_ws)"
    ]
   },

nlmod/dims/grid.py

@@ -113,6 +113,28 @@ def xy_to_icell2d(xy, ds):
     return icell2d
 
 
+def xy_to_row_col(xy, ds):
+    """get the row and column values of a point defined by its x and y coordinates.
+
+    Parameters
+    ----------
+    xy : list, tuple
+        coordinates of ta point.
+    ds : xarary dataset
+        model dataset.
+
+    Returns
+    -------
+    row : int
+        number of the row value of a cell containing the xy point.
+    col : int
+        number of the column value of a cell containing the xy point.
+    """
+    row = np.abs(ds.y.data - xy[1]).argmin()
+    col = np.abs(ds.x.data - xy[0]).argmin()
+    return row, col
+
+
 def xyz_to_cid(xyz, ds=None, modelgrid=None):
     """get the icell2d value of a point defined by its x and y coordinates.
 
@@ -1142,11 +1164,10 @@ def gdf_to_data_array_struc(
 
 
 def gdf_to_da(
-    gdf, ds, column, agg_method=None, fill_value=np.NaN, min_total_overlap=0.0,
-    ix=None
+    gdf, ds, column, agg_method=None, fill_value=np.NaN, min_total_overlap=0.0, ix=None
 ):
     """Project vector data on a grid. Aggregate data if multiple
-    geometries are in a single cell. Supports structured and vertex grids. 
+    geometries are in a single cell. Supports structured and vertex grids.
     This method replaces gdf_to_data_array_struc.
 
     Parameters
@@ -1385,12 +1406,17 @@ def aggregate_vector_per_cell(gdf, fields_methods, modelgrid=None):
             gdf_copy["area_times_field"] = gdf_copy["area"] * gdf_copy[field]
 
             # skipna is not implemented by groupby therefore we use min_count=1
-            celldata[field] = (
-                gdf_copy.groupby(by="cellid")["area_times_field"].sum(min_count=1) /
-                gdf_copy.groupby(by="cellid")["area"].sum(min_count=1)
-            )
-
-        elif method in ("nearest", "length_weighted", "max_length", "max_area", "center_grid"):
+            celldata[field] = gdf_copy.groupby(by="cellid")["area_times_field"].sum(
+                min_count=1
+            ) / gdf_copy.groupby(by="cellid")["area"].sum(min_count=1)
+
+        elif method in (
+            "nearest",
+            "length_weighted",
+            "max_length",
+            "max_area",
+            "center_grid",
+        ):
             for cid, group in tqdm(gr, desc="Aggregate vector data"):
                 agg_dic = _get_aggregates_values(group, {field: method}, modelgrid)
 
@@ -1403,7 +1429,7 @@ def aggregate_vector_per_cell(gdf, fields_methods, modelgrid=None):
     return celldata
 
 
-def gdf_to_bool_da(gdf, ds, ix=None, buffer=0., **kwargs):
+def gdf_to_bool_da(gdf, ds, ix=None, buffer=0.0, **kwargs):
     """convert a GeoDataFrame with polygon geometries into a data array
     corresponding to the modelgrid in which each cell is 1 (True) if one or
     more geometries are (partly) in that cell.
@@ -1430,7 +1456,7 @@ def gdf_to_bool_da(gdf, ds, ix=None, buffer=0., **kwargs):
     return da
 
 
-def gdf_to_bool_ds(gdf, ds, da_name, keep_coords=None, ix=None, buffer=0., **kwargs):
+def gdf_to_bool_ds(gdf, ds, da_name, keep_coords=None, ix=None, buffer=0.0, **kwargs):
     """convert a GeoDataFrame with polygon geometries into a model dataset with
     a data_array named 'da_name' in which each cell is 1 (True) if one or more
     geometries are (partly) in that cell.
@@ -1465,7 +1491,7 @@ def gdf_to_bool_ds(gdf, ds, da_name, keep_coords=None, ix=None, buffer=0., **kwa
     return ds_out
 
 
-def gdf_to_count_da(gdf, ds, ix=None, buffer=0., **kwargs):
+def gdf_to_count_da(gdf, ds, ix=None, buffer=0.0, **kwargs):
     """Counts in how many polygons a coordinate of ds appears.
 
     Parameters
@@ -1509,7 +1535,7 @@ def gdf_to_count_da(gdf, ds, ix=None, buffer=0., **kwargs):
         geoms = [gdf]
 
     for geom in geoms:
-        if buffer > 0.:
+        if buffer > 0.0:
             cids = ix.intersects(geom.buffer(buffer), **kwargs)["cellids"]
         else:
             cids = ix.intersects(geom, **kwargs)["cellids"]
@@ -1526,7 +1552,7 @@ def gdf_to_count_da(gdf, ds, ix=None, buffer=0., **kwargs):
     return da
 
 
-def gdf_to_count_ds(gdf, ds, da_name, keep_coords=None, ix=None, buffer=0., **kwargs):
+def gdf_to_count_ds(gdf, ds, da_name, keep_coords=None, ix=None, buffer=0.0, **kwargs):
     """Counts in how many polygons a coordinate of ds appears.
 
     Parameters

nlmod/gis.py

@@ -396,7 +396,7 @@ def ds_to_ugrid_nc_file(
     # Convert boolean layers to integer and int64 to int32
     for var in variables:
         if np.issubdtype(ds[var].dtype, bool):
-            ds[var].encoding["dtype"] = np.int
+            ds[var].encoding["dtype"] = np.int32
         elif np.issubdtype(ds[var].dtype, str) or np.issubdtype(ds[var].dtype, object):
             # convert the string to an index of unique strings
             index = np.unique(ds[var], return_inverse=True)[1]

nlmod/mfoutput/mfoutput.py

@@ -77,7 +77,7 @@ def _get_time_index(fobj, ds=None, gwf_or_gwt=None):
     return tindex
 
 
-def _create_da(arr, modelgrid, times):
+def _create_da(arr, modelgrid, times, add_nans=True, hdry=-1e30, hnoflo=1e30):
     """Create data array based on array, modelgrid, and time array.
 
     Parameters
@@ -88,6 +88,12 @@ def _create_da(arr, modelgrid, times):
         flopy modelgrid object
     times : list or array
         list or array containing times as floats (usually in days)
+    add_nans : bool, optional
+        If True, sets dry/no-flow cells to nan. The default is True.
+    hdry : float, optional
+        The value of dry cells. The default is -1e30.
+    hnoflo : float, optional
+        The value of no-flow cells. The default is 1e30.
 
     Returns
     -------
@@ -99,10 +105,9 @@ def _create_da(arr, modelgrid, times):
     dims, coords = get_dims_coords_from_modelgrid(modelgrid)
     da = xr.DataArray(data=arr, dims=("time",) + dims, coords=coords)
 
-    # set dry/no-flow to nan
-    hdry = -1e30
-    hnoflo = 1e30
-    da = da.where((da != hdry) & (da != hnoflo))
+    if add_nans:
+        # set dry/no-flow to nan
+        da = da.where((da != hdry) & (da != hnoflo))
 
     # set local time coordinates
     da.coords["time"] = ds_time_idx(times)
@@ -168,7 +173,7 @@ def _get_heads_da(
             stacked_arr = stacked_arr[:, :, 0, :]
 
     # create data array
-    da = _create_da(stacked_arr, modelgrid, hobj.get_times())
+    da = _create_da(stacked_arr, modelgrid, hobj.get_times(), **kwargs)
 
     return da
 
@@ -263,10 +268,12 @@ def _get_flopy_data_object(var, ds=None, gwml=None, fname=None, grbfile=None):
         extension = "_gwt.ucn"
     else:
         raise (ValueError(f"Unknown variable {var}"))
-    msg = f"Load the {var}s using either ds, {ml_name} or fname"
-    assert ((ds is not None) + (gwml is not None) + (fname is not None)) == 1, msg
+
     if fname is None:
         if ds is None:
+            if gwml is None:
+                msg = f"Load the {var}s using either ds, {ml_name} or fname"
+                raise (ValueError(msg))
             # return gwf.output.head(), gwf.output.budget() or gwt.output.concentration()
             return getattr(gwml.output, var)()
         fname = os.path.join(ds.model_ws, ds.model_name + extension)