functionallity for passing station specific style kwargs implemented …

…in lineplots

metobs_toolkit/dataset_visuals.py

@@ -55,7 +55,7 @@ def make_plot(
         legend=True,
         show_outliers=True,
         show_filled=True,
-        name_color_def={},
+        sta_plot_kwargs_dict={},
         _ax=None,  # needed for GUI, not recommended use
     ):
         """Make a timeseries plot.
@@ -100,12 +100,14 @@ def make_plot(
              If true the filled values for gaps and missing observations will
              be included in the plot. This is only true when colorby == 'name'.
              The default is True.
-        name_color_def : dict, optional
-             If colorby is 'name', a colormap is used as color defenitions for
-             the name. If a name_color_def dictionary is given, then the color
-             defenition (value) for a station name (key) is used as defined by
-             the user. Colors are strings that can be represent by matplotlib
-             name, or in hex-form. The default is {}.
+        sta_plot_kwargs_dict : dict, optional
+             sta_plot_kwargs_dict is a nested dictionary that can contain extra
+             styling arguments that is used for a specific station, if colorby=name.
+             The keys are the station names, and the values are a dict with the
+             keys elements of ['color', 'linewidth', 'zorder', 'linestyle']. Refer
+             to the corresponding keyword in matplotlib for their meaning and
+             possible types. The default is {}.
+
 
 
         Returns
@@ -271,7 +273,7 @@ def make_plot(
             show_outliers=show_outliers,
             show_filled=show_filled,
             settings=self.settings,
-            name_col_def=name_color_def,
+            sta_plot_kwargs_dict=sta_plot_kwargs_dict,
             _ax=_ax,
         )
 

metobs_toolkit/modeldata.py

@@ -1896,7 +1896,7 @@ def make_plot(
         show_outliers=True,
         show_filled=True,
         legend=True,
-        name_color_def={},
+        sta_plot_kwargs_dict={},
         _ax=None,  # needed for GUI, not recommended use
     ):
         """Plot timeseries of the modeldata.
@@ -1942,12 +1942,13 @@ def make_plot(
              The default is True.
         legend : bool, optional
              If True, a legend is added to the plot. The default is True.
-        name_color_def : dict, optional
-             If colorby is 'name', a colormap is used as color defenitions for
-             the name. If a name_color_def dictionary is given, then the color
-             defenition (value) for a station name (key) is used as defined by
-             the user. Colors are strings that can be represent by matplotlib
-             name, or in hex-form. The default is {}.
+        sta_plot_kwargs_dict : dict, optional
+             sta_plot_kwargs_dict is a nested dictionary that can contain extra
+             styling arguments that is used for a specific station.
+             The keys are the station names, and the values are a dict with the
+             keys elements of ['color', 'linewidth', 'zorder', 'linestyle']. Refer
+             to the corresponding keyword in matplotlib for their meaning and
+             possible types. The default is {}.
 
         Returns
         -------
@@ -2113,10 +2114,28 @@ def make_plot(
                 show_outliers=show_outliers,
                 show_filled=show_filled,
                 settings=Dataset.settings,
-                name_col_def=name_color_def,
+                sta_plot_kwargs_dict=sta_plot_kwargs_dict,
                 _ax=_ax,
             )
 
+            # use the col_map to update the sta_plot_kwargs_dict,
+            # so that the same colors are use for modeldata
+
+            # Note: a simplile dict update will not work since all other-than-color
+            # elements are removed
+            for staname, col in col_map.items():
+                if staname in sta_plot_kwargs_dict.keys():
+                    if (
+                        "color" in sta_plot_kwargs_dict[staname].keys()
+                    ):  # loop for readability
+                        # update color
+                        sta_plot_kwargs_dict[staname]["color"] = col
+                    else:
+                        # add color-pair
+                        sta_plot_kwargs_dict[staname]["color"] = col
+                else:
+                    sta_plot_kwargs_dict[staname] = {"color": col}
+
             # Make plot of the model on the previous axes
             ax, col_map = model_timeseries_plot(
                 df=model_df,
@@ -2126,7 +2145,7 @@ def make_plot(
                 show_primary_legend=False,
                 add_second_legend=True,
                 _ax=_ax,
-                colorby_name_colordict=col_map,
+                sta_plot_kwargs_dict=sta_plot_kwargs_dict,
             )
 
         else:
@@ -2138,7 +2157,7 @@ def make_plot(
                 ylabel=y_label,
                 show_primary_legend=legend,
                 add_second_legend=False,
-                name_col_def=name_color_def,
+                sta_plot_kwargs_dict=sta_plot_kwargs_dict,
                 _ax=_ax,
             )
 

metobs_toolkit/plotting_functions.py

@@ -523,6 +523,7 @@ def _create_linecollection(
     const_color=None,
     value_col_name="value",
     label_col_name="label",
+    line_force_kwargs={},
 ):
 
     # 1. convert datetime to numerics values
@@ -537,16 +538,33 @@ def _create_linecollection(
     points = np.array([inxval, linedf[value_col_name]]).T.reshape(-1, 1, 2)
     segments = np.concatenate([points[:-1], points[1:]], axis=1)
 
-    # 3. get styling info
+    # 3. styling attributes
+
+    style_kwargs = {
+        "color": const_color,
+        "linewidth": linewidth,
+        "zorder": linezorder,
+        "linestyle": None,
+    }
+
+    # 4. update styling attributes
+    style_kwargs.update(line_force_kwargs)
+
+    # 5. Construct arguments
     if const_color is None:
         color = linedf[label_col_name].map(colormapper).to_list()
     else:
-        color = [const_color] * linedf.shape[0]
-    linewidth = [linewidth] * linedf.shape[0]
-    zorder = linezorder
-    linestyle = linedf[label_col_name].map(linestylemapper).fillna("-").to_list()
+        color = [style_kwargs["color"]] * linedf.shape[0]
 
-    # 4. Make line collection
+    linewidth = [style_kwargs["linewidth"]] * linedf.shape[0]
+    zorder = style_kwargs["zorder"]
+
+    if style_kwargs["linestyle"] is None:
+        linestyle = linedf[label_col_name].map(linestylemapper).fillna("-").to_list()
+    else:
+        linestyle = style_kwargs["linestyle"]
+
+    # 6. create plot
     lc = LineCollection(
         segments=segments,
         colors=color,
@@ -566,9 +584,8 @@ def timeseries_plot(
     show_outliers,
     show_filled,
     settings,
-    name_col_def={},
+    sta_plot_kwargs_dict={},
     _ax=None,  # needed for GUI, not recommended use
-    colorby_name_colordict=None,
 ):  # when colorscheme will be reused
     """Make a timeseries plot.
 
@@ -596,9 +613,6 @@ def timeseries_plot(
     _ax : matplotlib.pyplot.axes
         An axes to plot on. If None, a new axes will be made. The
         default is None.
-    colorby_name_colorscheme : dict
-        A colormapper for the station names. If None, a new colormapper will
-        be created. The default is None.
 
     Returns
     -------
@@ -823,20 +837,19 @@ def timeseries_plot(
         # all lines are solid lines
         line_style_mapper = {lab: "-" for lab in line_labels}
 
-        # create color mapper if none is given
-        if colorby_name_colordict is None:
-            col_mapper = make_cat_colormapper(
-                mergedf.index.get_level_values("name").unique(),
-                plot_settings["time_series"]["colormap"],
-                name_col_def,
-            )
-        else:
-            # col_mapper = colorby_name_colordict
-            col_mapper = make_cat_colormapper(
-                mergedf.index.get_level_values("name").unique(),
-                plot_settings["time_series"]["colormap"],
-                colorby_name_colordict,
-            )
+        # create color mapper
+
+        col_mapper = make_cat_colormapper(
+            mergedf.index.get_level_values("name").unique(),
+            plot_settings["time_series"]["colormap"],
+        )
+
+        # update the colormapper using the station plot kwargs
+        kwargs_col_map = {}
+        for staname, stakwargs in sta_plot_kwargs_dict.items():
+            if "color" in stakwargs.keys():
+                kwargs_col_map[staname] = stakwargs["color"]
+        col_mapper.update(kwargs_col_map)
 
         # iterate over station and make line collection to avoid interpolation
         # sort mergedf by station name so the same colors are used for the same stations
@@ -852,14 +865,21 @@ def timeseries_plot(
             # interpolation in the plot
             stadf.loc[~stadf.index.isin(linedf.index), "value"] = np.nan
 
+            # plot kwargs to forece for this station
+            if sta in sta_plot_kwargs_dict.keys():
+                stakwargs = sta_plot_kwargs_dict[sta]
+            else:
+                stakwargs = {}
+
             # make line collection
             sta_line_lc = _create_linecollection(
                 linedf=stadf,
                 colormapper=None,
                 const_color=col_mapper[sta],
                 linestylemapper=line_style_mapper,
-                # plotsettings=plot_settings,
+                line_force_kwargs=stakwargs,
             )
+
             ax.add_collection(sta_line_lc)
 
         if show_legend is True:
@@ -912,13 +932,12 @@ def model_timeseries_plot(
     show_primary_legend,
     add_second_legend=True,
     _ax=None,  # needed for GUI, not recommended use
-    colorby_name_colordict=None,  # automatic --> not by user
     figsize=(15, 5),
     colormap="tab20",
     legend_n_columns=5,
     linewidth=2,
     linezorder=1,
-    name_col_def={},  # Defined by user
+    sta_plot_kwargs_dict={},
 ):
     """Make a timeseries plot for modeldata.
 
@@ -959,9 +978,6 @@ def model_timeseries_plot(
         The width of the plotted lines. The default is 2.
     linezorder: int, optional.
         The zorder of the lines in the plot. The default is 1.
-    name_col_def: dict, optional
-        A dictionary to force colors for a station. The keys are the names and
-        the values are the colors to use for them.
 
 
 
@@ -991,19 +1007,25 @@ def model_timeseries_plot(
     line_style_mapper = {"modeldata": "--"}
 
     # create color mapper if none is given
-    if colorby_name_colordict is None:
-        col_mapper = make_cat_colormapper(
-            df.index.get_level_values("name").unique(),
-            colormap,
-            name_col_def,
-        )
-    else:
-        col_mapper = colorby_name_colordict
+    col_mapper = make_cat_colormapper(
+        df.index.get_level_values("name").unique(), colormap
+    )
+
+    # update the colormapper using the station plot kwargs
+    kwargs_col_map = {}
+    for staname, stakwargs in sta_plot_kwargs_dict.items():
+        if "color" in stakwargs.keys():
+            kwargs_col_map[staname] = stakwargs["color"]
+    col_mapper.update(kwargs_col_map)
 
     # iterate over station and make line collection to avoid interpolation
     for sta in df.index.get_level_values("name").unique():
         stadf = xs_save(df, sta, "name")  # subset to one station
 
+        if sta in sta_plot_kwargs_dict.keys():
+            force_line_kwargs = sta_plot_kwargs_dict[sta]
+        else:
+            force_line_kwargs = {}
         # make line collection
         sta_line_lc = _create_linecollection(
             linedf=stadf,
@@ -1012,6 +1034,7 @@ def model_timeseries_plot(
             linestylemapper=line_style_mapper,
             linewidth=linewidth,
             linezorder=linezorder,
+            line_force_kwargs=force_line_kwargs,
         )
         ax.add_collection(sta_line_lc)