Merge pull request #34 from elmbeech/master

v4.0.3

Author: elmbeech

README.md

@@ -125,6 +125,10 @@ Developers, please make pull requests to the https://github.com/elmbeech/physice
 + evt generate lineage tree graph output files.
 
 ## Release Notes:
++ version 4.0.3 (2025-07-20): elmbeech/physicelldataloader
+    + timestep and timeseries **plot_contour**, **plot_scatter**, and **plot_timeseries** handle now **kwargs** arguments.
+    + minor bugfixes.
+
 + version 4.0.2 (2025-06-29): elmbeech/physicelldataloader
     + minor bugfixes.
 

man/docstring/mcds.plot_contour.md

@@ -70,6 +70,11 @@
                 or white (jpeg, tiff).
                 figure background color.
 
+            **kwargs: possible additional keyword arguments input,
+                handled by the matplotlib contour and contourf function.
+                + https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.contour.html
+                + https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.contourf.html
+
 ```
 
 ## output:

man/docstring/mcds.plot_scatter.md

@@ -75,6 +75,10 @@
                 or white (jpeg, tiff).
                 figure background color.
 
+            **kwargs: possible additional keyword arguments input,
+                handled by the pandas dataframe plot function.
+                + https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.html
+
 ```
 
 ## output:

man/docstring/mcdsts.plot_contour.md

@@ -62,6 +62,11 @@
                 or white (jpeg, tiff).
                 figure background color.
 
+            **kwargs: possible additional keyword arguments input,
+                handled by the matplotlib contour and contourf function.
+                + https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.contour.html
+                + https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.contourf.html
+
 ```
 
 ## output:

man/docstring/mcdsts.plot_scatter.md

@@ -72,6 +72,10 @@
                 or white (jpeg, tiff).
                 figure background color.
 
+            **kwargs: possible additional keyword arguments input,
+                handled by the pandas dataframe plot function.
+                + https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame
+
 ```
 
 ## output:

man/docstring/mcdsts.plot_timeseries.md

@@ -101,6 +101,10 @@
                 figure background color.
                 only relevant if ext not is None.
 
+            **kwargs: possible additional keyword arguments input,
+                handled by the pandas series plot function.
+                + https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.plot.html
+
 ```
 
 ## output:

man/img/physicelldataloafder_github_qr.png

@@ -1 +1 @@
-__version__ = '4.0.2'
+__version__ = '4.0.3'

pcdl/VERSION.py

@@ -521,7 +521,7 @@ def get_conc_attribute(self, values=1, drop=set(), keep=set(), allvalues=False):
         return dlr_variable_range
 
 
-    def plot_contour(self, focus, z_slice=0.0, extrema=None, alpha=1, fill=True, cmap='viridis', title='', grid=True, xlim=None, ylim=None, xyequal=True, figsizepx=None, ext='jpeg', figbgcolor=None):
+    def plot_contour(self, focus, z_slice=0.0, extrema=None, alpha=1, fill=True, cmap='viridis', title='', grid=True, xlim=None, ylim=None, xyequal=True, figsizepx=None, ext='jpeg', figbgcolor=None, **kwargs):
         """
         input:
             self: TimeSeries class instance
@@ -583,6 +583,11 @@ def plot_contour(self, focus, z_slice=0.0, extrema=None, alpha=1, fill=True, cma
                 or white (jpeg, tiff).
                 figure background color.
 
+            **kwargs: possible additional keyword arguments input,
+                handled by the matplotlib contour and contourf function.
+                + https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.contour.html
+                + https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.contourf.html
+
         output:
             fig: matplotlib figures, depending on ext, either as files or as
                 objects. the figures contains the contour plot and color bar.
@@ -653,6 +658,7 @@ def plot_contour(self, focus, z_slice=0.0, extrema=None, alpha=1, fill=True, cma
                 figsizepx = figsizepx,
                 ext = ext,
                 figbgcolor = figbgcolor,
+                **kwargs,
             )
             lo_output.append(o_output)
 
@@ -845,7 +851,7 @@ def get_cell_attribute(self, values=1, drop=set(), keep=set(), allvalues=False):
         return dl_variable_range
 
 
-    def plot_scatter(self, focus='cell_type', z_slice=0.0, z_axis=None, alpha=1, cmap='viridis', title='', grid=True, legend_loc='lower left', xlim=None, ylim=None, xyequal=True, s=1.0, figsizepx=None, ext='jpeg', figbgcolor=None):
+    def plot_scatter(self, focus='cell_type', z_slice=0.0, z_axis=None, alpha=1, cmap='viridis', title='', grid=True, legend_loc='lower left', xlim=None, ylim=None, xyequal=True, s=1.0, figsizepx=None, ext='jpeg', figbgcolor=None, **kwargs):
         """
         input:
             self: TimeSeries class instance
@@ -917,6 +923,10 @@ def plot_scatter(self, focus='cell_type', z_slice=0.0, z_axis=None, alpha=1, cma
                 or white (jpeg, tiff).
                 figure background color.
 
+            **kwargs: possible additional keyword arguments input,
+                handled by the pandas dataframe plot function.
+                + https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame
+
         output:
             fig: matplotlib figures, depending on ext, either as files or
                 as objects. the figures contains the scatter plot and
@@ -956,6 +966,7 @@ def plot_scatter(self, focus='cell_type', z_slice=0.0, z_axis=None, alpha=1, cma
                 figsizepx = figsizepx,
                 ext = ext,
                 figbgcolor = figbgcolor,
+                **kwargs,
             )
             lo_output.append(o_output)
 
@@ -1130,7 +1141,7 @@ def make_ome_tiff(self, cell_attribute='ID', conc_cutoff={}, focus=None, file=Tr
 
     ## TIME SERIES RELATED FUNCTIONS ##
 
-    def plot_timeseries(self, focus_cat=None, focus_num=None, aggregate_num=np.nanmean, frame='cell', z_slice=None, logy=False, ylim=None, secondary_y=None, subplots=False, sharex=False, sharey=False, linestyle='-', linewidth=None, cmap=None, color=None, grid=True, legend=True, yunit=None, title=None, ax=None, figsizepx=[640, 480], ext=None, figbgcolor=None):
+    def plot_timeseries(self, focus_cat=None, focus_num=None, aggregate_num=np.nanmean, frame='cell', z_slice=None, logy=False, ylim=None, secondary_y=None, subplots=False, sharex=False, sharey=False, linestyle='-', linewidth=None, cmap=None, color=None, grid=True, legend=True, yunit=None, title=None, ax=None, figsizepx=[640, 480], ext=None, figbgcolor=None, **kwargs):
         """
         input:
             self: TimeSeries class instance
@@ -1231,6 +1242,10 @@ def plot_timeseries(self, focus_cat=None, focus_num=None, aggregate_num=np.nanme
                 figure background color.
                 only relevant if ext not is None.
 
+            **kwargs: possible additional keyword arguments input,
+                handled by the pandas series plot function.
+                + https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.plot.html
+
         output:
             if ext is None: a fig matplotlib figure, containing the ax axis object, is returned.
             else: an image file is generated under the returned path.
@@ -1370,7 +1385,8 @@ def plot_timeseries(self, focus_cat=None, focus_num=None, aggregate_num=np.nanme
                 ylabel = ylabel,
                 xlabel = f"time [{mcds.get_unit_dict()['time']}]",
                 title = title,
-                ax = ax
+                ax = ax,
+                **kwargs,
             )
         else:
             # if color
@@ -1390,15 +1406,16 @@ def plot_timeseries(self, focus_cat=None, focus_num=None, aggregate_num=np.nanme
                 ylabel = ylabel,
                 xlabel = f"time [{mcds.get_unit_dict()['time']}]",
                 title = title,
-                ax = ax
+                ax = ax,
+                **kwargs,
             )
 
         # output
         if (ext is None):
             return fig
         else:
             if (focus_num == 'count'):
-                s_ofile = 'timeseries_{frame}_{focus_cat}_{focus_num}.{ext}'.replace(' ','_')
+                s_ofile = f'timeseries_{frame}_{focus_cat}_{focus_num}.{ext}'.replace(' ','_')
             else:
                 s_ofile = f"timeseries_{frame}_{focus_cat}_{focus_num}_{aggregate_num.__name__.replace('np.nan','')}.{ext}".replace(' ','_')
             s_pathfile = self.path + '/' + s_ofile

pcdl/timeseries.py

@@ -1118,7 +1118,7 @@ def get_conc_df(self, z_slice=None, halt=False, values=1, drop=set(), keep=set()
         return df_conc
 
 
-    def plot_contour(self, focus, z_slice=0.0, vmin=None, vmax=None, alpha=1, fill=True, cmap='viridis', title=None, grid=True, xlim=None, ylim=None, xyequal=True, ax=None, figsizepx=None, ext=None, figbgcolor=None):
+    def plot_contour(self, focus, z_slice=0.0, vmin=None, vmax=None, alpha=1, fill=True, cmap='viridis', title=None, grid=True, xlim=None, ylim=None, xyequal=True, ax=None, figsizepx=None, ext=None, figbgcolor=None, **kwargs):
         """
         input:
             focus: string
@@ -1188,6 +1188,11 @@ def plot_contour(self, focus, z_slice=0.0, vmin=None, vmax=None, alpha=1, fill=T
                 or white (jpeg, tiff).
                 figure background color.
 
+            **kwargs: possible additional keyword arguments input,
+                handled by the matplotlib contour and contourf function.
+                + https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.contour.html
+                + https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.contourf.html
+
         output:
             fig: matplotlib figure, depending on ext, either as object or as file.
                 the figure containing the contour plot and color bar.
@@ -1269,9 +1274,9 @@ def plot_contour(self, focus, z_slice=0.0, vmin=None, vmax=None, alpha=1, fill=T
 
         # get contour plot
         if fill:
-            ax.contourf(df_mesh.columns, df_mesh.index, df_mesh.values, vmin=vmin, vmax=vmax, alpha=alpha, cmap=cmap)
+            ax.contourf(df_mesh.columns, df_mesh.index, df_mesh.values, vmin=vmin, vmax=vmax, alpha=alpha, cmap=cmap, **kwargs)
         else:
-            ax.contour(df_mesh.columns, df_mesh.index, df_mesh.values, vmin=vmin, vmax=vmax, alpha=alpha, cmap=cmap)
+            ax.contour(df_mesh.columns, df_mesh.index, df_mesh.values, vmin=vmin, vmax=vmax, alpha=alpha, cmap=cmap, **kwargs)
 
         # set title
         if not (title is None):
@@ -1513,7 +1518,7 @@ def get_cell_attribute_list(self):
         return self.data['cell']['ls_cellattr'].copy()
 
 
-    def plot_scatter(self, focus='cell_type', z_slice=0.0, z_axis=None, alpha=1, cmap='viridis', title=None, grid=True, legend_loc='lower left', xlim=None, ylim=None, xyequal=True, s=1.0, ax=None, figsizepx=None, ext=None, figbgcolor=None):
+    def plot_scatter(self, focus='cell_type', z_slice=0.0, z_axis=None, alpha=1, cmap='viridis', title=None, grid=True, legend_loc='lower left', xlim=None, ylim=None, xyequal=True, s=1.0, ax=None, figsizepx=None, ext=None, figbgcolor=None, **kwargs):
         """
         input:
             focus: string; default is 'cell_type'
@@ -1588,6 +1593,10 @@ def plot_scatter(self, focus='cell_type', z_slice=0.0, z_axis=None, alpha=1, cma
                 or white (jpeg, tiff).
                 figure background color.
 
+            **kwargs: possible additional keyword arguments input,
+                handled by the pandas dataframe plot function.
+                + https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.html
+
         output:
             fig: matplotlib figure, depending on ext, either as object or as file.
                 the figure contains the scatter plot and color bar (numerical data)
@@ -1737,6 +1746,7 @@ def plot_scatter(self, focus='cell_type', z_slice=0.0, z_axis=None, alpha=1, cma
             s = 's',
             grid = grid,
             ax = ax,
+            **kwargs,
         )
 
         # plot categorical data legen