Formatting

Author: dweindl

petab/parameter_mapping.py

@@ -593,7 +593,7 @@ def merge_preeq_and_sim_pars_condition(
     This function is meant for the case where we cannot have different
     parameters (and scales) for preequilibration and simulation. Therefore,
     merge both and ensure matching scales and parameters.
-    ``condition_map_sim`` and ``condition_scale_map_sim`` will ne modified in
+    ``condition_map_sim`` and ``condition_scale_map_sim`` will be modified in
     place.
 
     Arguments:

petab/visualize/plotter.py

@@ -33,8 +33,10 @@ def __init__(self, figure: Figure, data_provider: DataProvider):
         self.data_provider = data_provider
 
     @abstractmethod
-    def generate_figure(self, subplot_dir: Optional[str] = None
-                        ) -> Optional[Dict[str, plt.Subplot]]:
+    def generate_figure(
+            self,
+            subplot_dir: Optional[str] = None
+    ) -> Optional[Dict[str, plt.Subplot]]:
         pass
 
 
@@ -65,9 +67,12 @@ def _error_column_for_plot_type_data(plot_type_data: str) -> Optional[str]:
             return 'noise_model'
         return None
 
-    def generate_lineplot(self, ax: 'matplotlib.pyplot.Axes',
-                          dataplot: DataPlot,
-                          plotTypeData: str) -> None:
+    def generate_lineplot(
+            self,
+            ax: 'matplotlib.pyplot.Axes',
+            dataplot: DataPlot,
+            plotTypeData: str
+    ) -> None:
         """
         Generate lineplot.
 
@@ -82,7 +87,6 @@ def generate_lineplot(self, ax: 'matplotlib.pyplot.Axes',
         plotTypeData:
             Specifies how replicates should be handled.
         """
-
         simu_color = None
         measurements_to_plot, simulations_to_plot = \
             self.data_provider.get_data_to_plot(dataplot,
@@ -152,9 +156,12 @@ def generate_lineplot(self, ax: 'matplotlib.pyplot.Axes',
                 label=label_base + " simulation", color=simu_color
             )
 
-    def generate_barplot(self, ax: 'matplotlib.pyplot.Axes',
-                         dataplot: DataPlot,
-                         plotTypeData: str) -> None:
+    def generate_barplot(
+            self,
+            ax: 'matplotlib.pyplot.Axes',
+            dataplot: DataPlot,
+            plotTypeData: str
+    ) -> None:
         """
         Generate barplot.
 
@@ -200,9 +207,12 @@ def generate_barplot(self, ax: 'matplotlib.pyplot.Axes',
                    color='white', edgecolor=color, **bar_kwargs,
                    label='simulation')
 
-    def generate_scatterplot(self, ax: 'matplotlib.pyplot.Axes',
-                             dataplot: DataPlot,
-                             plotTypeData: str) -> None:
+    def generate_scatterplot(
+            self,
+            ax: 'matplotlib.pyplot.Axes',
+            dataplot: DataPlot,
+            plotTypeData: str
+    ) -> None:
         """
         Generate scatterplot.
 
@@ -215,7 +225,6 @@ def generate_scatterplot(self, ax: 'matplotlib.pyplot.Axes',
         plotTypeData:
             Specifies how replicates should be handled.
         """
-
         measurements_to_plot, simulations_to_plot = \
             self.data_provider.get_data_to_plot(dataplot,
                                                 plotTypeData == PROVIDED)
@@ -228,9 +237,11 @@ def generate_scatterplot(self, ax: 'matplotlib.pyplot.Axes',
                    label=getattr(dataplot, LEGEND_ENTRY))
         self._square_plot_equal_ranges(ax)
 
-    def generate_subplot(self,
-                         ax,
-                         subplot: Subplot) -> None:
+    def generate_subplot(
+            self,
+            ax: plt.Axes,
+            subplot: Subplot
+    ) -> None:
         """
         Generate subplot based on markup provided by subplot.
 
@@ -241,7 +252,6 @@ def generate_subplot(self,
         subplot:
             Subplot visualization settings.
         """
-
         # set yScale
         if subplot.yScale == LIN:
             ax.set_yscale("linear")
@@ -270,7 +280,6 @@ def generate_subplot(self,
             for data_plot in subplot.data_plots:
                 self.generate_scatterplot(ax, data_plot, subplot.plotTypeData)
         else:
-
             # set xScale
             if subplot.xScale == LIN:
                 ax.set_xscale("linear")
@@ -345,7 +354,6 @@ def generate_figure(
         None:
             In case subplots are saved to file.
         """
-
         if subplot_dir is None:
             # compute, how many rows and columns we need for the subplots
             num_row = int(np.round(np.sqrt(self.figure.num_subplots)))
@@ -361,7 +369,7 @@ def generate_figure(
             axes = dict(zip([plot.plotId for plot in self.figure.subplots],
                             axes.flat))
 
-        for idx, subplot in enumerate(self.figure.subplots):
+        for subplot in self.figure.subplots:
             if subplot_dir is not None:
                 fig, ax = plt.subplots(figsize=self.figure.size)
                 fig.set_tight_layout(True)
@@ -419,6 +427,8 @@ class SeabornPlotter(Plotter):
     def __init__(self, figure: Figure, data_provider: DataProvider):
         super().__init__(figure, data_provider)
 
-    def generate_figure(self, subplot_dir: Optional[str] = None
-                        ) -> Optional[Dict[str, plt.Subplot]]:
+    def generate_figure(
+            self,
+            subplot_dir: Optional[str] = None
+    ) -> Optional[Dict[str, plt.Subplot]]:
         pass

petab/visualize/plotting.py

@@ -2,7 +2,7 @@
 import warnings
 from numbers import Number, Real
 from pathlib import Path
-from typing import Dict, List, Optional, Tuple, Union
+from typing import Dict, List, Optional, Tuple, Union, Literal
 
 import numpy as np
 import pandas as pd
@@ -130,6 +130,9 @@ def from_df(cls, plot_spec: pd.DataFrame):
 
         return cls(vis_spec_dict)
 
+    def __repr__(self):
+        return f"{self.__class__.__name__}({self.__dict__})"
+
 
 class Subplot:
     """
@@ -480,9 +483,13 @@ def _get_independent_var_values(self, data_df: pd.DataFrame,
 
         return uni_condition_id, col_name_unique, conditions_
 
-    def get_data_series(self, data_df: pd.DataFrame, data_col: str,
-                        dataplot: DataPlot,
-                        provided_noise: bool) -> DataSeries:
+    def get_data_series(
+            self,
+            data_df: pd.DataFrame,
+            data_col: Literal['measurement', 'simulation'],
+            dataplot: DataPlot,
+            provided_noise: bool
+    ) -> DataSeries:
         """
         Get data to plot from measurement or simulation DataFrame.
 
@@ -499,10 +506,8 @@ def get_data_series(self, data_df: pd.DataFrame, data_col: str,
         -------
         Data to plot
         """
-
         uni_condition_id, col_name_unique, conditions_ = \
-            self._get_independent_var_values(data_df,
-                                             dataplot)
+            self._get_independent_var_values(data_df, dataplot)
 
         dataset_id = getattr(dataplot, DATASET_ID)
 
@@ -643,8 +648,10 @@ def _data_df(self):
             None else self.simulations_data
 
     @staticmethod
-    def create_subplot(plot_id: str,
-                       subplot_vis_spec: pd.DataFrame) -> Subplot:
+    def create_subplot(
+            plot_id: str,
+            subplot_vis_spec: pd.DataFrame
+    ) -> Subplot:
         """
         Create subplot.
 
@@ -661,7 +668,6 @@ def create_subplot(plot_id: str,
 
                 Subplot
         """
-
         subplot_columns = [col for col in subplot_vis_spec.columns if col in
                            VISUALIZATION_DF_SUBPLOT_LEVEL_COLS]
         subplot = Subplot.from_df(plot_id,
@@ -677,9 +683,10 @@ def create_subplot(plot_id: str,
 
         return subplot
 
-    def parse_from_vis_spec(self,
-                            vis_spec: Optional[Union[str, Path, pd.DataFrame]],
-                            ) -> Tuple[Figure, DataProvider]:
+    def parse_from_vis_spec(
+            self,
+            vis_spec: Optional[Union[str, Path, pd.DataFrame]],
+    ) -> Tuple[Figure, DataProvider]:
         """
         Get visualization settings from a visualization specification.
 
@@ -694,7 +701,6 @@ def parse_from_vis_spec(self,
 
         A figure template with visualization settings and a data provider
         """
-
         # import visualization specification, if file was specified
         if isinstance(vis_spec, (str, Path)):
             vis_spec = core.get_visualization_df(vis_spec)