Auto-format code using pep8 (#289)

Co-authored-by: GitHub Actions <actions@github.com>

src/acom_music_box/data_output.py

@@ -143,6 +143,6 @@ def output(self):
         # Even if we are printing to the terminal, we still allow output to be written to csv if an output path is provided
         if (self.args.output_format == 'csv') or (self.args.output is not None and self.args.output_format == 'terminal'):
             self._output_csv()
-        
+
         if self.args.output_format == 'netcdf':
-            self._output_netcdf()
+            self._output_netcdf()

src/acom_music_box/plot_output.py

@@ -7,105 +7,105 @@
 
 logger = logging.getLogger(__name__)
 
+
 class PlotOutput:
-  """
-  A class to handle plotting operations for a DataFrame, including plotting species
-  concentrations over time using gnuplot or matplotlib.
-  
-  This class manages the plotting tool, species list, and data output formats based on
-  the provided arguments, ensuring valid paths and creating necessary directories.
-
-  Attributes
-  ----------
-  df : pandas.DataFrame
-      The DataFrame to be plotted.
-  args : argparse.Namespace
-      Command-line arguments or configurations specifying plot options.
-  species_list : list
-      A list of species to plot.
-      
-  Examples
-  --------
-  >>> import pandas as pd
-  >>> from argparse import Namespace
-  >>> df = pd.DataFrame({
-  ...     'time': [0, 1, 2],
-  ...     'CONC.A.mol m-3': [1, 2, 3],
-  ...     'CONC.B.mol m-3': [4, 5, 6],
-  ...     'CONC.C.mol m-3': [7, 8, 9]
-  ... })
-  >>> args = Namespace(plot='CONC.A,CONC.B', plot_tool='matplotlib')
-  >>> plot_output = PlotOutput(df, args)
-  >>> plot_output.plot()
-  """
-
-  def __init__(self, df, args):
     """
-    Initialize the PlotOutput class with a DataFrame and configuration arguments.
+    A class to handle plotting operations for a DataFrame, including plotting species
+    concentrations over time using gnuplot or matplotlib.
+
+    This class manages the plotting tool, species list, and data output formats based on
+    the provided arguments, ensuring valid paths and creating necessary directories.
 
-    Parameters
+    Attributes
     ----------
     df : pandas.DataFrame
-        The DataFrame containing the data to be output.
+        The DataFrame to be plotted.
     args : argparse.Namespace
-        Arguments specifying the plot configuration, such as plot tool and species list.
-    """
-
-    self.df = df.copy(deep=True)
-    self.args = args
-    self.species_list = self._format_species_list(self.args.plot.split(',') if self.args.plot else None)
-
-
-  def _format_species_list(self, species_list):
-    """
-    Format the species list for plotting.
-
-    This method formats the species list for plotting by adding the 'CONC.' prefix
-    to each species name if it is not already present.
-
-    Parameters
-    ----------
+        Command-line arguments or configurations specifying plot options.
     species_list : list
         A list of species to plot.
 
-    Returns
-    -------
-    list
-        A formatted list of species for plotting.
+    Examples
+    --------
+    >>> import pandas as pd
+    >>> from argparse import Namespace
+    >>> df = pd.DataFrame({
+    ...     'time': [0, 1, 2],
+    ...     'CONC.A.mol m-3': [1, 2, 3],
+    ...     'CONC.B.mol m-3': [4, 5, 6],
+    ...     'CONC.C.mol m-3': [7, 8, 9]
+    ... })
+    >>> args = Namespace(plot='CONC.A,CONC.B', plot_tool='matplotlib')
+    >>> plot_output = PlotOutput(df, args)
+    >>> plot_output.plot()
     """
 
-    plot_list = None
-    if species_list is not None:
-      plot_list = []
-      for species in species_list:
-          species = species.strip()
-          if 'CONC.' not in species:
-              species = f'CONC.{species}'
-          plot_list.append(species)
-
-    return plot_list
-
-  def _plot_with_gnuplot(self):
-      """
-      Plot the specified species using gnuplot.
-      """
-      # Prepare columns and data for plotting
-      columns = ['time'] + self.species_list
-      data_to_plot = self.df[columns]
-
-      data_csv = data_to_plot.to_csv(index=False)
-
-      try:
-          with tempfile.NamedTemporaryFile(suffix='.csv', mode='w+', delete=True) as data_file:
-              data_file.write(data_csv)
-              data_file.flush()
-              data_file_path = data_file.name
-
-              plot_commands = ',\n\t'.join(
-                  f"'{data_file_path}' using 1:{i+2} with lines title '{species}'" for i,
-                  species in enumerate(self.species_list))
-
-              gnuplot_command = f"""
+    def __init__(self, df, args):
+        """
+        Initialize the PlotOutput class with a DataFrame and configuration arguments.
+
+        Parameters
+        ----------
+        df : pandas.DataFrame
+            The DataFrame containing the data to be output.
+        args : argparse.Namespace
+            Arguments specifying the plot configuration, such as plot tool and species list.
+        """
+
+        self.df = df.copy(deep=True)
+        self.args = args
+        self.species_list = self._format_species_list(self.args.plot.split(',') if self.args.plot else None)
+
+    def _format_species_list(self, species_list):
+        """
+        Format the species list for plotting.
+
+        This method formats the species list for plotting by adding the 'CONC.' prefix
+        to each species name if it is not already present.
+
+        Parameters
+        ----------
+        species_list : list
+            A list of species to plot.
+
+        Returns
+        -------
+        list
+            A formatted list of species for plotting.
+        """
+
+        plot_list = None
+        if species_list is not None:
+            plot_list = []
+            for species in species_list:
+                species = species.strip()
+                if 'CONC.' not in species:
+                    species = f'CONC.{species}'
+                plot_list.append(species)
+
+        return plot_list
+
+    def _plot_with_gnuplot(self):
+        """
+        Plot the specified species using gnuplot.
+        """
+        # Prepare columns and data for plotting
+        columns = ['time'] + self.species_list
+        data_to_plot = self.df[columns]
+
+        data_csv = data_to_plot.to_csv(index=False)
+
+        try:
+            with tempfile.NamedTemporaryFile(suffix='.csv', mode='w+', delete=True) as data_file:
+                data_file.write(data_csv)
+                data_file.flush()
+                data_file_path = data_file.name
+
+                plot_commands = ',\n\t'.join(
+                    f"'{data_file_path}' using 1:{i+2} with lines title '{species}'" for i,
+                    species in enumerate(self.species_list))
+
+                gnuplot_command = f"""
               set datafile separator ",";
               set terminal dumb size 120,25;
               set xlabel 'Time';
@@ -114,53 +114,53 @@ def _plot_with_gnuplot(self):
               plot {plot_commands}
               """
 
-              subprocess.run(['gnuplot', '-e', gnuplot_command], check=True)
-      except FileNotFoundError as e:
-          logging.critical("gnuplot is not installed. Skipping plotting.")
-          raise e
-      except subprocess.CalledProcessError as e:
-          logging.error(f"Error occurred while plotting: {e}")
-          raise e
+                subprocess.run(['gnuplot', '-e', gnuplot_command], check=True)
+        except FileNotFoundError as e:
+            logging.critical("gnuplot is not installed. Skipping plotting.")
+            raise e
+        except subprocess.CalledProcessError as e:
+            logging.error(f"Error occurred while plotting: {e}")
+            raise e
+
+    def _plot_with_matplotlib(self):
+        """
+        Plot the specified species using matplotlib.
+        """
 
-  def _plot_with_matplotlib(self):
-      """
-      Plot the specified species using matplotlib.
-      """
+        indexed = self.df.set_index('time')
 
-      indexed = self.df.set_index('time')
+        fig, ax = plt.subplots()
+        indexed[self.species_list].plot(ax=ax)
 
-      fig, ax = plt.subplots()
-      indexed[self.species_list].plot(ax=ax)
+        ax.set(xlabel='Time [s]', ylabel='Concentration [mol m-3]', title='Time vs Species')
 
-      ax.set(xlabel='Time [s]', ylabel='Concentration [mol m-3]', title='Time vs Species')
+        ax.spines[:].set_visible(False)
+        ax.spines['left'].set_visible(True)
+        ax.spines['bottom'].set_visible(True)
 
-      ax.spines[:].set_visible(False)
-      ax.spines['left'].set_visible(True)
-      ax.spines['bottom'].set_visible(True)
+        ax.grid(alpha=0.5)
+        ax.legend()
 
-      ax.grid(alpha=0.5)
-      ax.legend()
+        # Enable interactive data cursors with hover functionality
+        cursor = mplcursors.cursor(hover=True)
 
-      # Enable interactive data cursors with hover functionality
-      cursor = mplcursors.cursor(hover=True)
+        # Customize the annotation format
+        @cursor.connect("add")
+        def on_add(sel):
+            sel.annotation.set_text(f'Time: {sel.target[0]:.2f}\nConcentration: {sel.target[1]:1.2e}')
 
-      # Customize the annotation format
-      @cursor.connect("add")
-      def on_add(sel):
-          sel.annotation.set_text(f'Time: {sel.target[0]:.2f}\nConcentration: {sel.target[1]:1.2e}')
+        plt.show()
 
-      plt.show()
-
-  def plot(self):
-      """
-      Plot the specified species using the selected plotting tool.
-      """
+    def plot(self):
+        """
+        Plot the specified species using the selected plotting tool.
+        """
 
-      if self.species_list is None:
-          logger.debug("No species provided for plotting.")
-          return
+        if self.species_list is None:
+            logger.debug("No species provided for plotting.")
+            return
 
-      if self.args.plot_tool == 'gnuplot':
-          self._plot_with_gnuplot()
-      else:
-          self._plot_with_matplotlib()
+        if self.args.plot_tool == 'gnuplot':
+            self._plot_with_gnuplot()
+        else:
+            self._plot_with_matplotlib()

tests/integration/test_executable_data_output.py

@@ -85,4 +85,4 @@ def test_create_directory_and_timestamped_netcdf(temp_dir):
 
 def test_run_configuration_file(temp_dir):
     result = subprocess.run(['music_box', '-c', Examples.Analytical.path], capture_output=True, text=True, cwd=temp_dir)
-    assert result.returncode == 0
+    assert result.returncode == 0

tests/unit/test_plot_output.py

@@ -1,3 +1,4 @@
+from acom_music_box.plot_output import PlotOutput
 import unittest
 import pandas as pd
 import shutil
@@ -7,7 +8,6 @@
 
 matplotlib.use('Agg')  # Use a non-interactive backend
 
-from acom_music_box.plot_output import PlotOutput
 
 class TestPlotOutput(unittest.TestCase):
 
@@ -44,5 +44,6 @@ def test_plot_with_matplotlib(self):
         plot_output = PlotOutput(self.df, args)
         plot_output.plot()
 
+
 if __name__ == '__main__':
-    unittest.main()
+    unittest.main()