topostats.plotting
==================

.. py:module:: topostats.plotting

.. autoapi-nested-parse::

   Plotting and summary of TopoStats output statistics.

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Attributes
----------

.. autoapisummary::

   topostats.plotting.LOGGER


Classes
-------

.. autoapisummary::

   topostats.plotting.TopoSum


Functions
---------

.. autoapisummary::

   topostats.plotting.toposum
   topostats.plotting.run_toposum


Module Contents
---------------

.. py:data:: LOGGER

.. py:class:: TopoSum(df: pandas.DataFrame = None, base_dir: Union[str, pathlib.Path] = None, csv_file: Union[str, pathlib.Path] = None, stat_to_sum: str = None, molecule_id: str = 'molecule_number', image_id: str = 'image', hist: bool = True, stat: str = 'count', bins: int = 12, kde: bool = True, cut: float = 20, figsize: tuple = (16, 9), alpha: float = 0.5, palette: str = 'deep', file_ext: str = 'png', output_dir: Union[str, pathlib.Path] = '.', var_to_label: dict = None, hue: str = 'basename')

   
   Class for summarising grain statistics in plots.
















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   .. py:attribute:: df


   .. py:attribute:: base_dir


   .. py:attribute:: stat_to_sum


   .. py:attribute:: molecule_id


   .. py:attribute:: image_id


   .. py:attribute:: hist


   .. py:attribute:: bins


   .. py:attribute:: stat


   .. py:attribute:: kde


   .. py:attribute:: cut


   .. py:attribute:: figsize


   .. py:attribute:: alpha


   .. py:attribute:: palette


   .. py:attribute:: file_ext


   .. py:attribute:: output_dir


   .. py:attribute:: var_to_label


   .. py:attribute:: hue


   .. py:attribute:: melted_data
      :value: None



   .. py:attribute:: summary_data
      :value: None



   .. py:attribute:: label
      :value: None



   .. py:method:: _setup_figure()

      
      Setup Matplotlib figure and axes.
















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   .. py:method:: _outfile(plot_suffix: str) -> str

      
      Generate the output file name with the appropriate suffix.

      :param plot_suffix: The suffix to append to the output file.
      :type plot_suffix: str

      :returns: Concanenated string of the outfile and plot_suffix.
      :rtype: str















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   .. py:method:: sns_plot() -> Optional[Tuple[matplotlib.pyplot.Figure, matplotlib.pyplot.Axes]]

      
      Plot the distribution of one or more statistics as either histogram, kernel density estimates or both. Uses
      base Seaborn.

      :returns: Tuple of Matplotlib figure and axes if plotting is successful, None otherwise.
      :rtype: Optional[Union[Tuple[plt.Figure, plt.Axes], None]]















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   .. py:method:: sns_violinplot() -> None

      
      Violin plot of data.
















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   .. py:method:: melt_data(df: pandas.DataFrame, stat_to_summarize: str, var_to_label: dict) -> pandas.DataFrame
      :staticmethod:


      
      Melt a dataframe into long format for plotting with Seaborn.
















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   .. py:method:: set_xlim(percent: float = 0.1) -> None

      
      Set the range of the x-axis.

      :param percent: Percentage of the observed range by which to extend the x-axis. Only used if supplied range is outside the
      :type percent: float
      :param observed values.:















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   .. py:method:: set_palette()

      
      Set the color palette.
















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   .. py:method:: save_plot(outfile: pathlib.Path) -> None

      
      Save the plot to the output_dir

      :param outfile: Output file name to save figure to.
      :type outfile: str















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   .. py:method:: _set_label(var: str)

      
      Get the label based on the column name(s).

      :param var: The variable for which a label is required.
      :type var: str















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.. py:function:: toposum(config: dict) -> Dict

   
   Process plotting and summarisation of data.

   :param config: Dictionary of summarisation options.
   :type config: dict

   :returns:  Dictionary of nested dictionaries. Each variable has its own dictionary with keys 'dist' and 'violin' which
              contain distribution like plots and violin plots respectively (if the later are required). Each 'dist' and
             'violin' is itself a dictionary with two elements 'figures' and 'axes' which correspond to MatplotLib 'fig' and
             'ax' for that plot.
   :rtype: Dict















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.. py:function:: run_toposum(args=None)

   
   Run Plotting
















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