rhg_compute_tools.design package

Submodules

rhg_compute_tools.design.colors module

rhg_compute_tools.design.plotting module

rhg_compute_tools.design.plotting.add_colorbar(ax, cmap='viridis', norm=None, orientation='vertical', **kwargs)[source]

Add a colorbar to a plot, using a pre-defined cmap and norm

Parameters:
  • ax (object) – matplotlib axis object
  • cmap (str or object, optional) – matplotlib.colors.cmap instance or name of a registered cmap (default viridis)
  • norm (object, optional) – matplotlib.colors.Normalize instance. default is a linear norm between the min and max of the first plotted object.
  • orientation (str, optional) – default ‘vertical’
  • **kwargs – passed to colorbar constructor
rhg_compute_tools.design.plotting.get_color_scheme(values, cmap=None, colors=None, levels=None, how=None)[source]

Generate a norm and color scheme from data

Parameters:
  • values (array-like) – data to be plotted, from which to generate cmap and norm. This should be an array, DataArray, etc. that we can use to find the min/max and/or quantiles of the data.
  • cmap (str, optional) – named matplotlib cmap (default inferred from data)
  • colors (list-like, optional) – list of colors to use in a discrete colormap, or with which to create a custom color map
  • levels (list-like, optional) – boundaries of discrete colormap, provide
  • how (str, optional) – Optional setting form {'linear', 'log', 'symlog', None}. Used to construct the returned norm object, which defines the way the colors map to values. By default, we the method is inferred from the values.
Returns:

  • cmap (object) – matplotlib.colors.cmap color mapping
  • norm (object) – matplotlib.colors.Normalize instance using the provided values, levels, color specification, and “how” method

Module contents

rhg_compute_tools.design.get_color_scheme(values, cmap=None, colors=None, levels=None, how=None)[source]

Generate a norm and color scheme from data

Parameters:
  • values (array-like) – data to be plotted, from which to generate cmap and norm. This should be an array, DataArray, etc. that we can use to find the min/max and/or quantiles of the data.
  • cmap (str, optional) – named matplotlib cmap (default inferred from data)
  • colors (list-like, optional) – list of colors to use in a discrete colormap, or with which to create a custom color map
  • levels (list-like, optional) – boundaries of discrete colormap, provide
  • how (str, optional) – Optional setting form {'linear', 'log', 'symlog', None}. Used to construct the returned norm object, which defines the way the colors map to values. By default, we the method is inferred from the values.
Returns:

  • cmap (object) – matplotlib.colors.cmap color mapping
  • norm (object) – matplotlib.colors.Normalize instance using the provided values, levels, color specification, and “how” method
rhg_compute_tools.design.add_colorbar(ax, cmap='viridis', norm=None, orientation='vertical', **kwargs)[source]

Add a colorbar to a plot, using a pre-defined cmap and norm

Parameters:
  • ax (object) – matplotlib axis object
  • cmap (str or object, optional) – matplotlib.colors.cmap instance or name of a registered cmap (default viridis)
  • norm (object, optional) – matplotlib.colors.Normalize instance. default is a linear norm between the min and max of the first plotted object.
  • orientation (str, optional) – default ‘vertical’
  • **kwargs – passed to colorbar constructor