lib5c.plotters.fits module

Module for plotting visualizations comparing fitted theoretical distributions to real data.

lib5c.plotters.fits.plot_fit(data, frozen_dist, legend=True, **kwargs)[source]

Base function for plotting fits.

Parameters

  • data (np.ndarray) – The real data to be compared to the theoretical distribution.

  • frozen_dist (scipy.stats.rv_frozen) – The theoretical distribution to be compared to the real data.

  • kwargs (kwargs) – Typical plotter kwargs.

Returns

The axis plotted on.

Return type

pyplot axis

lib5c.plotters.fits.plot_group_fit(obs, exp, i, j, frozen_dist, local=False, p=5, w=15, group_fractional_tolerance=0.1, vst=False, log=False, legend=True, **kwargs)[source]

Convenience function to select a subset of some data and compare it to a frozen distribution via plot_fit().

Parameters

  • obs (np.ndarray) – Regional matrix of the observed values.

  • exp (np.ndarray) – Regional matrix of the expected values.

  • j (i,) – Row and column indices, respectively, of the target point.

  • frozen_dist (scipy.stats.rv_frozen) – The theoretical distribution to be compared to the real data.

  • local (bool) – Pass True to compare the theoretical distribution to observed data points in a donut window around the target point. Pass False to compare the theoretical distribution to observed data points with similar expected values to the target point.

  • w (int) – The outer radius of the donut window to use when local=True.

  • p (int) – The inner radius of the donut window to use when local=True.

  • group_fractional_tolerance (float) – The fractional tolerance in expected value used to select points with “similar” expected values when local=False.

  • vst (bool) – Pass True if a VST-style step has been performed upstream and the expected values should be interpreted as already logged.

  • log (bool) – Pass True to log the selected observed data points before plotting.

  • kwargs (kwargs) – Typical plotter kwargs.

Returns

The axis plotted on.

Return type

pyplot axis