multi_tetraptych

kgpy.ctis.inversion.mart.stats.multi_tetraptych(independent, dependents, percentile_threshold_x=0.1, percentile_threshold_y=1.0, num_histogram_bins=100, x_axis_labels=('', '', '', ''), y_axis_labels=('', '', '', ''), dependents_labels=('', ''), red_line=False, contour='iqr', min_iqr_count=10)

Produces a figure with four subplots, each a 2D histogram between corresponding entries in x and y

Parameters:

• independent (typing.Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray, numpy.ndarray]) – tuple of 4 arrays, with moments to be along x-dimension of historam plots

• dependents (typing.List[typing.Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray, numpy.ndarray]]) – list of tuples of 4 arrays

• percentile_threshold_x (float) – parameter used to calculate max and min percentile values for arrays in x

• percentile_threshold_y (float) – parameter used to calculate max and min percentile values for arrays in y

• num_histogram_bins (int) – how many bins in each the x and y axes for the histogram

• x_axis_labels (typing.Tuple[str, str, str, str]) –

• y_axis_labels (typing.Tuple[str, str, str, str]) –

• dependents_labels (typing.Tuple[str, ...]) – list of strings to be used in legends on plots.

• red_line (bool) – if True, plot the “x=y” line in each subplot as a red line

• contour (str) – if True, plots contour of 25th, 50th, and 75th percentile.

• min_iqr_count (int) – minimum number of unique values in a column for that column to be considered in calculating the interquartile contour

Returns: