RIFT.misc.our_corner.corner(xs, bins=20, range=None, weights=None, color='k', smooth=None, smooth1d=None, no_1d=True, labels=None, label_kwargs=None, show_titles=False, title_fmt='.2f', title_kwargs=None, truths=None, truth_color='#4682b4', scale_hist=False, quantiles=None, verbose=False, fig=None, max_n_ticks=5, top_ticks=False, use_math_text=False, reverse=False, hist_kwargs=None, **hist2d_kwargs)

Make a sick corner plot showing the projections of a data set in a multi-dimensional space. kwargs are passed to hist2d() or used for matplotlib styling. Parameters ———- xs : array_like[nsamples, ndim]

The samples. This should be a 1- or 2-dimensional array. For a 1-D array this results in a simple histogram. For a 2-D array, the zeroth axis is the list of samples and the next axis are the dimensions of the space.

binsint or array_like[ndim,]

The number of bins to use in histograms, either as a fixed value for all dimensions, or as a list of integers for each dimension.

weightsarray_like[nsamples,]

The weight of each sample. If None (default), samples are given equal weight.

colorstr

A matplotlib style color for all histograms.

smooth, smooth1dfloat

The standard deviation for Gaussian kernel passed to scipy.ndimage.gaussian_filter to smooth the 2-D and 1-D histograms respectively. If None (default), no smoothing is applied.

labelsiterable (ndim,)

A list of names for the dimensions. If a xs is a pandas.DataFrame, labels will default to column names.

label_kwargsdict

Any extra keyword arguments to send to the set_xlabel and set_ylabel methods.

show_titlesbool

Displays a title above each 1-D histogram showing the 0.5 quantile with the upper and lower errors supplied by the quantiles argument.

title_fmtstring

The format string for the quantiles given in titles. If you explicitly set show_titles=True and title_fmt=None, the labels will be shown as the titles. (default: .2f)

title_kwargsdict

Any extra keyword arguments to send to the set_title command.

rangeiterable (ndim,)

A list where each element is either a length 2 tuple containing lower and upper bounds or a float in range (0., 1.) giving the fraction of samples to include in bounds, e.g., [(0.,10.), (1.,5), 0.999, etc.]. If a fraction, the bounds are chosen to be equal-tailed.

truthsiterable (ndim,)

A list of reference values to indicate on the plots. Individual values can be omitted by using None.

truth_colorstr

A matplotlib style color for the truths makers.

scale_histbool

Should the 1-D histograms be scaled in such a way that the zero line is visible?

quantilesiterable

A list of fractional quantiles to show on the 1-D histograms as vertical dashed lines.

verbosebool

If true, print the values of the computed quantiles.

plot_contoursbool

Draw contours for dense regions of the plot.

use_math_textbool

If true, then axis tick labels for very large or small exponents will be displayed as powers of 10 rather than using e.

reversebool

If true, plot the corner plot starting in the upper-right corner instead of the usual bottom-left corner

max_n_ticks: int

Maximum number of ticks to try to use

top_ticksbool

If true, label the top ticks of each axis

figmatplotlib.Figure

Overplot onto the provided figure object.

hist_kwargsdict

Any extra keyword arguments to send to the 1-D histogram plots.

**hist2d_kwargs

Any remaining keyword arguments are sent to corner.hist2d to generate the 2-D histogram plots.

RIFT.misc.our_corner.hist2d(x, y, bins=20, range=None, weights=None, levels=None, smooth=None, ax=None, color=None, plot_datapoints=True, plot_density=True, plot_contours=True, no_fill_contours=False, fill_contours=False, contour_kwargs=None, contourf_kwargs=None, data_kwargs=None, **kwargs)

Plot a 2-D histogram of samples. Parameters ———- x : array_like[nsamples,]

The samples.

yarray_like[nsamples,]

The samples.

levelsarray_like

The contour levels to draw.

axmatplotlib.Axes

A axes instance on which to add the 2-D histogram.

plot_datapointsbool

Draw the individual data points.

plot_densitybool

Draw the density colormap.

plot_contoursbool

Draw the contours.

no_fill_contoursbool

Add no filling at all to the contours (unlike setting fill_contours=False, which still adds a white fill at the densest points).

fill_contoursbool

Fill the contours.

contour_kwargsdict

Any additional keyword arguments to pass to the contour method.

contourf_kwargsdict

Any additional keyword arguments to pass to the contourf method.

data_kwargsdict

Any additional keyword arguments to pass to the plot method when adding the individual data points.

RIFT.misc.our_corner.quantile(x, q, weights=None)

Compute sample quantiles with support for weighted samples. Note —- When weights is None, this method simply calls numpy’s percentile function with the values of q multiplied by 100. Parameters ———- x : array_like[nsamples,]

The samples.

qarray_like[nquantiles,]

The list of quantiles to compute. These should all be in the range [0, 1].

weightsOptional[array_like[nsamples,]]

An optional weight corresponding to each sample. These

Returns

quantilesarray_like[nquantiles,]

The sample quantiles computed at q.

Raises

ValueError

For invalid quantiles; q not in [0, 1] or dimension mismatch between x and weights.