uadapy.plotting.plots_nd module

uadapy.plotting.plots_nd.maximize_axes_limits(axs, plot_mask=None)
uadapy.plotting.plots_nd.plot_contour(distributions, n_samples_kde=1000, resolution=128, ranges=None, quantiles: list = None, seed=55, fig=None, axs=None, distrib_colors=None, colorblind_safe=False, show_plot=False, plot_mask=None)

Visualizes a multidimensional distribution in a matrix of contour plots. For this, the 2D/1D marginal distributions have to be estimated for each combination of dimensions. This is done via KDE on samples drawn from the distribution.

Parameters:

  • distributions (list) – List of distributions to plot.

  • n_samples_kde (int) – Number of samples drawn per distribution to estimate the marginal 2D distributions via KDE. Default 1000.

  • resolution (int, optional) – The resolution for the pdf. Default is 128.

  • ranges (list or None, optional) – Array of ranges for all dimensions. If None, the ranges are calculated based on the distributions.

  • quantiles (list or None, optional) – List of quantiles to use for determining isovalues. If None, the 95%, 75%, and 25% quantiles are used.

  • seed (int) – Seed for the random number generator for reproducibility. It defaults to 55 if not provided.

  • fig (matplotlib.figure.Figure or None, optional) – Figure object to use for plotting. If None, a new figure will be created.

  • axs (Array of matplotlib.axes.Axes or None, optional) – Axes objects to use for plotting. If None, new axes will be created.

  • distrib_colors (list or None, optional) – List of colors to use for each distribution. If None, Matplotlib Set2 and glasbey colors will be used.

  • colorblind_safe (bool, optional) – If True, the plot will use colors suitable for colorblind individuals. Default is False.

  • show_plot (bool, optional) – If True, display the plot. Default is False.

  • plot_mask (2D boolean array or function (i,j)->bool, optional) – mask that specifies which subplots will be generated. By default every plot will be generated.

Returns:

  • matplotlib.figure.Figure – The figure object containing the plot.

  • list – List of Axes objects used for plotting.

Raises:

  • ValueError – If a quantile is not between 0 and 100 (exclusive), or if a quantile results in an index that is out of bounds.

  • Exception – If the dimension of the distribution is less than 2.

uadapy.plotting.plots_nd.plot_contour_samples(distributions, n_samples=100, n_samples_kde=1000, resolution=128, point_size=1, alpha=1, ranges=None, quantiles: list = None, seed=55, fig=None, axs=None, distrib_colors=None, colorblind_safe=False, show_plot=False)

Visualizes a multidimensional distribution in a matrix visualization where the upper triangle contains contour plots and the lower triangle contains scatterplots.

Parameters:

  • distributions (list) – List of distributions to plot.

  • n_samples (int) – Number of samples for the scatterplots.

  • n_samples_kde (int) – Number of samples drawn per distribution to estimate the marginal 2D distributions via KDE. Default 1000.

  • resolution (int, optional) – The resolution for the pdf. Default is 128.

  • point_size (float or None, optional) – Marker size (area in points^2). If None, matplotlib’s default is used. By default 1.

  • alpha (float, optional) – opacity value if the samples in the scatter plots. By default 1 (fully opaque)

  • ranges (list or None, optional) – Array of ranges for all dimensions. If None, the ranges are calculated based on the distributions.

  • quantiles (list or None, optional) – List of quantiles to use for determining isovalues. If None, the 95%, 75%, and 25% quantiles are used.

  • seed (int) – Seed for the random number generator for reproducibility. It defaults to 55 if not provided.

  • fig (matplotlib.figure.Figure or None, optional) – Figure object to use for plotting. If None, a new figure will be created.

  • axs (Array of matplotlib.axes.Axes or None, optional) – Axes objects to use for plotting. If None, new axes will be created.

  • distrib_colors (list or None, optional) – List of colors to use for each distribution. If None, Matplotlib Set2 and glasbey colors will be used.

  • colorblind_safe (bool, optional) – If True, the plot will use colors suitable for colorblind individuals. Default is False.

  • show_plot (bool, optional) – If True, display the plot. Default is False.

Returns:

  • matplotlib.figure.Figure – The figure object containing the plot.

  • list – List of Axes objects used for plotting.

Raises:

  • ValueError – If a quantile is not between 0 and 100 (exclusive), or if a quantile results in an index that is out of bounds.

  • Exception – If the dimension of the distribution is less than 2.

uadapy.plotting.plots_nd.plot_matrix_share_axes(axs)

Sets up the axis sharing for a plot matrix. I.e. all axes in the same column share X, and all axes in the same row (except for the diagonal) share Y.

uadapy.plotting.plots_nd.plot_samples(distributions, n_samples=100, seed=55, point_size=1, alpha=1, fig=None, axs=None, distrib_colors=None, colorblind_safe=False, show_plot=False, plot_mask=None)

Plot samples from the multivariate distribution as a SPLOM.

Parameters:

  • distributions (list) – List of distributions to plot.

  • n_samples (int) – Number of samples per distribution.

  • seed (int) – Seed for the random number generator for reproducibility. It defaults to 55 if not provided.

  • point_size (float or None, optional) – Marker size (area in points^2). If None, matplotlib’s default is used. By default 1.

  • alpha (float, optional) – opacity value if the samples in the scatter plots. By default 1 (fully opaque)

  • fig (matplotlib.figure.Figure or None, optional) – Figure object to use for plotting. If None, a new figure will be created.

  • axs (Array of matplotlib.axes.Axes or None, optional) – Axes objects to use for plotting. If None, new axes will be created.

  • distrib_colors (list or None, optional) – List of colors to use for each distribution. If None, Matplotlib Set2 and glasbey colors will be used.

  • colorblind_safe (bool, optional) – If True, the plot will use colors suitable for colorblind individuals. Default is False.

  • show_plot (bool, optional) – If True, display the plot. Default is False.

  • plot_mask (2D boolean array or function (i,j)->bool, optional) – mask that specifies which subplots will be generated. By default every plot will be generated.

Returns:

  • matplotlib.figure.Figure – The figure object containing the plot.

  • list – List of Axes objects used for plotting.