Toy P2CPs#

Tools for generating toy P2CPs.

hiveplotlib.datasets.toy_p2cps.example_p2cp(num_points: int = 50, noise: float = 0.5, random_seed: int = 0, four_colors: Tuple[str, str, str, str] = ('#de8f05', '#029e73', '#cc78bc', '#0173b2'), **p2cp_n_axes_kwargs) → P2CP#

Generate example P2CP of four gaussian blobs.

Points will be generated by calling hiveplotlib.datasets.toy_p2cps.four_gaussian_blobs_3d() and turned into a P2CP via hiveplotlib.p2cp_n_axes().

Parameters:

  • num_points – number of points in each Gaussian blob.

  • noise – noisiness of Gaussian blobs.

  • random_seed – random seed to generate consistent data between calls.

  • four_colors – four colors to use for four Gaussian blobs.

  • p2cp_n_axes_kwargs – additional keyword arguments for the underlying hiveplotlib.p2cp_n_axes() call.

Returns:

resulting P2CP instance.

hiveplotlib.datasets.toy_p2cps.four_gaussian_blobs_3d(num_points: int = 50, noise: float = 0.5, random_seed: int = 0) → DataFrame#

Generate a pandas dataframe of four Gaussian blobs in 3d.

This dataset serves as a simple example for showing 3d viz using Polar Parallel Coordinates Plots (P2CPs) instead of 3d plotting.

Parameters:

  • num_points – number of points in each blob.

  • noise – noisiness of Gaussian blobs.

  • random_seed – random seed to generate consistent data between calls.

Returns:

(num_points * 4, 4) pd.DataFrame of X, Y, Z, and blob labels.