dataset#

Class representing a dataset for morphing.

Classes

Dataset(name, data[, scale])

Class for representing a starting dataset and bounds.
class data_morph.data.dataset.Dataset(name: str, data: pd.DataFrame, scale: Number | None = None)[source]#

Bases: object

Class for representing a starting dataset and bounds.

../_images/data_morph-data-dataset-1.png

Upon creation, these bounds are automatically calculated. Use plot() to generate this visualization.#

Parameters:

  • name (str) – The name to use for the dataset.

  • data (pandas.DataFrame) – DataFrame containing columns x and y.

  • scale (numbers.Number, optional) – The factor to scale the data by (can be used to speed up morphing). Values in the data’s x and y columns will be divided by this value.

See also

DataLoader

Utility for creating Dataset objects from CSV files.

data: pd.DataFrame#

DataFrame containing columns x and y.

data_bounds: BoundingBox#

The bounds of the data.

marginals: tuple[tuple[np.ndarray, np.ndarray], tuple[np.ndarray, np.ndarray]]#

The counts per bin and bin boundaries for generating marginal plots.

morph_bounds: BoundingBox#

The limits for the morphing process.

name: str#

The name to use for the dataset.

plot(ax: Axes | None = None, show_bounds: bool = True, title: str | None = 'default', alpha: Number = 1) → Axes[source]#

Plot the dataset and its bounds.

Parameters:

  • ax (matplotlib.axes.Axes, optional) – An optional Axes object to plot on.

  • show_bounds (bool, default True) – Whether to plot the bounds of the dataset.

  • title (str | None, optional) – Title to use for the plot. The default will call str() on the Dataset. Pass None to leave the plot untitled.

  • alpha (Number, default 1) – The transparency to use for the points in the plot.

Returns:

The Axes object containing the plot.

Return type:

matplotlib.axes.Axes

plot_bounds: BoundingBox#

The bounds to use when plotting the morphed data.