spac.visualization.visualize_2D_scatter(x, y, labels=None, point_size=None, theme=None, ax=None, annotate_centers=False, x_axis_title='Component 1', y_axis_title='Component 2', plot_title=None, color_representation=None, **kwargs)[source]

Visualize 2D data using plt.scatter.

Parameters:

  • x (array-like) – Coordinates of the data.

  • y (array-like) – Coordinates of the data.

  • labels (array-like, optional) – Array of labels for the data points. Can be numerical or categorical.

  • point_size (float, optional) – Size of the points. If None, it will be automatically determined.

  • theme (str, optional) – Color theme for the plot. Defaults to ‘viridis’ if theme not recognized. For a list of supported themes, refer to Matplotlib’s colormap documentation: https://matplotlib.org/stable/tutorials/colors/colormaps.html

  • ax (matplotlib.axes.Axes, optional (default: None)) – Matplotlib axis object. If None, a new one is created.

  • annotate_centers (bool, optional (default: False)) – Annotate the centers of clusters if labels are categorical.

  • x_axis_title (str, optional) – Title for the x-axis.

  • y_axis_title (str, optional) – Title for the y-axis.

  • plot_title (str, optional) – Title for the plot.

  • color_representation (str, optional) – Description of what the colors represent.

  • **kwargs – Additional keyword arguments passed to plt.scatter.

Returns:

  • fig (matplotlib.figure.Figure) – The figure of the plot.

  • ax (matplotlib.axes.Axes) – The axes of the plot.