Source code for data_morph.shapes.bases.point_collection

"""Base class for shapes that are composed of points."""

from numbers import Number
from typing import Iterable

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.axes import Axes

from ...plotting.style import plot_with_custom_style
from .shape import Shape




class PointCollection(Shape):
    """
    Class representing a shape formed by a collection of points.

    Parameters
    ----------
    *points : Iterable[numbers.Number]
        An iterable of (x, y) values representing an arrangement of points.
    """

    def __init__(self, *points: Iterable[Number]) -> None:
        self.points = np.array(points)
        """numpy.ndarray: An array of (x, y) values
        representing an arrangement of points."""

        self._alpha = 1

    def __repr__(self) -> str:
        return f'<{self.__class__.__name__} of {len(self.points)} points>'



    def distance(self, x: Number, y: Number) -> float:
        """
        Calculate the minimum distance from the points of this shape
        to a point (x, y).

        Parameters
        ----------
        x, y : numbers.Number
            Coordinates of a point in 2D space.

        Returns
        -------
        float
            The minimum distance from the points of this shape
            to the point (x, y).
        """
        return np.min(
            np.linalg.norm(np.array(self.points) - np.array((x, y)), ord=2, axis=1)
        )




    @plot_with_custom_style
    def plot(self, ax: Axes = None) -> Axes:
        """
        Plot the shape.

        Parameters
        ----------
        ax : matplotlib.axes.Axes, optional
            An optional :class:`~matplotlib.axes.Axes` object to plot on.

        Returns
        -------
        matplotlib.axes.Axes
            The :class:`~matplotlib.axes.Axes` object containing the plot.
        """
        if not ax:
            fig, ax = plt.subplots(layout='constrained')
            fig.get_layout_engine().set(w_pad=0.2, h_pad=0.2)
        _ = ax.axis('equal')
        _ = ax.scatter(*self.points.T, s=5, color='k', alpha=self._alpha)
        return ax