| import numpy as np | |
| __all__ = ["label_points"] | |
| def label_points(coords, output_shape): | |
| """Assign unique integer labels to coordinates on an image mask | |
| Parameters | |
| ---------- | |
| coords : ndarray | |
| An array of N coordinates with dimension D | |
| output_shape : tuple | |
| The shape of the mask on which `coords` are labelled | |
| Returns | |
| ------- | |
| labels: ndarray | |
| A mask of zeroes containing unique integer labels at the `coords` | |
| Examples | |
| -------- | |
| >>> import numpy as np | |
| >>> from skimage.util._label import label_points | |
| >>> coords = np.array([[0, 1], [2, 2]]) | |
| >>> output_shape = (5, 5) | |
| >>> mask = label_points(coords, output_shape) | |
| >>> mask | |
| array([[0, 1, 0, 0, 0], | |
| [0, 0, 0, 0, 0], | |
| [0, 0, 2, 0, 0], | |
| [0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0]], dtype=uint64) | |
| Notes | |
| ----- | |
| - The labels are assigned to coordinates that are converted to | |
| integer and considered to start from 0. | |
| - Coordinates that are out of range of the mask raise an IndexError. | |
| - Negative coordinates raise a ValueError | |
| """ | |
| if coords.shape[1] != len(output_shape): | |
| raise ValueError("Dimensionality of points should match the " "output shape") | |
| if np.any(coords < 0): | |
| raise ValueError("Coordinates should be positive and start from 0") | |
| np_indices = tuple(np.transpose(np.round(coords).astype(int, copy=False))) | |
| labels = np.zeros(output_shape, dtype=np.uint64) | |
| labels[np_indices] = np.arange(1, coords.shape[0] + 1) | |
| return labels | |