update

.CondaPkg/env/Lib/site-packages/skimage/util/_label.py

@@ -0,0 +1,51 @@
+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