Fixed database typo and removed unnecessary class identifier.

venv/Lib/site-packages/skimage/util/unique.py

@@ -0,0 +1,50 @@
+import numpy as np
+
+
+def unique_rows(ar):
+    """Remove repeated rows from a 2D array.
+
+    In particular, if given an array of coordinates of shape
+    (Npoints, Ndim), it will remove repeated points.
+
+    Parameters
+    ----------
+    ar : 2-D ndarray
+        The input array.
+
+    Returns
+    -------
+    ar_out : 2-D ndarray
+        A copy of the input array with repeated rows removed.
+
+    Raises
+    ------
+    ValueError : if `ar` is not two-dimensional.
+
+    Notes
+    -----
+    The function will generate a copy of `ar` if it is not
+    C-contiguous, which will negatively affect performance for large
+    input arrays.
+
+    Examples
+    --------
+    >>> ar = np.array([[1, 0, 1],
+    ...                [0, 1, 0],
+    ...                [1, 0, 1]], np.uint8)
+    >>> unique_rows(ar)
+    array([[0, 1, 0],
+           [1, 0, 1]], dtype=uint8)
+    """
+    if ar.ndim != 2:
+        raise ValueError("unique_rows() only makes sense for 2D arrays, "
+                         "got %dd" % ar.ndim)
+    # the view in the next line only works if the array is C-contiguous
+    ar = np.ascontiguousarray(ar)
+    # np.unique() finds identical items in a raveled array. To make it
+    # see each row as a single item, we create a view of each row as a
+    # byte string of length itemsize times number of columns in `ar`
+    ar_row_view = ar.view('|S%d' % (ar.itemsize * ar.shape[1]))
+    _, unique_row_indices = np.unique(ar_row_view, return_index=True)
+    ar_out = ar[unique_row_indices]
+    return ar_out