cupy.unique#

cupy.unique(ar, return_index=False, return_inverse=False, return_counts=False, axis=None, *, equal_nan=True)[source]#

Find the unique elements of an array.

Returns the sorted unique elements of an array. There are three optional outputs in addition to the unique elements:

  • the indices of the input array that give the unique values

  • the indices of the unique array that reconstruct the input array

  • the number of times each unique value comes up in the input array

Parameters:
  • ar (array_like) – Input array. This will be flattened if it is not already 1-D.

  • return_index (bool, optional) – If True, also return the indices of ar (along the specified axis, if provided, or in the flattened array) that result in the unique array.

  • return_inverse (bool, optional) – If True, also return the indices of the unique array (for the specified axis, if provided) that can be used to reconstruct ar.

  • return_counts (bool, optional) – If True, also return the number of times each unique item appears in ar.

  • axis (int or None, optional) – The axis to operate on. If None, ar will be flattened. If an integer, the subarrays indexed by the given axis will be flattened and treated as the elements of a 1-D array with the dimension of the given axis, see the notes for more details. The default is None.

  • equal_nan (bool, optional) – If True, collapse multiple NaN values in the return array into one.

Returns:

If there are no optional outputs, it returns the cupy.ndarray of the sorted unique values. Otherwise, it returns the tuple which contains the sorted unique values and followings.

  • The indices of the first occurrences of the unique values in the original array. Only provided if return_index is True.

  • The indices to reconstruct the original array from the unique array. Only provided if return_inverse is True.

  • The number of times each of the unique values comes up in the original array. Only provided if return_counts is True.

Return type:

cupy.ndarray or tuple

Notes

When an axis is specified the subarrays indexed by the axis are sorted. This is done by making the specified axis the first dimension of the array (move the axis to the first dimension to keep the order of the other axes) and then flattening the subarrays in C order.

Warning

This function may synchronize the device.

See also

numpy.unique()