# Sorting, Searching, and Counting¶

cupy.argmax(a, axis=None, dtype=None, out=None, keepdims=False)[source]

Returns the indices of the maximum along an axis.

Parameters: a (cupy.ndarray) – Array to take argmax. axis (int) – Along which axis to find the maximum. a is flattened by default. dtype – Data type specifier. out (cupy.ndarray) – Output array. keepdims (bool) – If True, the axis axis is preserved as an axis of length one. The indices of the maximum of a along an axis. cupy.ndarray

numpy.argmax()

cupy.argmin(a, axis=None, dtype=None, out=None, keepdims=False)[source]

Returns the indices of the minimum along an axis.

Parameters: a (cupy.ndarray) – Array to take argmin. axis (int) – Along which axis to find the minimum. a is flattened by default. dtype – Data type specifier. out (cupy.ndarray) – Output array. keepdims (bool) – If True, the axis axis is preserved as an axis of length one. The indices of the minimum of a along an axis. cupy.ndarray

numpy.argmin()

cupy.count_nonzero(x)[source]

Counts the number of non-zero values in the array.

Parameters: x (cupy.ndarray) – The array for which to count non-zeros. Number of non-zero values in the array. int
cupy.nonzero(a)[source]

Return the indices of the elements that are non-zero.

Returns a tuple of arrays, one for each dimension of a, containing the indices of the non-zero elements in that dimension.

Parameters: a (cupy.ndarray) – array Indices of elements that are non-zero. tuple of arrays

numpy.nonzero()

cupy.flatnonzero(a)[source]

Return indices that are non-zero in the flattened version of a.

This is equivalent to a.ravel().nonzero()[0].

Parameters: a (cupy.ndarray) – input array Output array, containing the indices of the elements of a.ravel() that are non-zero. cupy.ndarray

numpy.flatnonzero()

cupy.where(condition, x=None, y=None)[source]

Return elements, either from x or y, depending on condition.

If only condition is given, return condition.nonzero().

Parameters: condition (cupy.ndarray) – When True, take x, otherwise take y. x (cupy.ndarray) – Values from which to choose on True. y (cupy.ndarray) – Values from which to choose on False. Each element of output contains elements of x when condition is True, otherwise elements of y. If only condition is given, return the tuple condition.nonzero(), the indices where condition is True. cupy.ndarray

numpy.where()