scipy.sparse.csr_array.

max#

csr_array.max(axis=None, out=None, *, explicit=False)[source]#

Return the maximum of the array/matrix or maximum along an axis.

By default, all elements are taken into account, not just the non-zero ones. But with explicit set, only the stored elements are considered.

Parameters:
axis{-2, -1, 0, 1, None} optional

Axis along which the sum is computed. The default is to compute the maximum over all elements, returning a scalar (i.e., axis = None).

outNone, optional

This argument is in the signature solely for NumPy compatibility reasons. Do not pass in anything except for the default value, as this argument is not used.

explicit{False, True} optional (default: False)

When set to True, only the stored elements will be considered. If a row/column is empty, the sparse.coo_array returned has no stored element (i.e. an implicit zero) for that row/column.

Added in version 1.15.0.

Returns:
amaxcoo_array or scalar

Maximum of a. If axis is None, the result is a scalar value. If axis is given, the result is a sparse.coo_array of dimension a.ndim - 1.

See also

min

The minimum value of a sparse array/matrix along a given axis.

numpy.max

NumPy’s implementation of ‘max’