scipy.sparse.bsr_matrix.min¶
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bsr_matrix.min(axis=None, out=None)[source]¶ Return the minimum of the matrix or maximum along an axis. This takes all elements into account, not just the non-zero ones.
Parameters: axis : {-2, -1, 0, 1, None} optional
Axis along which the sum is computed. The default is to compute the minimum over all the matrix elements, returning a scalar (i.e. axis = None).
out : None, 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.
Returns: amin : coo_matrix or scalar
Minimum of a. If axis is None, the result is a scalar value. If axis is given, the result is a sparse.coo_matrix of dimension
a.ndim - 1.See also
max- The maximum value of a sparse matrix along a given axis.
np.matrix.min- NumPy’s implementation of ‘min’ for matrices