min(self, axis=None, out=None)
Axis along which the sum is computed. The default is to compute the minimum over all the matrix elements, returning a scalar (i.e., :None:None:`axis` = :None:None:`None`).
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.
Minimum of a. If :None:None:`axis` is None, the result is a scalar value. If :None:None:`axis` is given, the result is a sparse.coo_matrix of dimension a.ndim - 1
.
Return the minimum of the matrix or maximum along an axis. This takes all elements into account, not just the non-zero ones.
max
The maximum value of a sparse matrix along a given axis.
numpy.matrix.min
NumPy's implementation of 'min' for matrices
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.sparse._data._minmax_mixin.max
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