dot(self, other)
Ordinary dot product
>>> import numpy as npSee :
... from scipy.sparse import csr_matrix
... A = csr_matrix([[1, 2, 0], [0, 0, 3], [4, 0, 5]])
... v = np.array([1, 0, -1])
... A.dot(v) array([ 1, -3, -1], dtype=int64)
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.sparse.linalg._isolve.lsqr.lsqr
scipy.sparse.linalg._isolve.minres.minres
scipy.sparse.linalg._isolve.iterative.gmres
scipy.sparse.linalg._isolve.tfqmr.tfqmr
scipy.sparse.linalg._dsolve.linsolve.spilu
scipy.sparse.linalg._dsolve.linsolve.spsolve_triangular
scipy.sparse.linalg._dsolve.linsolve.splu
scipy.sparse.linalg._isolve.lsmr.lsmr
scipy.sparse.linalg._matfuncs.inv
scipy.sparse.linalg._dsolve.linsolve.spsolve
scipy.sparse.linalg._isolve.iterative.qmr
scipy.sparse._base.spmatrix.dot
Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.
Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)
SVG is more flexible but power hungry; and does not scale well to 50 + nodes.
All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them