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'''

利用三元组完成稀疏矩阵相乘

'''

from numpy import *

def sparseToTriple(matrix):

m, n = shape(matrix)

triple = []

for i in range(m):

for j in range(n):

if matrix[i][j] != 0:

triple.append([i, j, matrix[i][j]])

return triple

def multiTriple(tripleA, tripleB):

rowA = shape(tripleA)[0]

rowB = shape(tripleB)[0]

multiMatrix = []

for i in range(rowA):

for j in range(rowB):

if tripleA[i][1] == tripleB[j][0]:

multiMatrix.append([tripleA[i][0], tripleB[j][1], tripleA[i][2]*tripleB[j][2]])

return multiMatrix

def tripleToSparse(triple, m, n):

outMatrix = zeros([m, n])

for pointTuple in triple:

mLocation = pointTuple[0]

nLocation = pointTuple[1]

value = pointTuple[2]

outMatrix[mLocation][nLocation] = value

return outMatrix

def matrixMultiple(matrixA, matrixB):

mA, nA = shape(matrixA)

mB, nB = shape(matrixB)

if nA != mB:

print("the two matries doesn't match!")

return -1

tripleA = sparseToTriple(matrixA)

tripleB = sparseToTriple(matrixB)

multiTriples = multiTriple(tripleA, tripleB)

print(multiTriples)

multiMatrix = tripleToSparse(multiTriples, mA, nB)

return multiMatrix

matrixA = [[3, 0, 0, 7],

[0, 0, -1, 0],

[-1, -2, 0, 0],

[0, 0, 0, 2]]

matrixB = [[0, 0, -2, 0, -1],

[0, 0, -3, 0, 0],

[-1, 0, 0, 0, 0],

[0, 0, 0, 3, 0]]

ans = matrixMultiple(matrixA, matrixB)

print(ans)