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33 lines
1.0 KiB
Python
33 lines
1.0 KiB
Python
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def matrixChainMultiply(seq):
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'''matrix chain multiply, find the optimalest comb to multiply
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eg ABCD, (AB)(CD), A((BC)D)
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seq: sequence of matrix's scale, eg [A.row,A.col,B.col,C.col,D.col]
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'''
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print(seq)
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n = len(seq)-1
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mat = [[0]*n for i in range(n)]
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mark = [[0]*n for i in range(n)]
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for l in range(1,n):
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for i in range(n):
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j = i+l
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if j>=n: continue
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mat[i][j] = None
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for k in range(i,j):
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tmp = mat[i][k]+mat[k+1][j]+seq[i]*seq[k+1]*seq[j+1]
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if mat[i][j] is None or mat[i][j]>tmp:
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mark[i][j] = k
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mat[i][j]= tmp
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s= findSolution(mark,0,n-1)
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print(s)
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return mat[0][n-1]
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def findSolution(mark,i,j):
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if j==i: return 'M{}'.format(i+1)
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if j-i==1: return 'M{} * M{}'.format(j,j+1)
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k = mark[i][j]
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return '('+findSolution(mark,i,k)+') * ('+findSolution(mark,k+1,j)+')'
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if __name__=='__main__':
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seq = [5,10,3,12,5,50,6]
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res = matrixChainMultiply(seq)
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print(res)
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