Create stressen.py
Browse files- stressen.py +167 -0
stressen.py
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import numpy as np
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num_addorsub=0
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num_mul=0
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num_assign=0
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def matrix_add(matrix_a, matrix_b):
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'''
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:param matrix_a:
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:param matrix_b:
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:return:matrix_c=matrix_a+matrix_b
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'''
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rows = len(matrix_a) # get numbers of rows
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columns = len(matrix_a[0]) # get numbers of cols
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matrix_c = [list() for i in range(rows)] # build matrix 2d list
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for i in range(rows):
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for j in range(columns):
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matrix_c_temp = matrix_a[i][j] + matrix_b[i][j]
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global num_addorsub,num_assign
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num_addorsub = num_addorsub + 1
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num_assign = num_assign + 1
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matrix_c[i].append(matrix_c_temp)
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return matrix_c
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def matrix_minus(matrix_a, matrix_b):
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'''
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:param matrix_a:
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:param matrix_b:
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:return:matrix_c=matrix_a-matrix_b
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'''
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rows = len(matrix_a)
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columns = len(matrix_a[0])
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matrix_c = [list() for i in range(rows)]
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for i in range(rows):
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for j in range(columns):
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matrix_c_temp = matrix_a[i][j] - matrix_b[i][j]
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global num_addorsub,num_assign
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num_addorsub = num_addorsub + 1
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num_assign=num_assign + 1
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matrix_c[i].append(matrix_c_temp)
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return matrix_c
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def matrix_divide(matrix_a, row, column):
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'''
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:param matrix_a:
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:param row:
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:param column:
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:return: matrix_b=matrix_a(row,column) to divide matrix_a
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'''
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rows = len(matrix_a)
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columns = len(matrix_a[0])
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matrix_b = [list() for i in range(rows // 2)]
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k = 0
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for i in range((row - 1) * rows // 2, row * rows // 2):
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for j in range((column - 1) * columns // 2, column * columns // 2):
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matrix_c_temp = matrix_a[i][j]
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matrix_b[k].append(matrix_c_temp)
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k += 1
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return matrix_b
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def matrix_merge(matrix_11, matrix_12, matrix_21, matrix_22):
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'''
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:param matrix_11:
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:param matrix_12:
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:param matrix_21:
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:param matrix_22:
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:return:mariix merged by 4 parts above
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'''
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length = len(matrix_11)
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matrix_all = [list() for i in range(length * 2)] # build a matrix of double rows
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for i in range(length):
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# for each row. matrix_all list contain row of matrix_11 and matrix_12
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matrix_all[i] = matrix_11[i] + matrix_12[i]
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for j in range(length):
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# for each row. matrix_all list contain row of matrix_21 and matrix_22
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matrix_all[length + j] = matrix_21[j] + matrix_22[j]
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return matrix_all
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def strassen(matrix_a, matrix_b):
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'''
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:param matrix_a:
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:param matrix_b:
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:return:matrix_a * matrix_b
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'''
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row_a = len(matrix_a)
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col_a = len(matrix_a[0])
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row_b = len(matrix_b)
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col_b = len(matrix_b[0])
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if col_a != row_b:
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print('matrix_a and matrix_b can not be multiplied')
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return
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global num_mul,num_addorsub
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if row_a == 1 or col_a == 1 or row_b == 1 or col_b == 1:
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matrix_all = [list() for i in range(row_a)]
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for i in range(row_a):
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for j in range(col_b):
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matrix_all_temp = 0
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for k in range(col_a):
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matrix_all_temp += matrix_a[i][k] * matrix_b[k][j]
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num_mul = num_mul + 1
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num_addorsub = num_addorsub + 1
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matrix_all[i].append(matrix_all_temp)
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else:
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# 10 first parts of computing
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s1 = matrix_minus((matrix_divide(matrix_b, 1, 2)), (matrix_divide(matrix_b, 2, 2)))
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s2 = matrix_add((matrix_divide(matrix_a, 1, 1)), (matrix_divide(matrix_a, 1, 2)))
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s3 = matrix_add((matrix_divide(matrix_a, 2, 1)), (matrix_divide(matrix_a, 2, 2)))
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s4 = matrix_minus((matrix_divide(matrix_b, 2, 1)), (matrix_divide(matrix_b, 1, 1)))
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s5 = matrix_add((matrix_divide(matrix_a, 1, 1)), (matrix_divide(matrix_a, 2, 2)))
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s6 = matrix_add((matrix_divide(matrix_b, 1, 1)), (matrix_divide(matrix_b, 2, 2)))
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s7 = matrix_minus((matrix_divide(matrix_a, 1, 2)), (matrix_divide(matrix_a, 2, 2)))
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s8 = matrix_add((matrix_divide(matrix_b, 2, 1)), (matrix_divide(matrix_b, 2, 2)))
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s9 = matrix_minus((matrix_divide(matrix_a, 1, 1)), (matrix_divide(matrix_a, 2, 1)))
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s10 = matrix_add((matrix_divide(matrix_b, 1, 1)), (matrix_divide(matrix_b, 1, 2)))
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# 7 second parts of computing
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p1 = strassen(matrix_divide(matrix_a, 1, 1), s1)
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p2 = strassen(s2, matrix_divide(matrix_b, 2, 2))
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p3 = strassen(s3, matrix_divide(matrix_b, 1, 1))
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p4 = strassen(matrix_divide(matrix_a, 2, 2), s4)
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p5 = strassen(s5, s6)
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p6 = strassen(s7, s8)
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p7 = strassen(s9, s10)
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# 4 final parts of result
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c11 = matrix_add(matrix_add(p5, p4), matrix_minus(p6, p2))
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c12 = matrix_add(p1, p2)
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c21 = matrix_add(p3, p4)
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c22 = matrix_minus(matrix_add(p5, p1), matrix_add(p3, p7))
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matrix_all = matrix_merge(c11, c12, c21, c22)
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global num_assign
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num_assign =num_assign+22
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return matrix_all
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def main():
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# statistical data
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A = np.random.random_integers(-5, 5, size=(256, 64))
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print("\nRandom Matrix A:\n", A)
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B = np.random.random_integers(-5, 5, size=(64, 128))
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print("\nRandom Matrix B:\n", B)
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C_verification=np.dot(A,B)
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result = strassen(A, B)
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print("\n A*B Result of matrixs by generate randomly\n",np.array(result))
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print("\nfrequency of add/sub",num_addorsub)
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print("frequency of assign", num_assign)
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print("frequency of mul", num_mul)
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if (C_verification==result).all():
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print("\nCorrect")
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else:
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print("\nWrong")
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if __name__ == '__main__':
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main()
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164 |
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# frequency of add/sub 4499186
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165 |
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# frequency of assign 3989370
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166 |
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# frequency of mul 941192
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167 |
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# 2097152
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