Evaluate Einstein’s summation convention of two multidimensional NumPy arrays
In Python, we can use the einsum() function of the NumPy package to compute Einstein’s summation convention of two given multidimensional arrays.
Syntax: numpy.einsum(subscripts, *operands, out=None)
Parameters:
subscripts : str
Specifies the subscripts for summation as comma separated list of subscript labels. An implicit (classical Einstein summation) calculation is performed unless the explicit indicator ‘->’ is included as well as subscript labels of the precise output form.
operands : list of array_like
These are the arrays for the operation.
out : ndarray, optional
If provided, the calculation is done into this array.
Returns: The calculation based on the Einstein summation convention.
Example 1: Einstein’s summation convention of two 2X2 matrices
Python3
# Importing library import numpy as np # Creating two 2X2 matrix matrix1 = np.array([[ 1 , 2 ], [ 0 , 2 ]]) matrix2 = np.array([[ 0 , 1 ], [ 3 , 4 ]]) print ( "Original matrix:" ) print (matrix1) print (matrix2) # Output result = np.einsum( "mk,kn" , matrix1, matrix2) print ( "Einstein’s summation convention of the two matrix:" ) print (result) |
Output:
Original matrix: [[1 2] [0 2]] [[0 1] [3 4]] Einstein’s summation convention of the two matrix: [[6 9] [6 8]]
Example 2: Einstein’s summation convention of two 3X3 matrices
Python3
# Importing library import numpy as np # Creating two 3X3 matrix matrix1 = np.array([[ 2 , 3 , 5 ], [ 4 , 0 , 2 ], [ 0 , 6 , 8 ]]) matrix2 = np.array([[ 0 , 1 , 5 ], [ 3 , 4 , 4 ], [ 8 , 3 , 0 ]]) print ( "Original matrix:" ) print (matrix1) print (matrix2) # Output result = np.einsum( "mk,kn" , matrix1, matrix2) print ( "Einstein’s summation convention of the two matrix:" ) print (result) |
Output:
Original matrix: [[2 3 5] [4 0 2] [0 6 8]] [[0 1 5] [3 4 4] [8 3 0]] Einstein’s summation convention of the two matrix: [[49 29 22] [16 10 20] [82 48 24]]
Example 3: Einstein’s summation convention of two 4X4 matrices
Python3
# Importing library import numpy as np # Creating two 4X4 matrix matrix1 = np.array([[ 1 , 2 , 3 , 5 ], [ 4 , 4 , 0 , 2 ], [ 0 , 1 , 6 , 8 ], [ 0 , 5 , 6 , 9 ]]) matrix2 = np.array([[ 0 , 1 , 9 , 2 ], [ 3 , 3 , 4 , 4 ], [ 1 , 8 , 3 , 0 ], [ 5 , 2 , 1 , 6 ]]) print ( "Original matrix:" ) print (matrix1) print (matrix2) # Output result = np.einsum( "mk,kn" , matrix1, matrix2) print ( "Einstein’s summation convention of the two matrix:" ) print (result) |
Output:
Original matrix: [[1 2 3 5] [4 4 0 2] [0 1 6 8] [0 5 6 9]] [[0 1 9 2] [3 3 4 4] [1 8 3 0] [5 2 1 6]] Einstein’s summation convention of the two matrix: [[34 41 31 40] [22 20 54 36] [49 67 30 52] [66 81 47 74]]
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