Matrix manipulation in Python
In python matrix can be implemented as 2D list or 2D Array. Forming matrix from latter, gives the additional functionalities for performing various operations in matrix. These operations and array are defines in module “numpy“.
Operation on Matrix :
1. add() :- This function is used to perform element wise matrix addition.
2. subtract() :- This function is used to perform element wise matrix subtraction.
3. divide() :- This function is used to perform element wise matrix division.
The element wise addition of matrix is : [[ 8 10] [13 15]] The element wise subtraction of matrix is : [[-6 -6] [-5 -5]] The element wise division of matrix is : [[ 0.14285714 0.25 ] [ 0.44444444 0.5 ]]
4. multiply() :- This function is used to perform element wise matrix multiplication.
5. dot() :- This function is used to compute the matrix multiplication, rather than element wise multiplication.
The element wise multiplication of matrix is : [[ 7 16] [36 50]] The product of matrices is : [[25 28] [73 82]]
6. sqrt() :- This function is used to compute the square root of each element of matrix.
7. sum(x,axis) :- This function is used to add all the elements in matrix. Optional “axis” argument computes the column sum if axis is 0 and row sum if axis is 1.
8. “T” :- This argument is used to transpose the specified matrix.
The element wise square root is : [[ 1. 1.41421356] [ 2. 2.23606798]] The summation of all matrix element is : 34 The column wise summation of all matrix is : [16 18] The row wise summation of all matrix is : [15 19] The transpose of given matrix is : [[1 4] [2 5]]
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