Examples of how to get the type of a matrix using numpy in python:
Get the type of a matrix using the attribute dtype
To get the type a matrix, a solution is to use dtype, example:
import numpy as np
A = np.array([[1.2, 2.3, 3.4]])
print(A.dtype)
returns
float64
Change the type of a matrix
To indicate the type of a matrix, a solution is to do:
A = np.array([[1.2, 2.3, 3.4]], dtype=int)
print(A)
print(A.dtype)
returns respectively
[[1 2 3]]
and
int64
Or to use astype to change the type of an existing matrix::
A = A.astype('float64')
print(A.dtype)
returns
float64
Combine matrix with different type
It is important to check the type of a matrix to avoid loosing information, an example let's consider the following matrix A:
A = np.array([[10, 20, 30], [60, 20, 10], [50, 30, 90]])
returns
[[10 20 30]
[60 20 10]
[50 30 90]]
and the matrix B:
B= np.array([[2.1, 7.3, 4.5]])
returns
[[2.1 7.3 4.5]]
Now, if the matrix A is updated using B, like:
A[1,:] = B
returns
[[10 20 30]
[ 2 7 4]
[50 30 90]]
but the elements of B have been modified. To avoid that a solution would have been to do first:
A = A.astype('float64')
A[1,:] = B
returns
[[10. 20. 30. ]
[ 2.1 7.3 4.5]
[50. 30. 90. ]]