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math,numpy - pyStudent - Apr-16-2021
I need write a function which generate a random matrix (bigger than 2x2). And calculate all the 2x2 part determinant of the generated matrix and generate a new matrix with that values.
that's my code:
arr = np.random.randint(1,10,(3,3)) matrix = np.zeros((3,3)) matrix[0][0] = int(np.linalg.det(arr[0:2,0:2])) matrix[0][1] = int(np.linalg.det(arr[0:2,1:3])) matrix[1][0] = int(np.linalg.det(arr[1:3,0:2])) matrix[1][1] = int(np.linalg.det(arr[1:3,1:3]))how can i edit this to work for exaple on a 4x4 or on a 16x16 matrix?
RE: math,numpy - Gribouillis - Apr-21-2021
I suggest
b = a[:-1,:-1] * a[1:,1:] - a[:-1,1:] * a[1:,:-1]For example
>>> import numpy as np >>> a = np.random.randint(1, 10,(5,6)) >>> b = a[:-1,:-1] * a[1:,1:] - a[:-1,1:] * a[1:,:-1] >>> print(a) [[4 1 8 9 4 4] [3 6 7 8 9 1] [9 4 8 6 5 7] [9 7 1 8 4 1] [1 4 9 5 4 7]] >>> print(b) [[ 21 -41 1 49 -32] [-42 20 -22 -14 58] [ 27 -52 58 -16 -23] [ 29 59 -67 12 24]]
RE: math,numpy - pyStudent - Apr-26-2021
Thanks for your solution.
It works perfectly.