sparse matrix representation python use
import numpy as np
from scipy.sparse import csr_matrix
# create a 2-D representation of the matrix
A = np.array([[1, 0, 0, 0, 0, 0], [0, 0, 2, 0, 0, 1],
[0, 0, 0, 2, 0, 0]])
print("Dense matrix representation: n", A)
# convert to sparse matrix representation
S = csr_matrix(A)
print("Sparse matrix: n",S)
# convert back to 2-D representation of the matrix
B = S.todense()
print("Dense matrix: n", B)how to convert a dense matrix into sparse matrix in python
# dense to sparse
from numpy import array
from scipy.sparse import csr_matrix
# create dense matrix
A = array([[1, 0, 0, 1, 0, 0], [0, 0, 2, 0, 0, 1], [0, 0, 0, 2, 0, 0]])
print(A)
# convert to sparse matrix (CSR method)
S = csr_matrix(A)
print(S)
# reconstruct dense matrix
B = S.todense()
print(B)Copyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
