import numpy as np
from scipy.sparse import coo_array

row = np.array([0, 0, 1, 2, 2])
col = np.array([0, 2, 2, 0, 0])
data = np.array([10, 3, 8, 4, 6], dtype=float)

coo = coo_array((data, (row, col)), shape=(3, 4))
csr = coo.tocsr()
weights = np.array([1.0, 2.0, 0.5, 0.0])

print("coo format:", coo.format)
print("coo shape:", coo.shape)
print("coo stored values:", coo.nnz)
print("csr format:", csr.format)
print("csr stored values:", csr.nnz)
print("dense rows:")
for dense_row in csr.toarray():
    print(dense_row)
print("row totals:", np.asarray(csr.sum(axis=1)).ravel())
print("matrix-vector product:", csr @ weights)