Format Conversion

Converting between sparse matrix formats.

Conversion Methods

1. To CSR

from scipy import sparse

def main():
    coo = sparse.random(5, 5, density=0.3, format='coo')
    csr = coo.tocsr()
    print(f"Converted to CSR: {type(csr)}")

if __name__ == "__main__":
    main()

2. To CSC

from scipy import sparse

def main():
    csr = sparse.random(5, 5, density=0.3, format='csr')
    csc = csr.tocsc()
    print(f"Converted to CSC: {type(csc)}")

if __name__ == "__main__":
    main()

3. To Dense

from scipy import sparse

def main():
    csr = sparse.random(5, 5, density=0.3, format='csr')

    # Method 1
    dense1 = csr.toarray()

    # Method 2
    dense2 = csr.todense()  # Returns matrix

    print(type(dense1))  # ndarray
    print(type(dense2))  # matrix

if __name__ == "__main__":
    main()

Conversion Table

From/To	.tocsr()	.tocsc()	.tocoo()	.tolil()	.toarray()
CSR	-	Fast	Fast	Slow	Fast
CSC	Fast	-	Fast	Slow	Fast
COO	Fast	Fast	-	Fast	Fast
LIL	Fast	Fast	Fast	-	Fast

Best Practices

1. Build then Convert

from scipy import sparse

def main():
    # Build with LIL
    lil = sparse.lil_matrix((1000, 1000))
    for i in range(1000):
        lil[i, i] = 2
        if i > 0:
            lil[i, i-1] = -1

    # Convert once for computation
    csr = lil.tocsr()

    # Use CSR for all operations
    x = csr @ [1]*1000
    print(f"Result norm: {sum(x)}")

if __name__ == "__main__":
    main()

2. Avoid Repeated Conversion

from scipy import sparse
import time

def main():
    A = sparse.random(1000, 1000, density=0.01, format='coo')

    # Bad: convert every iteration
    start = time.perf_counter()
    for _ in range(100):
        csr = A.tocsr()
        _ = csr.sum()
    bad_time = time.perf_counter() - start

    # Good: convert once
    start = time.perf_counter()
    csr = A.tocsr()
    for _ in range(100):
        _ = csr.sum()
    good_time = time.perf_counter() - start

    print(f"Bad (repeated): {bad_time:.4f} sec")
    print(f"Good (once):    {good_time:.4f} sec")

if __name__ == "__main__":
    main()

Summary

• Use .tocsr() for row operations and general arithmetic
• Use .tocsc() for column operations
• Use .toarray() only for small matrices or visualization
• Convert once, use many times