gram-schmidt-simple.py

import numpy as np

# A simple, no-frills gram schmidt implementation
def gram_schmidt(A):
    for k in range(0, A.shape[1]):
        # Normalize
        A[:, k] /= np.linalg.norm(A[:, k])
        # Subtract from vecs below
        for j in range(k+1, A.shape[1]):
            r = np.dot(A[:, k], A[:, j])
            A[:, j] -= r*A[:, k]
    return A