bem.py 文件源码

def _one_step(mu, u):
    """Evaluate the residual sum of squares fit for one set of mu values"""
    if np.abs(mu).max() > 1.0:
        return 1.0

    # Compose the data for the linear fitting, compute SVD, then residuals
    _compose_linear_fitting_data(mu, u)
    u['uu'], u['sing'], u['vv'] = linalg.svd(u['M'])
    u['resi'][:] = u['y'][:]
    for p in range(u['nfit'] - 1):
        dot = np.dot(u['uu'][p], u['y'])
        for k in range(u['nterms'] - 1):
            u['resi'][k] = u['resi'][k] - u['uu'][p, k] * dot

    # Return their sum of squares
    return np.dot(u['resi'], u['resi'])