nddl.py 文件源码

def _downsample_mask(X, pct):
    """ Create a boolean mask indicating which subset of X should be
    evaluated.
    """
    if pct < 1.0:
        Mask = np.zeros(X.shape, dtype=np.bool)
        m = X.shape[-2]
        n = X.shape[-1]
        nToEval = np.round(pct*m*n).astype(np.int32)
        idx = sobol(2, nToEval ,0)
        idx[0] = np.floor(m*idx[0])
        idx[1] = np.floor(n*idx[1])
        idx = idx.astype(np.int32)
        Mask[:,:,idx[0], idx[1]] = True
    else:
        Mask = np.ones(X.shape, dtype=np.bool)

    return Mask