carpet/proximity.py
def pseudo_soft_th_numpy(z, lbda, step_size):
    """ Pseudo Soft-thresholding for numpy array. """
    assert z.ndim == 2
    z_ = np.atleast_2d(_soft_th_numpy(z[:, 1:], lbda * step_size))
    z0_ = np.atleast_2d(z[:, 0])
    z0_ = z0_.T if z0_.shape[0] != z_.shape[0] else z0_
    return np.concatenate((z0_, z_), axis=1)
 Pseudo Soft-thresholding for numpy array. 
Pseudo Soft-thresholding for numpy array.
Pseudo Soft - thresholding for numpy array .
def pseudo_soft_th_numpy(z, lbda, step_size):
    assert z.ndim == 2
    z_ = np.atleast_2d(_soft_th_numpy(z[:, 1:], lbda * step_size))
    z0_ = np.atleast_2d(z[:, 0])
    z0_ = z0_.T if z0_.shape[0] != z_.shape[0] else z0_
    return np.concatenate((z0_, z_), axis=1)
def pseudo_soft_th_numpy ( z , lbda , step_size ) : assert z . ndim == 2 z_ = np . atleast_2d ( _soft_th_numpy ( z [ : , 1 : ] , lbda * step_size ) ) z0_ = np . atleast_2d ( z [ : , 0 ] ) z0_ = z0_ . T if z0_ . shape [ 0 ] != z_ . shape [ 0 ] else z0_ return np . concatenate ( ( z0_ , z_ ) , axis = 1 )
Pseudo Soft-thresholding for numpy array.
Pseudo Soft - thresholding for numpy array .
""" Pseudo Soft-thresholding for numpy array. """
z
lbda
step_size