Python Numpy阵列阈值加速

我想使用条件数组从另一个np.array构造一个np.array。对于每个值，如果满足条件，则必须应用一个操作，否则应用另一个操作。我写的计算是丑陋的，因为转换和返回一个列表。是否可以通过不转换为列表来提高速度

THR = 1.0
THR_REZ = 1.0 / THR**2

def thresholded_function(x):
  if x < THR:
    return THR_REZ
  else:
    return 1.0 / x**2

rad2 = .....some_np_array.....
rez = np.array([threshold(r2) for r2 in rad2])

使用-

样本运行-

In [267]: x = np.array([3,7,2,1,8])

In [268]: THR, THR_REZ = 5, 0

In [269]: np.where(x < THR, THR_REZ, 1.0/x**2)
Out[269]: array([ 0.        ,  0.02040816,  0.        ,  0.        ,  0.015625  ])

In [270]: def thresholded_function(x, THR, THR_REZ):
     ...:   if x < THR:
     ...:     return THR_REZ
     ...:   else:
     ...:     return 1.0 / x**2

In [272]: [thresholded_function(i,THR, THR_REZ) for i in x]
Out[272]: [0, 0.02040816326530612, 0, 0, 0.015625]

In [267]: x = np.array([3,7,2,1,8])

In [268]: THR, THR_REZ = 5, 0

In [269]: np.where(x < THR, THR_REZ, 1.0/x**2)
Out[269]: array([ 0.        ,  0.02040816,  0.        ,  0.        ,  0.015625  ])

In [270]: def thresholded_function(x, THR, THR_REZ):
     ...:   if x < THR:
     ...:     return THR_REZ
     ...:   else:
     ...:     return 1.0 / x**2

In [272]: [thresholded_function(i,THR, THR_REZ) for i in x]
Out[272]: [0, 0.02040816326530612, 0, 0, 0.015625]