Python Numpy,mask图像的生成详解

An array class with possibly masked values.
Masked values of True exclude the corresponding element from any computation.

Construction::

 x = MaskedArray(data, mask=nomask, dtype=None, copy=False, subok=True,
     ndmin=0, fill_value=None, keep_mask=True, hard_mask=None,
     shrink=True, order=None)

Parameters
----------
data : array_like
 Input data.
mask : sequence, optional
 Mask. Must be convertible to an array of booleans with the same
 shape as `data`. True indicates a masked (i.e. invalid) data.
fill_value : scalar, optional
 Value used to fill in the masked values when necessary.
 If None, a default based on the data-type is used.

import numpy.ma as npm
import numpy as np

data = np.random.randint(1, 10, size=[1, 5, 5])
mask = data < 5
arr = npm.array(data, mask=mask)
print(arr)

#[[[6 6 -- 8 --]
# [-- -- -- 6 7]
# [9 -- -- 6 9]
# [-- -- 5 -- 8]
# [6 9 -- 5 --]]]

import numpy as np

arr = np.random.randint(1, 10, size=[1, 5, 5])
mask = arr<5
arr[mask] = 0 # 把标记为True的值记为0
print(arr)

#[[[9 9 7 6 0]
# [0 0 6 9 0]
# [8 0 8 5 0]
# [0 5 5 8 9]
# [0 7 0 0 6]]]