Mask specific columns of a numpy array

问题:

I have a 2D numpy array A of (60,1000) dimensions.
Say, I have a variable idx=array([3,72,403, 512, 698]).

Now, I want to mask all the elements in the columns specified in idx. The values in these columns might appear in other columns but they shouldn't be masked.

Any help would be appriciated.

回答1:

In [22]: A = np.random.rand(5, 10)

In [23]: idx = np.array([1, 3, 5])

In [24]: m = np.zeros_like(A)

In [25]: m[:,idx] = 1

In [26]: Am = np.ma.masked_array(A, m)

In [27]: Am
Out[27]: 
masked_array(data =
 [[0.680447483547 -- 0.290757600047 -- 0.0718559525615 -- 0.334352145502
  0.0861242618662 0.527068091963 0.136280743038]
 [0.729374999214 -- 0.76026650048 -- 0.656082247985 -- 0.492464543871
  0.903026937193 0.0792660503403 0.892132409419]
 [0.0845266821684 -- 0.838838594048 -- 0.396344231382 -- 0.703748703373
  0.380441396691 0.010521007806 0.344945867845]
 [0.7501401585 -- 0.0685427000113 -- 0.587100320511 -- 0.780160645327
  0.276328587928 0.0665949459004 0.604174142611]
 [0.599926798275 -- 0.686378805503 -- 0.776940069716 -- 0.0452833614622
  0.598622591094 0.942843765543 0.528082379918]],
             mask =
 [[False  True False  True False  True False False False False]
 [False  True False  True False  True False False False False]
 [False  True False  True False  True False False False False]
 [False  True False  True False  True False False False False]
 [False  True False  True False  True False False False False]],
       fill_value = 1e+20)