I have a boolean mask array a of length n:
a = np.array([True, True, True, False, False])
I have a 2d array with n columns:
b = np.array([[1,2,3,4,5], [1,2,3,4,5]])
I want a new array which contains only the "True"-values, for example
c = ([[1,2,3], [1,2,3]])
c = a * b does not work because it contains also "0" for the false columns what I don't want
c = np.delete(b, a, 1) does not work
Any suggestions?
You probably want something like this:
>>> a = np.array([True, True, True, False, False])
>>> b = np.array([[1,2,3,4,5], [1,2,3,4,5]])
>>> b[:,a]
array([[1, 2, 3],
[1, 2, 3]])
Note that for this kind of indexing to work, it needs to be an ndarray, like you were using, not a list, or it'll interpret the False and True as 0 and 1 and give you those columns:
>>> b[:,[True, True, True, False, False]]
array([[2, 2, 2, 1, 1],
[2, 2, 2, 1, 1]])
ndarray of shape (2800000,600), trying to use a mask with 200 True values is slow. Are there any optimisations?
np.bool. So I added b[:,a.astype(np.bool)]You can use numpy.ma module and use np.ma.masked_array function to do so.
>>> x = np.array([1, 2, 3, -1, 5])
>>> mx = ma.masked_array(x, mask=[0, 0, 0, 1, 0])
masked_array(data=[1, 2, 3, --, 5], mask=[False, False, False, True, False], fill_value=999999)
Hope I'm not too late! Here's your array:
X = np.array([[1, 2, 3, 4, 5],
[1, 2, 3, 4, 5]])
Let's create an array of zeros of the same shape as X:
mask = np.zeros_like(X)
# array([[0, 0, 0, 0, 0],
# [0, 0, 0, 0, 0]])
Then, specify the columns that you want to mask out or hide with a 1. In this case, we want the last 2 columns to be masked out.
mask[:, -2:] = 1
# array([[0, 0, 0, 1, 1],
# [0, 0, 0, 1, 1]])
Create a masked array:
X_masked = np.ma.masked_array(X, mask)
# masked_array(data=[[1, 2, 3, --, --],
# [1, 2, 3, --, --]],
# mask=[[False, False, False, True, True],
# [False, False, False, True, True]],
# fill_value=999999)
We can then do whatever we want with X_masked, like taking the sum of each column (along axis=0):
np.sum(X_masked, axis=0)
# masked_array(data=[2, 4, 6, --, --],
# mask=[False, False],
# fill_value=1e+20)
Great thing about this is that X_masked is just a view of X, not a copy.
X_masked.base is X
# True