Boolean indexing on multidimensionnal array

Boolean indexing on multidimensionnal array

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Boolean indexing on multidimensionnal array
Tag : python , By : Nic Doye
Date : November 25 2020, 03:01 PM

Any of those help I'm very new in Python and in Numpy. In fact, I'm just learning. , You have 3 arrays in 1 array:
 [ 0,  1,  2,  3,  4],
 [ 5,  6,  7,  8,  9],
 [10, 11, 12, 13, 14]
 [15, 16, 17, 18, 19],
 [20, 21, 22, 23, 24],
 [25, 26, 27, 28, 29]

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Indexing a Boolean Array with another Boolean Array in Python

Tag : python , By : eataix
Date : March 29 2020, 07:55 AM
I wish this helpful for you I have a dataset with two Boolean arrays. , Here you go. That does exactly what you need.
errors_with_length = [b for b, l in zip(Boolean_error, Has_length) if l]
>>> list(itertools.compress(Boolean_error, Has_length))
[False, True, False, True, False, True, False, False, False, False]

weird result when using both slice indexing and boolean indexing on a 3d array

Tag : python , By : Lucyberad
Date : March 29 2020, 07:55 AM
will help you a[0, :, mask] mixes advanced indexing with slicing. The : is a "slice index", while the 0 (for this purpose) and mask are consider "advanced indexes".
The rules governing the behavior of indexing when both advanced indexing and slicing are combined state:

Numpy - Indexing with Boolean array

Tag : python , By : Vitalik
Date : March 29 2020, 07:55 AM
fixed the issue. Will look into that further I have a numpy array of shape (6,5) and i am trying to index it with Boolean arrays. I slice the boolean array along the columns and then use that slice to index the original array, everything is fine, however as soon as i do the same thing along the rows i get the below error. Below is my code, , Since there are only 5 entries in rows,
In [18]: rows
Out[18]: array([ True,  True, False, False, False], dtype=bool)
In [20]: arr.shape
Out[20]: (6, 5)

In [21]: rows.shape
Out[21]: (5,)
# select all rows but only columns where rows is `True`
In [19]: arr[:, rows]
array([[73, 20],
       [18, 66],
       [27, 83],
       [78, 74],
       [26, 18],
       [41, 16]])

Boolean indexing array through array of boolean indexes without loop

Tag : python , By : JoeCh
Date : March 29 2020, 07:55 AM
will help you Approach #1
Simply broadcast a to b's shape with np.broadcast_to and then mask it with b -
In [15]: np.broadcast_to(a,b.shape)[b]
Out[15]: array([0, 2, 2, 3])
_,r,c = np.nonzero(b)
out = a[r,c]
In [50]: np.random.seed(0)
    ...: a = np.random.rand(200,200)
    ...: b = np.random.rand(200,200,200)>0.5

In [51]: %timeit np.broadcast_to(a,b.shape)[b]
45.5 ms ± 381 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)

In [52]: %timeit a.ravel()[np.flatnonzero(b)%a.size]
94.6 ms ± 1.64 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

In [53]: %%timeit
    ...: _,r,c = np.nonzero(b)
    ...: out = a[r,c]
128 ms ± 1.46 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

Trying to understand boolean array indexing

Tag : python , By : jrf
Date : March 29 2020, 07:55 AM
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