/NumPy 1.17

# numpy.extract

`numpy.extract(condition, arr)` [source]

Return the elements of an array that satisfy some condition.

This is equivalent to `np.compress(ravel(condition), ravel(arr))`. If `condition` is boolean `np.extract` is equivalent to `arr[condition]`.

Note that `place` does the exact opposite of `extract`.

Parameters: `condition : array_like` An array whose nonzero or True entries indicate the elements of `arr` to extract. `arr : array_like` Input array of the same size as `condition`. `extract : ndarray` Rank 1 array of values from `arr` where `condition` is True.

#### Examples

```>>> arr = np.arange(12).reshape((3, 4))
>>> arr
array([[ 0,  1,  2,  3],
[ 4,  5,  6,  7],
[ 8,  9, 10, 11]])
>>> condition = np.mod(arr, 3)==0
>>> condition
array([[ True, False, False,  True],
[False, False,  True, False],
[False,  True, False, False]])
>>> np.extract(condition, arr)
array([0, 3, 6, 9])
```

If `condition` is boolean:

```>>> arr[condition]
array([0, 3, 6, 9])
```

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https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.extract.html