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# NumPy | logical_not method

schedule Aug 12, 2023
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Numpy's `logical_not(~)` whether each value in the input array evaluates to False. A useful interpretation of this method is that it flips the boolean, that is, True become False and vice versa.

# Parameters

1. `a` | `array_like`

The input array.

2. `out` | `Numpy array` | `optional`

Instead of creating a new array, you can place the computed result into the array specified by `out`.

3. `where` | `array` of `boolean` | `optional`

Values that are flagged as False will be ignored, that is, their original value will be uninitialized. If you specified the out parameter, the behavior is slightly different - the original value will be kept intact.

# Return value

If `a` is a scalar, then a single boolean is returned. Otherwise, a Numpy array of booleans is returned.

# Examples

## Basic usage

``` np.logical_not([False, True]) array([ True, False]) `````` np.logical_not([0, 1, 5]) array([ True, False, False]) ```

On a more practical note, suppose we wanted to find that numbers are not even from an array:

``` a = np.array([1,2,3,4,5])mask = np.logical_not(a%2==0)mask array([ True, False, True, False, True]) ```

To fetch the values that fit our criteria (i.e. the one flagged as True):

``` a[mask] array([1, 3, 5]) ```
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