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# NumPy | positive method

schedule Aug 11, 2023
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Numpy's `positive(~)` method returns a new copy of the input array. This means that modifying this new copy will not have an impact on the original input array. Note that this method does not convert negative values to positive values.

WARNING

Opt to use Numpy's `copy(~)` method instead.

# Parameters

1. `a` | `array-like`

The first input array.

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

Instead of creating a new array, you can place the 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

A scalar is returned if `a` is a scalar, otherwise a Numpy array is returned.

# Examples

## Basic usage

``` a = np.array([1,-2,3])b = np.positive(a)b array([1, -2, 3]) ```
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