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schedule Aug 12, 2023
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PythonNumPy
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Numpy's `deg2rad(~)` converts degrees to radians.

Note that this method is equivalent to Numpy's `radians(~)` method.

# Parameters

1. `a` | `array-like`

The input array of degrees that you want to convert to radians.

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. Since this is a source of confusion for many, check examples below.

# Return value

If `a` is a scalar, then a scalar is returned. Otherwise, a Numpy array of floats is returned.

# Examples

## Basic usage

``` np.degrad([90, 180]) array([1.57079633, 3.14159265]) ```

## Specifying an output array

``` a = np.zeros(2)np.degrad([90,180], out=a)a array([1.57079633, 3.14159265]) ```

``` np.degrad([90,180,270], where=[False, True, False]) array([7435.3435 , 3.14159265, 3463.2345 ]) ```

Here, only the second number was used for calculation since it has a corresponding boolean of `True` in the mask. You should notice how the values with `False` yielded strange results - in fact, you should disregard them because they are uninitialized numbers that are of no practical use.

Now, if you specified the `out` parameter, instead of uninitalized values, the original values will be left intact:

``` a = np.zeros(3)np.degrad([90,180,270], out=a, where=[False, True, False])a array([0. , 3.14159265, 0. ]) ```
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