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# Python – scipy.fft.dctn() method

With the help of scipy.fft.dctn() method, we can compute the multidimensional discrete cosine transform by selecting different types of sequences and return the transformed array by using this method.

Syntax :

```scipy.fft.dctn(x, type=2)
```

Return value: It will return the transformed array.

Example #1: In this example, we can see that by using scipy.fft.dctn() method, we are able to get the multidimensional discrete cosine transform by selecting different types of sequences by default it’s 2.

## Python3

 `# import scipy and numpy ` `from` `scipy ``import` `fft ` `import` `numpy as np ` ` `  `array_gfg ``=` `np.random.randn(``3``, ``3``) ` ` `  `# Using scipy.fft.dctn() method ` `gfg ``=` `fft.dctn(array_gfg) ` ` `  `print``(gfg)`

Output :

```[[ -4.16635907  -4.02741393  -3.60128725]
[ -4.53247906  -3.48696887   0.9338914 ]
[-10.02597376  -5.30097223   6.56879818]]
```

Example #2:

## Python3

 `# import scipy and numpy ` `from` `scipy ``import` `fft ` `import` `numpy as np ` ` `  `array_gfg ``=` `np.random.randn(``5``, ``5``) ` ` `  `# Using scipy.fft.dctn() method ` `gfg ``=` `fft.dctn(array_gfg, ``1``) ` ` `  `print``(gfg)`

Output :

```[[-22.58866562   4.34759109   6.27133607 -10.09673997   1.42277882]
[-10.38551445  -1.73284723   4.77719083  -8.1483736    2.31129559]
[  5.09865556   7.7860346   -1.99346709  -8.19680308   5.54398566]
[ 11.03512166 -13.2738255   -6.30390925   5.55873569  -3.67046116]
[ 11.70752959 -13.28207081   6.20179649  11.0564309    5.17738824]]
```
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