# Python | Numpy np.cholesky() method

Last Updated : 11 Nov, 2019

With the help of `np.cholesky()` method, we can get the cholesky decomposition by using `np.cholesky()` method.

Syntax : `np.cholesky(matrix)`
Return : Return the cholesky decomposition.

Example #1 :
In this example we can see that by using `np.cholesky()` method, we are able to get the cholesky decomposition in the form of matrix using this method.

 `# import numpy ` `import` `numpy as np ` ` `  `a ``=` `np.array([[``2``, ``-``3j``], [``5j``, ``15``]]) ` `# using np.cholesky() method ` `gfg ``=` `np.linalg.cholesky(a) ` ` `  `print``(gfg) `

Output :

[[1.41421356 + 0.j, 0. + 0.j]
[0. + 3.53553391j, 1.58113883 + 0.j]]

Example #2 :

 `# import numpy ` `import` `numpy as np ` ` `  `a ``=` `np.array([[``12``, ``-``13j``], [``4j``, ``8``]]) ` `# using np.cholesky() method ` `gfg ``=` `np.linalg.cholesky(a) ` ` `  `print``(gfg) `

Output :

[[3.46410162 + 0.j, 0. + 0.j]
[0. + 1.15470054j, 2.5819889 + 0.j]]

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