# Python | Numpy np.hermevander3d() method

Last Updated : 11 Dec, 2019

With the help of `np.hermevander3d()` method, we can get the pseudo vandermonde matrix of a given 3-D data having degrees x, y and z by using `np.hermevander3d()` method.

Syntax : `np.hermevander3d(x, y, z, [x_deg, y_deg, z_deg])`

Return : Return the pseudo vandermonde matrix of given 3-D data.

Example #1 :
In this example we can see that by using `np.hermevander3d()` method, we are able to get the pseudo vandermonde matrix of a given 3-D data having degree (x, y, z) by using this method.

 `# import numpy and hermevander3d ` `import` `numpy as np ` `from` `numpy.polynomial.hermite_e ``import` `hermevander3d ` ` `  `x ``=` `np.array([``1``, ``0.1``]) ` `y ``=` `np.array([``2``, ``0.2``]) ` `z ``=` `np.array([``3``, ``0.3``]) ` `x_deg, y_deg, z_deg ``=` `2``, ``3``, ``1` ` `  `# using np.hermevander3d() method ` `gfg ``=` `hermevander3d(x, y, z, [x_deg, y_deg, z_deg]) ` ` `  `print``(gfg) `

Output :

[[ 1.00000e+00 3.00000e+00 2.00000e+00 6.00000e+00 3.00000e+00
9.00000e+00 2.00000e+00 6.00000e+00 1.00000e+00 3.00000e+00
2.00000e+00 6.00000e+00 3.00000e+00 9.00000e+00 2.00000e+00
6.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00
0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00]
[ 1.00000e+00 3.00000e-01 2.00000e-01 6.00000e-02 -9.60000e-01
-2.88000e-01 -5.92000e-01 -1.77600e-01 1.00000e-01 3.00000e-02
2.00000e-02 6.00000e-03 -9.60000e-02 -2.88000e-02 -5.92000e-02
-1.77600e-02 -9.90000e-01 -2.97000e-01 -1.98000e-01 -5.94000e-02
9.50400e-01 2.85120e-01 5.86080e-01 1.75824e-01]]

Example #2 :

 `# import numpy and hermevander3d ` `import` `numpy as np ` `from` `numpy.polynomial.hermite_e ``import` `hermevander3d ` ` `  `x ``=` `np.array([``1.01``, ``2.02``, ``3.03``]) ` `y ``=` `np.array([``10.1``, ``20.2``, ``30.3``]) ` `z ``=` `np.array([``0.1``, ``0.2``, ``0.3``]) ` `x_deg, y_deg, z_deg ``=` `1``, ``1``, ``3` ` `  `# using np.hermevander3d() method ` `gfg ``=` `hermevander3d(x, y, z, [x_deg, y_deg, z_deg]) ` ` `  `print``(gfg) `

Output :

[[ 1. 0.1 -0.99 -0.299 10.1 1.01
-9.999 -3.0199 1.01 0.101 -0.9999 -0.30199
10.201 1.0201 -10.09899 -3.050099]
[ 1. 0.2 -0.96 -0.592 20.2 4.04
-19.392 -11.9584 2.02 0.404 -1.9392 -1.19584
40.804 8.1608 -39.17184 -24.155968]
[ 1. 0.3 -0.91 -0.873 30.3 9.09
-27.573 -26.4519 3.03 0.909 -2.7573 -2.64519
91.809 27.5427 -83.54619 -80.149257]]

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