  # Python | Numpy np.hermevander2d () method

NumPy | Python Methods and Functions

With the method `np.hermevander2d() `, we can get the pseudo-Vandermonde matrix for 2D data that has degrees x and y using ` np. hermevander2d () `.

Syntax: ` np.hermevander2d (x, y, [x_deg, y_deg]) `
Return: Return the pseudo vandermonde matrix of given 2-D data.

Example # 1:
B In this example, we can see that with ` np.hermevander2d () ` we can get a pseudo-vander data matrix of two-dimensional data having degree (x, y) using this method.

` `

` # import numpy and hermevander2d import numpy as np from numpy.polynomial.hermite_e import hermevander2d   x = np.array ([ 0.1 , 0.2 ]) y = np.array ([ 2 , 0.2 ]) x_deg, y_deg = 2 , 3 # using the np.hermevander2d () method gfg = hermevander2d (x, y, [x_deg , y_deg])   print (gfg) `

` `

Output:

[[1. 2. 3. 2. 0.1 0.2 0.3 0.2
-0.99 -1.98 -2.97 -1.98]
[1. 0.2 -0.96 -0.592 0.2 0.04 -0.192 -0.1184
-0.96 -0.192 0.9216 0.56832]]

Example No. 2 :

 ` # import numpy and hermevander2d ` ` import ` ` numpy as np ` ` from ` ` numpy.polynomial.hermite_e ` ` import ` ` hermevander2d `   ` x ` ` = ` ` np.array ([` ` 1.01 ` `, ` ` 2.02 < / code> , 3.03 ]) `` y = np.array ([ 10.1 , 20.2 , 30.3 ]) x_deg, y_deg = 1 , 1 # using the np.hermevander2d () method gfg = hermevander2d (x, y, [x_deg, y_deg])   print (gfg) `

Output:

[[1. 10.1 1.01 10.201]
[ one. 20.2 2.02 40.804]
[1. 30.3 3.03 91.809]]