Evaluate a 2-D Hermite_e series at points (x,y) using NumPy in Python
In this article, we will cover how to evaluate a 2-D Hermite_e series at points (x,y) in Python.
polynomial.hermite.hermval2d
The numpy.polynomial.hermite.hermval2d() from the NumPy library is used to Evaluate a 2-D Hermite_e series at points(x,y) in Python. If the parameters x and y are tuples or lists, they are converted to arrays otherwise they are treated as scalars and must have the same shape after conversion. In either case, x and y or their elements must support multiplication and addition with themselves as well as with the elements of c. If c is a one-dimensional array, a one is implicitly appended to its shape to make it two-dimensional. The final shape will be c.shape[2:] + x.shape.
Syntax: polynomial.hermite.hermval2d(x, y, c)
Parameters :
- x , y: array like compatible objects.
- c: array like object.
Returns : The values of the two-dimensional polynomial at coordinates formed by corresponding pairs of x and y values.
Example 1:
The NumPy package is imported. An array is created which represents coefficients of the Hermite series. polynomial.hermite.hermval2d(x, y, c) is used to evaluate a 2-D Hermite series, in the below example, arrays are given for x and y parameters which represent multiple points. The shape, datatype, and dimension of the array are found by using the .shape, .dtype, and .ndim attributes.
Python3
import numpy as np
from numpy.polynomial import hermite as H
array = np.array([[ 5 , 6 ],[ 7 , 8 ]])
print (array)
print ( "Shape of the array is : " ,array.shape)
print ( "The dimension of the array is : " ,array.ndim)
print ( "Datatype of our Array is : " ,array.dtype)
print (H.hermval2d([ 1 , 1 ],[ 2 , 2 ],array))
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Output:
[[5 6]
[7 8]]
Shape of the array is : (2, 2)
The dimension of the array is : 2
Datatype of our Array is : int64
[107. 107.]
Example 2:
In this example, scalars are given as x and y parameters which represent a single point and the 2-d Hermite series is evaluated at that point.
Python3
import numpy as np
from numpy.polynomial import hermite as H
array = np.array([[ 5 , 6 ],[ 7 , 8 ]])
print (array)
print ( "Shape of the array is : " ,array.shape)
print ( "The dimension of the array is : " ,array.ndim)
print ( "Datatype of our Array is : " ,array.dtype)
print (H.hermval2d( 1 , 2 ,array))
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Output:
[[5 6]
[7 8]]
Shape of the array is : (2, 2)
The dimension of the array is : 2
Datatype of our Array is : int64
107.0
Last Updated :
03 Jun, 2022
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