Evaluate a Hermite_e series at list of points x using NumPy in Python

In this article, we will cover how to evaluate a Hermite_e series at the list of points x using NumPy in Python.

numpy.polynomial.hermite.hermval

To evaluate a Hermite series at points x with a multidimensional coefficient array, NumPy provides a function called hermite.hermval(). It takes two parameters x and c. whereas x is a tuple or list. It is considered a scalar. But, the parameter x should support multiplication and addition within itself and with the elements of c. If c is a 1-D array, then it will have the same shape as x. If c is multidimensional, then the shape of the result depends on the value of the tensor.

Syntax: numpy.polynomial.hermite.hermval

Parameters:

• x: array like object. 
• c: Array of coefficients 
• tensor: optional value, boolean type.

Returns:  ndarray of Hermite_e series

Example 1:

The NumPy package is imported. An array is created which represents coefficients of the Hermite series. polynomial.hermite.hermval() is used to evaluate a Hermite series at a list of points x. The shape, datatype, and dimension of the array are found by using the .shape, .dtype, and .ndim attributes. x is a list. 

Python3

# importing packages
import numpy as np
from numpy.polynomial import hermite as H

# array of coefficients
array = np.array([10,20,30,40])
print(array)

# shape of the array is
print("Shape of the array is : ",array.shape)

# dimension of the array
print("The dimension of the array is : ",array.ndim)

# evaluating a hermite series at list of points x
print(H.hermval([1,2,3],array))

Output:

[10 20 30 40]
Shape of the array is :  (4,)
The dimension of the array is :  1
[ -50. 2110. 8350.]

Example 2:

The NumPy package is imported. An array is created using NumPy, which represents coefficients of the Hermite series. polynomial.hermite.hermval() is used to evaluate a Hermite series at a list of points x, where x is [2,3,4]. The shape, datatype, and dimension of the array are found by using the .shape, .dtype, and .ndim attributes. x is a list. 

Python3

# importing packages
import numpy as np
from numpy.polynomial import hermite as H

# array of coefficients
array = np.array([20,30,40,45])
print(array)

# shape of the array is
print("Shape of the array is : ",array.shape)

# dimension of the array
print("The dimension of the array is : ",array.ndim)

# evaluating a hermite series at list of points x
print(H.hermval([2,3,4],array, tensor=False))

Output:

[20 30 40 45]
Shape of the array is :  (4,)
The dimension of the array is :  1

[ 2500.  9660. 23620.]