In this article, we will cover how to evaluate a Hermite_e series at points x using NumPy in Python.
numpy.polynomial.hermite.hermval
The numpy.polynomial.hermite.hermval() method from the NumPy library is used to evaluate a Hermite series at points x. If the parameter x is a tuple or a list, it is turned into an array otherwise, it is regarded as 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.Â
- c: Array of coefficientsÂ
- tensor: optional value, boolean type.
Returns:Â 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 point x. The shape, datatype, and dimension of the array are found by using the .shape, .dtype, and .ndim attributes. In this example, x is a scalar.
Python3
import numpy as np from numpy.polynomial import hermite as H Â Â # array of coefficients array = np.array([5,6,7,8]) print(array) Â Â # shape of the array is print("Shape of the array is : ",array.shape) Â Â # dimension of the array print("The dimension of the array is : ",array.ndim) Â Â # evaluating a hermite series at points x print(H.hermval(1,array)) |
Output:
[5 6 7 8] Shape of the array is : (4,) The dimension of the array is : 1 -1.0
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 point x, where x is [1,2]. The shape, datatype, and dimension of the array are found by using the .shape, .dtype, and .ndim attributes. x is a list.Â
Python3
import numpy as np from numpy.polynomial import hermite as H Â Â # array of coefficients array = np.array([5,6,7,8]) print(array) Â Â # shape of the array is print("Shape of the array is : ",array.shape) Â Â # dimension of the array print("The dimension of the array is : ",array.ndim) Â Â # evaluating a hermite series at points x print(H.hermval([1,2],array)) |
Output:
[5 6 7 8] Shape of the array is : (4,) The dimension of the array is : 1 [ -1. 447.]
