In this article, we will be looking toward the approach to evaluating a Hermite_e series at a list of points x using Python and NumPy.
Example:
List: [6,7,8,9,10] Result: [102175. 191631. 329175. 529399. 808815.] Explanation: Hermite_e series at points x.
NumPy.polynomial.hermite_e.hermeval() method
To evaluate a Hermite_e series at a tuple of points x we need to call the hermite_e.hermeval() method of the Numpy library in Python. this method takes two parameters, the first parameter is the x, where x is a list or tuple, and the 2nd parameter is C, Â which is an array of coefficients. This method returns the coefficient of series after multiplication.
Syntax : np.polynomial.hermite_e.hermeval(x, c)
Parameter:
- x: list or tuple
- c: array of coefficient
Return : Return the coefficient of series after multiplication.
Example 1:
In this example, we created an array of 5 data points of one dimension and further created a list named x, then with the use of the hermite_e.hermeval() method, and pass the required parameters to evaluate the Hermite_e series at a list at points [6,7,8,9,10] in Python.
Python3
import numpy as np from numpy.polynomial import hermite_e   a = np.array([ 1 , 2 , 3 , 4 , 5 ])   # Dimensions of Array print ( "Dimensions of Array: " , a.ndim)   # Shape of the array print ( "\nShape of Array: " , a.shape)   # List x = [ 6 , 7 , 8 , 9 , 10 ]   # To evaluate a Hermite_e series at points x print ( "\nHermite series at point" , hermite_e.hermeval(x, a)) |
Output:
Dimensions of Array: Â 1
Shape of Array: Â (5,)
Hermite series at point [ 6325. 11997. 20733. 33457. 51213.]
Example 2:
In this example, we created a 2-D array of 10 data points and further created a list name x, then with the use of the hermite_e.hermeval() method, and pass the required parameters to evaluate the Hermite_e series at a list at points (11,12,13,14,15) in Python.
Python3
import numpy as np from numpy.polynomial import hermite_e   a = np.array([[ 1 , 2 , 3 , 4 , 5 ], [ 6 , 7 , 8 , 9 , 10 ]])   # Dimensions of Array print ( "Dimensions of Array: " , a.ndim)   # Shape of the array print ( "\nShape of Array: " , a.shape)   # list x = [ 11 , 12 , 13 , 14 , 15 ]   # To evaluate a Hermite_e series at points x print ( "\nHermite series at point" , hermite_e.hermeval(x, a)) |
Output:
Dimensions of Array: Â 2
Shape of Array: Â (2, 5)
Hermite series at point [[ 67. Â 73. Â 79. Â 85. Â 91.]
 [ 79.  86.  93. 100. 107.]
 [ 91.  99. 107. 115. 123.]
 [103. 112. 121. 130. 139.]
 [115. 125. 135. 145. 155.]]