In this article, we will be looking at the step-wise procedure to differentiate a Hermite series in Python.
Differentiate a Hermite series in Python:
Here, we need to call the np.hermder() function from the NumPy package. And pass the parameter, the first parameter will be the c, which is an array of Hermite series coefficients. Further, the next parameter is m which is non-negative (Default: 1).
Syntax: np.hermder(series, m)
Parameter:
- c: Array of Hermite series coefficients.
- m: Number of derivatives taken, must be non-negative. (Default: 1)
Return: Return the coefficient of differentiated series.
Example 1:
In this example, we have created the array containing 10 data points from series 1 to 10 and with the use of the np.hermder() function, we are differentiating the Hermite series in python.
Python3
import numpy as np from numpy.polynomial import hermite gfg = np.array([1,2,3,4,5,6,7,8,9,10]) print("Array - ", gfg) print("Dimension of Array:-",gfg.ndim) print("Datatype of Array:-",gfg.dtype) print("Shape of Array:-",gfg.shape) print("Differentiated Hermite series", hermite.hermder(gfg)) |
Output:
Array - [ 1 2 3 4 5 6 7 8 9 10] Dimension of Array:- 1 Datatype of Array:- int32 Shape of Array:- (10,) Differentiated Hermite series [ 4. 12. 24. 40. 60. 84. 112. 144. 180.]
Example 2:
In this example, we will differentiate a Hermite series from an array with 5 data points and m=2 using the np.hermder() function from the NumPy package of Python
Python3
import numpy as np from numpy.polynomial import hermite gfg = np.array([56,84,87,44,98]) print("Array - ", gfg) print("Dimension of Array:-",gfg.ndim) print("Datatype of Array:-",gfg.dtype) print("Shape of Array:-",gfg.shape) print("Differentiated Hermite series", hermite.hermder(gfg, m=2)) |
Output:
Array - [56 84 87 44 98] Dimension of Array:- 1 Datatype of Array:- int32 Shape of Array:- (5,) Differentiated Hermite series [ 696. 1056. 4704.]
