To differentiate a Hermite_e series, use the hermite_e.hermeder() method in Python. The 1st parameter, c is an array of Hermite_e series coefficients. If c is multidimensional the different axis correspond to different variables with the degree in each axis given by the corresponding index.
The 2nd parameter, m is the number of derivatives taken, must be non-negative. (Default: 1). The 3rd parameter, scl is a scalar. Each differentiation is multiplied by scl. The end result is multiplication by scl**m. This is for use in a linear change of variable. (Default: 1). The 4th parameter, axis is an Axis over which the derivative is taken.
Steps
At first, import the required library −
import numpy as np from numpy.polynomial import hermite_e as H
Create an array of coefficients −
c = np.array([1,2,3,4])
Display the array −
print("Our Array...\n",c)
Check the Dimensions −
print("\nDimensions of our Array...\n",c.ndim)
Get the Datatype −
print("\nDatatype of our Array object...\n",c.dtype)
Get the Shape −
print("\nShape of our Array object...\n",c.shape)
To differentiate a Hermite_e series, use the hermite_e.hermeder() method in Python −
print("\nResult...\n",H.hermeder(c, scl = -1))
Example
import numpy as np from numpy.polynomial import hermite_e as H # Create an array of coefficients c = np.array([1,2,3,4]) # Display the array print("Our Array...\n",c) # Check the Dimensions print("\nDimensions of our Array...\n",c.ndim) # Get the Datatype print("\nDatatype of our Array object...\n",c.dtype) # Get the Shape print("\nShape of our Array object...\n",c.shape) # To differentiate a Hermite_e series, use the hermite_e.hermeder() method in Python print("\nResult...\n",H.hermeder(c, scl = -1))
Output
Our Array... [1 2 3 4] Dimensions of our Array... 1 Datatype of our Array object... int64 Shape of our Array object... (4,) Result... [ -2. -6. -12.]