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Differentiate a Hermite series with multidimensional coefficients in Python
To differentiate a Hermite series, use the hermite.hermder() method in Python. The 1st parameter, c is an array of Hermite 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. (Default: 0).
Steps
At first, import the required library −
import numpy as np from numpy.polynomial import hermite as H
Create a multidimensional array of coefficients −
c = np.arange(4).reshape(2,2)
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 series, use the hermite.hermder() method in Python −
print("\nResult...\n",H.hermder(c))Example
import numpy as np
from numpy.polynomial import hermite as H
# Create a multidimensional array of coefficients
c = np.arange(4).reshape(2,2)
# 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 series, use the hermite.hermder() method in Python
print("\nResult...\n",H.hermder(c))Output
Our Array... [[0 1] [2 3]] Dimensions of our Array... 2 Datatype of our Array object... int64 Shape of our Array object... (2, 2) Result... [[4. 6.]]
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