# 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.]]

Updated on: 02-Mar-2022

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