To generate a Vandermonde matrix of the Hermite_e polynomial, use the hermite_e.hermvander() in Python Numpy. The method returns the pseudo-Vandermonde matrix. The shape of the returned matrix is x.shape + (deg + 1,), where The last index is the degree of the corresponding Hermite polynomial. The dtype will be the same as the converted x.
The parameter, x returns an Array of points. The dtype is converted to float64 or complex128 depending on whether any of the elements are complex. If x is scalar it is converted to a 1-D array. The parameter, deg is the degree of the resulting matrix.
Steps
At first, import the required library −
import numpy as np from numpy.polynomial import hermite_e as H
Create an array −
x = np.array([-2.+2.j, -1.+2.j, 0.+2.j, 1.+2.j, 2.+2.j])
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 generate a Vandermonde matrix of the Hermite_e polynomial, use the hermite_e.hermvander() in Python Numpy −
print("\nResult...\n",H.hermevander(x, 2))Example
import numpy as np
from numpy.polynomial import hermite_e as H
# Create an array
x = np.array([-2.+2.j, -1.+2.j, 0.+2.j, 1.+2.j, 2.+2.j])
# Display the array
print("Our Array...\n",x)
# Check the Dimensions
print("\nDimensions of our Array...\n",x.ndim)
# Get the Datatype
print("\nDatatype of our Array object...\n",x.dtype)
# Get the Shape
print("\nShape of our Array object...\n",x.shape)
# To generate a Vandermonde matrix of the Hermite_e polynomial, use the hermite_e.hermvander() in Python Numpy
print("\nResult...\n",H.hermevander(x, 2))Output
Our Array... [-2.+2.j -1.+2.j 0.+2.j 1.+2.j 2.+2.j] Dimensions of our Array... 1 Datatype of our Array object... complex128 Shape of our Array object... (5,) Result... [[ 1.+0.j -2.+2.j -1.-8.j] [ 1.+0.j -1.+2.j -4.-4.j] [ 1.+0.j 0.+2.j -5.+0.j] [ 1.+0.j 1.+2.j -4.+4.j] [ 1.+0.j 2.+2.j -1.+8.j]]