python-scipyHow do I use Python and SciPy to perform spline interpolation?

Spline interpolation is a method of constructing new data points within the range of a discrete set of known data points. Python and SciPy provide a convenient set of functions for performing spline interpolation.

Example code

import numpy as np
from scipy.interpolate import interp1d

# Create a set of data points
x = np.linspace(0, 10, num=11, endpoint=True)
y = np.cos(-x**2/9.0)

# Create a linear interpolation function
f = interp1d(x, y)

# Interpolate at new points
xnew = np.linspace(0, 10, num=41, endpoint=True)
ynew = f(xnew)

The code above creates a set of data points x and y and then creates a linear interpolation function f using interp1d. The function f is then used to interpolate at new points xnew and ynew.

Code explanation

1. import numpy as np: imports the NumPy library as np
2. from scipy.interpolate import interp1d: imports the interp1d function from the SciPy library
3. x = np.linspace(0, 10, num=11, endpoint=True): creates a set of data points x between 0 and 10 with 11 points
4. y = np.cos(-x**2/9.0): creates a set of data points y for each x point using the cosine function
5. f = interp1d(x, y): creates a linear interpolation function f using interp1d
6. xnew = np.linspace(0, 10, num=41, endpoint=True): creates a set of new points xnew between 0 and 10 with 41 points
7. ynew = f(xnew): uses the linear interpolation function f to interpolate at the new points xnew and creates a set of new points ynew

Helpful links

• NumPy Documentation
• SciPy Documentation

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