How can I visualize interpolation using SciPy?

How can I visualize interpolation using SciPy?

You can use SciPy's interp1d for 1D interpolation and Matplotlib for visualization. Would you like a code example?

Yes, please provide a code example for 1D interpolation.

Here's a simple example:

import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import interp1d

# Sample data
x = np.array([0, 1, 2, 3, 4])
y = np.array([0, 1, 0, 1, 0])

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

# New x values for interpolation
x_new = np.linspace(0, 4, 10)

# Plotting
plt.plot(x, y, 'o', label='data points')
plt.plot(x_new, f(x_new), '-', label='linear interpolation')
plt.legend()
plt.show()

What types of interpolation can I use with interp1d?

You can use several types of interpolation with interp1d, including 'linear', 'nearest', 'zero', 'slinear', 'quadratic', and 'cubic'. Would you like to see examples of any specific type?

Yes, can you show me an example of cubic interpolation?

Sure! Here's how you can modify the previous example for cubic interpolation:

# Create cubic interpolation function
f_cubic = interp1d(x, y, kind='cubic')

# Plotting
plt.plot(x, y, 'o', label='data points')
plt.plot(x_new, f_cubic(x_new), '-', label='cubic interpolation')
plt.legend()
plt.show()