How to Create Smoother Lines in Your PyPlot Graphs Using scipy.interpolate.spline?

Smoothing Lines with PyPlot

Your goal is to smoothen the line connecting data points in your graph to enhance its visual appeal. While some tutorials might seem intimidating, there's a straightforward approach using scipy.interpolate.spline.

<code class="python">import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import spline

# Example data
T = np.array([6, 7, 8, 9, 10, 11, 12])
power = np.array([1.53E+03, 5.92E+02, 2.04E+02, 7.24E+01, 2.72E+01, 1.10E+01, 4.70E+00])

# Set the number of points for smoothing
num_points = 300

# Create a new x-axis with more points
xnew = np.linspace(T.min(), T.max(), num_points)

# Interpolate data using a spline
power_smooth = spline(T, power, xnew)

# Plot the smoothed line
plt.plot(xnew, power_smooth)
plt.show()</code>

In this script, spline interpolates the original data points and generates a smoother curve. Adjust num_points to control the smoothness level.

Before Smoothing:
[Image of unsmoothed line graph]

After Smoothing:
[Image of smoothed line graph]

With this technique, you can easily improve the visual appeal of your plots in PyPlot.

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