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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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