How to Create a Smooth Line in a PyPlot Graph?

Plotting a Smooth Line in PyPlot

Problem:

When plotting a graph using PyPlot, the connecting lines between data points may appear rigid and discontinuous. This can be undesirable in certain scenarios.

Question:

How to smoothen the connecting lines in a PyPlot graph?

Solution:

To achieve a smoother line, one can utilize scipy's spline interpolation technique. Here's how:

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

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])

# Create a dense array of points for interpolation
xnew = np.linspace(T.min(), T.max(), 300)

# Interpolate the data using a cubic spline
power_smooth = scipy.interpolate.spline(T, power, xnew)

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

Note: The 'spline' function in scipy is deprecated in version 0.19.0. Use the 'BSpline' class instead. Here's an updated version:

<code class="python">from scipy.interpolate import make_interp_spline, BSpline

# Create a dense array of points for interpolation
xnew = np.linspace(T.min(), T.max(), 300)

# Create a B-spline interpolation object
spl = make_interp_spline(T, power, k=3)  # type: BSpline

# Evaluate the interpolation at the new points
power_smooth = spl(xnew)

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

The 'k' argument in 'make_interp_spline' controls the smoothness of the spline. Higher values of 'k' result in smoother lines.

The resulting plot will exhibit a smooth connecting line between data points, providing a more visually appealing representation of the data.

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