Note
Go to the end to download the full example code.
1.5.12.8. Curve fittingΒΆ
Demos a simple curve fitting
First generate some data
import numpy as np
# Seed the random number generator for reproducibility
rng = np.random.default_rng(27446968)
x_data = np.linspace(-5, 5, num=50)
noise = 0.01 * np.cos(100 * x_data)
a, b = 2.9, 1.5
y_data = a * np.cos(b * x_data) + noise
# And plot it
import matplotlib.pyplot as plt
plt.figure(figsize=(6, 4))
plt.scatter(x_data, y_data)
<matplotlib.collections.PathCollection object at 0x7f22c5ff8f80>
Now fit a simple sine function to the data
[2.900026 1.50012043 1.57079633]
And plot the resulting curve on the data
plt.figure(figsize=(6, 4))
plt.scatter(x_data, y_data, label="Data")
plt.plot(x_data, test_func(x_data, *params), label="Fitted function")
plt.legend(loc="best")
plt.show()
Total running time of the script: (0 minutes 0.109 seconds)