To plot yscale with class by name, we can take the following steps
- Set the figure size and adjust the padding between and around the subplots.
- Create y data points using numpy.
- Create x data points using numpy.
- Add a subplot to the current figure at index 1.
- Plot x and y data points using plot() method.
- For linear class by name, use yscale("linear") method.
- Set the title of the current subplot.Repeat the steps from 4 to 5 with different indices, yscale() class by name, and title of the plot.
- To display the figure, use show() method.
Example
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True
y = np.random.normal(loc=0.5, scale=0.4, size=1000)
y = y[(y > 0) & (y < 1)]
y.sort()
x = np.arange(len(y))
# linear
plt.subplot(221)
plt.plot(x, y)
plt.yscale('linear')
plt.title('linear')
# log
plt.subplot(222)
plt.plot(x, y)
plt.yscale('log')
plt.title('log')
# symmetric log
plt.subplot(223)
plt.plot(x, y - y.mean())
plt.yscale('symlog', linthreshy=0.01)
plt.title('symlog')
# logit
plt.subplot(224)
plt.plot(x, y)
plt.yscale('logit')
plt.title('logit')
plt.show()Output
