2.4. Matplotlib Scales

  • Linear

  • Logarithmic

  • Symmetrical log (partially linear linthreshx: int)

  • Logit - reversed logarithmic

  • Subtracting x.mean() is used to better highlight the function

2.4.1. Linear Scale

import matplotlib.pyplot as plt
import numpy as np


x = np.linspace(0, 10, 1000)
y = x - x.mean()

plt.yscale('linear')

plt.plot(x, y)
plt.show()  # doctest: +SKIP

2.4.2. Logarithmic Scale

import matplotlib.pyplot as plt
import numpy as np


x = np.linspace(0, 10, 1000)
y = x - x.mean()

plt.yscale('log')

plt.plot(x, y)
plt.show()  # doctest: +SKIP

2.4.3. Symmetrical Logarithmic Scale

import matplotlib.pyplot as plt
import numpy as np


x = np.linspace(0, 10, 1000)
y = x - x.mean()

plt.yscale('symlog', linthresh=0.01)

plt.plot(x, y)
plt.show()  # doctest: +SKIP

2.4.4. Logit Scale

import matplotlib.pyplot as plt
import numpy as np


x = np.linspace(0, 10, 1000)
y = x - x.mean()

plt.yscale('logit')

plt.plot(x, y)
plt.show()  # doctest: +SKIP