"""

===============

Scales overview

===============

Illustrate the scale transformations applied to axes, e.g. log, symlog, logit.

See `matplotlib.scale` for a full list of built-in scales,

:doc:`/gallery/scales/custom_scale` for how to create your own scale, and

:doc:`/gallery/mplot3d/scales3d` for using scales on 3D axes.

"""

import matplotlib.pyplot as plt

import numpy as np

x = np.arange(400)

y = np.linspace(0.002, 1, 400)

fig, axs = plt.subplots(3, 2, figsize=(6, 8), layout='constrained')

axs[0, 0].plot(x, y)

axs[0, 0].set_yscale('linear')

axs[0, 0].set_title('linear')

axs[0, 0].grid(True)

axs[0, 1].plot(x, y)

axs[0, 1].set_yscale('log')

axs[0, 1].set_title('log')

axs[0, 1].grid(True)

axs[1, 0].plot(x, y - y.mean())

axs[1, 0].set_yscale('symlog', linthresh=0.02)

axs[1, 0].set_title('symlog')

axs[1, 0].grid(True)

axs[1, 1].plot(x, y)

axs[1, 1].set_yscale('logit')

axs[1, 1].set_title('logit')

axs[1, 1].grid(True)

axs[2, 0].plot(x, y - y.mean())

axs[2, 0].set_yscale('asinh', linear_width=0.01)

axs[2, 0].set_title('asinh')

axs[2, 0].grid(True)

# Function x**(1/2)

def forward(x):

return x**(1/2)

def inverse(x):

return x**2

axs[2, 1].plot(x, y)

axs[2, 1].set_yscale('function', functions=(forward, inverse))

axs[2, 1].set_title('function: $x^{1/2}$')

axs[2, 1].grid(True)

axs[2, 1].set_yticks(np.arange(0, 1.2, 0.2))

plt.show()

# %%

#

# .. admonition:: References

#

# The use of the following functions, methods, classes and modules is shown

# in this example:

#

# - `matplotlib.axes.Axes.set_xscale`

# - `matplotlib.axes.Axes.set_yscale`

# - `matplotlib.scale.LinearScale`

# - `matplotlib.scale.LogScale`

# - `matplotlib.scale.SymmetricalLogScale`

# - `matplotlib.scale.LogitScale`

# - `matplotlib.scale.FuncScale`