'''
Demonstrate use of a log color scale in contourf
'''

import matplotlib.pyplot as plt
import numpy as np
from numpy import ma
from matplotlib import colors, ticker, cm
from matplotlib.mlab import bivariate_normal

N = 100
x = np.linspace(-3.0, 3.0, N)
y = np.linspace(-2.0, 2.0, N)

X, Y = np.meshgrid(x, y)

# A low hump with a spike coming out of the top right.
# Needs to have z/colour axis on a log scale so we see both hump and spike.
# linear scale only shows the spike.
z = (bivariate_normal(X, Y, 0.1, 0.2, 1.0, 1.0)
     + 0.1 * bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0))

# Put in some negative values (lower left corner) to cause trouble with logs:
z[:5, :5] = -1

# The following is not strictly essential, but it will eliminate
# a warning.  Comment it out to see the warning.
z = ma.masked_where(z <= 0, z)


# Automatic selection of levels works; setting the
# log locator tells contourf to use a log scale:
fig, ax = plt.subplots()
cs = ax.contourf(X, Y, z, locator=ticker.LogLocator(), cmap=cm.PuBu_r)

# Alternatively, you can manually set the levels
# and the norm:
#lev_exp = np.arange(np.floor(np.log10(z.min())-1),
#                    np.ceil(np.log10(z.max())+1))
#levs = np.power(10, lev_exp)
#cs = P.contourf(X, Y, z, levs, norm=colors.LogNorm())

# The 'extend' kwarg does not work yet with a log scale.

cbar = fig.colorbar(cs)

plt.show() 

　

Traceback (most recent call last):
  File "M:\______\contourf_log.py", line 9, in 
    from matplotlib.mlab import bivariate_normal
ImportError: cannot import name 'bivariate_normal' from 'matplotlib.mlab' 
(C:\Users\______\AppData\Local\Programs\Python\Python311\Lib\site-packages\matplotlib\mlab.py) 

Traceback (most recent call last):
  File "E:\______\contourf_log.py", line 9, in 
    from matplotlib.mlab import bivariate_normal
ImportError: cannot import name 'bivariate_normal' from 'matplotlib.mlab' 
  (C:\Program Files\Python312\Lib\site-packages\matplotlib\mlab.py) 

"""
============================
Contourf and log color scale
============================

Demonstrate use of a log color scale in contourf
"""

import matplotlib.pyplot as plt
import numpy as np
from numpy import ma

from matplotlib import cm, ticker

N = 100
x = np.linspace(-3.0, 3.0, N)
y = np.linspace(-2.0, 2.0, N)

X, Y = np.meshgrid(x, y)

# A low hump with a spike coming out.
# Needs to have z/colour axis on a log scale, so we see both hump and spike.
# A linear scale only shows the spike.
Z1 = np.exp(-X**2 - Y**2)
Z2 = np.exp(-(X * 10)**2 - (Y * 10)**2)
z = Z1 + 50 * Z2

# Put in some negative values (lower left corner) to cause trouble with logs:
z[:5, :5] = -1

# The following is not strictly essential, but it will eliminate
# a warning.  Comment it out to see the warning.
z = ma.masked_where(z <= 0, z)


# Automatic selection of levels works; setting the
# log locator tells contourf to use a log scale:
fig, ax = plt.subplots()
cs = ax.contourf(X, Y, z, locator=ticker.LogLocator(), cmap=cm.PuBu_r)

# Alternatively, you can manually set the levels
# and the norm:
# lev_exp = np.arange(np.floor(np.log10(z.min())-1),
#                    np.ceil(np.log10(z.max())+1))
# levs = np.power(10, lev_exp)
# cs = ax.contourf(X, Y, z, levs, norm=colors.LogNorm())

cbar = fig.colorbar(cs)

plt.show()

# %%
#
# .. admonition:: References
#
#    The use of the following functions, methods, classes and modules is shown
#    in this example:
#
#    - `matplotlib.axes.Axes.contourf` / `matplotlib.pyplot.contourf`
#    - `matplotlib.figure.Figure.colorbar` / `matplotlib.pyplot.colorbar`
#    - `matplotlib.axes.Axes.legend` / `matplotlib.pyplot.legend`
#    - `matplotlib.ticker.LogLocator` 

　Python 3.11.6 (matplotlib 3.7.1) 及び Python 3.12.0 (matplotlib 3.8.1) 共に、正常実行です。
　

• 2023/11/16 Ver=1.04 Python 3.12.0 (matplotlib 3.8.1)で確認
• 2023/11/16 Ver=1.04 Python 3.11.6 (matplotlib 3.7.1)で確認
• 2023/03/30 Ver=1.03 Python 3.11.2 で確認
• 2020/10/30 Ver=1.01 Python 3.7.8 で確認
• 2018/11/25 Ver=1.01 初版リリース

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