带有对数轴的 matplotlib 图形，但没有科学/指数符号 [英] matplotlib figure with logarithmic axis but ticks without scientific/exponential notation

问题描述

我正在制作一个图形，其中 x 轴应以对数间隔排列，但我想手动设置刻度标签，并且我希望刻度标签以普通的%.2f"表示法出现，而不是指数表示法.以下解决方案基于

解决方案

ScalarFormatter 的使用肯定是可能的.然后，您需要确保未显示此问题中所示的次要刻度标签:

I am making a figure where the x-axis should be logarithmically spaced, but I want to manually set the tick labels, and I want the tick labels to appear in ordinary '%.2f' notation, not exponential notation. The following solution based on Matplotlib - logarithmic scale, but require non-logarithmic labels suggests to use ScalarFormatter, but does not work with matplotlib 2.0:

x = np.logspace(2, 3, 100)
y = x

fig, ax = plt.subplots(1, 1)
xscale = ax.set_xscale('log')
ax.set_xticks((100, 200, 300, 500))
xlim = ax.set_xlim(100, 1000)

from matplotlib.ticker import ScalarFormatter
ax.get_xaxis().set_major_formatter(ScalarFormatter())

__=ax.plot(x, y)

解决方案

The use of a ScalarFormatter is sure possible. You would then need to make sure that no minor ticklabels are shown as seen in this question: Matplotlib: setting x-limits also forces tick labels?

In your case the code would then look like:

import matplotlib.pyplot as plt
import numpy as np

x = np.logspace(2, 3, 100)
y = x

fig, ax = plt.subplots(1, 1)
xscale = ax.set_xscale('log')
ax.set_xticks((100, 200, 300, 500))
xlim = ax.set_xlim(100, 1000)

import matplotlib.ticker

ax.get_xaxis().set_major_formatter(matplotlib.ticker.ScalarFormatter())
ax.get_xaxis().set_minor_formatter(matplotlib.ticker.NullFormatter())

__=ax.plot(x, y)

plt.show()

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