更改子图上的刻度号 [英] change ticks number on a subplot

问题描述

如果我有一个子图，如何更改它的NUMBER刻度?我不知道数据的最大值和最小值.

If I have a subplot how can I change its NUMBER of ticks? I don't know the maximum and the minimum of the data.

我的代码是:

azal = rif.add_subplot(111)
azal.plot(eels*(10**9), averspe, label='data')
azal.plot(eels*(10**9), beck, label='fit')
azal.set_yscale('log')
azal.set_xscale('log')
h2 = azal.axvline(x = p2*(10**9), color='r')
azal.legend(bbox_to_anchor=(1.05, 1), loc=4, fontsize='xx-large', borderaxespad=0.)
rif.canvas.draw()                

推荐答案

您可以使用

You can use the matplotlib.ticker.MaxNLocator to automatically choose a maximum of N nicely spaced ticks.

下面给出了一个仅用于y轴的玩具示例，您可以通过将ax.yaxis.set_major_locator替换为ax.xaxis.set_major_locator来将其用于x轴.

A toy example is given below for the y-axis only, you can use it for the x-axis by replacing ax.yaxis.set_major_locator with ax.xaxis.set_major_locator.

如果您有对数图，则可以使用 matplotlib.ticker.LogLocator 和numticks关键字参数.在这种情况下，您可以将定义yticks的行替换为yticks = ticker.LogLocator(numticks=M).

If you've got a log plot then you can use matplotlib.ticker.LogLocator with the numticks keyword argument. In which case you'd replace the line defining yticks with yticks = ticker.LogLocator(numticks=M).

import matplotlib.pyplot as plt
from matplotlib import ticker

import numpy as np

N = 10

x = np.arange(N)
y = np.random.randn(N)

fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x,y)

# Create your ticker object with M ticks
M = 3
yticks = ticker.MaxNLocator(M)

# Set the yaxis major locator using your ticker object. You can also choose the minor
# tick positions with set_minor_locator.
ax.yaxis.set_major_locator(yticks)

plt.show()

`

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