如何删除matplotlib对数

如何删除matplotlib对数 - 对数图上的科学记数法(How to remove scientific notation on a matplotlib log-log plot)

我知道之前已经问过这个问题，但我尝试了所有可能的解决方案，但没有一个能为我工作。

所以，我在matplotlib中有一个log-log图，我想避免在x轴上的科学记数法。

这是我的代码：

from numpy import array, log, pi import matplotlib.pyplot as plt from scipy.optimize import curve_fit import matplotlib.ticker as mticker plt.rc('axes.formatter', useoffset=False) tc = array([7499680.0, 12508380.0, 23858280.0, 34877020.0, 53970660.0, 89248580.0, 161032860.0, 326814160.0, 784460200.0]) theta = array([70, 60, 50, 45, 40, 35, 30, 25, 20]) plt.scatter(theta,tc) ax=plt.gca() ax.set_xscale('log') ax.set_yscale('log') ax.xaxis.set_major_formatter(mticker.ScalarFormatter()) ax.xaxis.get_major_formatter().set_scientific(False) ax.xaxis.get_major_formatter().set_useOffset(False) plt.show()

这是输出：

如您所见，x轴上的数字仍然是科学记数法。 我想将它们显示为20,30,40 ...我尝试了所有可能的解决方案而没有结果。

非常感谢所有有帮助的人。

NB。 我不能使用plt.loglog（）命令，因为我正在对数据进行一些曲线拟合，我需要它。

NB2。 我注意到发生了一件非常奇怪的事情：如果我将代码更改为yaxis.get_mayor_formatter（）...，它就可以在y轴上运行！ 它只是在x上，它不起作用。 这怎么可能？

编辑：也许不清楚，但如果你看一下代码，有3种方法应该影响x-ticks的显示： plt.rc('axes.formatter', useoffset=False) ， ax.xaxis.set_major_formatter(mticker.ScalarFormatter())和ax.xaxis.get_major_formatter().set_scientific(False) 。 根据我发现的情况，他们是3种方法应该都可以单独使用，但他们没有。 当然，我也一个接一个地尝试过，而不是一起尝试。

I know that this question has been asked before, but I tried all the possible solutions and none of them worked for me.

So, I have a log-log plot in matplotlib, and I would like to avoid scientific notation on the x-axis.

This is my code:

from numpy import array, log, pi import matplotlib.pyplot as plt from scipy.optimize import curve_fit import matplotlib.ticker as mticker plt.rc('axes.formatter', useoffset=False) tc = array([7499680.0, 12508380.0, 23858280.0, 34877020.0, 53970660.0, 89248580.0, 161032860.0, 326814160.0, 784460200.0]) theta = array([70, 60, 50, 45, 40, 35, 30, 25, 20]) plt.scatter(theta,tc) ax=plt.gca() ax.set_xscale('log') ax.set_yscale('log') ax.xaxis.set_major_formatter(mticker.ScalarFormatter()) ax.xaxis.get_major_formatter().set_scientific(False) ax.xaxis.get_major_formatter().set_useOffset(False) plt.show()

And this is the output:

As you can see, the numbers on the x-axis are still in scientific notation. I would like to display them as 20, 30, 40... I tried every possible solution with no result.

Thank you very much to everyone that will help.

NB. I can't use the plt.loglog() command, because I am doing some curve fitting on the data and I need it like that.

NB2. I noticed a very weird thing happening: if I change the code to yaxis.get_mayor_formatter()..., it works on the y-axis! It is just on the x one that it's not working. How is it possible?

Edit: maybe it is not clear, but if you look at the code, there are 3 methods that should affect the display of the x-ticks: plt.rc('axes.formatter', useoffset=False), ax.xaxis.set_major_formatter(mticker.ScalarFormatter()) and ax.xaxis.get_major_formatter().set_scientific(False). They are 3 methods that should all do the trick alone, according to what I found around, but they don't. Of course I also tried them one by one and not all together.

最满意答案

那些是x轴上的小刻度（即它们不是10的整数幂），而不是主要的刻度。 matplotlib自动确定是否应该标记主要或次要标记 - 在这种情况下，因为您没有在x范围内显示任何主要标记，所以标记了次要标记）。 因此，您需要使用set_minor_formatter方法：

ax.xaxis.set_minor_formatter(mticker.ScalarFormatter())

它在y轴上工作的原因是因为那些刻度是主要的刻度（即整数幂为10），而不是小刻度。

Those are minor ticks on the x-axis (i.e. they are not on integer powers of 10), not major ticks. matplotlib automatically detemines if it should label the major or minor ticks - in this case because you don't have any major ticks displayed in the x range, the minor ticks are being labelled). So, you need to use the set_minor_formatter method:

ax.xaxis.set_minor_formatter(mticker.ScalarFormatter())

The reason it works on the y-axis is because those ticks are major ticks (i.e. on integer powers of 10), not minor ticks.