Matplotlib对数标度为零 [英] Matplotlib logarithmic scale with zero value
问题描述
我有一个非常庞大且稀疏的垃圾邮件Twitter帐户数据集,它要求我缩放x轴才能可视化各种变量(tweets_count,关注者/关注者等).
I have a very large and sparse dataset of spam twitter accounts and it requires me to scale the x axis in order to be able to visualize the distribution (histogram, kde etc) and cdf of the various variables (tweets_count, number of followers/following etc).
> describe(spammers_class1$tweets_count)
var n mean sd median trimmed mad min max range skew kurtosis se
1 1 1076817 443.47 3729.05 35 57.29 43 0 669873 669873 53.23 5974.73 3.59
在此数据集中,值0具有很高的重要性(实际上0应该具有最高的密度).但是,使用对数标度时,这些值将被忽略.我曾想过将值更改为0.1,但是,有10个-1个关注者的垃圾邮件帐户是没有意义的.
In this dataset, the value 0 has a huge importance (actually 0 should have the highest density). However, with a logarithmic scale these values are ignored. I thought of changing the value to 0.1 for example, but it will not make sense that there are spam accounts that have 10^-1 followers.
那么,python和matplotlib中的解决方法是什么?
So, what would be a workaround in python and matplotlib ?
推荐答案
为每个x
值添加1,然后然后记录日志:
Add 1 to each x
value, then take the log:
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.ticker as ticker
fig, ax = plt.subplots()
x = [0, 10, 100, 1000]
y = [100, 20, 10, 50]
x = np.asarray(x) + 1
y = np.asarray(y)
ax.plot(x, y)
ax.set_xscale('log')
ax.set_xlim(x.min(), x.max())
ax.xaxis.set_major_formatter(ticker.FuncFormatter(lambda x, pos: '{0:g}'.format(x-1)))
ax.xaxis.set_major_locator(ticker.FixedLocator(x))
plt.show()
使用
ax.xaxis.set_major_formatter(ticker.FuncFormatter(lambda x, pos: '{0:g}'.format(x-1)))
ax.xaxis.set_major_locator(ticker.FixedLocator(x))
根据x
的非对数值重新标记刻度线.
to relabel the tick marks according to the non-log values of x
.
(我最初的建议是使用plt.xticks(x, x-1)
,但这会影响所有轴.为了隔离对一个特定轴的更改,我将所有命令调用都更改为ax
,而不是对plt
的调用.)
(My original suggestion was to use plt.xticks(x, x-1)
, but this would affect all axes. To isolate the changes to one particular axes, I changed all commands calls to ax
, rather than calls to plt
.)
matplotlib
删除包含NaN
,inf
或-inf
值的点.由于log(0)
是-inf
,因此与x=0
相对应的点将从对数图中删除.
matplotlib
removes points which contain a NaN
, inf
or -inf
value. Since log(0)
is -inf
, the point corresponding to x=0
would be removed from a log plot.
如果将所有x值都增加1,因为log(1) = 0
,对应于x=0
的点将不会在对数图上的x=log(1)=0
处绘制.
If you increase all the x-values by 1, since log(1) = 0
, the point corresponding to x=0
will not be plotted at x=log(1)=0
on the log plot.
剩余的x值也将移动一个,但对眼睛来说并不重要,因为log(x+1)
对于x
的较大值来说非常接近log(x)
.
The remaining x-values will also be shifted by one, but it will not matter to the eye since log(x+1)
is very close to log(x)
for large values of x
.
这篇关于Matplotlib对数标度为零的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!