如何在3D历史记录python/matplotlib中自定义轴 [英] How to customize axes in 3D hist python/matplotlib

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本文介绍了如何在3D历史记录python/matplotlib中自定义轴的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我正在尝试使用3D条形图绘制该数据集

I am trying to plot this data set using 3D bar

  B    A   freq
  1  2003     2
  1  2003     2
  2  2008     1
  2  2007     2
  2  2007     2
  3  2004     1
  1  2004     3
  1  2004     3
  1  2004     3

我已经在这里编写了代码.

I have written the code here.

  data = pandas.DataFrame({'A':[2003,2003,2008,2007,2007,2004,2004,2004,2004] , 'B': [1,1,2,2,2,3,1,1,1] ,'C': [2,2,1,2,2,1,3,3,3] })
        fig = plt.figure()
        ax = plt.axes(projection='3d')
        # put 0s on the y-axis, and put the y axis on the z-axis

        #ax.plot(data.A.values, data.B.values,data.freq.values, marker='o', linestyle='--', color="blue", label='ys=0, zdir=z')
        xpos= range(len( data.A.values))
        ypos= range(len( data.B.values))
        zpos= range(len( data.freq.values))

        ax.bar3d(xpos, ypos, zpos, data.A.values, data.B.values,data.freq.values, color='b', alpha=0.5)

        x_formatter = matplotlib.ticker.ScalarFormatter(useOffset=False)
        ax.xaxis.set_major_formatter(x_formatter)

        ax.set_xticks(data.A.values)
        ax.set_yticks(data.B.values)
        ax.set_zticks(data.freq.values)


        plt.savefig("test.png", dpi=300)
        plt.show()

但这似乎不是正确的方法?显示我们如何自定义轴可以帮助任何人吗?

But it doesn't seem to be the right way to do that? Can any one help by showing how do we customize axes ?

当我使用情节时它会起作用

It works when I use plot

ax.plot(data.A.values, data.B.values,data.freq.values,marker='o', linestyle='--', color='r')

代替bar3D

ax.bar3d(xpos, ypos, zpos, data.A.values, data.B.values,data.freq.values, color='b', alpha=0.5)

但是我想使用3D直方图来更好地理解.

but I wanna use 3D histogram for better understading.

推荐答案

似乎您误解了 bar3d 函数上的参数:

It seems you're misunderstanding the parameters on the bar3d function:

bar3d(x, y, z, dx, dy, dz)

  • 参数 x y z 是x,y和z轴上条形的坐标.
  • 参数 dx dy dz 分别是x,y和z轴上条形的大小.
  • Parameters x, y and z are the coordinates of the bars on the x, y and z axis respectively.
  • Parameters dx, dy and dz are the sizes of the bars on the x, y and z axis respectively.

例如,如果要绘制以下数据集:

For example, if you want to plot the following dataset:

{'A': [1, 2], 'B': [2003, 2008] ,'freq': [2, 3] }

您必须像这样定义这些参数:

You have to define these parameters like so:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

xpos = [1, 2]
ypos = [2003, 2008]
zpos = [0, 0]

dx = 1
dy = 1
dz = [2, 3]

fig = plt.figure()
ax = plt.axes(projection='3d')
ax.bar3d(xpos, ypos, zpos, dx, dy, dz)
plt.show()

这是:

  • 您在高度 2 (1,2003,0)(x,y,z)中绘制了一个条形图.
  • 您在(2,2008,0)(x,y,z)中绘制一个条形,高度为 3 .
  • 两个条形图在x轴和y轴上的大小均为 1 ,但可能会更少,这只是一个美学问题.
  • You plot one bar in (1, 2003, 0) (x, y, z) with height 2.
  • You plot one bar in (2, 2008, 0) (x, y, z) with height 3.
  • Both bars have a size of 1 on the x and y axis, it could be less though, it's just an aesthetic issue.

上面的脚本生成以下图:

The script above generates the following plot:

如果您查看图片,会发现一些较小的格式问题:

If you look at the image you'll notice some minor format problems:

  • 年份以指数表示.
  • 条形图不在其(x,y)坐标上居中.

我们实际上可以通过一些调整来解决此问题:

We can actually solve this with a few tweaks:

import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

xpos = [1, 2]
ypos = [2003, 2008]
zpos = [0, 0]

dx = 1
dy = 1
dz = [2, 3]

# Move each (x, y) coordinate to center it on the tick

xpos = map(lambda x: x - 0.5, xpos)
ypos = map(lambda y: y - 0.5, ypos)

fig = plt.figure()
ax = plt.axes(projection='3d')
ax.bar3d(xpos, ypos, zpos, dx, dy, dz)

# Do not print years in exponential notation

y_formatter = matplotlib.ticker.ScalarFormatter(useOffset=False)
ax.yaxis.set_major_formatter(y_formatter)

plt.show()

最后这就是我们得到的:

And finally this is what we'll get:

这篇关于如何在3D历史记录python/matplotlib中自定义轴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!

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