Gnuplot互换轴 [英] Gnuplot interchanging Axes

问题描述

我想用gnuplot复制此图:

I would like to reproduce this plot with gnuplot:

我的数据具有以下格式:

My data has this format:

数据
1:时间
2:价格
3:音量

Data
1: time
2: price
3: volume

我尝试过:

plot file using 1:2 with lines, '' using 1:3 axes x1y2 with impulses

给出正常时间序列图，以y1作为价格，y2作为数量.
接下来，我尝试了:

Which gives a normal time series chart with y1 as price and y2 as volume.
Next, I tried:

plot file using 2:1 with lines, '' using 2:3 axes x1y2 with impulses 

哪个给出价格序列，其中y1作为时间，y2作为数量. 但是，我需要价格保持在y1，数量保持在x2.

Which gives prices series with y1 as time and y2 as volume. However, I need the price to remain at y1 and volume at x2.

也许是这样的:

plot file using 1:2 with lines,' ' using 2:3 axes y1x2 with impulses

但是，这不能满足我的需求.

However, that does not give what I want.

推荐答案

Gnuplot没有绘制这种水平箱形图的官方方法.但是，您可以使用boxxyerrorbars(速记boxxy)来实现此目的.

Gnuplot has no official way to draw this kind of horizontal boxplots. However, you can use the boxxyerrorbars (shorthand boxxy) to achieve this.

由于我没有您的实际示例的任何测试数据，因此我从高斯随机游走中生成了一个数据文件.要生成数据，请运行以下python脚本:

As I don't have any test data of your actual example, I generated a data file from a Gaussian random-walk. To generate the data run the following python script:

from numpy import zeros, savetxt, random

N = 500
g = zeros(N)
for i in range(1, N):
    g[i] = g[i-1] + random.normal()

savetxt('randomwalk.dat', g, delimiter='\t', fmt='%.3f')

接下来，我对位置数据"进行分箱(在您的情况下为体积数据).为此，可以使用smooth frequency.对于相同的x值，这将计算y值的总和.因此，首先我使用适当的装箱功能，该功能会在一定范围(x +-binwidth/2)中返回相同的值.输出数据保存在文件中，因为绘图时必须交换x和y值:

As next thing, I do binning of the 'position data' (which in your case would be the volume data). For this one can use smooth frequency. This computes the sum of the y values for the same x-values. So first I use a proper binning function, which returns the same value for a certain range (x +- binwidth/2). The output data is saved in a file, because for the plotting we must exchange x and y value:

binwidth = 2
hist(x) = floor(x+0.5)/binwidth

set output "| head -n -2 > randomwalk.hist"
set table
plot 'randomwalk.dat' using (hist($1)):(1) smooth frequency
unset table
unset output

通常一个人应该可以使用set table "randomwalk.hist"，但是由于存在错误，一个人需要这种解决方法来过滤表输出的最后一个条目，请参阅我对.

Normally one should be able to use set table "randomwalk.hist", but due to a bug, one needs this workaround to filter out the last entry of the table output, see my answer to Why does the 'set table' option in Gnuplot re-write the first entry in the last line?.

现在实际的绘图部分是:

Now the actual plotting part is:

unset key
set x2tics
set xtics nomirror

set xlabel 'time step'
set ylabel 'position value'
set x2label 'frequency'

set style fill solid 1.0 border lt -1

set terminal pngcairo
set output 'randwomwalk.png'

plot 'randomwalk.hist' using ($2/2.0):($1*binwidth):($2/2.0):(binwidth/2.0) with boxxy lc rgb '#00cc00' axes x2y1,\
     'randomwalk.dat' with lines lc rgb 'black'

给出结果(使用4.6.3，当然取决于您的随机数据):

which gives the result (with 4.6.3, depends of course on your random data):

因此，对于您的数据结构，以下脚本应该起作用:

So, for your data structure, the following script should work:

reset
binwidth = 2
hist(x) = floor(x+0.5)/binwidth
file = 'data.txt'
histfile = 'pricevolume.hist'

set table histfile
plot file using (hist($2)):($3) smooth unique
unset table

# get the number of records to skip the last one
stats histfile using 1 nooutput

unset key
set x2tics
set xtics nomirror

set xlabel 'time'
set ylabel 'price'
set x2label 'volume'

set style fill solid 1.0 border lt -1

plot histfile using ($2/2.0):($1*binwidth):($2/2.0):(binwidth/2.0) every ::::(STATS_records-2) with boxxy lc rgb '#00cc00' axes x2y1,\
     file with lines using 1:2 lc rgb 'black'

请注意，这一次跳过最后一个table条目是通过使用stats命令计数所有条目，然后使用every跳过最后一个条目来完成的(是的，STATS_records-2是正确的，因为点编号从0开始).此变体不需要任何外部工具.

Note, that this time the skipping of the last table entry is done by counting all entries with the stats command, and skipping the last one with every (yes, STATS_records-2 is correct, because the point numbering starts at 0). This variant doesn't need any external tool.

我还使用smooth unique来计算的平均值，而不是求和(用smooth frequency完成).

I also use smooth unique, which computes the average value of the , instead of the sum (which is done with smooth frequency).

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