如何使用matplotlib获得密度/概率图

Question

我试图在这个paper中获得图7的左上角和右上角。我得到了图7的左上方面板，但无法得到它的右上方面板。我的代码的密度部分在输出中生成绿线和蓝线，这是不正确的。如何获得概率部分（图7的右上图）并将其与我的数字相结合？

输入文件的一小部分（ input.txt ）：

0.0000000 0.0000474 0.0000393 
400.0000000 0.1775423 0.1091695 
800.0000000 0.2363394 0.1158220 
1200.0000000 0.2146373 0.1323802 
1600.0000000 0.2629943 0.1379013 
2000.0000000 0.2353280 0.1205457 
2400.0000000 0.2548243 0.1285356 
2800.0000000 0.2507923 0.1243078 
3200.0000000 0.3038598 0.1328937 
3600.0000000 0.2438334 0.1171351 
4000.0000000 0.2399136 0.1386342
4400.0000000 0.2263989 0.1232137 
4800.0000000 0.2036292 0.1274123 
5200.0000000 0.2136007 0.1262307 
5600.0000000 0.2685070 0.1408818 
6000.0000000 0.2805652 0.1222442 
6400.0000000 0.2328329 0.1256370 
6800.0000000 0.2660308 0.1135865 
7200.0000000 0.2446094 0.1089109 
7600.0000000 0.2729914 0.1254719 
8000.0000000 0.3119634 0.1378875 
8400.0000000 0.3347659 0.1309574 
8800.0000000 0.3206002 0.1289072 
9200.0000000 0.2670084 0.1275363 
9600.0000000 0.2712551 0.1324258 
10000.0000000 0.2453061 0.1368878 

代码：

#!/usr/bin/python
import numpy as np
import pylab as plot
import matplotlib.pyplot as plt
import numpy, scipy, pylab, random
from matplotlib.ticker import MultipleLocator
import matplotlib as mpl
from matplotlib.ticker import MaxNLocator
from scipy import stats

with open("input.xvg", "r") as f:
    x=[]
    y1=[]
    y2=[]
    for line in f:
        if not line.strip() or line.startswith('@') or line.startswith('#'): continue
        row = line.split()
        x.append(float(row[0])*0.001)
        y1.append(float(row[1]))
        y2.append(float(row[2]))


fig = plt.figure(figsize=(3.2,2.2), dpi=300)
ax = plt.subplot(111)


plt.xlim(0, 1000)
plt.ylim(0, 0.7)
ax.xaxis.set_major_locator(MaxNLocator(10))
ax.yaxis.set_major_locator(MaxNLocator(7))
ax.xaxis.set_minor_locator(MultipleLocator(50))
ax.yaxis.set_minor_locator(MultipleLocator(0.05))

plt.plot(x, y1, 'orange', label='A',  linewidth=0.5)
plt.plot(x, y2, 'black', label='B',  linewidth=0.5)


plt.xlabel('Time (ns)', fontsize=8)
plt.ylabel('RMSD (nm)', fontsize=8)


for axis in ['top','bottom','left','right']:
  ax.spines[axis].set_linewidth(0.5)

plt.subplots_adjust(top=0.95)
plt.subplots_adjust(bottom=0.18)
plt.subplots_adjust(left=0.14)
plt.subplots_adjust(right=0.95)


plt.tick_params(axis='both', which='major', labelsize=7)
plt.tick_params(axis='both', which='minor', labelsize=0)

#for the density part
density1 = stats.kde.gaussian_kde(y1)
density2 = stats.kde.gaussian_kde(y2)
plt.plot(x, density1(y1))
plt.plot(x, density2(y2))

plt.savefig("output.png", dpi=300)

输出：

Answer 1

您必须注意的第一件事是两个图在不同的轴上，尽管它们共享相同的y轴。如果没有额外的格式化首先解决问题会更容易，然后您可以应用您的特殊格式。

#!/usr/bin/python
import numpy as np
import pylab as plot
import matplotlib.pyplot as plt
import numpy, scipy, pylab, random
from matplotlib.ticker import MultipleLocator
import matplotlib as mpl
from matplotlib.ticker import MaxNLocator
from scipy import stats

with open("input.txt", "r") as f:
    x=[]
    y1=[]
    y2=[]
    for line in f:
        if not line.strip() or line.startswith('@') or line.startswith('#'): continue
        row = line.split()
        x.append(float(row[0])*0.001)
        y1.append(float(row[1]))
        y2.append(float(row[2]))



fig, (ax1, ax2) =plt.subplots(1, 2, sharey=True)

ax1.axis([0, 10, 0, 0.7])


ax1.plot(x, y1, 'orange', label='A',  linewidth=1)
ax1.plot(x, y2, 'black', label='B',  linewidth=1)

#for the density part

density1 = stats.kde.gaussian_kde(y1)
density2 = stats.kde.gaussian_kde(y2)

# plot the pdf for the full range of y-axis 
y_range = np.linspace(0, 0.7, 100)
ax2.plot(density1(y_range), y_range, 'orange')
ax2.plot(density2(y_range), y_range, 'black')

# display y-axis tick on the right 
ax2.yaxis.tick_right()
# remove the spacing between the two axes
plt.subplots_adjust(wspace=0, hspace=0)

# deal with the overlaping x-axis label at the center
# you can remove the label corresponding to the last element of the frist axis 
xticks = ax1.xaxis.get_major_ticks()
xticks[-1].label1.set_visible(False)

# modifying the number of y ticks 
ax2.yaxis.set_major_locator(MaxNLocator(4.0)) 
ax2.yaxis.set_minor_locator(MultipleLocator(0.1))

plt.savefig("output.png", dpi=300)

结果如

剩下的只是格式化。