如何使用matplotlib獲得密度/概率圖

Question

我試圖在paper中獲得圖7的左上角和右上角的面板。我得到了圖7的左上圖，但無法獲得右上圖。我的代碼的密度部分在輸出中生成綠色和藍色線條，這是不正確的。我怎樣才能得到概率部分（圖7的右上圖）並將其與我的數字相結合？

輸入文件（input.txt中）一小部分：

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 

代碼：

#!/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) 

輸出：

Answer 1

的第一件事喲你必須注意的是，儘管它們共享相同的y軸，但這兩個圖是在不同的軸上。如果不先進行額外的格式化，解決問題將更加容易，那麼您可以應用特殊的格式。

#!/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) 

結果看起來像

剩下的就是純粹的格式。