[英]how to get a density/probability plot using matplotlib
我试图让这个图7的左上和右上面板纸 。 我得到了图7的左上方面板,但无法获得其右上方面板。 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的右上方面板)并将其与我的图结合?
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
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)
首先要注意的是,尽管两个图共享相同的y轴,但它们在不同的轴上。 如果不首先进行额外的格式化,则解决该问题将更加容易,然后您可以应用特殊的格式化。
#!/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)
结果看起来像
剩下的仅仅是格式化。
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