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How to plot in multiple subplots(13个回答)
6天前关闭。
我尝试生成两个散点图(并排),matplotlib中的代码非常简单明了。然而,我的数据集有些复杂,这意味着对于每个x值,都有2-3个对应的y值,所以我为此创建了一个数组。
下面是生成一个图的代码:
import matplotlib.pyplot as plt
import numpy as np
plt.close('all')
data = np.array([
[-2, 22.8],
[-2, 0.3],
[-2, 3.1],
[-1, -1.7],
[-1, 4.8],
[-1, -0.7],
[ 0, -2.6],
[ 0, -0.03],
[ 1, -5.7],
[ 1, -1.5],
[ 1, -3.9],
[ 2, -21.5],
[ 2, -7.7],
])
custom_annotations = ["K464E", "K472E", "R470E", "K464A", "M155E", "K472A", "M155A", "Q539A", "M155R", "D244A", "E247A", "E247R", "D244K"]
plt.scatter(data[:,0], data[:,1], marker='o', c=data[:,1], edgecolors='black', linewidths=1, alpha=0.75)
# plt.colorbar(orientation='horizontal')
plt.xlabel(r'$\Delta q$')
plt.ylabel(r'$\delta V_{0.5}$ Apo wild-type mHCN2 (mV)')
plt.axvline(0, c=(.5, .5, .5), ls= '--')
plt.axhline(0, c=(.5, .5, .5), ls= '--')
for i, txt in enumerate(custom_annotations):
plt.annotate(txt, (data[i,0], data[i,1]))
当我试图生成一个由两个组成的面板时,我直观地定义了一个为data 1,另一个为data 2,然后继续使用matplotlib代码,如下所示:
import matplotlib.pyplot as plt
import numpy as np
data1 = np.array([
[-2, 22.8],
[-2, 19.6],
[-2, 0.3],
[-1, 8.9],
[-1, 13.7],
[-1, 14.7,],
[ 0, 1.9],
[ 0, -1.8],
[ 1, -3],
[ 1, -5.9],
[ 1, -13.4],
[ 2, -5.7],
[ 2, -6.8],
])
data2 = np.array([
[-2, 22.8],
[-2, 0.3],
[-2, 3.1],
[-1, -1.7],
[-1, 4.8],
[-1, -0.7],
[ 0, -2.6],
[ 0, -0.03],
[ 1, -5.7],
[ 1, -1.5],
[ 1, -3.9],
[ 2, -21.5],
[ 2, -7.7],
])
custom_annotations = ["K464E", "K472E", "R470E", "K464A", "M155E", "K472A", "M155A", "Q539A", "M155R", "D244A", "E247A", "E247R", "D244K"]
ax1.scatter(data1[:,0], data1[:,1])
ax2.scatter(data2[:,0], data2[:,1])
ax1.set_title('Experimental Apo mHCN2 Channel')
ax1.set_xlabel(r'$\Delta q$')
ax1.set_ylabel(r'$\delta V_{0.5}$ Apo wild-type mHCN2 (mV)')
ax2.set_title('Electrostatic Potential Calculations - Holo mHCN2 Channel')
ax2.set_xlabel(r'$\Delta q$')
ax2.set_ylabel(r'$\delta V_{0.5}$ Apo wild-type mHCN2 (mV)')
plt.axvline(0, c=(.5, .5, .5), ls= '--')
plt.axhline(0, c=(.5, .5, .5), ls= '--')
for i, txt in enumerate(custom_annotations):
plt.annotate(txt, (data1[i,0], data1[i,1]))
plt.annotate(txt, (data2[i,0], data2[i,1]))
plt.show()
这产生了一个空的情节,所以应该有什么致命的错误。
此外,由于两个数据集之间y轴上的值差异很大,所以i最终具有不同的y轴间距,有没有办法解决这个问题?
1条答案
按热度按时间dojqjjoe1#