如何創建一個包含兩個散點圖的面板？

我嘗試生成兩個散點圖（并排），matplotlib 中的代碼非常簡單明了。但是，我的資料集有點復雜，這意味著對于每個 x 值，有 2-3 個對應的 y 值，所以我為此創建了一個陣列。

這是生成一個圖的代碼：

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]))

當我嘗試生成兩個面板時，我直觀地將一個定義為 data1，另一個定義為 data2，然后繼續使用 matplotlib 代碼，方法如下：

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()

這產生了一個空的情節，所以應該有一些致命的錯誤。

此外，由于兩個資料集之間 y 軸上的值差異很大，我最終得到不同的 y 軸間距，有沒有辦法解決這個問題？

uj5u.com熱心網友回復：

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"]

fig, axs = plt.subplots(1,2, figsize=(12,9), sharey='row')
ax1,ax2 = axs

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'$\Delta q$')

for ax in axs:
    ax.axvline(0, c=(.5, .5, .5), ls= '--')
    ax.axhline(0, c=(.5, .5, .5), ls= '--')

for i, txt in enumerate(custom_annotations):
    ax1.annotate(txt, (data1[i,0], data1[i,1]))
    ax2.annotate(txt, (data2[i,0], data2[i,1]))
    
plt.show()

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