如何單獨顏色注釋和共享 y 軸？

Question

我想分享兩個子圖的 y 軸（y 軸標題在兩個圖之間。

我寫了這個：

ax1,ax2 = axs

ax1.scatter(data1[:,0], data1[:,1])
ax2.scatter(data2[:,0], data2[:,1])


ax1.set_xlabel(r'$\Delta  V_{0.5}$  Apo wild-type mHCN2 (mV)')
ax2.set_xlabel(r'$\Delta q$')

axs.get_shared_y_axes(r'$\Delta \psi_mem$  cAMP-bound wild-type mHCN2 (mV)')

拋出了這個錯誤：

AttributeError: 'numpy.ndarray' object 沒有屬性 'get_shared_y_axes'

我還需要根據我指定的顏色 class 為 plot 上的每個點着色，不知何故，對這些點的迭代不起作用，知道嗎？

我的完整代碼：

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.patches as mpatches


from scipy.stats import t



data1 = np.array([
    [22.8, 22.8],
    [19.6, 0.3],
    [0.3, 3.1],
    [8.9, -1.7],
    [13.7, 4.8],
    [14.7, -0.7],
    [1.9, -2.6],
    [-1.8, -0.03],
    [-3, -5.7],
    [-5.9, -1.5],
    [-13.4, -3.9],
    [-5.7, -21.5],
    [-6.8, -7.7],
]) 

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=(17,9))
ax1,ax2 = axs

ax1.scatter(data1[:,0], data1[:,1])
ax2.scatter(data2[:,0], data2[:,1])


ax1.set_xlabel(r'$\Delta  V_{0.5}$  Apo wild-type mHCN2 (mV)')
ax2.set_xlabel(r'$\Delta q$')

axs.get_shared_y_axes(r'$\Delta \psi_mem$  cAMP-bound wild-type mHCN2 (mV)')

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]))

# Defining custom 'xlim' and 'ylim' values.
custom_xlim = (-3, 3)
custom_ylim = (-25, 25)

# Setting the values for all axes.
plt.setp(axs, xlim=custom_xlim, ylim=custom_ylim)


classes = ["K464E", "K472E", "R470E", "K464A", "M155E", "K472A", "M155A", "Q539A", "M155R", "D244A", "E247A", "E247R", "D244K"]
class_colours = ["r", "r", "r", "r", "r", "r", "g", "g", "b", "b", "b", "b", "b"]
recs = []
for i in range(0,len(class_colours)):
    recs.append(mpatches.Rectangle((0,0),1,1,fc=class_colours[i]))
plt.legend(recs,classes,loc=1)
plt.show()

編輯：在下面，您會看到我已經用我希望包含的內容生成的 plot。 共享的 y 軸應該是黃色箭頭所在的位置。 關於“個人顏色注釋，我需要根據用紅色箭頭突出顯示的 colour_class 為 plot 上的每個點着色。

Answer 1

我不太確定我是否完全理解有關 colors 的問題，但是您可以設置c=關鍵字參數以將單個 colors 應用於散點（參見下面的代碼）。

關於共享 y 軸，可能有幾種解決方案：

第一個解決方案：您可以在創建圖形/軸時使用關鍵字參數sharey=True ：

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.patches as mpatches


from scipy.stats import t



data1 = np.array([
    [22.8, 22.8],
    [19.6, 0.3],
    [0.3, 3.1],
    [8.9, -1.7],
    [13.7, 4.8],
    [14.7, -0.7],
    [1.9, -2.6],
    [-1.8, -0.03],
    [-3, -5.7],
    [-5.9, -1.5],
    [-13.4, -3.9],
    [-5.7, -21.5],
    [-6.8, -7.7],
]) 

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"]
classes = ["K464E", "K472E", "R470E", "K464A", "M155E", "K472A", "M155A", "Q539A", "M155R", "D244A", "E247A", "E247R", "D244K"]
class_colours = ["r", "r", "r", "r", "r", "r", "g", "g", "b", "b", "b", "b", "b"]

fig, axs = plt.subplots(1,2, figsize=(17,9), sharey=True)
ax1,ax2 = axs

ax1.scatter(data1[:,0], data1[:,1])
ax2.scatter(data2[:,0], data2[:,1], c=class_colours)


ax1.set_xlabel(r'$\Delta  V_{0.5}$  Apo wild-type mHCN2 (mV)')
ax2.set_xlabel(r'$\Delta q$')
ax1.set_ylabel(r'$\Delta \psi_mem$  cAMP-bound wild-type mHCN2 (mV)')

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]))

# Defining custom 'xlim' and 'ylim' values.
custom_xlim = (-3, 3)
custom_ylim = (-25, 25)

# Setting the values for all axes.
plt.setp(axs, xlim=custom_xlim, ylim=custom_ylim)

recs = []
for i in range(0,len(class_colours)):
    recs.append(mpatches.Rectangle((0,0),1,1,fc=class_colours[i]))
plt.legend(recs,classes,loc=1)
plt.show()

第二種解決方案：不使用sharey=True ，您只需將第一個子圖的 y 軸向右移動：

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.patches as mpatches


from scipy.stats import t



data1 = np.array([
    [22.8, 22.8],
    [19.6, 0.3],
    [0.3, 3.1],
    [8.9, -1.7],
    [13.7, 4.8],
    [14.7, -0.7],
    [1.9, -2.6],
    [-1.8, -0.03],
    [-3, -5.7],
    [-5.9, -1.5],
    [-13.4, -3.9],
    [-5.7, -21.5],
    [-6.8, -7.7],
]) 

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"]
classes = ["K464E", "K472E", "R470E", "K464A", "M155E", "K472A", "M155A", "Q539A", "M155R", "D244A", "E247A", "E247R", "D244K"]
class_colours = ["r", "r", "r", "r", "r", "r", "g", "g", "b", "b", "b", "b", "b"]

fig, axs = plt.subplots(1,2, figsize=(17,9))
ax1,ax2 = axs

ax1.scatter(data1[:,0], data1[:,1])
ax2.scatter(data2[:,0], data2[:,1], c=class_colours)


ax1.set_xlabel(r'$\Delta  V_{0.5}$  Apo wild-type mHCN2 (mV)')
ax1.yaxis.tick_right()
ax2.set_xlabel(r'$\Delta q$')
ax2.set_ylabel(r'$\Delta \psi_mem$  cAMP-bound wild-type mHCN2 (mV)')

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]))

# Defining custom 'xlim' and 'ylim' values.
custom_xlim = (-3, 3)
custom_ylim = (-25, 25)

# Setting the values for all axes.
plt.setp(axs, xlim=custom_xlim, ylim=custom_ylim)

recs = []
for i in range(0,len(class_colours)):
    recs.append(mpatches.Rectangle((0,0),1,1,fc=class_colours[i]))
plt.legend(recs,classes,loc=1)
plt.show()