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[英]How can I update matplotlib subplot axes in an interactive plot when the subplots are viewing different axis regions?
[英]How to plot figures to different subplot axes in matplotlib
我試圖用一個 3d 子圖和 3 個 2d 子圖的組合來繪制一個圖形。 為什么它們相互重疊?
這是我的代碼:
fig = plt.figure(figsize=(10,10))
ax = fig.add_subplot(3, 2, 1, projection='3d')
ax = plt.axes(projection='3d')
ax.scatter3D(extents[0], extents[1], extents[2], color='yellow')
ax = fig.add_subplot(3, 2, 2)
ax = sns.distplot(extents[0], color='red')
ax.set_title("Extent_0 Distribution")
ax = fig.add_subplot(3, 2, 4)
ax = sns.distplot(extents[1], color='blue')
ax.set_title("Extent_1 Distribution")
ax = fig.add_subplot(3, 2, 6)
ax = sns.distplot(extents[2], color='green')
ax.set_title("Extent_2 Distribution")
plt.show()
ax = fig.add_subplot(3, 2, 1, projection='3d')
創建一個ax
,然后您使用ax = plt.axes(projection='3d')
重新分配變量; 這不會陰謀ax
。ax
參數
sns.histplot(df['freq: 1x'], ax=ax)
sns.distplot
已經廢棄了displot
或histplot
。import pandas as pd
import numpy as np # for sample data
# sinusoidal sample data
sample_length = range(1, 3+1)
rads = np.arange(0, 2*np.pi, 0.01)
data = np.array([np.sin(t*rads) for t in sample_length])
df = pd.DataFrame(data.T, index=pd.Series(rads.tolist(), name='radians'), columns=[f'freq: {i}x' for i in sample_length])
# plot the figures and correctly use the ax parameter
fig = plt.figure(figsize=(10,10))
ax = fig.add_subplot(3, 2, 1, projection='3d')
ax.scatter3D(df['freq: 1x'], df['freq: 2x'], df['freq: 3x'], color='green', s=5)
ax = fig.add_subplot(3, 2, 2)
sns.histplot(df['freq: 1x'], ax=ax)
ax.set_title("Extent_0 Distribution")
ax = fig.add_subplot(3, 2, 4)
sns.histplot(df['freq: 2x'], ax=ax)
ax.set_title("Extent_1 Distribution")
ax = fig.add_subplot(3, 2, 6)
sns.histplot(df['freq: 3x'], ax=ax)
ax.set_title("Extent_2 Distribution")
plt.tight_layout()
nrows
來增加 3D 圖的大小。
gs1 = fig.add_gridspec(nrows=4, ncols=3)
fig = plt.figure(constrained_layout=False, figsize=(10, 10))
gs1 = fig.add_gridspec(nrows=3, ncols=3)
ax1 = fig.add_subplot(gs1[:-1, :], projection='3d')
ax1.scatter3D(df['freq: 1x'], df['freq: 2x'], df['freq: 3x'], color='green', s=10)
ax2 = fig.add_subplot(gs1[-1, 0])
sns.histplot(df['freq: 1x'], kde=True, ax=ax2)
ax2.set_title("Extent_0 Distribution")
ax3 = fig.add_subplot(gs1[-1, 1])
sns.histplot(df['freq: 2x'], kde=True, ax=ax3)
ax3.set_title("Extent_1 Distribution")
ax4 = fig.add_subplot(gs1[-1, 2])
sns.histplot(df['freq: 3x'], kde=True, ax=ax4)
ax4.set_title("Extent_2 Distribution")
plt.tight_layout()
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