所以我有 8 個 3d 圖（7 個 3d 圖和一個 2d 圖）
我想以 4 x 2 格式定位它們。這是我的代碼：
sensor_data = self._util_sensor(sub_df)
fig = plt.figure()
fig.tight_layout()
ax = fig.add_subplot(1, 2, 1, projection = '3d')
ax.scatter(sensor_data['chest'][0], sensor_data['chest'][1], sensor_data['chest'][2])
ax.set_title('Chest')
ax = fig.add_subplot(1, 2, 2)
ax.scatter(sensor_data['ecg'][0], sensor_data['ecg'][1])
ax.set_title('ECG')
ax = fig.add_subplot(2, 2, 1, projection = '3d')
ax.scatter(sensor_data['left_accel'][0], sensor_data['left_accel'][1], sensor_data['left_accel'][2])
ax.set_title('left accel')
ax = fig.add_subplot(2, 2, 2, projection = '3d')
ax.scatter(sensor_data['left_gyro'][0], sensor_data['left_gyro'][1], sensor_data['left_gyro'][2])
ax.set_title('left gyro')
ax = fig.add_subplot(3, 2, 1, projection = '3d')
ax.scatter(sensor_data['left_mag'][0], sensor_data['left_mag'][1], sensor_data['left_mag'][2])
ax.set_title('left mag')
ax = fig.add_subplot(3, 2, 2, projection = '3d')
ax.scatter(sensor_data['right_accel'][0], sensor_data['right_accel'][1], sensor_data['right_accel'][2])
ax.set_title('right accel')
ax = fig.add_subplot(4, 2, 1, projection = '3d')
ax.scatter(sensor_data['right_gyro'][0], sensor_data['right_gyro'][1], sensor_data['right_gyro'][2])
ax.set_title('right gyro')
ax = fig.add_subplot(4, 2, 2, projection = '3d')
ax.scatter(sensor_data['right_mag'][0], sensor_data['right_mag'][1], sensor_data['right_mag'][2])
ax.set_title('right mag')
plt.show()
結果如下圖。如何正確格式化這些？
uj5u.com熱心網友回復：
您在add_subplot. 我希望這會有所幫助：
fig = plt.figure()
for i in range(6):
ax = fig.add_subplot(3, 2, i 1, projection = '3d')
第一個數字是行和列的（總）數，第三個數字是“索引”，即每個子圖從 1..6（=行 * 列）開始。
這是它的樣子：
但是要在這里完全回答這個問題，需要做的是：
fig = plt.figure(figsize=(6, 12))
ax1 = fig.add_subplot(3, 2, 1, projection = '3d')
ax2 = fig.add_subplot(3, 2, 2)
ax3 = fig.add_subplot(3, 2, 3, projection = '3d')
ax4 = fig.add_subplot(3, 2, 4, projection = '3d')
ax5 = fig.add_subplot(3, 2, 5, projection = '3d')
ax6 = fig.add_subplot(3, 2, 6, projection = '3d')
然后，您可以將軸 (ax1..6) 用作，例如，
ax2.plot([1, 3, 2, 7])
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標籤：Python matplotlib 阴谋 3d