jupyter bqplot數字更緊密的佈局

我已經使用bqplot在Jupyter筆記本中創建了幾個圖。這些繪圖使用Jupyter小部件HBox和VBox佈局屬性進行排列。但是，我無法弄清楚如何在各個子圖之間獲得緊密的佈局。獲得更緊密佈局的最佳方法是什麼？jupyter bqplot數字更緊密的佈局

下面是在Jupyter筆記本中運行的Python代碼示例。

import numpy as np 
from bqplot import * 
from IPython.display import Javascript, display, clear_output 
import ipywidgets as widgets 

size = 100 
scale = 100. 
np.random.seed(0) 
x_data = np.arange(size) 
y_data = np.cumsum(np.random.randn(size) * scale) 

x_sc = LinearScale() 
y_sc = LinearScale() 

ax_x = Axis(label='X', scale=x_sc, grid_lines='solid') 
ax_y = Axis(label='Y', scale=y_sc, orientation='vertical', grid_lines='solid') 

line = Lines(x=x_data, y=x_data, scales={'x': x_sc, 'y': y_sc}) 

figy=[] 
for i in range(2): 
    figx=[] 
    for j in range(3): 
     figx.append(Figure(axes=[ax_x, ax_y], marks=[line], title='Example' + str(i*3+j), fig_margin = dict(top=30, bottom=10, left=20, right=20))) 
    figy.append(widgets.HBox(figx)) 
display(widgets.VBox(figy, align_content = 'stretch'))

來源

2017-06-20 DougR

這裏是一個解決方案：

import numpy as np 
from bqplot import * 
from IPython.display import Javascript, display, clear_output 
import ipywidgets as widgets 

size = 100 
scale = 100. 
np.random.seed(0) 
x_data = np.arange(size) 
y_data = np.cumsum(np.random.randn(size) * scale) 

x_sc = LinearScale() 
y_sc = LinearScale() 

ax_x = Axis(label='X', scale=x_sc, grid_lines='solid') 
ax_y = Axis(label='Y', scale=y_sc, orientation='vertical', grid_lines='solid') 

line = Lines(x=x_data, y=x_data, scales={'x': x_sc, 'y': y_sc}) 

fig_layout = widgets.Layout(width='auto', height='auto') 

figy=[] 
for i in range(2): 
    figx=[] 
    for j in range(3): 
     figx.append(Figure(layout=fig_layout, axes=[ax_x, ax_y], marks=[line], title='Example' + str(i*3+j), fig_margin = dict(top=30, bottom=10, left=20, right=20))) 
    figy.append(widgets.HBox(figx)) 
display(widgets.VBox(figy, align_content = 'stretch'))

基本上覆蓋該圖的屬性layout。 bqplot數字有固定的自然高度。