如何将ipywidget滑块的默认位置更改为matplotlib图形的侧面?

bqplot 而不是matplotlib,结果更简单。

import numpy as np
from bqplot import pyplot as plt
from IPython.display import display
from ipywidgets import interactive, fixed, IntSlider, HBox, Layout

plt.figure(min_aspect_ratio=1, max_aspect_ratio=1)

xs = np.random.randint(0, 5000 + 1, 100)
ys = np.random.randint(0, 5000 + 1, 100)

scat = plt.scatter(xs, ys)

def rotate(theta, xs, ys):
    new_xs = xs * np.cos(np.deg2rad(theta)) - ys * np.sin(np.deg2rad(theta))
    new_xs -= new_xs.min()
    new_ys = xs * np.sin(np.deg2rad(theta)) + ys * np.cos(np.deg2rad(theta))
    new_ys -= new_ys.min()
    return new_xs, new_ys

def update_plot(theta, xs, ys):
    new_xs, new_ys = rotate(theta, xs, ys)
    scat.x, scat.y = new_xs, new_ys

w = interactive(update_plot, 
             theta=IntSlider(min=-180, max=180, step=5,value=0, orientation='vertical'), 
             xs=fixed(xs), 
             ys=fixed(ys))

box_layout = Layout(display='flex', flex_flow='row', justify_content='center', align_items='center')
display(HBox([plt.current_figure(), w], layout=box_layout))

bqplot update_plot

从 BQ图 文档:

在bqplot中,plot的每一个属性都是一个交互属性 小部件,只需从几个小部件中创建一个复杂且功能丰富的GUI Python代码的简单行。

我将保留公认的James答案,因为它回答了原始问题。

children 变成一个 HBox .交互式的子窗口小部件遵循此约定;(小部件0,小部件1…,输出),其中元组的最后一个成员是控制小部件的输出。您可以在声明之前或之后定义HBox的布局。 Read more on the layouts available here .

以下解决方案有几个注意事项;图形最初可能不会显示,您可能需要在控件出现之前对其进行调整,然后使用 %matplotlib notebook

from IPython.display import display
from ipywidgets import interactive, fixed, IntSlider, HBox, Layout
import numpy as np
import matplotlib.pylab as plt
%matplotlib notebook

def rotate(theta, xs, ys):
    new_xs = xs * np.cos(np.deg2rad(theta)) - ys * np.sin(np.deg2rad(theta))
    new_xs -= new_xs.min()
    new_ys = xs * np.sin(np.deg2rad(theta)) + ys * np.cos(np.deg2rad(theta))
    new_ys -= new_ys.min()
    return new_xs, new_ys

def update_plot(theta, xs, ys):
    fig = plt.figure(figsize=(8,4))
    ax = fig.add_subplot(111)
    scat, = ax.plot(xs, ys, 'kx', markersize=1)
    ax.grid(which='both', color='.25', lw=.1)
    ax.set_aspect('equal'), ax.set_title('Rotate')
    new_xs, new_ys = rotate(theta, xs, ys)
    scat.set_xdata(new_xs), scat.set_ydata(new_ys)
    ax.set_xlim(new_xs.min() - 500, new_xs.max() + 500)
    ax.set_ylim(new_ys.min() - 500, new_ys.max() + 500)

xs = np.random.randint(0, 5000, 50)
ys = np.random.randint(0, 5000, 50)
w = interactive(update_plot,
                theta=IntSlider(min=-180, max=180, step=5, value=0,orientation='vertical'), 
                xs=fixed(xs),
                ys=fixed(ys))

# Define the layout here.
box_layout = Layout(display='flex', flex_flow='row', justify_content='space-between', align_items='center')

display(HBox([w.children[1],w.children[0]], layout=box_layout))

更新:

ipywidgets gitter .

from IPython.display import display, clear_output
from ipywidgets import interact, fixed, IntSlider, HBox, Layout, Output, VBox
import numpy as np 
import matplotlib.pyplot as plt
%matplotlib inline

def rotate(theta, xs, ys):
    new_xs = xs * np.cos(np.deg2rad(theta)) - ys * np.sin(np.deg2rad(theta))
    new_xs -= new_xs.min()
    new_ys = xs * np.sin(np.deg2rad(theta)) + ys * np.cos(np.deg2rad(theta))
    new_ys -= new_ys.min()
    return new_xs, new_ys

out = Output(layout={'width': '300px', 'height': '300px'})

def update_plot(change): 
    theta = change['new'] # new slider value 
    with out: 
        clear_output(wait=True)
        fig = plt.figure(figsize=(4,4))
        ax = fig.add_subplot(111)
        scat, = ax.plot(xs, ys, 'kx', markersize=1)
        ax.grid(which='both', color='.25', lw=.1)
        ax.set_aspect('equal'), ax.set_title('Rotate')
        new_xs, new_ys = rotate(theta, xs, ys) 
        scat.set_xdata(new_xs), scat.set_ydata(new_ys)
        ax.set_xlim(new_xs.min() - 500, new_xs.max() + 500)
        ax.set_ylim(new_ys.min() - 500, new_ys.max() + 500)
        plt.show()

xs = np.random.randint(0, 5000, 50) 
ys = np.random.randint(0, 5000, 50) 

slider = IntSlider(min=-180, max=180, step=5, value=0, orientation='vertical') 
slider.observe(update_plot, 'value')
update_plot({'new': slider.value}) 
display(HBox([out, slider]))