我正在研究如何将垂直IntSlider的位置更改为matplotlib图的右侧。这是代码:
from ipywidgets import interact, fixed, IntSlider
import numpy as np
from matplotlib import pyplot as plt
%matplotlib notebook
fig = plt.figure(figsize=(8,4))
xs = np.random.random_integers(0, 5000, 50)
ys = np.random.random_integers(0, 5000, 50)
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')
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.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)
w = interact(update_plot,
theta=IntSlider(min=-180, max=180, step=5,value=0, orientation='vertical'),
xs=fixed(xs),
ys=fixed(ys))
这就是我所拥有的:
这就是我想要的:
可能有一种非常简单的方法可以做到这一点,但我无法弄清楚自己。
我尝试将fig
和interactive
窗口小部件放入VBox
,然后将VBox
与IPython.display
包裹起来,并且它没有工作
在示例中无法找到直接的解决方案。
EDIT1:
ipywidgets提供了一个Output()
类,用于捕获输出区域并在小部件上下文中使用它。
我会试着弄清楚如何使用它。
这是对象: https://github.com/jupyter-widgets/ipywidgets/blob/master/ipywidgets/widgets/widget_output.py
答案 0 :(得分:2)
您可以通过创建交互式窗口小部件然后将children
加载到HBox
来解决此问题。互动的儿童小部件遵循这一惯例; (widget_0,widget_1 ...,output)其中元组的最后一个成员是控件小部件的输出。您可以在声明之前或之后定义HBox的布局。 Read more on the layouts available here
以下解决方案有几点需要注意;图表最初可能不会显示,您可能需要在控件出现之前进行调整,第二次使用%matplotlib notebook
魔法时控件可能会在更新时导致大量闪烁。除此之外,我认为这应该像你想要的那样工作;
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
这是Jason Grout的ipywidgets gitter解决方案。
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]))
答案 1 :(得分:2)
我决定使用bqplot代替matplotlib来尝试此示例,结果证明它更简单。
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
旨在成为一个交互式小部件。这种方式可以简单地添加到输出中,而不必将其包装到update_plot
函数中。
来自bqplot
文档:
在bqplot中,绘图的每个属性都是交互式的 小部件。这允许用户将任何绘图与IPython集成 从小部件创建复杂且功能丰富的GUI的小部件 简单的Python代码行。
我会接受詹姆斯接受的答案,因为它回答了原来的问题。