ipywidgets:使用交互时避免闪烁

时间:2017-04-08 10:09:40

标签: python matplotlib jupyter-notebook ipywidgets

我用一个基于随机正态,伽马,指数和均匀分布的直方图的四个子图制作了一个图。我用matplotlib和Jupyter笔记本制作了它。这是一个通过ipywidgets lib的互动人物。特别是,有四个滑动条控制每个直方图上的样本大小并相应地更新它们。但是,在更新直方图时,它会令人烦恼地闪烁。有什么方法可以避免这种情况吗? THX。

现在要在jupyter笔记本上运行的代码:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib notebook
from ipywidgets import *

n = 1000
x1 = np.random.normal(-2.5, 1, n)
x2 = np.random.gamma(2, 1.5, n)
x3 = np.random.exponential(2, n)+7
x4 = np.random.uniform(14,20, n)
x = [x1, x2, x3, x4]

fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(10,7))
axs = [ax1,ax2,ax3,ax4]

titles = ['x1\nNormal', 'x2\nGamma', 'x3\nExponential', 'x4\nUniform']
subplots_axes = [[-7,2,0,250], [0,4.5,0,250], [7,25,0,250], [14,20,0,250]]

bins = [np.arange(-6, 6, 0.5),
np.arange(0, 10, 0.5),
np.arange(7, 17, 0.5),
np.arange(14, 24, 0.5)]

fig.subplots_adjust(hspace=0.5)

def plt_dist(s, sample):
    axs[s].hist(x[s][:sample], bins=bins[s], linewidth=0, color='#1F77B4')
    axs[s].axis(subplots_axes[s])
    axs[s].set_title('{}'.format(titles[s]))
    axs[s].set_ylabel('Frequency')
    axs[s].set_xlabel('Value')
    axs[s].annotate('n = {}'.format(sample), xycoords='axes fraction', xy = [0.8,0.9])
    display(fig)

for s in range(0,4):
    sld_bar = interact(plt_dist, s = fixed(s), sample = widgets.IntSlider(min=100,max=1000+45,step=1,value=100))

1 个答案:

答案 0 :(得分:1)

display(fig)会做什么或者需要做什么并不是很清楚。

对我来说,移除那一行而不是清除axs[s].clear()函数开头的轴(plt_hist)就可以了,并且“闪烁”不再存在。

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib notebook
from ipywidgets import *

n = 1000
x1 = np.random.normal(-2.5, 1, n)
x2 = np.random.gamma(2, 1.5, n)
x3 = np.random.exponential(2, n)+7
x4 = np.random.uniform(14,20, n)
x = [x1, x2, x3, x4]

fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(10,7))
axs = [ax1,ax2,ax3,ax4]

titles = ['x1\nNormal', 'x2\nGamma', 'x3\nExponential', 'x4\nUniform']
subplots_axes = [[-7,2,0,250], [0,4.5,0,250], [7,25,0,250], [14,20,0,250]]

bins = [np.arange(-6, 6, 0.5),
np.arange(0, 10, 0.5),
np.arange(7, 17, 0.5),
np.arange(14, 24, 0.5)]

fig.subplots_adjust(hspace=0.5)

def plt_dist(s, sample):
    axs[s].clear() # <-- clear axes
    axs[s].hist(x[s][:sample], bins=bins[s], linewidth=0, color='#1F77B4')
    axs[s].axis(subplots_axes[s])
    axs[s].set_title('{}'.format(titles[s]))
    axs[s].set_ylabel('Frequency')
    axs[s].set_xlabel('Value')
    axs[s].annotate('n = {}'.format(sample), xycoords='axes fraction', xy = [0.8,0.9])
    #display(fig)  <--- delete this

for s in range(0,4):
    sld_bar = interact(plt_dist, s = fixed(s), 
              sample = widgets.IntSlider(min=100,max=1000+45,step=1,value=100))