Python 绘图与可视化 matplotlib 动态条形图 bar

bar的参考链接:https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.bar.html

第一种办法

一种方法是每次都重新画,包括清除figure

def animate(fi):
        bars=[]
        if len(frames)>fi:
            # axs.text(0.1,0.90,time_template%(time.time()-start_time),transform=axs.transAxes)#所以这样
            time_text.set_text(time_template%(0.1*fi))#这个必须没有axs.cla()才行
            # axs.cla()
            axs.set_title('bubble_sort_visualization')
            axs.set_xticks([])
            axs.set_yticks([])
            bars=axs.bar(list(range(Data.data_count)),#个数
                         [d.value for d in frames[fi]],#数据
                         1,                             #宽度
                         color=[d.color for d in frames[fi]]#颜色
                         ).get_children()
        return bars
    anim=animation.FuncAnimation(fig,animate,frames=len(frames), interval=frame_interval,repeat=False)

 

这样效率很低,而且也有一些不可取的弊端,比如每次都需要重新设置xticks、假如figure上添加的有其他东西,这些东西也一并被clear了,还需要重新添加,比如text,或者labale。

 

第二种办法

参考链接:https://stackoverflow.com/questions/16249466/dynamically-updating-a-bar-plot-in-matplotlib

这个链接里的内容和上面的差不多:https://stackoverflow.com/questions/34372021/python-matplotlib-animate-bar-and-plot-in-one-picture/34372367#34372367

可以像平时画线更新data那样来更新bar的高

import matplotlib.pyplot as plt
import numpy as np
from matplotlib import animation


fig=plt.figure(1,figsize=(4,3))
ax=fig.add_subplot(111)
ax.set_title('bar_animate_test')
#ax.set_xticks([])注释了这个是能看到变化,要不看不到变化,不对,能看到变化,去了注释吧
#ax.set_yticks([])
ax.set_xlabel('xlable')
N=5
frames=50
x=np.arange(1,N+1)

collection=[]
collection.append([i for i in x])
for i in range(frames):
    collection.append([ci+1 for ci in collection[i]])
print(collection)
xstd=[0,1,2,3,4]
bars=ax.bar(x,collection[0],0.30)
def animate(fi):
    # collection=[i+1 for i in x]
   ax.set_ylim(0,max(collection[fi])+3)#对于问题3,添加了这个
    for rect ,yi in zip(bars,collection[fi]):
        rect.set_height(yi)
    # bars.set_height(collection)
    return bars
anim=animation.FuncAnimation(fig,animate,frames=frames,interval=10,repeat=False)
plt.show()

  

  

问题

  *)TypeError: 'numpy.int32' object is not iterable

x=np.arange(1,N+1)
collection=[i for i in x] #collection=[i for i in list(x)]#错误的认为是dtype的原因,将这里改成了list(x) for i in range(frames): collection.append([ci+1 for ci in collection[i]])#问题的原因是因为此时的collection还是一个一位数组,所以这个collection[i]是一个x里的一个数,并不是一个列表,我竟然还以为的dtype的原因,又改了 xstd=[0,1,2,3,4]

  应该是

collection=[]
collection.append([i for i in x])#成为二维数组
for i in range(frames):
    collection.append([ci+1 for ci in collection[i]])

  然后又出现了下面的问题:

  *)TypeError: only size-1 arrays can be converted to Python scalars

Traceback (most recent call last):
  File "forTest.py", line 22, in 
    bars=ax.bar(x,collection,0.30)
  File "C:\Users\Administrator.SC-201605202132\Envs\sort\lib\site-packages\matplotlib\__init__.py", line 1589, in inner
    return func(ax, *map(sanitize_sequence, args), **kwargs)
  File "C:\Users\Administrator.SC-201605202132\Envs\sort\lib\site-packages\matplotlib\axes\_axes.py", line 2430, in bar
    label='_nolegend_',
  File "C:\Users\Administrator.SC-201605202132\Envs\sort\lib\site-packages\matplotlib\patches.py", line 707, in __init__
    Patch.__init__(self, **kwargs)
  File "C:\Users\Administrator.SC-201605202132\Envs\sort\lib\site-packages\matplotlib\patches.py", line 89, in __init__
    self.set_linewidth(linewidth)
  File "C:\Users\Administrator.SC-201605202132\Envs\sort\lib\site-packages\matplotlib\patches.py", line 368, in set_linewidth
    self._linewidth = float(w)
TypeError: only size-1 arrays can be converted to Python scalars

  参考链接:https://www.cnblogs.com/Summerio/p/9723099.html

  应该是传递的参数错误,仔细想了一下,在报错的代码行中,collection原来是没错的,因为原来是一维数组,现在变成二维了,改为

bars=ax.bar(x,collection[0],0.30)

  好了

   *)出现的问题,在上面的代码中,运行的时候不会画布的大小不会变,会又条形图溢出的情况,在animate()中添加了

def animate(fi):
    # collection=[i+1 for i in x]
    ax.set_ylim(0,max(collection[fi])+3)#添加了这个
    for rect ,yi in zip(bars,collection[fi]):
        rect.set_height(yi)

    # bars.set_height(collection)
    return bars

  

  

别的属性

  *)条形图是怎样控制间隔的:

  是通过控制宽度

width=1,#没有间隔,每个条形图会紧挨着

  *)errorbar:

  是加一个横线,能通过xerr和yerr来调整方向

xstd=[0,1,2,3,4]
bars=ax.bar(x,collection,0.30,xerr=xstd)

  

 

转载于:https://www.cnblogs.com/Gaoqiking/p/11261336.html

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