python - 如何更新可滚动、matplotlib 和 multiplot 中的艺术家

Question

我正在尝试根据这个问题的答案创建一个可滚动的多图: Creating a scrollable multiplot with python's pylab

使用 ax.plot() 创建的线条正在正确更新，但是我无法弄清楚如何更新使用 xvlines() 和 创建的艺术家填充之间()。

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from matplotlib.widgets import Slider

#create dataframes
dfs={}
for x in range(100):
    col1=np.random.normal(10,0.5,30)
    col2=(np.repeat([5,8,7],np.round(np.random.dirichlet(np.ones(3),size=1)*31)[0].tolist()))[:30]
    col3=np.random.randint(4,size=30)
    dfs[x]=pd.DataFrame({'col1':col1,'col2':col2,'col3':col3})

#create figure,axis,subplot
fig = plt.figure()
gs = gridspec.GridSpec(1,1,hspace=0,wspace=0,left=0.1,bottom=0.1)
ax = plt.subplot(gs[0])
ax.set_ylim([0,12])

#slider
frame=0
axframe = plt.axes([0.13, 0.02, 0.75, 0.03])
sframe = Slider(axframe, 'frame', 0, 99, valinit=0,valfmt='%d')

#plots
ln1,=ax.plot(dfs[0].index,dfs[0]['col1'])
ln2,=ax.plot(dfs[0].index,dfs[0]['col2'],c='black')

#artists
ax.fill_between(dfs[0].index,y1=dfs[0]['col2']-0.5,y2=dfs[0]['col2']+0.5,where=dfs[0]['col2']==5,facecolor='r',edgecolors='none',alpha=0.5)
ax.fill_between(dfs[0].index,y1=dfs[0]['col2']-0.5,y2=dfs[0]['col2']+0.5,where=dfs[0]['col2']==8,facecolor='b',edgecolors='none',alpha=0.5)
ax.fill_between(dfs[0].index,y1=dfs[0]['col2']-0.5,y2=dfs[0]['col2']+0.5,where=dfs[0]['col2']==7,facecolor='g',edgecolors='none',alpha=0.5)
ax.vlines(x=dfs[0]['col3'].index,ymin=0,ymax=dfs[0]['col3'],color='black')

#update plots
def update(val):
    frame = np.floor(sframe.val)
    ln1.set_ydata(dfs[frame]['col1'])
    ln2.set_ydata(dfs[frame]['col2'])
    ax.set_title('Frame ' + str(int(frame)))
    plt.draw()

#connect callback to slider 
sframe.on_changed(update)
plt.show()

这是现在的样子

我不能应用与 plot() 相同的方法，因为以下会产生错误消息:

ln3,=ax.fill_between(dfs[0].index,y1=dfs[0]['col2']-0.5,y2=dfs[0]['col2']+0.5,where=dfs[0]['col2']==5,facecolor='r',edgecolors='none',alpha=0.5)
TypeError: 'PolyCollection' object is not iterable

这就是它在每一帧上的样子

Answer 1

fill_between 返回一个 PolyCollection，它在创建时需要一个(或多个)顶点列表。不幸的是，我还没有找到一种方法来检索用于创建给定 PolyCollection 的顶点，但在您的情况下，直接创建 PolyCollection 很容易(因此避免使用 fill_between)，然后在帧更改时更新其顶点。

下面是您的代码版本，可以满足您的需求:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from matplotlib.widgets import Slider

from matplotlib.collections import PolyCollection

#create dataframes
dfs={}
for x in range(100):
    col1=np.random.normal(10,0.5,30)
    col2=(np.repeat([5,8,7],np.round(np.random.dirichlet(np.ones(3),size=1)*31)[0].tolist()))[:30]
    col3=np.random.randint(4,size=30)
    dfs[x]=pd.DataFrame({'col1':col1,'col2':col2,'col3':col3})

#create figure,axis,subplot
fig = plt.figure()
gs = gridspec.GridSpec(1,1,hspace=0,wspace=0,left=0.1,bottom=0.1)
ax = plt.subplot(gs[0])
ax.set_ylim([0,12])

#slider
frame=0
axframe = plt.axes([0.13, 0.02, 0.75, 0.03])
sframe = Slider(axframe, 'frame', 0, 99, valinit=0,valfmt='%d')

#plots
ln1,=ax.plot(dfs[0].index,dfs[0]['col1'])
ln2,=ax.plot(dfs[0].index,dfs[0]['col2'],c='black')

##additional code to update the PolyCollections
val_r = 5
val_b = 8
val_g = 7

def update_collection(collection, value, frame = 0):
    xs = np.array(dfs[frame].index)
    ys = np.array(dfs[frame]['col2'])

    ##we need to catch the case where no points with y == value exist:
    try:
        minx = np.min(xs[ys == value])
        maxx = np.max(xs[ys == value])
        miny = value-0.5
        maxy = value+0.5
        verts = np.array([[minx,miny],[maxx,miny],[maxx,maxy],[minx,maxy]])
    except ValueError:
        verts = np.zeros((0,2))
    finally:
        collection.set_verts([verts])

#artists

##ax.fill_between(dfs[0].index,y1=dfs[0]['col2']-0.5,y2=dfs[0]['col2']+0.5,where=dfs[0]['col2']==5,facecolor='r',edgecolors='none',alpha=0.5)
reds = PolyCollection([],facecolors = ['r'], alpha = 0.5)
ax.add_collection(reds)
update_collection(reds,val_r)

##ax.fill_between(dfs[0].index,y1=dfs[0]['col2']-0.5,y2=dfs[0]['col2']+0.5,where=dfs[0]['col2']==8,facecolor='b',edgecolors='none',alpha=0.5)
blues = PolyCollection([],facecolors = ['b'], alpha = 0.5)
ax.add_collection(blues)
update_collection(blues, val_b)

##ax.fill_between(dfs[0].index,y1=dfs[0]['col2']-0.5,y2=dfs[0]['col2']+0.5,where=dfs[0]['col2']==7,facecolor='g',edgecolors='none',alpha=0.5)
greens = PolyCollection([],facecolors = ['g'], alpha = 0.5)
ax.add_collection(greens)
update_collection(greens, val_g)

ax.vlines(x=dfs[0]['col3'].index,ymin=0,ymax=dfs[0]['col3'],color='black')

#update plots
def update(val):
    frame = np.floor(sframe.val)
    ln1.set_ydata(dfs[frame]['col1'])
    ln2.set_ydata(dfs[frame]['col2'])
    ax.set_title('Frame ' + str(int(frame)))

    ##updating the PolyCollections:
    update_collection(reds,val_r, frame)
    update_collection(blues,val_b, frame)
    update_collection(greens,val_g, frame)

    plt.draw()

#connect callback to slider 
sframe.on_changed(update)
plt.show()

三个 PolyCollections(reds、blues 和 greens)中的每一个都只有四个顶点(矩形的边缘)，这是根据给定的数据确定的(在 update_collections 中完成)。结果如下所示:

在 Python 3.5 中测试