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How to update artists in scrollable, matplotlib and multipot

I am trying to create a scrollable multiplier based on the answer to this question: Creating a scrollable multiset with pylab python

Lines created using ax.plot() are updated correctly, however I cannot figure out how to update artists created using xvlines() and fill_between() .

 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()

Here is what it looks like at the moment enter image description here

I cannot apply the same approach as for plot() , as the following error message:

 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

This is what each frame should have looked like. enter image description here

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fill_between returns a PolyCollection , which expects the creation of a list (or several lists) of vertices upon creation. Unfortunately, I did not find a way to get the vertices that were used to create the specified PolyCollection , but in your case it’s enough to just create a PolyCollection directly (thereby avoiding the use of fill_between ), and then update your vertices after changing frames.

Below is the version of your code that does what you are after:

 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()

Each of the three PolyCollections ( reds , blues and greens ) has only four vertices (edges of the rectangles), which are determined based on the data (which is done in update_collections ). The result is as follows:

example result of a given code

Tested in Python 3.5

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