Animate gradient bar chart - matplotlib

The following code animates a bar chart. I’m trying to apply a gradient and text labels to this animation though. The autolabel() function aims to add the text label and the gradientbars()functions aims to add the gradient. When applying here functions however, the animation just produces a still image.

I’m also hoping to adjust the gradient to a fixed point. Specifically, rather than applying the gradient to the extent of the individual bar height, I’m hoping to apply a max level of 6. Please see figure below regarding this.

I’ve commented out the specific functions below so the code works but applying them will produced the figure attached.

fig, ax = plt.subplots()
ax.grid(False)

data = np.random.randint(5, size=(10, 5))

x = ['A','B','C','D','E']
plt.ylim(0, 6)

rects = plt.bar(x, data[0])

def autolabel(rects):

    '''
    Attach a text label above each bar displaying its height
    '''
    for rect in rects:
        height = rect.get_height()
        ax.text(rect.get_x() + rect.get_width()/2., 1.05 * height,
                '%d' % int(height),
                ha = 'center', va = 'bottom')

def gradientbars(bars):

    grad = np.atleast_2d(np.linspace(0,5,256)).T

    cmap = 'Blues'
    
    ax = bars[0].axes
    lim = ax.get_xlim() + ax.get_ylim()

    for bar in bars:
    
        bar.set_zorder(1)
        bar.set_facecolor("none")
    
        x,y = bar.get_xy()
        w,h = bar.get_width(), bar.get_height()    
   
        ax.imshow(grad, extent = [x, x + w, y, y + h], aspect = "auto", zorder = 0, cmap = cmap)
    
    ax.axis(lim)

#autolabel(rects)

#gradientbars(rects)

def animate(i):

    for rect, yi in zip(rects, data[i]):
        rect.set_height(yi)

anim = animation.FuncAnimation(fig, animate, frames = len(data), interval = 100)

plt.show()

def autolabel(rects):
    '''
    Attach a text label above each bar displaying its height
    '''
    ts = []
    for rect in rects:
        height = rect.get_height()
        t = ax.text(rect.get_x() + rect.get_width()/2., 1.05 * height,
                '%d' % int(height),
                ha = 'center', va = 'bottom')
        ts.append(t)
    return ts

def gradientbars(bars, cmap, vmin, vmax):
    g = np.linspace(vmin,vmax,100)
    grad = np.vstack([g,g]).T
    xmin,xmax = ax.get_xlim()
    ymin,ymax = ax.get_ylim()
    ims = []
    for bar in bars:
        bar.set_facecolor('none')
        im = ax.imshow(grad, aspect="auto", zorder=0, cmap=cmap, vmin=vmin, vmax=vmax, extent=(xmin,xmax,ymin,ymax))
        im.set_clip_path(bar)
        ims.append(im)
    return ims

Nbars=5
Nframes=10
vmin=0
vmax=6
cmap = 'Blues'
data = np.random.choice([0,1,2],size=(Nframes,Nbars))
data = data.cumsum(axis=1)
data[data>6] = 6
x=[chr(ord('A')+i) for i in range(Nbars)]
print(x)
print(data)

fig, ax = plt.subplots()
ax.grid(False)
plt.ylim(vmin, vmax)
rects = plt.bar(x,data[0])
labels = autolabel(rects)
imgs = gradientbars(rects, cmap=cmap, vmin=vmin, vmax=vmax)

def animate(i):
    for rect,label,img,yi in zip(rects, labels, imgs, data[i]):
        rect.set_height(yi)
        label.set_text('%d'%int(yi))
        label.set_y(yi)
        img.set_clip_path(rect)

anim = animation.FuncAnimation(fig, animate, frames = len(data), interval = 500)
plt.show()