CODEWITHSUNDEEP
pythonmatplotlibstacked-bar-chart
Tangerine Dream
Tangerine Dream

Reputation: 27

Stacked bar chart with custom gradient coloring

Here's what I came up with by plotting thick line segments.

Here's what I came up with by plotting thick line segments. The coloration is blue, with varying alpha, 0 < alpha < 1.

My workaround doens't work as I'd like because I don't have a legend (I want a legend that shows a gradient of the blue at varying alpha).

Additionally, I've found that matplotlib scales funny. There should be no overlap of the bars, but if I adjust the window size, the gap between the line segments will change.This is the same figure as the earlier one, just after I've resized the figure window with my mouse.This is the same figure as the earlier one, just after I've resized the figure window with my mouse.

I'm not sure if there's a better way to go about accomplishing this, or if there's a different package I can use. Here's the snippet of code that I'm using.

import matplotlib.pyplot as plt
x1  =[0, 19, 39, 46, 60, 79]
x2 = [19, 39, 46, 60, 79, 90]
alpha_list = [-0.8402, -0.6652, 0.0, -0.5106, -0.8074, 0.0]
plt.figure()
for idx,x in enumerate(x1):
    plt.plot([x1[idx],x2[idx]],[0,0],color = 'blue',alpha=alpha_list[idx],linewidth =20)
plt.show()

Upvotes: 1

Views: 441

Answers (2)

ImportanceOfBeingErnest
ImportanceOfBeingErnest

Reputation: 339220

I suppose alpha is just a workaround for using different shades of blue? In that case the Blues colormap can be used instead.
Several lines can be plotted using a LineCollection.

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection

x1  =[0, 19, 39, 46, 60, 79]
x2 = [19, 39, 46, 60, 79, 90]
alpha_list = [-0.8402, -0.6652, 0.0, -0.5106, -0.8074, 0.0]

verts = np.dstack((np.c_[x1, x2], np.zeros((len(x1), 2))))

fig, ax = plt.subplots()
lc = LineCollection(verts, linewidth=40, cmap="Blues_r", array=np.array(alpha_list))
ax.add_collection(lc)

ax.autoscale()
ax.set_ylim(-1,1)
fig.colorbar(lc)
plt.show()

enter image description here

Upvotes: 3

dubbbdan
dubbbdan

Reputation: 2720

I think a workaround would be to use plt.barh. Here is an example using normalized color maps. Each color gets converted to RGBA before it can be passed to plt.barh.

import matplotlib.pyplot as plt
from matplotlib import colors
import matplotlib.cm as cmx

x1  =[0, 19, 39, 46, 60, 79]
x2 = [19, 39, 46, 60, 79, 90]

values = range(len(x1))
jet = cm = plt.get_cmap('jet') 
cNorm  = colors.Normalize(vmin=0, vmax=values[-1])
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet)

fig, ax = plt.subplots()

for idx, x, y in zip(values,x1, x2):          
    colorVal = scalarMap.to_rgba(values[idx])  
    start = x
    end = y
    width=end-start
    ax.barh(y = 0, width = width, left=start, height = 0.1, label = str(idx), color=colorVal)         
ax.set_ylim(-.5,0.5)
ax.legend()

which returns: enter image description here

If you really want to just change the alpha transparency of a single color, you would just have to input alpha_list[idx] for the last element to the RGBA tuple colorVal. For some reason, RGBA did not like negative alpha values, so notice I changed them all to positive

fig, ax = plt.subplots()
alpha_list = [0.8402, 0.6652, 0.01, 0.5106, 0.8074, 0.0]
for idx, x, y in zip(values,x1, x2):          
    colorVal = (0.0, 0.3, 1.0, alpha_list[idx])
    start = x
    end = y
    width=end-start
    ax.barh(y = 0, width = width, left=start, height = 0.1, label = str(idx), color=colorVal)         


ax.set_ylim(-.5,0.5)
ax.legend()

enter image description here

Upvotes: 0

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