Matplotlib : Horizontal Bar Plot with Color Range

Question

Please forgive the crude explanation but I'm unsure how to describe the issue and as they say, a picture says a thousand words, so what I am trying to achieve is to draw a graph in matplotlib that looks like the below: whereby the scale of the color range is the same across all bars as the x limits of the x-axis.

The closest I have got to so far is this (please ignore the fact it's not horizontal - I was planning on editing that once I had figured out the coloring):

fig, ax = plt.subplots()
mpl.pyplot.viridis()
bars = ax.bar(df['Profile'], df['noise_result'])
grad = np.atleast_2d(np.linspace(0,1,256)).T
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=1,interpolation='nearest')
ax.axis(lim)

which only results in a graph like below:

Many thanks

Davide_sd · Accepted Answer · 2022-04-30 16:13:21Z

1

I'm going along with your approach. The idea is to:

choose an appropriate colormap
create a normalizer for the bar values.
create a mappable which is going to map the normalized values to the colormap in order to create a colorbar.

import matplotlib.pyplot as plt
import matplotlib.cm as cm
from matplotlib.colors import Normalize
import pandas as pd
import numpy as np

df = pd.DataFrame({'key':['A', 'B', 'C', 'D', 'E'], 'val':[100, 20, 70, 40, 100]})

# create a normalizer
norm = Normalize(vmin=df['val'].min(), vmax=df['val'].max())
# choose a colormap
cmap = cm.plasma
# map values to a colorbar
mappable = cm.ScalarMappable(norm=norm, cmap=cmap)
mappable.set_array(df['val'])


fig, ax = plt.subplots()
bars = ax.bar(df['key'], df['val'])

ax = bars[0].axes
lim = ax.get_xlim()+ax.get_ylim()
for bar, val in zip(bars, df['val']):
    grad = np.atleast_2d(np.linspace(0,val,256)).T
    bar.set_zorder(1)
    bar.set_facecolor('none')
    x, y = bar.get_xy()
    w, h = bar.get_width(), bar.get_height()
    ax.imshow(np.flip(grad), extent=[x,x+w,y,y+h], aspect='auto', zorder=1,interpolation='nearest', cmap=cmap, norm=norm)
ax.axis(lim)
cb = fig.colorbar(mappable)
cb.set_label("Values")

answered Apr 30, 2022 at 16:13

Davide_sd

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1 Comment

JohanC Over a year ago

For horizontal bars, you could use the same code, but using grad = np.atleast_2d(np.linspace(0,val,256)) without the transpose.

gerald · Accepted Answer · 2022-04-30 16:41:53Z

0

Using what you have, you could change line 12 to: ax.imshow(grad, extent=[x,x+w,y,y+h], aspect='auto', zorder=1, cmap = plt.get_cmap('gist_heat_r')) or some other color map from: https://matplotlib.org/stable/tutorials/colors/colormaps.html You could also change line 3 to start as: bars = ax.barh for horizontal bars.

edited Apr 30, 2022 at 16:41

answered Apr 30, 2022 at 16:25

gerald

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