I want to plot a simple 1D histogram where the bars should follow the color-coding of a given colormap.
Here's an MWE
:
import numpy as n
import matplotlib.pyplot as plt
# Random gaussian data.
Ntotal = 1000
data = 0.05 * n.random.randn(Ntotal) + 0.5
# This is the colormap I'd like to use.
cm = plt.cm.get_cmap('RdYlBu_r')
# Plot histogram.
n, bins, patches = plt.hist(data, 25, normed=1, color='green')
plt.show()
which outputs this:
Instead of the color being green
for the entire histogram, I'd like the columns to follow a color-coding given by the colormap defined in cm
and the values of the bins
. This would mean that bins closer to zero (not in height but in position) should look bluer and those closer to one redder, according to the chosen colormap RdYlBu_r
.
Since plt.histo
doesn't take a cmap
argument I don't know how to tell it to use the colormap defined in cm
.
The hist
command returns a list of patches, so you can iterate over them and set their color like so:
import numpy as n
import matplotlib.pyplot as plt
# Random gaussian data.
Ntotal = 1000
data = 0.05 * n.random.randn(Ntotal) + 0.5
# This is the colormap I'd like to use.
cm = plt.cm.get_cmap('RdYlBu_r')
# Plot histogram.
n, bins, patches = plt.hist(data, 25, normed=1, color='green')
bin_centers = 0.5 * (bins[:-1] + bins[1:])
# scale values to interval [0,1]
col = bin_centers - min(bin_centers)
col /= max(col)
for c, p in zip(col, patches):
plt.setp(p, 'facecolor', cm(c))
plt.show()
To get the colors, you need to call the colormap with a value between 0 and 1. Resulting figure: