File: hexbin_demo.py

package info (click to toggle)
matplotlib 3.10.1%2Bdfsg1-5
  • links: PTS, VCS
  • area: main
  • in suites: forky
  • size: 78,340 kB
  • sloc: python: 147,118; cpp: 62,988; objc: 1,679; ansic: 1,426; javascript: 786; makefile: 92; sh: 53
file content (45 lines) | stat: -rw-r--r-- 1,188 bytes parent folder | download | duplicates (2)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
"""
=====================
Hexagonal binned plot
=====================

`~.Axes.hexbin` is a 2D histogram plot, in which the bins are hexagons and
the color represents the number of data points within each bin.
"""

import matplotlib.pyplot as plt
import numpy as np

# Fixing random state for reproducibility
np.random.seed(19680801)

n = 100_000
x = np.random.standard_normal(n)
y = 2.0 + 3.0 * x + 4.0 * np.random.standard_normal(n)
xlim = x.min(), x.max()
ylim = y.min(), y.max()

fig, (ax0, ax1) = plt.subplots(ncols=2, sharey=True, figsize=(9, 4))

hb = ax0.hexbin(x, y, gridsize=50, cmap='inferno')
ax0.set(xlim=xlim, ylim=ylim)
ax0.set_title("Hexagon binning")
cb = fig.colorbar(hb, ax=ax0, label='counts')

hb = ax1.hexbin(x, y, gridsize=50, bins='log', cmap='inferno')
ax1.set(xlim=xlim, ylim=ylim)
ax1.set_title("With a log color scale")
cb = fig.colorbar(hb, ax=ax1, label='counts')

plt.show()

# %%
#
# .. tags:: plot-type: histogram, plot-type: hexbin, domain: statistics
#
# .. admonition:: References
#
#    The use of the following functions, methods, classes and modules is shown
#    in this example:
#
#    - `matplotlib.axes.Axes.hexbin` / `matplotlib.pyplot.hexbin`