Sebastian Raschka

<- [back] to the matplotlib-gallery repository



In [1]:
%load_ext watermark
In [2]:
%watermark -u -d -v -p matplotlib,numpy
Last updated: 21/08/2014 

CPython 3.4.1
IPython 2.0.0

matplotlib 1.3.1
numpy 1.8.2

[More information](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/ipython_magic/watermark.ipynb) about the `watermark` magic command extension.

In [3]:
%matplotlib inline



Heatmaps in matplotlib

Sections





Simple heat maps

In [4]:
import numpy as np

# Sample from a bivariate Gaussian distribution
mean = [0,0]
cov = [[0,1],[1,0]] 
x, y = np.random.multivariate_normal(mean, cov, 10000).T



Using NumPy's histogram2d

In [5]:
from matplotlib import pyplot as plt

hist, xedges, yedges = np.histogram2d(x,y)
X,Y = np.meshgrid(xedges,yedges)
plt.imshow(hist)
plt.grid(True)
plt.colorbar()
plt.show()
In [6]:
# changing the interpolation

plt.imshow(hist, interpolation='nearest')
plt.grid(True)
plt.colorbar()
plt.show()



Using hist2d from matplotlib

In [7]:
plt.hist2d(x, y, bins=10)
plt.colorbar()
plt.grid()
plt.show()
In [8]:
# changing the bin-size

plt.hist2d(x, y, bins=40)
plt.colorbar()
plt.grid()
plt.show()



Using pcolor from matplotlib

In [9]:
plt.pcolor(hist)
plt.colorbar()
plt.grid()
plt.show()



Using matshow from matplotlib

In [4]:
import numpy as np
import matplotlib.pyplot as plt

columns = ['A', 'B', 'C', 'D']
rows = ['1', '2', '3', '4']

data = np.random.random((4,4))

fig = plt.figure()

ax = fig.add_subplot(111)

cax = ax.matshow(data, interpolation='nearest')
fig.colorbar(cax)

ax.set_xticklabels([''] + columns)
ax.set_yticklabels([''] + rows)

plt.show()



Using different color maps



Available color maps

In [27]:
from math import ceil
import numpy as np

# Sample from a bivariate Gaussian distribution
mean = [0,0]
cov = [[0,1],[1,0]] 
x, y = np.random.multivariate_normal(mean, cov, 10000).T


size = len(plt.cm.datad.keys())
all_maps = list(plt.cm.datad.keys())

fig, ax = plt.subplots(ceil(size/4), 4, figsize=(12,100))

counter = 0
for row in ax:
    for col in row:
        try:
            col.imshow(hist, cmap=all_maps[counter])
            col.set_title(all_maps[counter])
        except IndexError:
           break
        counter += 1

plt.tight_layout()
plt.show()