A 2-D Heatmap is an information perception instrument that assists with addressing the size of the peculiarity in type of shadings. In python, we can plot 2-D Heatmaps utilizing Matplotlib bundle. There are various strategies to plot 2-D Heatmaps, some of them are examined underneath.
Utilizing Matplotlib, I need to plot a 2D hotness map. My information is a n-by-n Numpy exhibit, each with a worth somewhere in the range of 0 and 1. So for the (I, j) component of this exhibit, I need to plot a square at the (I, j) coordinate in my hotness map, whose tone is relative to the component’s worth in the cluster.
Method 1: Using matplotlib.pyplot.imshow() Function
Syntax:matplotlib.pyplot.imshow(X, cmap=None, norm=None, aspect=None, interpolation=None, alpha=None, vmin=None,
vmax=None, origin=None, extent=None, shape=<deprecated parameter>, filternorm=1, filterrad=4.0,
imlim=<deprecated parameter>, resample=None, url=None, \*, data=None, \*\*kwargs)
- Python3
# Program to plot 2-D Heat map# using matplotlib.pyplot.imshow() methodimport numpy as npimport matplotlib.pyplot as plt data = np.random.random(( 12 , 12 ))plt.imshow( data , cmap = 'autumn' , interpolation = 'nearest' ) plt.title( "2-D Heat Map" )plt.show() |
Output:
eevibes
Method 2: Using Seaborn Library
For this we use seaborn.heatmap() function
Syntax: seaborn.heatmap(data, *, vmin=None, vmax=None, cmap=None, center=None, robust=False,annot=None,
fmt=’.2g’, annot_kws=None, linewidths=0, linecolor=’white’, cbar=True, cbar_kws=None, cbar_ax=None,
square=False, xticklabels=’auto’, yticklabels=’auto’, mask=None, ax=None, **kwargs)
- Python3
# Program to plot 2-D Heat map# using seaborn.heatmap() methodimport numpy as npimport seaborn as snsimport matplotlib.pylab as plt data_set = np.random.rand( 10 , 10 )ax = sns.heatmap( data_set , linewidth = 0.5 , cmap = 'coolwarm' ) plt.title( "2-D Heat Map" )plt.show() |
Output:
eevibes
Method 3: Using matplotlib.pyplot.pcolormesh() Function
Syntax:matplotlib.pyplot.pcolormesh(*args, alpha=None, norm=None, cmap=None, vmin=None, vmax=None,
shading=’flat’, antialiased=False, data=None, **kwargs)
- Python3
# Program to plot 2-D Heat map# using matplotlib.pyplot.pcolormesh() methodimport matplotlib.pyplot as pltimport numpy as np Z = np.random.rand( 15 , 15 ) plt.pcolormesh( Z , cmap = 'summer' ) plt.title( '2-D Heat Map' )plt.show() |
Output:
eevibes
Also Read: Learn Arrays in C and C++