6

I use matplotlib.pyplot.pcolor() to plot a heatmap with matplotlib:

enter image description here

import numpy as np
import matplotlib.pyplot as plt    

def heatmap(data, title, xlabel, ylabel):
    plt.figure()
    plt.title(title)
    plt.xlabel(xlabel)
    plt.ylabel(ylabel)
    c = plt.pcolor(data, edgecolors='k', linewidths=4, cmap='RdBu', vmin=0.0, vmax=1.0)
    plt.colorbar(c)

def main():
    title = "ROC's AUC"
    xlabel= "Timeshift"
    ylabel="Scales"
    data =  np.random.rand(8,12)
    heatmap(data, title, xlabel, ylabel)
    plt.show()

if __name__ == "__main__":
    main()

Is any way to add the corresponding value in each cell, e.g.:

(from Matlab's Customizable Heat Maps)

enter image description here

(I don't need the additional % for my current application, though I'd be curious to know for the future)

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4 Answers 4

Reset to default
10

You need to add all the text by calling axes.text(), here is an example:

import numpy as np
import matplotlib.pyplot as plt    

title = "ROC's AUC"
xlabel= "Timeshift"
ylabel="Scales"
data =  np.random.rand(8,12)


plt.figure(figsize=(12, 6))
plt.title(title)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
c = plt.pcolor(data, edgecolors='k', linewidths=4, cmap='RdBu', vmin=0.0, vmax=1.0)

def show_values(pc, fmt="%.2f", **kw):
    from itertools import izip
    pc.update_scalarmappable()
    ax = pc.get_axes()
    for p, color, value in izip(pc.get_paths(), pc.get_facecolors(), pc.get_array()):
        x, y = p.vertices[:-2, :].mean(0)
        if np.all(color[:3] > 0.5):
            color = (0.0, 0.0, 0.0)
        else:
            color = (1.0, 1.0, 1.0)
        ax.text(x, y, fmt % value, ha="center", va="center", color=color, **kw)

show_values(c)

plt.colorbar(c)

the output:

enter image description here

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1 Comment

It works great, thanks! Hopefully one day displaying the numbers will be available as an option in pcolor().
9

You could use Seaborn, which is a Python visualization library based on matplotlib that provides a high-level interface for drawing attractive statistical graphics.

Heatmap example:

import seaborn as sns
sns.set()

flights_long = sns.load_dataset("flights")
flights = flights_long.pivot("month", "year", "passengers")

sns.heatmap(flights, annot=True, fmt="d")

# To display the heatmap 
import matplotlib.pyplot as plt
plt.show()

# To save the heatmap as a file:
fig = heatmap.get_figure()
fig.savefig('heatmap.pdf')

enter image description here

Documentation: https://seaborn.pydata.org/generated/seaborn.heatmap.html

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Comments

2

If that's of interest to anyone, here is below the code I use to imitate the picture from Matlab's Customizable Heat Maps I had included in the question).

import numpy as np
import matplotlib.pyplot as plt


def show_values(pc, fmt="%.2f", **kw):
    '''
    Heatmap with text in each cell with matplotlib's pyplot
    Source: http://stackoverflow.com/a/25074150/395857 
    By HYRY
    '''
    from itertools import izip
    pc.update_scalarmappable()
    ax = pc.get_axes()
    for p, color, value in izip(pc.get_paths(), pc.get_facecolors(), pc.get_array()):
        x, y = p.vertices[:-2, :].mean(0)
        if np.all(color[:3] > 0.5):
            color = (0.0, 0.0, 0.0)
        else:
            color = (1.0, 1.0, 1.0)
        ax.text(x, y, fmt % value, ha="center", va="center", color=color, **kw)

def cm2inch(*tupl):
    '''
    Specify figure size in centimeter in matplotlib
    Source: http://stackoverflow.com/a/22787457/395857
    By gns-ank
    '''
    inch = 2.54
    if type(tupl[0]) == tuple:
        return tuple(i/inch for i in tupl[0])
    else:
        return tuple(i/inch for i in tupl)

def heatmap(AUC, title, xlabel, ylabel, xticklabels, yticklabels):
    '''
    Inspired by:
    - http://stackoverflow.com/a/16124677/395857 
    - http://stackoverflow.com/a/25074150/395857
    '''

    # Plot it out
    fig, ax = plt.subplots()    
    c = ax.pcolor(AUC, edgecolors='k', linestyle= 'dashed', linewidths=0.2, cmap='RdBu', vmin=0.0, vmax=1.0)

    # put the major ticks at the middle of each cell
    ax.set_yticks(np.arange(AUC.shape[0]) + 0.5, minor=False)
    ax.set_xticks(np.arange(AUC.shape[1]) + 0.5, minor=False)

    # set tick labels
    #ax.set_xticklabels(np.arange(1,AUC.shape[1]+1), minor=False)
    ax.set_xticklabels(xticklabels, minor=False)
    ax.set_yticklabels(yticklabels, minor=False)

    # set title and x/y labels
    plt.title(title)
    plt.xlabel(xlabel)
    plt.ylabel(ylabel)      

    # Remove last blank column
    plt.xlim( (0, AUC.shape[1]) )

    # Turn off all the ticks
    ax = plt.gca()    
    for t in ax.xaxis.get_major_ticks():
        t.tick1On = False
        t.tick2On = False
    for t in ax.yaxis.get_major_ticks():
        t.tick1On = False
        t.tick2On = False

    # Add color bar
    plt.colorbar(c)

    # Add text in each cell 
    show_values(c)

    # resize 
    fig = plt.gcf()
    fig.set_size_inches(cm2inch(40, 20))



def main():
    x_axis_size = 19
    y_axis_size = 10
    title = "ROC's AUC"
    xlabel= "Timeshift"
    ylabel="Scales"
    data =  np.random.rand(y_axis_size,x_axis_size)
    xticklabels = range(1, x_axis_size+1) # could be text
    yticklabels = range(1, y_axis_size+1) # could be text   
    heatmap(data, title, xlabel, ylabel, xticklabels, yticklabels)
    plt.savefig('image_output.png', dpi=300, format='png', bbox_inches='tight') # use format='svg' or 'pdf' for vectorial pictures
    plt.show()


if __name__ == "__main__":
    main()
    #cProfile.run('main()') # if you want to do some profiling

Output:

enter image description here

It looks nicer when there are some patterns:

enter image description here

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2 Comments

To keep this helpful code snippet up to date: "izip" was removed in Python3 so just remove the import and use zip; "get_axes()" is deprecated - instead just write ".axes"
@Chaoste Thanks!
1

Same as @HYRY aswer, but python3 compatible version:

import numpy as np
import matplotlib.pyplot as plt    

title = "ROC's AUC"
xlabel= "Timeshift"
ylabel="Scales"
data =  np.random.rand(8,12)


plt.figure(figsize=(12, 6))
plt.title(title)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
c = plt.pcolor(data, edgecolors='k', linewidths=4, cmap='RdBu', vmin=0.0, vmax=1.0)

def show_values(pc, fmt="%.2f", **kw):
    pc.update_scalarmappable()
    ax = pc.axes
    for p, color, value in zip(pc.get_paths(), pc.get_facecolors(), pc.get_array()):
        x, y = p.vertices[:-2, :].mean(0)
        if np.all(color[:3] > 0.5):
            color = (0.0, 0.0, 0.0)
        else:
            color = (1.0, 1.0, 1.0)
        ax.text(x, y, fmt % value, ha="center", va="center", color=color, **kw)

show_values(c)

plt.colorbar(c)
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1 Comment

Hi I'm trying to use your code, but when I call this it returns an array of all values for a row of the pcolor, but only a single cell's vertices and so I get an error trying to add the value text to the cell. Any idea why?

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