Generating grid with color gradient based on data set in python matplotlib

Question

I have a dictionary of tuples of two non-negative integers (a,b), with a and b both at most 20. The dictionary maps each tuple to a float value between zero and one. I would like to create a two-dimensional grid where the unit square in the i-th column and the j-th row (corresponding to the tuple (i,j)) is colored with a grayscale value between white and black and proportional to its float value.

To clarify, my dictionary looks something like:

dict={(0, 0) : 0.04679,
      (0, 2) : 0.10936,
      (0, 4) : 0.17872000000000005,
      (2, 4) : 0.15046000000000004,
      (4, 4) : 0.026240000000000003,
      (1, 1) : 0.02055,
      (1, 2) : 0.10275
      ...
      }

I am unsure how to go about plotting this. Any help would be appreciated!

William Miller · Accepted Answer · 2019-04-11 01:58:23Z

2

I'm sure there is a cleaner way to do this but this works -

import matplotlib.pyplot as plt
import numpy as np

d={(0, 0) : 0.04679,
   (0, 2) : 0.10936,
   (0, 4) : 0.17872000000000005,
   (2, 4) : 0.15046000000000004,
   (4, 4) : 0.026240000000000003,
   (1, 1) : 0.02055,
   (1, 2) : 0.10275
   (3, 3) : 0.84,
   (3, 2) : 0.62
}

x = []
y = []
v = []
for e in d.items():
    x.append(e[0][0])
    y.append(e[0][1])
    v.append(e[1])
m = np.zeros((max(x)+1, max(y)+1))
for ii in range(len(v)):
    m[x[ii]][y[ii]] = v[ii]
plt.matshow(m, cmap=plt.get_cmap('gray'), vmin=0.0, vmax=1.0)
plt.show()

The idea here is to parse the dictionary into a 2D numpy array which can then be directly plotted by plt.matshow(). If you want the missing values to be populated by ones instead of zeros you can use m = np.ones() instead of np.zeros(). If you don't want the minimum and maximum fixed to 0.0 and 1.0 respectively you can simply omit vmin=0.0 and vmax=1.0 in the call to matshow().

answered Apr 11, 2019 at 1:58

William Miller

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1 Comment

Ezra Erives Over a year ago

This is exactly what I was looking for. Thank you!

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