Matplotlib: Using strings as values instead of numbers

Question

My data is a 100 x 100 array of strings which are all hex codes:

[['#10060e' '#11070f' '#060409' ... '#08030a' '#09030d' '#12050f']
['#110600' '#09010e' '#0d0210' ... '#09030f' '#08060b' '#160a0a']
['#0a070e' '#13060f' '#0c040f' ... '#0c0610' '#0e040c' '#0a020f']
...
['#0c020d' '#09040b' '#10070c' ... '#0a090f' '#160613' '#08000f']
['#0a020f' '#09040a' '#150812' ... '#11040d' '#07040b' '#0b060d']
['#0d0715' '#0e020c' '#140710' ... '#0a0112' '#12090e' '#0c020d']]

Matplotlib: throws this error: TypeError: cannot perform reduce with flexible type

I think the issue it is having is it cannot give a colour to these as they are strings, not numbers. I can only find examples where all the data is numerical and has a colour map applied to it, nothing where every bit of data's colour is specified. I would like to tell Matplotlib what colour I'd like all of these to be using, surprise surprise, the hex codes. How can I go about doing that?

Full(er) code sample:

z = np.asanyarray(pixel_arr)
x = np.arange(0, width, 1)  # len = 100
y = np.arange(0, height, 1)  # len = 100

fig, ax = plt.subplots()
ax.pcolormesh(x, y, z)
plt.show()

I didn't realise that was possible. Will have a go at it later today. Would you be able to point me in the direction of some sample code? — F1rools22
– F1rools22, Commented May 17, 2021 at 18:10

Reti43 · Accepted Answer · 2021-05-17 18:37:38Z

I would like to tell Matplotlib what colour I'd like all of these to be using

It sounds like you have a bunch of pixel values you want to plot, i.e., an image. So you can treat it like one.

import matplotlib.pyplot as plt
import numpy as np

data = np.array([['#10060e', '#11070f', '#060409', '#08030a', '#09030d', '#12050f'],
                 ['#110600', '#09010e', '#0d0210', '#09030f', '#08060b', '#160a0a'],
                 ['#0a070e', '#13060f', '#0c040f', '#0c0610', '#0e040c', '#0a020f'],
                 ['#0c020d', '#09040b', '#10070c', '#0a090f', '#160613', '#08000f'],
                 ['#0a020f', '#09040a', '#150812', '#11040d', '#07040b', '#0b060d'],
                 ['#0d0715', '#0e020c', '#140710', '#0a0112', '#12090e', '#0c020d']])

img = [[tuple(bytes.fromhex(pixel[1:])) for pixel in row] for row in data]
img = np.array(img, dtype=np.uint8)
plt.imshow(img)
plt.show()

The output may be dark at first glance, but that's because I used the data you showed us, which all happen to be very dark pixels.

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