Matt Hall kwinkunks

Ripping data from pseudocolour images

Because viridis, like all good colourmaps, is perceptually linear, it's easy to get the data from it: just use a greyscale version of the image. But you can rip the data from any pseudocolour image if you know (or can guess) the colourmap.

In the rip-data.py example, here's the approach:

Read the image and transform the values to the range 0-1.
Guess the colourmap, in this case it's viridis. Matplotlib conveniently gives us the RGB triples that make up a colourmap.

mpl2qgis

See script below.

Make sure the Python file is executable. Then:

$ ./mpl2qgis.py viridis bone

This writes a file colourmaps.xml. Result:

	import numpy as np

	arr = np.random.randint(0, 256, (200, 200), dtype=np.uint8)

	def func(arr1d):
	kernel = np.ones(3) / 3
	return np.convolve(arr1d, kernel, mode='same')

	first_pass = np.apply_along_axis(func, axis=0, arr=arr)
	final_result = np.apply_along_axis(func, axis=1, arr=first_pass)

	import numpy as np
	import matplotlib.pyplot as plt
	from matplotlib.patches import Rectangle
	import requests
	from io import StringIO
	from welly import Well

	# Fetch LAS file.
	url = "https://dropbox.com/s/n52qezp5byap4mi/WellA.las?raw=1"
	r = requests.get(url)

	"""
	Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
	BSD License
	"""
	import numpy as np

	# data I/O
	data = open('input.txt', 'r').read() # should be simple plain text file
	chars = list(set(data))
	data_size, vocab_size = len(data), len(chars)

	colours = {
	'Alkali-feldpar syenite': (244, 60, 108),
	'Alkali-feldspar granite': (255, 209, 220),
	'Alkali-feldspar rhyolite': (254, 220, 126),
	'Alkali-feldspar trachyte': (254, 183, 134),
	'Alkalic intrusive rock': (255, 111, 145),
	'Alkalic volcanic rock': (194, 65, 0),
	'Alkaline basalt': (169, 101, 55),
	'Alluvial fan': (255, 255, 183),
	'Alluvial terrace': (250, 238, 122),