Created
February 3, 2014 14:08
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# Abbreviated way to create groups of (nearly) identical values. | |
import numpy as np | |
# Random example data. | |
a = np.array([11.1, 1, 1, 2, 3, 4, 5, 5, 1, 5, 5, 6, 6, 7, 9, 7, 8, 7, 10, 11.1, 11.2]) | |
EPS = 1e-7 # matching precision | |
asorted = np.sort(a) # line up the values neatly, but don't alter | |
# Get all indices where a change in value occurs | |
indices = np.where(np.abs(np.diff(asorted)) > EPS)[0] + 1 | |
# Group identical values | |
groups = np.array([asorted[i1:i2] for i1, i2 in zip(np.concatenate(([0], indices)), np.concatenate((indices, [None])))]) |
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