I need to normalize a list of values to fit in a probability distribution, i.e. between 0.0 and 1.0.
I understand how to normalize, but was curious if Python had a function to automate this.
I'd like to go from:
raw = [0.07, 0.14, 0.07]
to
normed = [0.25, 0.50, 0.25]
Use :
norm = [float(i)/sum(raw) for i in raw]
to normalize against the sum to ensure that the sum is always 1.0 (or as close to as possible).
use
norm = [float(i)/max(raw) for i in raw]
to normalize against the maximum
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