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Histogram data in bins but there are 2**64 (almost un-bound) bins.

Project description

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This UnBoundhHistogram has bins with a fixed width. But if needed, it offers an almost un-bound amount of 2**64 bins. Making a histogram in an almost un bound range is usefule when one does not know the range of the data in advance and when streaming thrhough the data is costly. UnBoundhHistogram was created to histogram vast streams of data generated in costly simulations for particle physics. Buzz word bingo: big data.

Install

pip install un_bound_histogram

Usage

import un_bound_histogram
import numpy

prng = numpy.random.Generator(numpy.random.PCG64(1337))

h = un_bound_histogram.UnBoundHistogram(bin_width=0.1)

h.assign(x=prng.normal(loc=5.0, scale=2.0, size=1000000))

# assign multiple times to grow the histogram.
h.assign(x=prng.normal(loc=-3.0, scale=1.0, size=1000000))
h.assign(x=prng.normal(loc=1.0, scale=0.5, size=1000000))

assert 0.9 < h.percentile(50) < 1.1
assert h.sum() == 3 * 1000000

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