un-bound-histogram 0.1.0

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

The UnBoundHistogram has a few statistical estimators built in, such as modus() and quantile()/percentile().

There is also a two dimensional implementation UnBoundHistogram2d. See tests for examples.

import un_bound_histogram
import numpy as np

prng = np.random.Generator(np.random.PCG64(9))
SIZE = 100000
XLOC = 3.0
YLOC = -4.5

ubh = un_bound_histogram.UnBoundHistogram2d(
    x_bin_width=0.1,
    y_bin_width=0.1,
)

ubh.assign(
    x=prng.normal(loc=XLOC, scale=1.0, size=SIZE),
    y=prng.normal(loc=YLOC, scale=1.0, size=SIZE),
)

xb_max, yb_max = ubh.argmax()
x_max = xb_max * ubh.x_bin_width
y_max = yb_max * ubh.y_bin_width

assert XLOC - 0.5 < x_max < XLOC + 0.5
assert YLOC - 0.5 < y_max < YLOC + 0.5

x_range, y_range = ubh.range()

assert x_range[0] <= xb_max <= x_range[1]
assert y_range[0] <= yb_max <= y_range[1]

assert ubh.sum() == SIZE