Binning Utils

A collection of tools to help with binning.

Binning

The Binning is powerful dict which contains many bin related quantities and is soley constructed from the edges of a binning.

import numpy as np
import binning_utils
binning_utils.Binning(bin_edges=np.linspace(0, 1, 9))

{'num': 4,
 'edges': array([0.  , 0.25, 0.5 , 0.75, 1.  ]),
 'centers': array([0.125, 0.375, 0.625, 0.875]),
 'widths': array([0.25, 0.25, 0.25, 0.25]),
 'start': 0.0,
 'stop': 1.0,
 'limits': array([0., 1.])}

random drawing

Draw the bin to which a sample is randomly assigned to. This assumes that the distribution of samples is uniform over the entire range of the binning. You can provide the aperture of the bins though. (This is the widths of the bins if the binning is one dimensional).

import numpy as np
import binning_utils
prng = np.random.Generator(np.random.PCG64(19))

assignment = binning_utils.draw_random_bin(
    prng=prng,
    bin_apertures=[1000, 4000, 2000, 3000],
    size=10000,
)

print(np.unique(assignment, return_counts=True))

(array([0, 1, 2, 3]), array([ 974, 3950, 2060, 3016]))

power10

Create binning in geomspace which is aligned to decades.

import binning_utils
binning_utils.power10.space(
    start_decade=0,
    start_bin=0,
    stop_decade=2,
    stop_bin=1,
    num_bins_per_decade=3,
)
array([ 1., 2.15, 4.64, 10., 21.54, 46.41, 100.])

powerspace

To make bin edges for distributions occuring in power laws. For example to histogram the energies of cosmic rays which occur in a power law with slope -2.7

import binning_utils
binning_utils.powerspace(
    start=1,
    stop=10,
    power_slope=-2.7,
    size=10,
)
array([ 1.        ,  1.07017144,  1.15544801,  1.26196439,  1.39995703,
    1.58808152,  1.86493297,  2.32807878,  3.33799855, 10.        ])

sphere

Make tiles of roughly same areas on the surface of a sphere using a Fibonacci spacing.

import binning_utils
vertices_on_sphere = binning_utils.sphere.fibonacci_space(
    size=100,
    max_zenith_distance_rad=0.5,
)