spherical-histogram 0.1.6

Install

pip install spherical_histogram

Usage

First a HemisphereHistogram histogram is initialized. When providing general parameters for the desired binning such as num_vertices and max_zenith_distance_rad, the geometry of the hemisphere will be made on the fly using a Fibonacci spacing.

import spherical_histogram
import numpy as np

hist = spherical_histogram.HemisphereHistogram(
    num_vertices=200,
    max_zenith_distance_rad=np.deg2rad(90),
)

A Fibonacci spaced mesh of triangles which defines the bins of the histogram.

Distribution of solid angles in the upper mesh. The triangles have similar zizes. Outliers are mostly caused by the hard cut on the zenith distance.

Or by defining the binning explicitly using a triangle mesh with vertices and faces.

import spherical_histogram

geom = spherical_histogram.geometry.HemisphereGeometry(
    vertices=[[0, 0, 1], [0, 0.02, 1], [0.02, 0, 1]],
    faces=[[0, 1, 2]],
)

hist = spherical_histogram.HemisphereHistogram(bin_geometry=geom)

Afer initializing, we can histogram directions. This can be done multiple times with any of the three options

Azimuth and zenith angle

hist.assign_azimuth_zenith(azimuth_rad=0.2, zenith_rad=0.1)

The direction vector’s x and y components

hist.assign_cx_cy(cx=0.3, cy=0.2)

Or with the full direction vector (x, y, and z).

hist.assign_cx_cy_cz(cx=0.2, cy=0.3, cz=np.sqrt(1 - 0.2 ** 2 - 0.3 ** 2))

After all directions where assigned to the histogram, the result is found in

hist.bin_counts

and in

hist.overflow

where overflow counts all the directions which could not be assigned to a bin and bin_counts is an array with one bount for each face in the hemispherical mesh of triangles.

The assign functions accept both scalar and array like parameters for an easy numpy integration. When the directions are assignes in array like parameters the loop for the assignment happens in the underlying c implementation and is rather fast and efficient.