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Abstracted, continuous, and normalised of version of the Hirsch index (h-index) from academic writing for use as a statistical measure of even distribution

Project description

Hirsch 🦌

Python implementation of the familiar discrete Hirsch index (h-index) from academic writing, with an abstracted continuous version for use as a statistical measure of even distribution

Installation

pip install hirsch

Usage

Discrete

Get the h-index of some discrete data, e.g. the number of citations an author has received on their papers:

from hirsch import hirsch
citations = [0, 1, 1, 2, 1, 6, 5, 13, 14, 10, 59, 145, 68]
h = hirsch(citations)

discrete

Continuous

Calculate a continuous h-index for some normalised and binned data, e.g. fractional populations:

from hirsch import hirsch
fractions = [0.1,0.5,0.6,0.3,0.2,0.5,0.4]
h = hirsch(fractions, continuous=True)

continuous

Calculate a continuous h-index for a set of samples from known populations (continuous=True assumed):

from hirsch import hirsch
samples = [1,2,3,4,10,20,10]
populations = [10,10,10,10,20,30,40]
h = hirsch(samples, populations)

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