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)
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)
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)
Metadata
Release files for hirsch 0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| hirsch-0.1.tar.gz | 15.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hirsch-0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 31.0 kB
Release files / hirsch-0.1.tar.gz
| Download URL | hirsch-0.1.tar.gz |
|---|---|
| Size | 15.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/5.1.1 CPython/3.9.20
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Release files / hirsch-0.1-py3-none-any.whl
| Download URL | hirsch-0.1-py3-none-any.whl |
|---|---|
| Size | 15.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.9.20
|