https://github.com/inseefrlab/btbpy

A Python package which provides functions dedicated to urban analysis and kernel density estimation.
https://github.com/inseefrlab/btbpy

geography package python statistical-package urban-data-science

Last synced: 3 months ago
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A Python package which provides functions dedicated to urban analysis and kernel density estimation.

• Host: GitHub
• URL: https://github.com/inseefrlab/btbpy
• Owner: InseeFrLab
• License: gpl-3.0
• Created: 2021-03-03T07:49:54.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2024-12-06T09:59:36.000Z (7 months ago)
• Last Synced: 2025-01-21T22:25:00.931Z (5 months ago)
• Topics: geography, package, python, statistical-package, urban-data-science
• Language: Jupyter Notebook
• Homepage: https://pybtb.readthedocs.io/en/latest/
• Size: 3.02 MB
• Stars: 1
• Watchers: 4
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# `btbpy`: Kernel Density Estimation for Urban Geography

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`btbpy` is a partial transposition of R `btb` package, available on the [CRAN](https://cran.r-project.org/web/packages/btb/index.html). `btbpy` stands for *beyond the border for Python users*

Documentation website: https://pybtb.readthedocs.io/en/latest/

## Contributions

Developer and maintainer of `btbpy` package :

* Julien Jamme, 

* [Lino Galiana](https://github.com/linogaliana/)

* François Sémécurbe

Authors and Contributors of R `btb` package:

Arlindo Dos Santos [cre],

François Sémécurbe [drt, aut],

Auriane Renaud [ctb],

Farida Marouchi [ctb]

Joachim Timoteo [ctb]

## What do `btbpy` and `btb` do ?

The `kernelSmoothing()` function allows you to square and smooth geolocated data. It calculates a classical kernel smoothing (conservative) or a geographically weighted median. There are only two major call modes of the function. The smoothing with quantiles method is not available on the `btbpy` package.

The first call mode is `kernelSmoothing(obs, epsg, cellsize, bandwith)` for a classical kernel smoothing and automatic grid.

The second call mode is `kernelSmoothing(obs, epsg, cellsize, bandwith, centroids)` for a classical kernel smoothing and user grid.

## References

        

Geographically weighted summary statistics : a framework for localised exploratory data analysis, C.Brunsdon & al., in Computers, Environment and Urban Systems C.Brunsdon & al. (2002) , 

Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition, Diggle, pp. 83-86, (2003) .