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Showing content from https://github.com/InseeFrLab/btbpy below:

InseeFrLab/btbpy: A Python package which provides functions dedicated to urban analysis and kernel density estimation.

btbpy: Kernel Density Estimation for Urban Geography

btbpy is a partial transposition of R btb package, available on the CRAN. btbpy stands for beyond the border for Python users

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

Developer and maintainer of btbpy package :

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.

Geographically weighted summary statistics : a framework for localised exploratory data analysis, C.Brunsdon & al., in Computers, Environment and Urban Systems C.Brunsdon & al. (2002) doi:10.1016/S0198-9715(01)00009-6, Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition, Diggle, pp. 83-86, (2003) doi:10.1080/13658816.2014.937718.


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