I am looking for Ripley's k function implementation in Python. But so far haven't been able to find any spatial modules implementing this in scipy or elsewhere.
I have created Voronoi tessellation of a fibre composite and need to perform analysis using Ripley's K and pair distribution functions compared to a Poisson distribution.
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2 Answers
Solved my problem, this is for others looking to do same analysis.
Definitely recommend using R for spatial analysis. A transfer from python is simple because all you need is coordinates of your point pattern.
Write a csv of x,y and z coordinates of your points using python
R has good functionality of reading csv using command read.csv("filename"). Make sure the directory is set properly using setwd command.
- Convert the csv you just read to a ppp(point pattern which R understands) using as.ppp command.
- Continue to use Kest, Gest etc for required spatial analysis.
Cheers.
Now (2021) there is a Ripley's K implementation for Python, easy to install
And also a more comprehensive package that includes Ripley's K, G, F and includes MC simulations for p-values, very nice.
