PyInterpolate

PyInterpolate is designed as the Python library for geostatistics. It's role is to provide access to spatial statistics tools used in a wide range of studies.

Status

Pre-Beta version: package is tested and the main structure is preserved but future changes are very likely to occur. Look into projects and issues tab to learn more.

Setup

Setup is described in the file SETUP.md: https://github.com/szymon-datalions/pyinterpolate/blob/master/SETUP.md

Commercial and scientific projects where library has been used

• Tick-Borne Disease Detector (Data Lions company) for the European Space Agency (2019-2020).

Community

Join our community in Discord: https://discord.gg/3EMuRkj

Bibliography

PyInterpolate was created thanks to many resources and all of them are pointed here:

• Armstrong M., Basic Linear Geostatistics, Springer 1998,
• GIS Algorithms by Ningchuan Xiao: https://uk.sagepub.com/en-gb/eur/gis-algorithms/book241284
• Pardo-Iguzquiza E., VARFIT: a fortran-77 program for fitting variogram models by weighted least squares, Computers & Geosciences 25, 251-261, 1999,
• Goovaerts P., Kriging and Semivariogram Deconvolution in the Presence of Irregular Geographical Units, Mathematical Geology 40(1), 101-128, 2008
• Deutsch C.V., Correcting for Negative Weights in Ordinary Kriging, Computers & Geosciences Vol.22, No.7, pp. 765-773, 1996

Requirements and dependencies

• Python 3.7.6

• Numpy 1.18.3

• Scipy 1.4.1

• GeoPandas 0.7.0

• Fiona 1.18.13.post1 (Mac OS) / Fiona 1.8 (Linux)

• Rtree 0.9.4 (Mac OS), Rtree >= 0.8 & < 0.9 (Linux)

• Descartes 1.1.0

• Pyproj 2.6.0

• Shapely 1.7.0

• Matplotlib 3.2.1

Package structure

High level overview:

::

• pyinterpolate
  • calculations - distance calculation
  • data_processing - preparation of spatial data and data processing tasks,
  • data visualization - interpolation of smooth surfaces as rasters,
  • kriging - Ordinary Kriging, Simple Kriging, Poisson Kriging: centroid based, area-to-area, area-to-point,
  • misc - compare different kriging techniques,
  • semivariance - calculate semivariance, fit semivariograms and regularize semivariogram,
  • tutorials - tutorials (Basic, Intermediate and Advanced)

Development

• poisson kriging tutorials,
• inverse distance weighting,
• documentation

Known Bugs