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.
version 0.2.3
- more parameters to store (and access) in TheoreticalSemivariogram class,
- error weighting against the linear regression model (ax + b),
- global mean for Simple Kriging as a required parameter,
- tqdm progress bar to RegularizedSemivariogram.transform() and interpolate_raster() functions,
- refactored Semivariogram Regularization: ranges are controlled by algorithm, not an user,
- added pull request template,
- added issues templates,
- bug in spherical semivariogram model,
- experimental variogram as points (not a solid line),
- inverse distance weighting function: algorithm, tests, documentation and new tutorial,
- changed output names of regularized data (ArealKriging.regularize_data) from estimated value to reg.est and from estimated prediction error to reg.err,
- error related to the id column as a string removed,
- TheoreticalSemivariogram params attribute changed to nugget, sill and range attributes.
version 0.2.2.post2
- directional semivariograms methods, docs and tests added,
- check if points are within elliptical area around point of interest method, docs and tests added,
- broken dependency in README.md corrected.
version 0.2.2.post1
- variogram point cloud methods, tutorials, docs and tests added,
- updated tutorials and baseline datasets to show examples with spatial correlation,
- updated README.md: contribution, example, sample image,
- data is tested against duplicates (points with the same coordinates),
- removed bug in interpolate_raster() method.