Metadata-Version: 2.1
Name: pyinterpolate
Version: 0.2.1
Summary: Spatial interpolation Python module
Home-page: https://github.com/szymon-datalions/pyinterpolate
Author: Szymon Moliński
Author-email: simon@ml-gis-service.com
License: UNKNOWN
Download-URL: https://github.com/szymon-datalions/pyinterpolate/archive/v0.2.tar.gz
Project-URL: Webpage, https://pyinterpolate.com
Project-URL: Bug Reports, https://github.com/szymon-datalions/pyinterpolate/issues
Project-URL: Sponsor page, https://datalions.eu/
Project-URL: Source, https://github.com/szymon-datalions/pyinterpolate/
Description: ![License](https://img.shields.io/github/license/szymon-datalions/pyinterpolate) ![Build Status](https://travis-ci.com/szymon-datalions/pyinterpolate.svg?branch=master) ![Documentation Status](https://readthedocs.org/projects/pyinterpolate/badge/?version=latest) [![CodeFactor](https://www.codefactor.io/repository/github/szymon-datalions/pyinterpolate/badge)](https://www.codefactor.io/repository/github/szymon-datalions/pyinterpolate)
        
        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. This package helps you **interpolate spatial data** with *Kriging* technique. In the close future you'll use more spatial interpolation tools.
        
        If you’re:
        
        - GIS expert,
        - geologist,
        - mining engineer,
        - ecologist,
        - public health specialist,
        - data scientist.
        
        Then this package may be useful for you. You could use it for:
        
        - spatial interpolation and spatial prediction,
        - alone or with machine learning libraries,
        - for point and areal datasets.
        
        Pyinterpolate allows you to perform:
        
        1. Ordinary Kriging and Simple Kriging (spatial interpolation from points),
        2. Centroid-based Kriging of Polygons (spatial interpolation from blocks and areas),
        3. Area-to-area and Area-to-point Poisson Kriging of Polygons (spatial interpolation and data deconvolution from areas to points).
        
        
        Status
        ------
        
        Beta version: package is tested and the main structure is preserved but future changes are very likely to occur.
        
        
        Setup
        -----
        
        Setup by pip: pip install pyinterpolate / **Python 3.7** is required!
        
        Manual setup is described in the file SETUP.md: https://github.com/szymon-datalions/pyinterpolate/blob/master/SETUP.md We pointed there most common problems related to third-party packages.
        
        
        
        Commercial and scientific projects where library has been used
        --------------------------------------------------------------
        
        * Tick-Borne Disease Detector (Data Lions company) for the European Space Agency (2019-2020).
        * B2C project related to the prediction of demand for specific flu medications,
        * B2G project related to the large-scale infrastructure maintenance.
        
        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
            - [x] **distance** - distance calculation
            - [x] **io** - reads and prepares input spatial datasets,
            - [x] **transform** - transforms spatial datasets,
            - [x] **viz** - interpolation of smooth surfaces from points into rasters,
            - [x] **kriging** - Ordinary Kriging, Simple Kriging, Poisson Kriging: centroid based, area-to-area, area-to-point,
            - [x] **misc** - compare different kriging techniques,
            - [x] **semivariance** - calculate semivariance, fit semivariograms and regularize semivariogram,
            - [x] **tutorials** - tutorials (Basic, Intermediate and Advanced)
        
        Functions documentation
        -----------------------
        
        Pyinterpolate https://pyinterpolate.readthedocs.io/en/latest/
        
        
        Development
        ===========
        
        - inverse distance weighting,
        - semivariogram analysis and visualization methods,
        - see Projects page of this repository!
        
        
        Known Bugs
        ==========
        
        - (still) not detected!
        
Keywords: Spatial interpolation,Kriging,Area Kriging,Block Kriging,Poisson Kriging,Geostatistics
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: GIS
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
