Metadata-Version: 2.1
Name: pyquickmaps
Version: 0.1.1
Summary: A slim python library to link (seafloor) maps and sampling data with prediction methods. Needs scipy, numpy, matplotlib, pykrige, osgeo, rasterio.
Home-page: UNKNOWN
Author: Timm Schoening
Author-email: tschoening@geomar.de
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
Classifier: Operating System :: OS Independent
Requires-Dist: gdal (>=3)
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: pykrige
Requires-Dist: rasterio
Requires-Dist: scipy
Requires-Dist: sklearn

Do you have 2D spatial data (aka maps) and sampling data from locations inside these maps? Do you maybe want to extrapolate sampling data (aka measurements) to the full extent of a map? Then you probably need a better toolkit than this but pyquickmaps might help you to achieve a quick'n'dirty result.


