fastpynuts.experimental
The submodule fastpynuts.experimental contains NUTSfinderBenchmark, a class which is intended for
experimental purposes.
Module Contents
Classes
Implements various experimental methods to find corresponding NUTS regions for benchmark purposes. |
API
- class fastpynuts.experimental.NUTSfinderBenchmark(geojsonfile, buffer_geoms=0, min_level=0, max_level=3)
Bases:
fastpynuts.fastpynuts.NUTSfinderImplements various experimental methods to find corresponding NUTS regions for benchmark purposes.
Following methods are available:
tree: Exploits the hierarchical structure of the NUTS regions. First checks the coordinates against the NUTS level 0 regions. Then, the children regions of level 1 are checked, etc. At each level, region candidates are determined by a fast R-tree test, followed by a point-in-polygon check of the candidates.
rtree: A single R-tree is constructed for all regions, independent of level. Region candidates are then determined by the R-tree’s
intersect()method, followed by a point-in-polygon check of the candidates.bbox: Sequentially performs a point-in-bbox test of all regions, followed by a point-in-polygon check of the candidates.
poly: Sequentially performs a point-in-polygon test of all regions.
Initialization
- find(lon, lat, method='tree', valid_point=False, verbose=False, **kwargs)
Find a point’s NUTS regions by longitude and latitude. For large-scale applications, if it is known, that the point corresponds to a valid location within the NUTS regions, use
valid_point = Truefor a speedup.
- classmethod from_web(scale=1, year=2021, epsg=4326, datadir='.data', **kwargs)
- find_level(lon, lat, level, valid_point=False)