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106 lines
3.2 KiB
Python
106 lines
3.2 KiB
Python
from geopandas import read_file, datasets
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from geopandas.sindex import VALID_QUERY_PREDICATES
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predicates = sorted(VALID_QUERY_PREDICATES, key=lambda x: (x is None, x))
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geom_types = ("mixed", "points", "polygons")
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def generate_test_df():
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world = read_file(datasets.get_path("naturalearth_lowres"))
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capitals = read_file(datasets.get_path("naturalearth_cities"))
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countries = world.to_crs("epsg:3395")[["geometry"]]
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capitals = capitals.to_crs("epsg:3395")[["geometry"]]
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mixed = capitals.append(countries) # get a mix of geometries
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points = capitals
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polygons = countries
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# filter out invalid geometries
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data = {
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"mixed": mixed[mixed.is_valid],
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"points": points[points.is_valid],
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"polygons": polygons[polygons.is_valid],
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}
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# ensure index is pre-generated
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for data_type in data.keys():
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data[data_type].sindex.query(data[data_type].geometry.values.data[0])
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return data
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class BenchIntersection:
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param_names = ["input_geom_type", "tree_geom_type"]
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params = [
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geom_types,
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geom_types,
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]
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def setup(self, *args):
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self.data = generate_test_df()
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# cache bounds so that bound creation is not counted in benchmarks
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self.bounds = {
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data_type: [g.bounds for g in self.data[data_type].geometry]
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for data_type in self.data.keys()
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}
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def time_intersects(self, input_geom_type, tree_geom_type):
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tree = self.data[tree_geom_type].sindex
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for bounds in self.bounds[input_geom_type]:
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tree.intersection(bounds)
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class BenchIndexCreation:
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param_names = ["tree_geom_type"]
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params = [
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geom_types,
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]
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def setup(self, *args):
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self.data = generate_test_df()
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def time_index_creation(self, tree_geom_type):
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"""Time creation of spatial index.
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Note: requires running a single query to ensure that
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lazy-building indexes are actually built.
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"""
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# Note: the GeoDataFram._sindex_generated attribute will
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# be removed by GH#1444 but is kept so that
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# benchmarks can be run comparing pre GH#1444 to
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# post GH#1444
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self.data[tree_geom_type]._sindex_generated = None
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self.data[tree_geom_type].geometry.values._sindex = None
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tree = self.data[tree_geom_type].sindex
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# also do a single query to ensure the index is actually
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# generated and used
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tree.query(
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self.data[tree_geom_type].geometry.values.data[0]
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)
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class BenchQuery:
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param_names = ["predicate", "input_geom_type", "tree_geom_type"]
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params = [
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predicates,
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geom_types,
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geom_types,
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]
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def setup(self, *args):
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self.data = generate_test_df()
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def time_query_bulk(self, predicate, input_geom_type, tree_geom_type):
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self.data[tree_geom_type].sindex.query_bulk(
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self.data[input_geom_type].geometry.values.data,
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predicate=predicate,
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)
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def time_query(self, predicate, input_geom_type, tree_geom_type):
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tree = self.data[tree_geom_type].sindex
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for geom in self.data[input_geom_type].geometry.values.data:
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tree.query(
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geom,
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predicate=predicate
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)
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