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result_pygeoda_complete_1.txt
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result_pygeoda_complete_1.txt
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Test pyGeoDa local moran with Natregimes using permutation_method=brutal-force
./data/natregimes.shp 999 brutal-force 1: 0.5914509296417236 seconds
./data/natregimes.shp 999 brutal-force 8: 0.08591008186340332 seconds
./data/natregimes.shp 999 brutal-force 16: 0.05975604057312012 seconds
./data/natregimes.shp 9999 brutal-force 1: 6.03707218170166 seconds
./data/natregimes.shp 9999 brutal-force 8: 0.8514440059661865 seconds
./data/natregimes.shp 9999 brutal-force 16: 0.5646729469299316 seconds
./data/natregimes.shp 99999 brutal-force 1: 58.92710328102112 seconds
./data/natregimes.shp 99999 brutal-force 8: 8.485954999923706 seconds
./data/natregimes.shp 99999 brutal-force 16: 5.570709943771362 seconds
Test pyGeoDa local moran with SDOH using permutation_method=brutal-force
./data/us-sdoh-2014.shp 999 brutal-force 1: 17.454599857330322 seconds
./data/us-sdoh-2014.shp 999 brutal-force 8: 2.4892380237579346 seconds
./data/us-sdoh-2014.shp 999 brutal-force 16: 1.6712172031402588 seconds
./data/us-sdoh-2014.shp 9999 brutal-force 1: 175.07298302650452 seconds
./data/us-sdoh-2014.shp 9999 brutal-force 8: 25.021250009536743 seconds
./data/us-sdoh-2014.shp 9999 brutal-force 16: 16.907100200653076 seconds
./data/us-sdoh-2014.shp 99999 brutal-force 1: 1727.7120940685272 seconds
./data/us-sdoh-2014.shp 99999 brutal-force 8: 248.83428502082825 seconds
./data/us-sdoh-2014.shp 99999 brutal-force 16: 166.1402678489685 seconds
Test pyGeoDa local moran with NYC using permutation_method=brutal-force
./data/NYC_Area2010_2data.shp 999 brutal-force 1: 28.46846580505371 seconds
./data/NYC_Area2010_2data.shp 999 brutal-force 8: 4.277080059051514 seconds
./data/NYC_Area2010_2data.shp 999 brutal-force 16: 2.896711826324463 seconds
./data/NYC_Area2010_2data.shp 9999 brutal-force 1: 282.76479601860046 seconds
./data/NYC_Area2010_2data.shp 9999 brutal-force 8: 42.7974419593811 seconds
./data/NYC_Area2010_2data.shp 9999 brutal-force 16: 28.276558876037598 seconds
./data/NYC_Area2010_2data.shp 99999 brutal-force 1: 2821.240134000778 seconds
./data/NYC_Area2010_2data.shp 99999 brutal-force 8: 422.4912781715393 seconds
./data/NYC_Area2010_2data.shp 99999 brutal-force 16: 283.2045419216156 seconds
Test pyGeoDa local moran with Chicago_Parcels using permutation_method=brutal-force
./data/Chicago_parcels_points.shp 999 brutal-force 1: 389.7134437561035 seconds
./data/Chicago_parcels_points.shp 999 brutal-force 8: 57.798383951187134 seconds
./data/Chicago_parcels_points.shp 999 brutal-force 16: 43.7291738986969 seconds
./data/Chicago_parcels_points.shp 9999 brutal-force 1: 3842.998600959778 seconds
./data/Chicago_parcels_points.shp 9999 brutal-force 8: 556.979868888855 seconds
./data/Chicago_parcels_points.shp 9999 brutal-force 16: 436.6491787433624 seconds
./data/Chicago_parcels_points.shp 99999 brutal-force 1: 53586.285209178925 seconds
./data/Chicago_parcels_points.shp 99999 brutal-force 8: 1964.156000137329 seconds
./data/Chicago_parcels_points.shp 99999 brutal-force 16: 1349.4739561080933 seconds
Test pyGeoDa local moran with Chicago_Parcels using permutation_method=brutal-force (knn=10 no duplicates)
./data/Chicago_parcels_points.shp 99999 brutal-force 1: 13525.546596050262 seconds
./data/Chicago_parcels_points.shp 99999 brutal-force 8: 1605.97736287117 seconds
./data/Chicago_parcels_points.shp 99999 brutal-force 16: 1161.3201611042023 seconds
./data/Chicago_parcels_points.shp 999 brutal-force 1: 119.42543983459473 seconds
./data/Chicago_parcels_points.shp 999 brutal-force 8: 16.434907913208008 seconds
./data/Chicago_parcels_points.shp 999 brutal-force 16: 12.032907962799072 seconds
./data/Chicago_parcels_points.shp 9999 brutal-force 1: 1222.1919560432434 seconds
./data/Chicago_parcels_points.shp 9999 brutal-force 8: 162.7958836555481 seconds
./data/Chicago_parcels_points.shp 9999 brutal-force 16: 120.59185600280762 seconds