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296 lines
15 KiB
296 lines
15 KiB
import os, unittest |
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from decimal import Decimal |
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from django.db.models import Q |
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from django.contrib.gis.gdal import DataSource |
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from django.contrib.gis.geos import GEOSGeometry, Point, LineString |
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from django.contrib.gis.measure import D # alias for Distance |
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from django.contrib.gis.db.models import GeoQ |
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from django.contrib.gis.tests.utils import oracle, postgis, no_oracle |
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from models import AustraliaCity, Interstate, SouthTexasCity, SouthTexasCityFt, CensusZipcode, SouthTexasZipcode |
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from data import au_cities, interstates, stx_cities, stx_zips |
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class DistanceTest(unittest.TestCase): |
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# A point we are testing distances with -- using a WGS84 |
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# coordinate that'll be implicitly transormed to that to |
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# the coordinate system of the field, EPSG:32140 (Texas South Central |
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# w/units in meters) |
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stx_pnt = GEOSGeometry('POINT (-95.370401017314293 29.704867409475465)', 4326) |
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# Another one for Australia |
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au_pnt = GEOSGeometry('POINT (150.791 -34.4919)', 4326) |
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def get_names(self, qs): |
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cities = [c.name for c in qs] |
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cities.sort() |
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return cities |
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def test01_init(self): |
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"Initialization of distance models." |
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# Loading up the cities. |
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def load_cities(city_model, data_tup): |
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for name, x, y in data_tup: |
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c = city_model(name=name, point=Point(x, y, srid=4326)) |
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c.save() |
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load_cities(SouthTexasCity, stx_cities) |
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load_cities(SouthTexasCityFt, stx_cities) |
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load_cities(AustraliaCity, au_cities) |
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self.assertEqual(9, SouthTexasCity.objects.count()) |
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self.assertEqual(9, SouthTexasCityFt.objects.count()) |
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self.assertEqual(11, AustraliaCity.objects.count()) |
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# Loading up the South Texas Zip Codes. |
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for name, wkt in stx_zips: |
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poly = GEOSGeometry(wkt, srid=4269) |
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SouthTexasZipcode(name=name, poly=poly).save() |
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CensusZipcode(name=name, poly=poly).save() |
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self.assertEqual(4, SouthTexasZipcode.objects.count()) |
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self.assertEqual(4, CensusZipcode.objects.count()) |
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# Loading up the Interstates. |
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for name, wkt in interstates: |
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Interstate(name=name, line=GEOSGeometry(wkt, srid=4326)).save() |
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self.assertEqual(1, Interstate.objects.count()) |
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def test02_dwithin(self): |
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"Testing the `dwithin` lookup type." |
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# Distances -- all should be equal (except for the |
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# degree/meter pair in au_cities, that's somewhat |
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# approximate). |
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tx_dists = [(7000, 22965.83), D(km=7), D(mi=4.349)] |
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au_dists = [(0.5, 32000), D(km=32), D(mi=19.884)] |
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# Expected cities for Australia and Texas. |
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tx_cities = ['Downtown Houston', 'Southside Place'] |
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au_cities = ['Mittagong', 'Shellharbour', 'Thirroul', 'Wollongong'] |
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# Performing distance queries on two projected coordinate systems one |
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# with units in meters and the other in units of U.S. survey feet. |
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for dist in tx_dists: |
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if isinstance(dist, tuple): dist1, dist2 = dist |
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else: dist1 = dist2 = dist |
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qs1 = SouthTexasCity.objects.filter(point__dwithin=(self.stx_pnt, dist1)) |
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qs2 = SouthTexasCityFt.objects.filter(point__dwithin=(self.stx_pnt, dist2)) |
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for qs in qs1, qs2: |
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self.assertEqual(tx_cities, self.get_names(qs)) |
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# Now performing the `dwithin` queries on a geodetic coordinate system. |
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for dist in au_dists: |
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if isinstance(dist, D) and not oracle: type_error = True |
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else: type_error = False |
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if isinstance(dist, tuple): |
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if oracle: dist = dist[1] |
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else: dist = dist[0] |
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# Creating the query set. |
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qs = AustraliaCity.objects.order_by('name') |
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if type_error: |
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# A TypeError should be raised on PostGIS when trying to pass |
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# Distance objects into a DWithin query using a geodetic field. |
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self.assertRaises(TypeError, AustraliaCity.objects.filter, point__dwithin=(self.au_pnt, dist)) |
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else: |
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self.assertEqual(au_cities, self.get_names(qs.filter(point__dwithin=(self.au_pnt, dist)))) |
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def test03a_distance_method(self): |
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"Testing the `distance` GeoQuerySet method on projected coordinate systems." |
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# The point for La Grange, TX |
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lagrange = GEOSGeometry('POINT(-96.876369 29.905320)', 4326) |
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# Reference distances in feet and in meters. Got these values from |
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# using the provided raw SQL statements. |
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# SELECT ST_Distance(point, ST_Transform(ST_GeomFromText('POINT(-96.876369 29.905320)', 4326), 32140)) FROM distapp_southtexascity; |
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m_distances = [147075.069813, 139630.198056, 140888.552826, |
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138809.684197, 158309.246259, 212183.594374, |
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70870.188967, 165337.758878, 139196.085105] |
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# SELECT ST_Distance(point, ST_Transform(ST_GeomFromText('POINT(-96.876369 29.905320)', 4326), 2278)) FROM distapp_southtexascityft; |
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ft_distances = [482528.79154625, 458103.408123001, 462231.860397575, |
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455411.438904354, 519386.252102563, 696139.009211594, |
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232513.278304279, 542445.630586414, 456679.155883207] |
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# Testing using different variations of parameters and using models |
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# with different projected coordinate systems. |
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dist1 = SouthTexasCity.objects.distance(lagrange, field_name='point') |
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dist2 = SouthTexasCity.objects.distance(lagrange) # Using GEOSGeometry parameter |
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dist3 = SouthTexasCityFt.objects.distance(lagrange.ewkt) # Using EWKT string parameter. |
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dist4 = SouthTexasCityFt.objects.distance(lagrange) |
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# Original query done on PostGIS, have to adjust AlmostEqual tolerance |
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# for Oracle. |
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if oracle: tol = 2 |
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else: tol = 5 |
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# Ensuring expected distances are returned for each distance queryset. |
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for qs in [dist1, dist2, dist3, dist4]: |
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for i, c in enumerate(qs): |
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self.assertAlmostEqual(m_distances[i], c.distance.m, tol) |
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self.assertAlmostEqual(ft_distances[i], c.distance.survey_ft, tol) |
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def test03b_distance_method(self): |
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"Testing the `distance` GeoQuerySet method on geodetic coordnate systems." |
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if oracle: tol = 2 |
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else: tol = 5 |
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# Now testing geodetic distance aggregation. |
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hillsdale = AustraliaCity.objects.get(name='Hillsdale') |
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if not oracle: |
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# PostGIS is limited to disance queries only to/from point geometries, |
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# ensuring a TypeError is raised if something else is put in. |
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self.assertRaises(TypeError, AustraliaCity.objects.distance, 'LINESTRING(0 0, 1 1)') |
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self.assertRaises(TypeError, AustraliaCity.objects.distance, LineString((0, 0), (1, 1))) |
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# Got the reference distances using the raw SQL statements: |
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# SELECT ST_distance_spheroid(point, ST_GeomFromText('POINT(151.231341 -33.952685)', 4326), 'SPHEROID["WGS 84",6378137.0,298.257223563]') FROM distapp_australiacity WHERE (NOT (id = 11)); |
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spheroid_distances = [60504.0628825298, 77023.948962654, 49154.8867507115, 90847.435881812, 217402.811862568, 709599.234619957, 640011.483583758, 7772.00667666425, 1047861.7859506, 1165126.55237647] |
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# SELECT ST_distance_sphere(point, ST_GeomFromText('POINT(151.231341 -33.952685)', 4326)) FROM distapp_australiacity WHERE (NOT (id = 11)); st_distance_sphere |
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sphere_distances = [60580.7612632291, 77143.7785056615, 49199.2725132184, 90804.4414289463, 217712.63666124, 709131.691061906, 639825.959074112, 7786.80274606706, 1049200.46122281, 1162619.7297006] |
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# Testing with spheroid distances first. |
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qs = AustraliaCity.objects.exclude(id=hillsdale.id).distance(hillsdale.point, spheroid=True) |
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for i, c in enumerate(qs): |
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self.assertAlmostEqual(spheroid_distances[i], c.distance.m, tol) |
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if postgis: |
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# PostGIS uses sphere-only distances by default, testing these as well. |
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qs = AustraliaCity.objects.exclude(id=hillsdale.id).distance(hillsdale.point) |
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for i, c in enumerate(qs): |
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self.assertAlmostEqual(sphere_distances[i], c.distance.m, tol) |
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@no_oracle # Oracle already handles geographic distance calculation. |
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def test03c_distance_method(self): |
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"Testing the `distance` GeoQuerySet method used with `transform` on a geographic field." |
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# Normally you can't compute distances from a geometry field |
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# that is not a PointField (on PostGIS). |
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self.assertRaises(TypeError, CensusZipcode.objects.distance, self.stx_pnt) |
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# We'll be using a Polygon (created by buffering the centroid |
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# of 77005 to 100m) -- which aren't allowed in geographic distance |
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# queries normally, however our field has been transformed to |
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# a non-geographic system. |
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z = SouthTexasZipcode.objects.get(name='77005') |
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# Reference query: |
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# SELECT ST_Distance(ST_Transform("distapp_censuszipcode"."poly", 32140), ST_GeomFromText('<buffer_wkt>', 32140)) FROM "distapp_censuszipcode"; |
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dists_m = [3553.30384972258, 1243.18391525602, 2186.15439472242] |
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# Having our buffer in the SRID of the transformation and of the field |
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# -- should get the same results. The first buffer has no need for |
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# transformation SQL because it is the same SRID as what was given |
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# to `transform()`. The second buffer will need to be transformed, |
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# however. |
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buf1 = z.poly.centroid.buffer(100) |
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buf2 = buf1.transform(4269, clone=True) |
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for buf in [buf1, buf2]: |
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qs = CensusZipcode.objects.exclude(name='77005').transform(32140).distance(buf) |
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self.assertEqual(['77002', '77025', '77401'], self.get_names(qs)) |
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for i, z in enumerate(qs): |
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self.assertAlmostEqual(z.distance.m, dists_m[i], 5) |
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def test04_distance_lookups(self): |
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"Testing the `distance_lt`, `distance_gt`, `distance_lte`, and `distance_gte` lookup types." |
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# Retrieving the cities within a 20km 'donut' w/a 7km radius 'hole' |
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# (thus, Houston and Southside place will be excluded as tested in |
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# the `test02_dwithin` above). |
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qs1 = SouthTexasCity.objects.filter(point__distance_gte=(self.stx_pnt, D(km=7))).filter(point__distance_lte=(self.stx_pnt, D(km=20))) |
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qs2 = SouthTexasCityFt.objects.filter(point__distance_gte=(self.stx_pnt, D(km=7))).filter(point__distance_lte=(self.stx_pnt, D(km=20))) |
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for qs in qs1, qs2: |
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cities = self.get_names(qs) |
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self.assertEqual(cities, ['Bellaire', 'Pearland', 'West University Place']) |
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# Doing a distance query using Polygons instead of a Point. |
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z = SouthTexasZipcode.objects.get(name='77005') |
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qs = SouthTexasZipcode.objects.exclude(name='77005').filter(poly__distance_lte=(z.poly, D(m=275))) |
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self.assertEqual(['77025', '77401'], self.get_names(qs)) |
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# If we add a little more distance 77002 should be included. |
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qs = SouthTexasZipcode.objects.exclude(name='77005').filter(poly__distance_lte=(z.poly, D(m=300))) |
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self.assertEqual(['77002', '77025', '77401'], self.get_names(qs)) |
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def test05_geodetic_distance_lookups(self): |
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"Testing distance lookups on geodetic coordinate systems." |
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if not oracle: |
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# Oracle doesn't have this limitation -- PostGIS only allows geodetic |
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# distance queries from Points to PointFields. |
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mp = GEOSGeometry('MULTIPOINT(0 0, 5 23)') |
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self.assertRaises(TypeError, |
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AustraliaCity.objects.filter(point__distance_lte=(mp, D(km=100)))) |
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# Too many params (4 in this case) should raise a ValueError. |
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self.assertRaises(ValueError, |
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AustraliaCity.objects.filter, point__distance_lte=('POINT(5 23)', D(km=100), 'spheroid', '4')) |
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# Not enough params should raise a ValueError. |
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self.assertRaises(ValueError, |
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AustraliaCity.objects.filter, point__distance_lte=('POINT(5 23)',)) |
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# Getting all cities w/in 550 miles of Hobart. |
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hobart = AustraliaCity.objects.get(name='Hobart') |
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qs = AustraliaCity.objects.exclude(name='Hobart').filter(point__distance_lte=(hobart.point, D(mi=550))) |
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cities = self.get_names(qs) |
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self.assertEqual(cities, ['Batemans Bay', 'Canberra', 'Melbourne']) |
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# Cities that are either really close or really far from Wollongong -- |
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# and using different units of distance. |
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wollongong = AustraliaCity.objects.get(name='Wollongong') |
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d1, d2 = D(yd=19500), D(nm=400) # Yards (~17km) & Nautical miles. |
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# Normal geodetic distance lookup (uses `distance_sphere` on PostGIS. |
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gq1 = GeoQ(point__distance_lte=(wollongong.point, d1)) |
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gq2 = GeoQ(point__distance_gte=(wollongong.point, d2)) |
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qs1 = AustraliaCity.objects.exclude(name='Wollongong').filter(gq1 | gq2) |
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# Geodetic distance lookup but telling GeoDjango to use `distance_spheroid` |
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# instead (we should get the same results b/c accuracy variance won't matter |
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# in this test case). Using `Q` instead of `GeoQ` to be different (post-qsrf |
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# it doesn't matter). |
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if postgis: |
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gq3 = Q(point__distance_lte=(wollongong.point, d1, 'spheroid')) |
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gq4 = Q(point__distance_gte=(wollongong.point, d2, 'spheroid')) |
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qs2 = AustraliaCity.objects.exclude(name='Wollongong').filter(gq3 | gq4) |
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querysets = [qs1, qs2] |
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else: |
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querysets = [qs1] |
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for qs in querysets: |
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cities = self.get_names(qs) |
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self.assertEqual(cities, ['Adelaide', 'Hobart', 'Shellharbour', 'Thirroul']) |
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def test06_area(self): |
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"Testing the `area` GeoQuerySet method." |
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# Reference queries: |
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# SELECT ST_Area(poly) FROM distapp_southtexaszipcode; |
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area_sq_m = [5437908.90234375, 10183031.4389648, 11254471.0073242, 9881708.91772461] |
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# Tolerance has to be lower for Oracle and differences |
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# with GEOS 3.0.0RC4 |
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tol = 2 |
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for i, z in enumerate(SouthTexasZipcode.objects.area()): |
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self.assertAlmostEqual(area_sq_m[i], z.area.sq_m, tol) |
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def test07_length(self): |
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"Testing the `length` GeoQuerySet method." |
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# Reference query (should use `length_spheroid`). |
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# SELECT ST_length_spheroid(ST_GeomFromText('<wkt>', 4326) 'SPHEROID["WGS 84",6378137,298.257223563, AUTHORITY["EPSG","7030"]]'); |
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len_m = 473504.769553813 |
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qs = Interstate.objects.length() |
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if oracle: tol = 2 |
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else: tol = 5 |
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self.assertAlmostEqual(len_m, qs[0].length.m, tol) |
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def test08_perimeter(self): |
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"Testing the `perimeter` GeoQuerySet method." |
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# Reference query: |
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# SELECT ST_Perimeter(distapp_southtexaszipcode.poly) FROM distapp_southtexaszipcode; |
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perim_m = [18404.3550889361, 15627.2108551001, 20632.5588368978, 17094.5996143697] |
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if oracle: tol = 2 |
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else: tol = 7 |
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for i, z in enumerate(SouthTexasZipcode.objects.perimeter()): |
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self.assertAlmostEqual(perim_m[i], z.perimeter.m, tol) |
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# Running on points; should return 0. |
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for i, c in enumerate(SouthTexasCity.objects.perimeter(model_att='perim')): |
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self.assertEqual(0, c.perim.m) |
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def suite(): |
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s = unittest.TestSuite() |
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s.addTest(unittest.makeSuite(DistanceTest)) |
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return s
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