<reponame>huicheese/Django-test3<filename>django/contrib/gis/tests/distapp/tests.py<gh_stars>0
import os, unittest
from decimal import Decimal

from django.db.models import Q
from django.contrib.gis.gdal import DataSource
from django.contrib.gis.geos import GEOSGeometry, Point, LineString
from django.contrib.gis.measure import D # alias for Distance
from django.contrib.gis.tests.utils import oracle, postgis, spatialite, no_oracle, no_spatialite

from models import AustraliaCity, Interstate, SouthTexasInterstate, \
    SouthTexasCity, SouthTexasCityFt, CensusZipcode, SouthTexasZipcode
from data import au_cities, interstates, stx_interstates, stx_cities, stx_zips

class DistanceTest(unittest.TestCase):

    # A point we are testing distances with -- using a WGS84
    # coordinate that'll be implicitly transormed to that to
    # the coordinate system of the field, EPSG:32140 (Texas South Central
    # w/units in meters)
    stx_pnt = GEOSGeometry('POINT (-95.370401017314293 29.704867409475465)', 4326)
    # Another one for Australia
    au_pnt = GEOSGeometry('POINT (150.791 -34.4919)', 4326)

    def get_names(self, qs):
        cities = [c.name for c in qs]
        cities.sort()
        return cities

    def test01_init(self):
        "Initialization of distance models."

        # Loading up the cities.
        def load_cities(city_model, data_tup):
            for name, x, y in data_tup:
                city_model(name=name, point=Point(x, y, srid=4326)).save()

        def load_interstates(imodel, data_tup):
            for name, wkt in data_tup:
                imodel(name=name, path=wkt).save()

        load_cities(SouthTexasCity, stx_cities)
        load_cities(SouthTexasCityFt, stx_cities)
        load_cities(AustraliaCity, au_cities)

        self.assertEqual(9, SouthTexasCity.objects.count())
        self.assertEqual(9, SouthTexasCityFt.objects.count())
        self.assertEqual(11, AustraliaCity.objects.count())

        # Loading up the South Texas Zip Codes.
        for name, wkt in stx_zips:
            poly = GEOSGeometry(wkt, srid=4269)
            SouthTexasZipcode(name=name, poly=poly).save()
            CensusZipcode(name=name, poly=poly).save()
        self.assertEqual(4, SouthTexasZipcode.objects.count())
        self.assertEqual(4, CensusZipcode.objects.count())

        # Loading up the Interstates.
        load_interstates(Interstate, interstates)
        load_interstates(SouthTexasInterstate, stx_interstates)

        self.assertEqual(1, Interstate.objects.count())
        self.assertEqual(1, SouthTexasInterstate.objects.count())

    @no_spatialite
    def test02_dwithin(self):
        "Testing the `dwithin` lookup type."
        # Distances -- all should be equal (except for the
        # degree/meter pair in au_cities, that's somewhat
        # approximate).
        tx_dists = [(7000, 22965.83), D(km=7), D(mi=4.349)]
        au_dists = [(0.5, 32000), D(km=32), D(mi=19.884)]

        # Expected cities for Australia and Texas.
        tx_cities = ['Downtown Houston', 'Southside Place']
        au_cities = ['Mittagong', 'Shellharbour', 'Thirroul', 'Wollongong']

        # Performing distance queries on two projected coordinate systems one
        # with units in meters and the other in units of U.S. survey feet.
        for dist in tx_dists:
            if isinstance(dist, tuple): dist1, dist2 = dist
            else: dist1 = dist2 = dist
            qs1 = SouthTexasCity.objects.filter(point__dwithin=(self.stx_pnt, dist1))
            qs2 = SouthTexasCityFt.objects.filter(point__dwithin=(self.stx_pnt, dist2))
            for qs in qs1, qs2:
                self.assertEqual(tx_cities, self.get_names(qs))

        # Now performing the `dwithin` queries on a geodetic coordinate system.
        for dist in au_dists:
            if isinstance(dist, D) and not oracle: type_error = True
            else: type_error = False

            if isinstance(dist, tuple):
                if oracle: dist = dist[1]
                else: dist = dist[0]

            # Creating the query set.
            qs = AustraliaCity.objects.order_by('name')
            if type_error:
                # A TypeError should be raised on PostGIS when trying to pass
                # Distance objects into a DWithin query using a geodetic field.
                self.assertRaises(TypeError, AustraliaCity.objects.filter, point__dwithin=(self.au_pnt, dist))
            else:
                self.assertEqual(au_cities, self.get_names(qs.filter(point__dwithin=(self.au_pnt, dist))))

    def test03a_distance_method(self):
        "Testing the `distance` GeoQuerySet method on projected coordinate systems."
        # The point for La Grange, TX
        lagrange = GEOSGeometry('POINT(-96.876369 29.905320)', 4326)
        # Reference distances in feet and in meters. Got these values from
        # using the provided raw SQL statements.
        #  SELECT ST_Distance(point, ST_Transform(ST_GeomFromText('POINT(-96.876369 29.905320)', 4326), 32140)) FROM distapp_southtexascity;
        m_distances = [147075.069813, 139630.198056, 140888.552826,
                       138809.684197, 158309.246259, 212183.594374,
                       70870.188967, 165337.758878, 139196.085105]
        #  SELECT ST_Distance(point, ST_Transform(ST_GeomFromText('POINT(-96.876369 29.905320)', 4326), 2278)) FROM distapp_southtexascityft;
        # Oracle 11 thinks this is not a projected coordinate system, so it's s
        # not tested.
        ft_distances = [482528.79154625, 458103.408123001, 462231.860397575,
                        455411.438904354, 519386.252102563, 696139.009211594,
                        232513.278304279, 542445.630586414, 456679.155883207]

        # Testing using different variations of parameters and using models
        # with different projected coordinate systems.
        dist1 = SouthTexasCity.objects.distance(lagrange, field_name='point')
        dist2 = SouthTexasCity.objects.distance(lagrange)  # Using GEOSGeometry parameter
        if spatialite or oracle:
            dist_qs = [dist1, dist2]
        else:
            dist3 = SouthTexasCityFt.objects.distance(lagrange.ewkt) # Using EWKT string parameter.
            dist4 = SouthTexasCityFt.objects.distance(lagrange)
            dist_qs = [dist1, dist2, dist3, dist4]

        # Original query done on PostGIS, have to adjust AlmostEqual tolerance
        # for Oracle.
        if oracle: tol = 2
        else: tol = 5

        # Ensuring expected distances are returned for each distance queryset.
        for qs in dist_qs:
            for i, c in enumerate(qs):
                self.assertAlmostEqual(m_distances[i], c.distance.m, tol)
                self.assertAlmostEqual(ft_distances[i], c.distance.survey_ft, tol)

    @no_spatialite
    def test03b_distance_method(self):
        "Testing the `distance` GeoQuerySet method on geodetic coordnate systems."
        if oracle: tol = 2
        else: tol = 5

        # Now testing geodetic distance aggregation.
        hillsdale = AustraliaCity.objects.get(name='Hillsdale')
        if not oracle:
            # PostGIS is limited to disance queries only to/from point geometries,
            # ensuring a TypeError is raised if something else is put in.
            self.assertRaises(ValueError, AustraliaCity.objects.distance, 'LINESTRING(0 0, 1 1)')
            self.assertRaises(ValueError, AustraliaCity.objects.distance, LineString((0, 0), (1, 1)))

        # Got the reference distances using the raw SQL statements:
        #  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));
        spheroid_distances = [60504.0628825298, 77023.948962654, 49154.8867507115, 90847.435881812, 217402.811862568, 709599.234619957, 640011.483583758, 7772.00667666425, 1047861.7859506, 1165126.55237647]
        #  SELECT ST_distance_sphere(point, ST_GeomFromText('POINT(151.231341 -33.952685)', 4326)) FROM distapp_australiacity WHERE (NOT (id = 11));  st_distance_sphere
        sphere_distances = [60580.7612632291, 77143.7785056615, 49199.2725132184, 90804.4414289463, 217712.63666124, 709131.691061906, 639825.959074112, 7786.80274606706, 1049200.46122281, 1162619.7297006]

        # Testing with spheroid distances first.
        qs = AustraliaCity.objects.exclude(id=hillsdale.id).distance(hillsdale.point, spheroid=True)
        for i, c in enumerate(qs):
            self.assertAlmostEqual(spheroid_distances[i], c.distance.m, tol)
        if postgis:
            # PostGIS uses sphere-only distances by default, testing these as well.
            qs =  AustraliaCity.objects.exclude(id=hillsdale.id).distance(hillsdale.point)
            for i, c in enumerate(qs):
                self.assertAlmostEqual(sphere_distances[i], c.distance.m, tol)

    @no_oracle # Oracle already handles geographic distance calculation.
    def test03c_distance_method(self):
        "Testing the `distance` GeoQuerySet method used with `transform` on a geographic field."
        # Normally you can't compute distances from a geometry field
        # that is not a PointField (on PostGIS).
        self.assertRaises(ValueError, CensusZipcode.objects.distance, self.stx_pnt)

        # We'll be using a Polygon (created by buffering the centroid
        # of 77005 to 100m) -- which aren't allowed in geographic distance
        # queries normally, however our field has been transformed to
        # a non-geographic system.
        z = SouthTexasZipcode.objects.get(name='77005')

        # Reference query:
        # SELECT ST_Distance(ST_Transform("distapp_censuszipcode"."poly", 32140), ST_GeomFromText('<buffer_wkt>', 32140)) FROM "distapp_censuszipcode";
        dists_m = [3553.30384972258, 1243.18391525602, 2186.15439472242]

        # Having our buffer in the SRID of the transformation and of the field
        # -- should get the same results. The first buffer has no need for
        # transformation SQL because it is the same SRID as what was given
        # to `transform()`.  The second buffer will need to be transformed,
        # however.
        buf1 = z.poly.centroid.buffer(100)
        buf2 = buf1.transform(4269, clone=True)
        ref_zips = ['77002', '77025', '77401']

        for buf in [buf1, buf2]:
            qs = CensusZipcode.objects.exclude(name='77005').transform(32140).distance(buf)
            self.assertEqual(ref_zips, self.get_names(qs))
            for i, z in enumerate(qs):
                self.assertAlmostEqual(z.distance.m, dists_m[i], 5)

    def test04_distance_lookups(self):
        "Testing the `distance_lt`, `distance_gt`, `distance_lte`, and `distance_gte` lookup types."
        # Retrieving the cities within a 20km 'donut' w/a 7km radius 'hole'
        # (thus, Houston and Southside place will be excluded as tested in
        # the `test02_dwithin` above).
        qs1 = SouthTexasCity.objects.filter(point__distance_gte=(self.stx_pnt, D(km=7))).filter(point__distance_lte=(self.stx_pnt, D(km=20)))

        # Can't determine the units on SpatiaLite from PROJ.4 string, and
        # Oracle 11 incorrectly thinks it is not projected.
        if spatialite or oracle:
            dist_qs = (qs1,)
        else:
            qs2 = SouthTexasCityFt.objects.filter(point__distance_gte=(self.stx_pnt, D(km=7))).filter(point__distance_lte=(self.stx_pnt, D(km=20)))
            dist_qs = (qs1, qs2)

        for qs in dist_qs:
            cities = self.get_names(qs)
            self.assertEqual(cities, ['Bellaire', 'Pearland', 'West University Place'])

        # Doing a distance query using Polygons instead of a Point.
        z = SouthTexasZipcode.objects.get(name='77005')
        qs = SouthTexasZipcode.objects.exclude(name='77005').filter(poly__distance_lte=(z.poly, D(m=275)))
        self.assertEqual(['77025', '77401'], self.get_names(qs))
        # If we add a little more distance 77002 should be included.
        qs = SouthTexasZipcode.objects.exclude(name='77005').filter(poly__distance_lte=(z.poly, D(m=300)))
        self.assertEqual(['77002', '77025', '77401'], self.get_names(qs))

    @no_spatialite
    def test05_geodetic_distance_lookups(self):
        "Testing distance lookups on geodetic coordinate systems."
        if not oracle:
            # Oracle doesn't have this limitation -- PostGIS only allows geodetic
            # distance queries from Points to PointFields.
            mp = GEOSGeometry('MULTIPOINT(0 0, 5 23)')
            self.assertRaises(TypeError,
                              AustraliaCity.objects.filter(point__distance_lte=(mp, D(km=100))))
            # Too many params (4 in this case) should raise a ValueError.
            self.assertRaises(ValueError,
                              AustraliaCity.objects.filter, point__distance_lte=('POINT(5 23)', D(km=100), 'spheroid', '4'))

        # Not enough params should raise a ValueError.
        self.assertRaises(ValueError,
                          AustraliaCity.objects.filter, point__distance_lte=('POINT(5 23)',))

        # Getting all cities w/in 550 miles of Hobart.
        hobart = AustraliaCity.objects.get(name='Hobart')
        qs = AustraliaCity.objects.exclude(name='Hobart').filter(point__distance_lte=(hobart.point, D(mi=550)))
        cities = self.get_names(qs)
        self.assertEqual(cities, ['Batemans Bay', 'Canberra', 'Melbourne'])

        # Cities that are either really close or really far from Wollongong --
        # and using different units of distance.
        wollongong = AustraliaCity.objects.get(name='Wollongong')
        d1, d2 = D(yd=19500), D(nm=400) # Yards (~17km) & Nautical miles.

        # Normal geodetic distance lookup (uses `distance_sphere` on PostGIS.
        gq1 = Q(point__distance_lte=(wollongong.point, d1))
        gq2 = Q(point__distance_gte=(wollongong.point, d2))
        qs1 = AustraliaCity.objects.exclude(name='Wollongong').filter(gq1 | gq2)

        # Geodetic distance lookup but telling GeoDjango to use `distance_spheroid`
        # instead (we should get the same results b/c accuracy variance won't matter
        # in this test case).
        if postgis:
            gq3 = Q(point__distance_lte=(wollongong.point, d1, 'spheroid'))
            gq4 = Q(point__distance_gte=(wollongong.point, d2, 'spheroid'))
            qs2 = AustraliaCity.objects.exclude(name='Wollongong').filter(gq3 | gq4)
            querysets = [qs1, qs2]
        else:
            querysets = [qs1]

        for qs in querysets:
            cities = self.get_names(qs)
            self.assertEqual(cities, ['Adelaide', 'Hobart', 'Shellharbour', 'Thirroul'])

    def test06_area(self):
        "Testing the `area` GeoQuerySet method."
        # Reference queries:
        # SELECT ST_Area(poly) FROM distapp_southtexaszipcode;
        area_sq_m = [5437908.90234375, 10183031.4389648, 11254471.0073242, 9881708.91772461]
        # Tolerance has to be lower for Oracle and differences
        # with GEOS 3.0.0RC4
        tol = 2
        for i, z in enumerate(SouthTexasZipcode.objects.area()):
            self.assertAlmostEqual(area_sq_m[i], z.area.sq_m, tol)

    def test07_length(self):
        "Testing the `length` GeoQuerySet method."
        # Reference query (should use `length_spheroid`).
        # SELECT ST_length_spheroid(ST_GeomFromText('<wkt>', 4326) 'SPHEROID["WGS 84",6378137,298.257223563, AUTHORITY["EPSG","7030"]]');
        len_m1 = 473504.769553813
        len_m2 = 4617.668

        if spatialite:
            # Does not support geodetic coordinate systems.
            self.assertRaises(ValueError, Interstate.objects.length)
        else:
            qs = Interstate.objects.length()
            if oracle: tol = 2
            else: tol = 5
            self.assertAlmostEqual(len_m1, qs[0].length.m, tol)

        # Now doing length on a projected coordinate system.
        i10 = SouthTexasInterstate.objects.length().get(name='I-10')
        self.assertAlmostEqual(len_m2, i10.length.m, 2)

    @no_spatialite
    def test08_perimeter(self):
        "Testing the `perimeter` GeoQuerySet method."
        # Reference query:
        # SELECT ST_Perimeter(distapp_southtexaszipcode.poly) FROM distapp_southtexaszipcode;
        perim_m = [18404.3550889361, 15627.2108551001, 20632.5588368978, 17094.5996143697]
        if oracle: tol = 2
        else: tol = 7
        for i, z in enumerate(SouthTexasZipcode.objects.perimeter()):
            self.assertAlmostEqual(perim_m[i], z.perimeter.m, tol)

        # Running on points; should return 0.
        for i, c in enumerate(SouthTexasCity.objects.perimeter(model_att='perim')):
            self.assertEqual(0, c.perim.m)

    def test09_measurement_null_fields(self):
        "Testing the measurement GeoQuerySet methods on fields with NULL values."
        # Creating SouthTexasZipcode w/NULL value.
        SouthTexasZipcode.objects.create(name='78212')
        # Performing distance/area queries against the NULL PolygonField,
        # and ensuring the result of the operations is None.
        htown = SouthTexasCity.objects.get(name='Downtown Houston')
        z = SouthTexasZipcode.objects.distance(htown.point).area().get(name='78212')
        self.assertEqual(None, z.distance)
        self.assertEqual(None, z.area)

def suite():
    s = unittest.TestSuite()
    s.addTest(unittest.makeSuite(DistanceTest))
    return s

import os, unittest
from decimal import Decimal

from django.db.models import Q
from django.contrib.gis.gdal import DataSource
from django.contrib.gis.geos import GEOSGeometry, Point, LineString
from django.contrib.gis.measure import D # alias for Distance
from django.contrib.gis.tests.utils import oracle, postgis, spatialite, no_oracle, no_spatialite

from models import AustraliaCity, Interstate, SouthTexasInterstate, \
    SouthTexasCity, SouthTexasCityFt, CensusZipcode, SouthTexasZipcode
from data import au_cities, interstates, stx_interstates, stx_cities, stx_zips

class DistanceTest(unittest.TestCase):

    # A point we are testing distances with -- using a WGS84
    # coordinate that'll be implicitly transormed to that to
    # the coordinate system of the field, EPSG:32140 (Texas South Central
    # w/units in meters)
    stx_pnt = GEOSGeometry('POINT (-95.370401017314293 29.704867409475465)', 4326)
    # Another one for Australia
    au_pnt = GEOSGeometry('POINT (150.791 -34.4919)', 4326)

    def get_names(self, qs):
        cities = [c.name for c in qs]
        cities.sort()
        return cities

    def test01_init(self):
        "Initialization of distance models."

        # Loading up the cities.
        def load_cities(city_model, data_tup):
            for name, x, y in data_tup:
                city_model(name=name, point=Point(x, y, srid=4326)).save()

        def load_interstates(imodel, data_tup):
            for name, wkt in data_tup:
                imodel(name=name, path=wkt).save()

        load_cities(SouthTexasCity, stx_cities)
        load_cities(SouthTexasCityFt, stx_cities)
        load_cities(AustraliaCity, au_cities)

        self.assertEqual(9, SouthTexasCity.objects.count())
        self.assertEqual(9, SouthTexasCityFt.objects.count())
        self.assertEqual(11, AustraliaCity.objects.count())

        # Loading up the South Texas Zip Codes.
        for name, wkt in stx_zips:
            poly = GEOSGeometry(wkt, srid=4269)
            SouthTexasZipcode(name=name, poly=poly).save()
            CensusZipcode(name=name, poly=poly).save()
        self.assertEqual(4, SouthTexasZipcode.objects.count())
        self.assertEqual(4, CensusZipcode.objects.count())

        # Loading up the Interstates.
        load_interstates(Interstate, interstates)
        load_interstates(SouthTexasInterstate, stx_interstates)

        self.assertEqual(1, Interstate.objects.count())
        self.assertEqual(1, SouthTexasInterstate.objects.count())

    @no_spatialite
    def test02_dwithin(self):
        "Testing the `dwithin` lookup type."
        # Distances -- all should be equal (except for the
        # degree/meter pair in au_cities, that's somewhat
        # approximate).
        tx_dists = [(7000, 22965.83), D(km=7), D(mi=4.349)]
        au_dists = [(0.5, 32000), D(km=32), D(mi=19.884)]

        # Expected cities for Australia and Texas.
        tx_cities = ['Downtown Houston', 'Southside Place']
        au_cities = ['Mittagong', 'Shellharbour', 'Thirroul', 'Wollongong']

        # Performing distance queries on two projected coordinate systems one
        # with units in meters and the other in units of U.S. survey feet.
        for dist in tx_dists:
            if isinstance(dist, tuple): dist1, dist2 = dist
            else: dist1 = dist2 = dist
            qs1 = SouthTexasCity.objects.filter(point__dwithin=(self.stx_pnt, dist1))
            qs2 = SouthTexasCityFt.objects.filter(point__dwithin=(self.stx_pnt, dist2))
            for qs in qs1, qs2:
                self.assertEqual(tx_cities, self.get_names(qs))

        # Now performing the `dwithin` queries on a geodetic coordinate system.
        for dist in au_dists:
            if isinstance(dist, D) and not oracle: type_error = True
            else: type_error = False

            if isinstance(dist, tuple):
                if oracle: dist = dist[1]
                else: dist = dist[0]

            # Creating the query set.
            qs = AustraliaCity.objects.order_by('name')
            if type_error:
                # A TypeError should be raised on PostGIS when trying to pass
                # Distance objects into a DWithin query using a geodetic field.
                self.assertRaises(TypeError, AustraliaCity.objects.filter, point__dwithin=(self.au_pnt, dist))
            else:
                self.assertEqual(au_cities, self.get_names(qs.filter(point__dwithin=(self.au_pnt, dist))))

    def test03a_distance_method(self):
        "Testing the `distance` GeoQuerySet method on projected coordinate systems."
        # The point for La Grange, TX
        lagrange = GEOSGeometry('POINT(-96.876369 29.905320)', 4326)
        # Reference distances in feet and in meters. Got these values from
        # using the provided raw SQL statements.
        #  SELECT ST_Distance(point, ST_Transform(ST_GeomFromText('POINT(-96.876369 29.905320)', 4326), 32140)) FROM distapp_southtexascity;
        m_distances = [147075.069813, 139630.198056, 140888.552826,
                       138809.684197, 158309.246259, 212183.594374,
                       70870.188967, 165337.758878, 139196.085105]
        #  SELECT ST_Distance(point, ST_Transform(ST_GeomFromText('POINT(-96.876369 29.905320)', 4326), 2278)) FROM distapp_southtexascityft;
        # Oracle 11 thinks this is not a projected coordinate system, so it's s
        # not tested.
        ft_distances = [482528.79154625, 458103.408123001, 462231.860397575,
                        455411.438904354, 519386.252102563, 696139.009211594,
                        232513.278304279, 542445.630586414, 456679.155883207]

        # Testing using different variations of parameters and using models
        # with different projected coordinate systems.
        dist1 = SouthTexasCity.objects.distance(lagrange, field_name='point')
        dist2 = SouthTexasCity.objects.distance(lagrange)  # Using GEOSGeometry parameter
        if spatialite or oracle:
            dist_qs = [dist1, dist2]
        else:
            dist3 = SouthTexasCityFt.objects.distance(lagrange.ewkt) # Using EWKT string parameter.
            dist4 = SouthTexasCityFt.objects.distance(lagrange)
            dist_qs = [dist1, dist2, dist3, dist4]

        # Original query done on PostGIS, have to adjust AlmostEqual tolerance
        # for Oracle.
        if oracle: tol = 2
        else: tol = 5

        # Ensuring expected distances are returned for each distance queryset.
        for qs in dist_qs:
            for i, c in enumerate(qs):
                self.assertAlmostEqual(m_distances[i], c.distance.m, tol)
                self.assertAlmostEqual(ft_distances[i], c.distance.survey_ft, tol)

    @no_spatialite
    def test03b_distance_method(self):
        "Testing the `distance` GeoQuerySet method on geodetic coordnate systems."
        if oracle: tol = 2
        else: tol = 5

        # Now testing geodetic distance aggregation.
        hillsdale = AustraliaCity.objects.get(name='Hillsdale')
        if not oracle:
            # PostGIS is limited to disance queries only to/from point geometries,
            # ensuring a TypeError is raised if something else is put in.
            self.assertRaises(ValueError, AustraliaCity.objects.distance, 'LINESTRING(0 0, 1 1)')
            self.assertRaises(ValueError, AustraliaCity.objects.distance, LineString((0, 0), (1, 1)))

        # Got the reference distances using the raw SQL statements:
        #  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));
        spheroid_distances = [60504.0628825298, 77023.948962654, 49154.8867507115, 90847.435881812, 217402.811862568, 709599.234619957, 640011.483583758, 7772.00667666425, 1047861.7859506, 1165126.55237647]
        #  SELECT ST_distance_sphere(point, ST_GeomFromText('POINT(151.231341 -33.952685)', 4326)) FROM distapp_australiacity WHERE (NOT (id = 11));  st_distance_sphere
        sphere_distances = [60580.7612632291, 77143.7785056615, 49199.2725132184, 90804.4414289463, 217712.63666124, 709131.691061906, 639825.959074112, 7786.80274606706, 1049200.46122281, 1162619.7297006]

        # Testing with spheroid distances first.
        qs = AustraliaCity.objects.exclude(id=hillsdale.id).distance(hillsdale.point, spheroid=True)
        for i, c in enumerate(qs):
            self.assertAlmostEqual(spheroid_distances[i], c.distance.m, tol)
        if postgis:
            # PostGIS uses sphere-only distances by default, testing these as well.
            qs =  AustraliaCity.objects.exclude(id=hillsdale.id).distance(hillsdale.point)
            for i, c in enumerate(qs):
                self.assertAlmostEqual(sphere_distances[i], c.distance.m, tol)

    @no_oracle # Oracle already handles geographic distance calculation.
    def test03c_distance_method(self):
        "Testing the `distance` GeoQuerySet method used with `transform` on a geographic field."
        # Normally you can't compute distances from a geometry field
        # that is not a PointField (on PostGIS).
        self.assertRaises(ValueError, CensusZipcode.objects.distance, self.stx_pnt)

        # We'll be using a Polygon (created by buffering the centroid
        # of 77005 to 100m) -- which aren't allowed in geographic distance
        # queries normally, however our field has been transformed to
        # a non-geographic system.
        z = SouthTexasZipcode.objects.get(name='77005')

        # Reference query:
        # SELECT ST_Distance(ST_Transform("distapp_censuszipcode"."poly", 32140), ST_GeomFromText('<buffer_wkt>', 32140)) FROM "distapp_censuszipcode";
        dists_m = [3553.30384972258, 1243.18391525602, 2186.15439472242]

        # Having our buffer in the SRID of the transformation and of the field
        # -- should get the same results. The first buffer has no need for
        # transformation SQL because it is the same SRID as what was given
        # to `transform()`.  The second buffer will need to be transformed,
        # however.
        buf1 = z.poly.centroid.buffer(100)
        buf2 = buf1.transform(4269, clone=True)
        ref_zips = ['77002', '77025', '77401']

        for buf in [buf1, buf2]:
            qs = CensusZipcode.objects.exclude(name='77005').transform(32140).distance(buf)
            self.assertEqual(ref_zips, self.get_names(qs))
            for i, z in enumerate(qs):
                self.assertAlmostEqual(z.distance.m, dists_m[i], 5)

    def test04_distance_lookups(self):
        "Testing the `distance_lt`, `distance_gt`, `distance_lte`, and `distance_gte` lookup types."
        # Retrieving the cities within a 20km 'donut' w/a 7km radius 'hole'
        # (thus, Houston and Southside place will be excluded as tested in
        # the `test02_dwithin` above).
        qs1 = SouthTexasCity.objects.filter(point__distance_gte=(self.stx_pnt, D(km=7))).filter(point__distance_lte=(self.stx_pnt, D(km=20)))

        # Can't determine the units on SpatiaLite from PROJ.4 string, and
        # Oracle 11 incorrectly thinks it is not projected.
        if spatialite or oracle:
            dist_qs = (qs1,)
        else:
            qs2 = SouthTexasCityFt.objects.filter(point__distance_gte=(self.stx_pnt, D(km=7))).filter(point__distance_lte=(self.stx_pnt, D(km=20)))
            dist_qs = (qs1, qs2)

        for qs in dist_qs:
            cities = self.get_names(qs)
            self.assertEqual(cities, ['Bellaire', 'Pearland', 'West University Place'])

        # Doing a distance query using Polygons instead of a Point.
        z = SouthTexasZipcode.objects.get(name='77005')
        qs = SouthTexasZipcode.objects.exclude(name='77005').filter(poly__distance_lte=(z.poly, D(m=275)))
        self.assertEqual(['77025', '77401'], self.get_names(qs))
        # If we add a little more distance 77002 should be included.
        qs = SouthTexasZipcode.objects.exclude(name='77005').filter(poly__distance_lte=(z.poly, D(m=300)))
        self.assertEqual(['77002', '77025', '77401'], self.get_names(qs))

    @no_spatialite
    def test05_geodetic_distance_lookups(self):
        "Testing distance lookups on geodetic coordinate systems."
        if not oracle:
            # Oracle doesn't have this limitation -- PostGIS only allows geodetic
            # distance queries from Points to PointFields.
            mp = GEOSGeometry('MULTIPOINT(0 0, 5 23)')
            self.assertRaises(TypeError,
                              AustraliaCity.objects.filter(point__distance_lte=(mp, D(km=100))))
            # Too many params (4 in this case) should raise a ValueError.
            self.assertRaises(ValueError,
                              AustraliaCity.objects.filter, point__distance_lte=('POINT(5 23)', D(km=100), 'spheroid', '4'))

        # Not enough params should raise a ValueError.
        self.assertRaises(ValueError,
                          AustraliaCity.objects.filter, point__distance_lte=('POINT(5 23)',))

        # Getting all cities w/in 550 miles of Hobart.
        hobart = AustraliaCity.objects.get(name='Hobart')
        qs = AustraliaCity.objects.exclude(name='Hobart').filter(point__distance_lte=(hobart.point, D(mi=550)))
        cities = self.get_names(qs)
        self.assertEqual(cities, ['Batemans Bay', 'Canberra', 'Melbourne'])

        # Cities that are either really close or really far from Wollongong --
        # and using different units of distance.
        wollongong = AustraliaCity.objects.get(name='Wollongong')
        d1, d2 = D(yd=19500), D(nm=400) # Yards (~17km) & Nautical miles.

        # Normal geodetic distance lookup (uses `distance_sphere` on PostGIS.
        gq1 = Q(point__distance_lte=(wollongong.point, d1))
        gq2 = Q(point__distance_gte=(wollongong.point, d2))
        qs1 = AustraliaCity.objects.exclude(name='Wollongong').filter(gq1 | gq2)

        # Geodetic distance lookup but telling GeoDjango to use `distance_spheroid`
        # instead (we should get the same results b/c accuracy variance won't matter
        # in this test case).
        if postgis:
            gq3 = Q(point__distance_lte=(wollongong.point, d1, 'spheroid'))
            gq4 = Q(point__distance_gte=(wollongong.point, d2, 'spheroid'))
            qs2 = AustraliaCity.objects.exclude(name='Wollongong').filter(gq3 | gq4)
            querysets = [qs1, qs2]
        else:
            querysets = [qs1]

        for qs in querysets:
            cities = self.get_names(qs)
            self.assertEqual(cities, ['Adelaide', 'Hobart', 'Shellharbour', 'Thirroul'])

    def test06_area(self):
        "Testing the `area` GeoQuerySet method."
        # Reference queries:
        # SELECT ST_Area(poly) FROM distapp_southtexaszipcode;
        area_sq_m = [5437908.90234375, 10183031.4389648, 11254471.0073242, 9881708.91772461]
        # Tolerance has to be lower for Oracle and differences
        # with GEOS 3.0.0RC4
        tol = 2
        for i, z in enumerate(SouthTexasZipcode.objects.area()):
            self.assertAlmostEqual(area_sq_m[i], z.area.sq_m, tol)

    def test07_length(self):
        "Testing the `length` GeoQuerySet method."
        # Reference query (should use `length_spheroid`).
        # SELECT ST_length_spheroid(ST_GeomFromText('<wkt>', 4326) 'SPHEROID["WGS 84",6378137,298.257223563, AUTHORITY["EPSG","7030"]]');
        len_m1 = 473504.769553813
        len_m2 = 4617.668

        if spatialite:
            # Does not support geodetic coordinate systems.
            self.assertRaises(ValueError, Interstate.objects.length)
        else:
            qs = Interstate.objects.length()
            if oracle: tol = 2
            else: tol = 5
            self.assertAlmostEqual(len_m1, qs[0].length.m, tol)

        # Now doing length on a projected coordinate system.
        i10 = SouthTexasInterstate.objects.length().get(name='I-10')
        self.assertAlmostEqual(len_m2, i10.length.m, 2)

    @no_spatialite
    def test08_perimeter(self):
        "Testing the `perimeter` GeoQuerySet method."
        # Reference query:
        # SELECT ST_Perimeter(distapp_southtexaszipcode.poly) FROM distapp_southtexaszipcode;
        perim_m = [18404.3550889361, 15627.2108551001, 20632.5588368978, 17094.5996143697]
        if oracle: tol = 2
        else: tol = 7
        for i, z in enumerate(SouthTexasZipcode.objects.perimeter()):
            self.assertAlmostEqual(perim_m[i], z.perimeter.m, tol)

        # Running on points; should return 0.
        for i, c in enumerate(SouthTexasCity.objects.perimeter(model_att='perim')):
            self.assertEqual(0, c.perim.m)

    def test09_measurement_null_fields(self):
        "Testing the measurement GeoQuerySet methods on fields with NULL values."
        # Creating SouthTexasZipcode w/NULL value.
        SouthTexasZipcode.objects.create(name='78212')
        # Performing distance/area queries against the NULL PolygonField,
        # and ensuring the result of the operations is None.
        htown = SouthTexasCity.objects.get(name='Downtown Houston')
        z = SouthTexasZipcode.objects.distance(htown.point).area().get(name='78212')
        self.assertEqual(None, z.distance)
        self.assertEqual(None, z.area)

def suite():
    s = unittest.TestSuite()
    s.addTest(unittest.makeSuite(DistanceTest))
    return s
# alias for Distance # A point we are testing distances with -- using a WGS84 # coordinate that'll be implicitly transormed to that to # the coordinate system of the field, EPSG:32140 (Texas South Central # w/units in meters) # Another one for Australia # Loading up the cities. # Loading up the South Texas Zip Codes. # Loading up the Interstates. # Distances -- all should be equal (except for the # degree/meter pair in au_cities, that's somewhat # approximate). # Expected cities for Australia and Texas. # Performing distance queries on two projected coordinate systems one # with units in meters and the other in units of U.S. survey feet. # Now performing the `dwithin` queries on a geodetic coordinate system. # Creating the query set. # A TypeError should be raised on PostGIS when trying to pass # Distance objects into a DWithin query using a geodetic field. # The point for La Grange, TX # Reference distances in feet and in meters. Got these values from # using the provided raw SQL statements. #  SELECT ST_Distance(point, ST_Transform(ST_GeomFromText('POINT(-96.876369 29.905320)', 4326), 32140)) FROM distapp_southtexascity; #  SELECT ST_Distance(point, ST_Transform(ST_GeomFromText('POINT(-96.876369 29.905320)', 4326), 2278)) FROM distapp_southtexascityft; # Oracle 11 thinks this is not a projected coordinate system, so it's s # not tested. # Testing using different variations of parameters and using models # with different projected coordinate systems. # Using GEOSGeometry parameter # Using EWKT string parameter. # Original query done on PostGIS, have to adjust AlmostEqual tolerance # for Oracle. # Ensuring expected distances are returned for each distance queryset. # Now testing geodetic distance aggregation. # PostGIS is limited to disance queries only to/from point geometries, # ensuring a TypeError is raised if something else is put in. # Got the reference distances using the raw SQL statements: #  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)); #  SELECT ST_distance_sphere(point, ST_GeomFromText('POINT(151.231341 -33.952685)', 4326)) FROM distapp_australiacity WHERE (NOT (id = 11));  st_distance_sphere # Testing with spheroid distances first. # PostGIS uses sphere-only distances by default, testing these as well. # Oracle already handles geographic distance calculation. # Normally you can't compute distances from a geometry field # that is not a PointField (on PostGIS). # We'll be using a Polygon (created by buffering the centroid # of 77005 to 100m) -- which aren't allowed in geographic distance # queries normally, however our field has been transformed to # a non-geographic system. # Reference query: # SELECT ST_Distance(ST_Transform("distapp_censuszipcode"."poly", 32140), ST_GeomFromText('<buffer_wkt>', 32140)) FROM "distapp_censuszipcode"; # Having our buffer in the SRID of the transformation and of the field # -- should get the same results. The first buffer has no need for # transformation SQL because it is the same SRID as what was given # to `transform()`.  The second buffer will need to be transformed, # however. # Retrieving the cities within a 20km 'donut' w/a 7km radius 'hole' # (thus, Houston and Southside place will be excluded as tested in # the `test02_dwithin` above). # Can't determine the units on SpatiaLite from PROJ.4 string, and # Oracle 11 incorrectly thinks it is not projected. # Doing a distance query using Polygons instead of a Point. # If we add a little more distance 77002 should be included. # Oracle doesn't have this limitation -- PostGIS only allows geodetic # distance queries from Points to PointFields. # Too many params (4 in this case) should raise a ValueError. # Not enough params should raise a ValueError. # Getting all cities w/in 550 miles of Hobart. # Cities that are either really close or really far from Wollongong -- # and using different units of distance. # Yards (~17km) & Nautical miles. # Normal geodetic distance lookup (uses `distance_sphere` on PostGIS. # Geodetic distance lookup but telling GeoDjango to use `distance_spheroid` # instead (we should get the same results b/c accuracy variance won't matter # in this test case). # Reference queries: # SELECT ST_Area(poly) FROM distapp_southtexaszipcode; # Tolerance has to be lower for Oracle and differences # with GEOS 3.0.0RC4 # Reference query (should use `length_spheroid`). # SELECT ST_length_spheroid(ST_GeomFromText('<wkt>', 4326) 'SPHEROID["WGS 84",6378137,298.257223563, AUTHORITY["EPSG","7030"]]'); # Does not support geodetic coordinate systems. # Now doing length on a projected coordinate system. # Reference query: # SELECT ST_Perimeter(distapp_southtexaszipcode.poly) FROM distapp_southtexaszipcode; # Running on points; should return 0. # Creating SouthTexasZipcode w/NULL value. # Performing distance/area queries against the NULL PolygonField, # and ensuring the result of the operations is None.