Adust the as_table tag to render a pick link if appropriate
The templates are adjusted to pass on a 'reference' value, which
is the url_name of the view from which the entity should be picked.
The as_table (and related) function(s) construct and then pass on
this argument and enable takes_contex so that we have access to the
context of the enclosing template.
We only extract ReferenceProperties that end with '_link_id' since
that is how all RP's are currently named. It is not possible to
create a field with the same name as the RP, as GAE will try to
interpret it's contents as the key of an entity before even calling
any function we can override.
Patch by: Sverre Rabbelier
import os, unittestfrom decimal import Decimalfrom django.db.models import Qfrom django.contrib.gis.gdal import DataSourcefrom django.contrib.gis.geos import GEOSGeometry, Point, LineStringfrom django.contrib.gis.measure import D # alias for Distancefrom django.contrib.gis.db.models import GeoQfrom django.contrib.gis.tests.utils import oracle, postgis, no_oraclefrom models import AustraliaCity, Interstate, SouthTexasCity, SouthTexasCityFt, CensusZipcode, SouthTexasZipcodefrom data import au_cities, interstates, stx_cities, stx_zipsclass 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: c = city_model(name=name, point=Point(x, y, srid=4326)) c.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. for name, wkt in interstates: Interstate(name=name, line=GEOSGeometry(wkt, srid=4326)).save() self.assertEqual(1, Interstate.objects.count()) 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; 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 dist3 = SouthTexasCityFt.objects.distance(lagrange.ewkt) # Using EWKT string parameter. dist4 = SouthTexasCityFt.objects.distance(lagrange) # 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 [dist1, dist2, dist3, dist4]: 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) 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(TypeError, AustraliaCity.objects.distance, 'LINESTRING(0 0, 1 1)') self.assertRaises(TypeError, 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(TypeError, 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) for buf in [buf1, buf2]: qs = CensusZipcode.objects.exclude(name='77005').transform(32140).distance(buf) self.assertEqual(['77002', '77025', '77401'], 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))) qs2 = SouthTexasCityFt.objects.filter(point__distance_gte=(self.stx_pnt, D(km=7))).filter(point__distance_lte=(self.stx_pnt, D(km=20))) for qs in qs1, qs2: 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)) 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 = GeoQ(point__distance_lte=(wollongong.point, d1)) gq2 = GeoQ(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). Using `Q` instead of `GeoQ` to be different (post-qsrf # it doesn't matter). 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_m = 473504.769553813 qs = Interstate.objects.length() if oracle: tol = 2 else: tol = 5 self.assertAlmostEqual(len_m, qs[0].length.m, tol) 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 suite(): s = unittest.TestSuite() s.addTest(unittest.makeSuite(DistanceTest)) return s