GMaps related JS changed to use new google namespace.
Google is going to change permanently in the future the way to
load its services, so better stay safe.
Also this commit shows uses of the new melange.js module.
Fixes Issue 634.
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.db.models import GeoQ
from django.contrib.gis.tests.utils import oracle, postgis, no_oracle
from models import AustraliaCity, Interstate, SouthTexasCity, SouthTexasCityFt, CensusZipcode, SouthTexasZipcode
from data import au_cities, 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:
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