django1/django/contrib/gis/tests/distapp/tests.py

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