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