import os, unittest

from django.contrib.gis.geos import *

from django.contrib.gis.db.models import Collect, Count, Extent, F, Union

from django.conf import settings

from models import City, Location, DirectoryEntry, Parcel, Book, Author

cities = (('Aurora', 'TX', -97.516111, 33.058333),

          ('Roswell', 'NM', -104.528056, 33.387222),

          ('Kecksburg', 'PA',  -79.460734, 40.18476),

           )

class RelatedGeoModelTest(unittest.TestCase):

    def test01_setup(self):

        "Setting up for related model tests."

        for name, state, lon, lat in cities:

            loc = Location.objects.create(point=Point(lon, lat))

            c = City.objects.create(name=name, state=state, location=loc)

    def test02_select_related(self):

        "Testing `select_related` on geographic models (see #7126)."

        qs1 = City.objects.all()

        qs2 = City.objects.select_related()

        qs3 = City.objects.select_related('location')

        for qs in (qs1, qs2, qs3):

            for ref, c in zip(cities, qs):

                nm, st, lon, lat = ref

                self.assertEqual(nm, c.name)

                self.assertEqual(st, c.state)

                self.assertEqual(Point(lon, lat), c.location.point)

    @no_mysql

    def test03_transform_related(self):

        "Testing the `transform` GeoQuerySet method on related geographic models."

        # All the transformations are to state plane coordinate systems using

        # US Survey Feet (thus a tolerance of 0 implies error w/in 1 survey foot).

        tol = 0

        def check_pnt(ref, pnt):

            self.assertAlmostEqual(ref.x, pnt.x, tol)

            self.assertAlmostEqual(ref.y, pnt.y, tol)

            self.assertEqual(ref.srid, pnt.srid)

        # Each city transformed to the SRID of their state plane coordinate system.

        transformed = (('Kecksburg', 2272, 'POINT(1490553.98959621 314792.131023984)'),

                       ('Roswell', 2257, 'POINT(481902.189077221 868477.766629735)'),

                       ('Aurora', 2276, 'POINT(2269923.2484839 7069381.28722222)'),

                       )

        for name, srid, wkt in transformed:

            # Doing this implicitly sets `select_related` select the location.

            # TODO: Fix why this breaks on Oracle.

            qs = list(City.objects.filter(name=name).transform(srid, field_name='location__point'))

            check_pnt(GEOSGeometry(wkt, srid), qs[0].location.point)

    @no_mysql

    @no_spatialite

    def test04a_related_extent_aggregate(self):

        "Testing the `extent` GeoQuerySet aggregates on related geographic models."

        # This combines the Extent and Union aggregates into one query

        aggs = City.objects.aggregate(Extent('location__point'))

        # One for all locations, one that excludes Roswell.

        all_extent = (-104.528060913086, 33.0583305358887,-79.4607315063477, 40.1847610473633)

        txpa_extent = (-97.51611328125, 33.0583305358887,-79.4607315063477, 40.1847610473633)

        e1 = City.objects.extent(field_name='location__point')

        e2 = City.objects.exclude(name='Roswell').extent(field_name='location__point')

        e3 = aggs['location__point__extent']

        # The tolerance value is to four decimal places because of differences

        # between the Oracle and PostGIS spatial backends on the extent calculation.

        tol = 4

        for ref, e in [(all_extent, e1), (txpa_extent, e2), (all_extent, e3)]:

            for ref_val, e_val in zip(ref, e): self.assertAlmostEqual(ref_val, e_val, tol)

    @no_mysql

    def test04b_related_union_aggregate(self):

        "Testing the `unionagg` GeoQuerySet aggregates on related geographic models."

        # This combines the Extent and Union aggregates into one query

        aggs = City.objects.aggregate(Union('location__point'))

        # These are the points that are components of the aggregate geographic

        # union that is returned.

        p1 = Point(-104.528056, 33.387222)

        p2 = Point(-97.516111, 33.058333)

        p3 = Point(-79.460734, 40.18476)

        # Creating the reference union geometry depending on the spatial backend,

        # as Oracle will have a different internal ordering of the component

        # geometries than PostGIS.  The second union aggregate is for a union

        # query that includes limiting information in the WHERE clause (in other

        # words a `.filter()` precedes the call to `.unionagg()`).

            ref_u1 = MultiPoint(p3, p1, p2, srid=4326)

            ref_u2 = MultiPoint(p3, p2, srid=4326)

        else:

            ref_u1 = MultiPoint(p1, p2, p3, srid=4326)

            ref_u2 = MultiPoint(p2, p3, srid=4326)

        u1 = City.objects.unionagg(field_name='location__point')

        u2 = City.objects.exclude(name='Roswell').unionagg(field_name='location__point')

        u3 = aggs['location__point__union']

        self.assertEqual(ref_u1, u1)

        self.assertEqual(ref_u2, u2)

        self.assertEqual(ref_u1, u3)

    def test05_select_related_fk_to_subclass(self):

        "Testing that calling select_related on a query over a model with an FK to a model subclass works"

        # Regression test for #9752.

        l = list(DirectoryEntry.objects.all().select_related())

    def test06_f_expressions(self):

        "Testing F() expressions on GeometryFields."

        # Constructing a dummy parcel border and getting the City instance for

        # assigning the FK.

        b1 = GEOSGeometry('POLYGON((-97.501205 33.052520,-97.501205 33.052576,-97.501150 33.052576,-97.501150 33.052520,-97.501205 33.052520))', srid=4326)

        pcity = City.objects.get(name='Aurora')

        # First parcel has incorrect center point that is equal to the City;

        # it also has a second border that is different from the first as a

        # 100ft buffer around the City.

        c1 = pcity.location.point

        c2 = c1.transform(2276, clone=True)

        b2 = c2.buffer(100)

        p1 = Parcel.objects.create(name='P1', city=pcity, center1=c1, center2=c2, border1=b1, border2=b2)

        # Now creating a second Parcel where the borders are the same, just

        # in different coordinate systems.  The center points are also the

        # the same (but in different coordinate systems), and this time they

        # actually correspond to the centroid of the border.

        c1 = b1.centroid

        c2 = c1.transform(2276, clone=True)

        p2 = Parcel.objects.create(name='P2', city=pcity, center1=c1, center2=c2, border1=b1, border2=b1)

        # Should return the second Parcel, which has the center within the

        # border.

        qs = Parcel.objects.filter(center1__within=F('border1'))

        self.assertEqual(1, len(qs))

        self.assertEqual('P2', qs[0].name)

            # This time center2 is in a different coordinate system and needs

            # to be wrapped in transformation SQL.

            qs = Parcel.objects.filter(center2__within=F('border1'))

            self.assertEqual(1, len(qs))

            self.assertEqual('P2', qs[0].name)

        # Should return the first Parcel, which has the center point equal

        # to the point in the City ForeignKey.

        qs = Parcel.objects.filter(center1=F('city__location__point'))

        self.assertEqual(1, len(qs))

        self.assertEqual('P1', qs[0].name)

            # This time the city column should be wrapped in transformation SQL.

            qs = Parcel.objects.filter(border2__contains=F('city__location__point'))

            self.assertEqual(1, len(qs))

            self.assertEqual('P1', qs[0].name)

    def test07_values(self):

        "Testing values() and values_list() and GeoQuerySets."

        # GeoQuerySet and GeoValuesQuerySet, and GeoValuesListQuerySet respectively.

        gqs = Location.objects.all()

        gvqs = Location.objects.values()

        gvlqs = Location.objects.values_list()

        # Incrementing through each of the models, dictionaries, and tuples

        # returned by the different types of GeoQuerySets.

        for m, d, t in zip(gqs, gvqs, gvlqs):

            # The values should be Geometry objects and not raw strings returned

            # by the spatial database.

            self.assertEqual(m.point, d['point'])

            self.assertEqual(m.point, t[1])

    def test08_defer_only(self):

        "Testing defer() and only() on Geographic models."

        qs = Location.objects.all()

        def_qs = Location.objects.defer('point')

        for loc, def_loc in zip(qs, def_qs):

            self.assertEqual(loc.point, def_loc.point)

    def test09_pk_relations(self):

        "Ensuring correct primary key column is selected across relations. See #10757."

        # Adding two more cities, but this time making sure that their location

        # ID values do not match their City ID values.

        loc1 = Location.objects.create(point='POINT (-95.363151 29.763374)')

        loc2 = Location.objects.create(point='POINT (-96.801611 32.782057)')

        dallas = City.objects.create(name='Dallas', state='TX', location=loc2)

        houston = City.objects.create(name='Houston', state='TX', location=loc1)

        # The expected ID values -- notice the last two location IDs

        # are out of order.  We want to make sure that the related

        # location ID column is selected instead of ID column for

        # the city.

        city_ids = (1, 2, 3, 4, 5)

        loc_ids = (1, 2, 3, 5, 4)

        ids_qs = City.objects.order_by('id').values('id', 'location__id')

        for val_dict, c_id, l_id in zip(ids_qs, city_ids, loc_ids):

            self.assertEqual(val_dict['id'], c_id)

            self.assertEqual(val_dict['location__id'], l_id)

    def test10_combine(self):

        "Testing the combination of two GeoQuerySets.  See #10807."

        buf1 = City.objects.get(name='Aurora').location.point.buffer(0.1)

        buf2 = City.objects.get(name='Kecksburg').location.point.buffer(0.1)

        qs1 = City.objects.filter(location__point__within=buf1)

        qs2 = City.objects.filter(location__point__within=buf2)

        combined = qs1 | qs2

        names = [c.name for c in combined]

        self.assertEqual(2, len(names))

        self.failUnless('Aurora' in names)

        self.failUnless('Kecksburg' in names)

    def test11_geoquery_pickle(self):

        "Ensuring GeoQuery objects are unpickled correctly.  See #10839."

        import pickle

        from django.contrib.gis.db.models.sql import GeoQuery

        qs = City.objects.all()

        q_str = pickle.dumps(qs.query)

        q = pickle.loads(q_str)

        self.assertEqual(GeoQuery, q.__class__)

    # TODO: fix on Oracle -- get the following error because the SQL is ordered

    # by a geometry object, which Oracle apparently doesn't like:

    #  ORA-22901: cannot compare nested table or VARRAY or LOB attributes of an object type

    @no_oracle

    def test12a_count(self):

        "Testing `Count` aggregate use with the `GeoManager` on geo-fields."

        # Creating a new City, 'Fort Worth', that uses the same location

        # as Dallas.

        dallas = City.objects.get(name='Dallas')

        ftworth = City.objects.create(name='Fort Worth', state='TX', location=dallas.location)

        # Count annotation should be 2 for the Dallas location now.

        loc = Location.objects.annotate(num_cities=Count('city')).get(id=dallas.location.id)

        self.assertEqual(2, loc.num_cities)

    def test12b_count(self):

        "Testing `Count` aggregate use with the `GeoManager` on non geo-fields. See #11087."

        # Creating some data for the Book/Author non-geo models that

        # use GeoManager.  See #11087.

        tp = Author.objects.create(name='Trevor Paglen')

        Book.objects.create(title='Torture Taxi', author=tp)

        Book.objects.create(title='I Could Tell You But Then You Would Have to be Destroyed by Me', author=tp)

        Book.objects.create(title='Blank Spots on the Map', author=tp)

        wp = Author.objects.create(name='William Patry')

        Book.objects.create(title='Patry on Copyright', author=wp)

        # Should only be one author (Trevor Paglen) returned by this query, and

        # the annotation should have 3 for the number of books.  Also testing

        # with a `GeoValuesQuerySet` (see #11489).

        qs = Author.objects.annotate(num_books=Count('books')).filter(num_books__gt=1)

        vqs = Author.objects.values('name').annotate(num_books=Count('books')).filter(num_books__gt=1)

        self.assertEqual(1, len(qs))

        self.assertEqual(3, qs[0].num_books)

        self.assertEqual(1, len(vqs))

        self.assertEqual(3, vqs[0]['num_books'])

    # TODO: The phantom model does appear on Oracle.

    @no_oracle

    def test13_select_related_null_fk(self):

        "Testing `select_related` on a nullable ForeignKey via `GeoManager`. See #11381."

        no_author = Book.objects.create(title='Without Author')

        b = Book.objects.select_related('author').get(title='Without Author')

        # Should be `None`, and not a 'dummy' model.

        self.assertEqual(None, b.author)

    @no_mysql

    @no_oracle

    @no_spatialite

    def test14_collect(self):

        "Testing the `collect` GeoQuerySet method and `Collect` aggregate."

        # Reference query:

        #    WHERE "relatedapp_city"."state" = 'TX';

        ref_geom = fromstr('MULTIPOINT(-97.516111 33.058333,-96.801611 32.782057,-95.363151 29.763374,-96.801611 32.782057)')

        c1 = City.objects.filter(state='TX').collect(field_name='location__point')

        c2 = City.objects.filter(state='TX').aggregate(Collect('location__point'))['location__point__collect']

        for coll in (c1, c2):

            # Even though Dallas and Ft. Worth share same point, Collect doesn't

            # consolidate -- that's why 4 points in MultiPoint.

            self.assertEqual(4, len(coll))

            self.assertEqual(ref_geom, coll)

    # TODO: Related tests for KML, GML, and distance lookups.

def suite():

    s = unittest.TestSuite()

    s.addTest(unittest.makeSuite(RelatedGeoModelTest))

    return s