232 lines
11 KiB
Python
232 lines
11 KiB
Python
import os
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import re
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from django.utils.unittest import TestCase
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from django.contrib.gis.db.models import Union, Extent3D
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from django.contrib.gis.geos import GEOSGeometry, Point, Polygon
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from django.contrib.gis.utils import LayerMapping, LayerMapError
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from models import City3D, Interstate2D, Interstate3D, \
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InterstateProj2D, InterstateProj3D, \
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Point2D, Point3D, MultiPoint3D, Polygon2D, Polygon3D
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data_path = os.path.realpath(os.path.join(os.path.dirname(__file__), '..', 'data'))
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city_file = os.path.join(data_path, 'cities', 'cities.shp')
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vrt_file = os.path.join(data_path, 'test_vrt', 'test_vrt.vrt')
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# The coordinates of each city, with Z values corresponding to their
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# altitude in meters.
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city_data = (
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('Houston', (-95.363151, 29.763374, 18)),
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('Dallas', (-96.801611, 32.782057, 147)),
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('Oklahoma City', (-97.521157, 34.464642, 380)),
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('Wellington', (174.783117, -41.315268, 14)),
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('Pueblo', (-104.609252, 38.255001, 1433)),
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('Lawrence', (-95.235060, 38.971823, 251)),
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('Chicago', (-87.650175, 41.850385, 181)),
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('Victoria', (-123.305196, 48.462611, 15)),
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)
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# Reference mapping of city name to its altitude (Z value).
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city_dict = dict((name, coords) for name, coords in city_data)
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# 3D freeway data derived from the National Elevation Dataset:
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# http://seamless.usgs.gov/products/9arc.php
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interstate_data = (
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('I-45',
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'LINESTRING(-95.3708481 29.7765870 11.339,-95.3694580 29.7787980 4.536,-95.3690305 29.7797359 9.762,-95.3691886 29.7812450 12.448,-95.3696447 29.7850144 10.457,-95.3702511 29.7868518 9.418,-95.3706724 29.7881286 14.858,-95.3711632 29.7896157 15.386,-95.3714525 29.7936267 13.168,-95.3717848 29.7955007 15.104,-95.3717719 29.7969804 16.516,-95.3717305 29.7982117 13.923,-95.3717254 29.8000778 14.385,-95.3719875 29.8013539 15.160,-95.3720575 29.8026785 15.544,-95.3721321 29.8040912 14.975,-95.3722074 29.8050998 15.688,-95.3722779 29.8060430 16.099,-95.3733818 29.8076750 15.197,-95.3741563 29.8103686 17.268,-95.3749458 29.8129927 19.857,-95.3763564 29.8144557 15.435)',
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( 11.339, 4.536, 9.762, 12.448, 10.457, 9.418, 14.858,
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15.386, 13.168, 15.104, 16.516, 13.923, 14.385, 15.16 ,
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15.544, 14.975, 15.688, 16.099, 15.197, 17.268, 19.857,
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15.435),
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),
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)
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# Bounding box polygon for inner-loop of Houston (in projected coordinate
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# system 32140), with elevation values from the National Elevation Dataset
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# (see above).
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bbox_wkt = 'POLYGON((941527.97 4225693.20,962596.48 4226349.75,963152.57 4209023.95,942051.75 4208366.38,941527.97 4225693.20))'
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bbox_z = (21.71, 13.21, 9.12, 16.40, 21.71)
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def gen_bbox():
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bbox_2d = GEOSGeometry(bbox_wkt, srid=32140)
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bbox_3d = Polygon(tuple((x, y, z) for (x, y), z in zip(bbox_2d[0].coords, bbox_z)), srid=32140)
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return bbox_2d, bbox_3d
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class Geo3DTest(TestCase):
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"""
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Only a subset of the PostGIS routines are 3D-enabled, and this TestCase
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tries to test the features that can handle 3D and that are also
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available within GeoDjango. For more information, see the PostGIS docs
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on the routines that support 3D:
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http://postgis.refractions.net/documentation/manual-1.4/ch08.html#PostGIS_3D_Functions
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"""
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def test01_3d(self):
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"Test the creation of 3D models."
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# 3D models for the rest of the tests will be populated in here.
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# For each 3D data set create model (and 2D version if necessary),
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# retrieve, and assert geometry is in 3D and contains the expected
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# 3D values.
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for name, pnt_data in city_data:
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x, y, z = pnt_data
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pnt = Point(x, y, z, srid=4326)
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City3D.objects.create(name=name, point=pnt)
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city = City3D.objects.get(name=name)
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self.failUnless(city.point.hasz)
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self.assertEqual(z, city.point.z)
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# Interstate (2D / 3D and Geographic/Projected variants)
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for name, line, exp_z in interstate_data:
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line_3d = GEOSGeometry(line, srid=4269)
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# Using `hex` attribute because it omits 3D.
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line_2d = GEOSGeometry(line_3d.hex, srid=4269)
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# Creating a geographic and projected version of the
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# interstate in both 2D and 3D.
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Interstate3D.objects.create(name=name, line=line_3d)
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InterstateProj3D.objects.create(name=name, line=line_3d)
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Interstate2D.objects.create(name=name, line=line_2d)
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InterstateProj2D.objects.create(name=name, line=line_2d)
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# Retrieving and making sure it's 3D and has expected
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# Z values -- shouldn't change because of coordinate system.
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interstate = Interstate3D.objects.get(name=name)
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interstate_proj = InterstateProj3D.objects.get(name=name)
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for i in [interstate, interstate_proj]:
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self.failUnless(i.line.hasz)
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self.assertEqual(exp_z, tuple(i.line.z))
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# Creating 3D Polygon.
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bbox2d, bbox3d = gen_bbox()
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Polygon2D.objects.create(name='2D BBox', poly=bbox2d)
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Polygon3D.objects.create(name='3D BBox', poly=bbox3d)
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p3d = Polygon3D.objects.get(name='3D BBox')
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self.failUnless(p3d.poly.hasz)
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self.assertEqual(bbox3d, p3d.poly)
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def test01a_3d_layermapping(self):
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"Testing LayerMapping on 3D models."
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from models import Point2D, Point3D
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point_mapping = {'point' : 'POINT'}
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mpoint_mapping = {'mpoint' : 'MULTIPOINT'}
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# The VRT is 3D, but should still be able to map sans the Z.
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lm = LayerMapping(Point2D, vrt_file, point_mapping, transform=False)
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lm.save()
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self.assertEqual(3, Point2D.objects.count())
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# The city shapefile is 2D, and won't be able to fill the coordinates
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# in the 3D model -- thus, a LayerMapError is raised.
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self.assertRaises(LayerMapError, LayerMapping,
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Point3D, city_file, point_mapping, transform=False)
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# 3D model should take 3D data just fine.
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lm = LayerMapping(Point3D, vrt_file, point_mapping, transform=False)
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lm.save()
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self.assertEqual(3, Point3D.objects.count())
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# Making sure LayerMapping.make_multi works right, by converting
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# a Point25D into a MultiPoint25D.
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lm = LayerMapping(MultiPoint3D, vrt_file, mpoint_mapping, transform=False)
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lm.save()
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self.assertEqual(3, MultiPoint3D.objects.count())
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def test02a_kml(self):
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"Test GeoQuerySet.kml() with Z values."
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h = City3D.objects.kml(precision=6).get(name='Houston')
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# KML should be 3D.
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# `SELECT ST_AsKML(point, 6) FROM geo3d_city3d WHERE name = 'Houston';`
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ref_kml_regex = re.compile(r'^<Point><coordinates>-95.363\d+,29.763\d+,18</coordinates></Point>$')
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self.failUnless(ref_kml_regex.match(h.kml))
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def test02b_geojson(self):
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"Test GeoQuerySet.geojson() with Z values."
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h = City3D.objects.geojson(precision=6).get(name='Houston')
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# GeoJSON should be 3D
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# `SELECT ST_AsGeoJSON(point, 6) FROM geo3d_city3d WHERE name='Houston';`
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ref_json_regex = re.compile(r'^{"type":"Point","coordinates":\[-95.363151,29.763374,18(\.0+)?\]}$')
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self.failUnless(ref_json_regex.match(h.geojson))
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def test03a_union(self):
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"Testing the Union aggregate of 3D models."
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# PostGIS query that returned the reference EWKT for this test:
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# `SELECT ST_AsText(ST_Union(point)) FROM geo3d_city3d;`
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ref_ewkt = 'SRID=4326;MULTIPOINT(-123.305196 48.462611 15,-104.609252 38.255001 1433,-97.521157 34.464642 380,-96.801611 32.782057 147,-95.363151 29.763374 18,-95.23506 38.971823 251,-87.650175 41.850385 181,174.783117 -41.315268 14)'
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ref_union = GEOSGeometry(ref_ewkt)
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union = City3D.objects.aggregate(Union('point'))['point__union']
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self.failUnless(union.hasz)
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self.assertEqual(ref_union, union)
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def test03b_extent(self):
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"Testing the Extent3D aggregate for 3D models."
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# `SELECT ST_Extent3D(point) FROM geo3d_city3d;`
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ref_extent3d = (-123.305196, -41.315268, 14,174.783117, 48.462611, 1433)
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extent1 = City3D.objects.aggregate(Extent3D('point'))['point__extent3d']
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extent2 = City3D.objects.extent3d()
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def check_extent3d(extent3d, tol=6):
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for ref_val, ext_val in zip(ref_extent3d, extent3d):
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self.assertAlmostEqual(ref_val, ext_val, tol)
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for e3d in [extent1, extent2]:
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check_extent3d(e3d)
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def test04_perimeter(self):
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"Testing GeoQuerySet.perimeter() on 3D fields."
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# Reference query for values below:
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# `SELECT ST_Perimeter3D(poly), ST_Perimeter2D(poly) FROM geo3d_polygon3d;`
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ref_perim_3d = 76859.2620451
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ref_perim_2d = 76859.2577803
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tol = 6
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self.assertAlmostEqual(ref_perim_2d,
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Polygon2D.objects.perimeter().get(name='2D BBox').perimeter.m,
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tol)
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self.assertAlmostEqual(ref_perim_3d,
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Polygon3D.objects.perimeter().get(name='3D BBox').perimeter.m,
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tol)
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def test05_length(self):
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"Testing GeoQuerySet.length() on 3D fields."
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# ST_Length_Spheroid Z-aware, and thus does not need to use
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# a separate function internally.
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# `SELECT ST_Length_Spheroid(line, 'SPHEROID["GRS 1980",6378137,298.257222101]')
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# FROM geo3d_interstate[2d|3d];`
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tol = 3
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ref_length_2d = 4368.1721949481
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ref_length_3d = 4368.62547052088
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self.assertAlmostEqual(ref_length_2d,
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Interstate2D.objects.length().get(name='I-45').length.m,
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tol)
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self.assertAlmostEqual(ref_length_3d,
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Interstate3D.objects.length().get(name='I-45').length.m,
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tol)
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# Making sure `ST_Length3D` is used on for a projected
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# and 3D model rather than `ST_Length`.
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# `SELECT ST_Length(line) FROM geo3d_interstateproj2d;`
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ref_length_2d = 4367.71564892392
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# `SELECT ST_Length3D(line) FROM geo3d_interstateproj3d;`
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ref_length_3d = 4368.16897234101
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self.assertAlmostEqual(ref_length_2d,
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InterstateProj2D.objects.length().get(name='I-45').length.m,
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tol)
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self.assertAlmostEqual(ref_length_3d,
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InterstateProj3D.objects.length().get(name='I-45').length.m,
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tol)
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def test06_scale(self):
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"Testing GeoQuerySet.scale() on Z values."
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# Mapping of City name to reference Z values.
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zscales = (-3, 4, 23)
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for zscale in zscales:
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for city in City3D.objects.scale(1.0, 1.0, zscale):
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self.assertEqual(city_dict[city.name][2] * zscale, city.scale.z)
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def test07_translate(self):
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"Testing GeoQuerySet.translate() on Z values."
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ztranslations = (5.23, 23, -17)
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for ztrans in ztranslations:
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for city in City3D.objects.translate(0, 0, ztrans):
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self.assertEqual(city_dict[city.name][2] + ztrans, city.translate.z)
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