2010-12-02 05:58:21 +00:00
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import os
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import re
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2011-10-17 18:45:22 +00:00
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2015-04-24 15:24:07 +00:00
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from django.contrib.gis.db.models import Extent3D, Union
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2015-01-19 15:09:41 +00:00
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from django.contrib.gis.db.models.functions import (
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AsGeoJSON,
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AsKML,
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Length,
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Perimeter,
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Scale,
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Translate,
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)
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2015-04-24 15:24:07 +00:00
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from django.contrib.gis.geos import GEOSGeometry, LineString, Point, Polygon
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2016-11-07 12:00:40 +00:00
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from django.test import TestCase, skipUnlessDBFeature
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2009-11-16 18:49:00 +00:00
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2019-03-03 18:33:48 +00:00
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from ..utils import FuncTestMixin
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2015-04-24 15:24:07 +00:00
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from .models import (
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City3D,
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Interstate2D,
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Interstate3D,
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InterstateProj2D,
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InterstateProj3D,
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MultiPoint3D,
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Point2D,
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Point3D,
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Polygon2D,
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Polygon3D,
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)
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2013-05-11 03:08:45 +00:00
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2017-01-20 13:01:02 +00:00
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data_path = os.path.realpath(os.path.join(os.path.dirname(__file__), "..", "data"))
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2009-11-16 18:49:00 +00:00
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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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2014-12-06 21:00:09 +00:00
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city_dict = {name: coords for name, coords in city_data}
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2009-11-16 18:49:00 +00:00
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2011-10-17 18:45:22 +00:00
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# 3D freeway data derived from the National Elevation Dataset:
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2009-11-16 18:49:00 +00:00
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# http://seamless.usgs.gov/products/9arc.php
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interstate_data = (
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2011-10-17 18:45:22 +00:00
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(
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"I-45",
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2014-09-04 12:15:09 +00:00
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"LINESTRING(-95.3708481 29.7765870 11.339,-95.3694580 29.7787980 4.536,"
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"-95.3690305 29.7797359 9.762,-95.3691886 29.7812450 12.448,"
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"-95.3696447 29.7850144 10.457,-95.3702511 29.7868518 9.418,"
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"-95.3706724 29.7881286 14.858,-95.3711632 29.7896157 15.386,"
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"-95.3714525 29.7936267 13.168,-95.3717848 29.7955007 15.104,"
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"-95.3717719 29.7969804 16.516,-95.3717305 29.7982117 13.923,"
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"-95.3717254 29.8000778 14.385,-95.3719875 29.8013539 15.160,"
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"-95.3720575 29.8026785 15.544,-95.3721321 29.8040912 14.975,"
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"-95.3722074 29.8050998 15.688,-95.3722779 29.8060430 16.099,"
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"-95.3733818 29.8076750 15.197,-95.3741563 29.8103686 17.268,"
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"-95.3749458 29.8129927 19.857,-95.3763564 29.8144557 15.435)",
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2013-10-27 01:27:42 +00:00
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(
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11.339,
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4.536,
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9.762,
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12.448,
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10.457,
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9.418,
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14.858,
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2013-12-12 20:23:24 +00:00
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15.386,
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13.168,
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15.104,
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16.516,
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13.923,
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14.385,
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15.16,
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15.544,
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14.975,
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15.688,
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16.099,
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15.197,
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17.268,
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19.857,
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15.435,
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2009-11-16 18:49:00 +00:00
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),
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2022-02-03 19:24:19 +00:00
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),
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2013-10-18 09:02:43 +00:00
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)
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2009-11-16 18:49:00 +00:00
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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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2012-09-22 09:38:19 +00:00
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bbox_data = (
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2014-09-04 12:15:09 +00:00
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"POLYGON((941527.97 4225693.20,962596.48 4226349.75,963152.57 4209023.95,"
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"942051.75 4208366.38,941527.97 4225693.20))",
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2012-09-22 09:38:19 +00:00
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(21.71, 13.21, 9.12, 16.40, 21.71),
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)
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2009-11-16 18:49:00 +00:00
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2017-01-19 07:39:46 +00:00
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class Geo3DLoadingHelper:
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2012-09-22 09:38:19 +00:00
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def _load_interstate_data(self):
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2009-11-16 18:49:00 +00:00
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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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2020-05-12 06:52:23 +00:00
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line_2d = LineString([coord[:2] for coord in line_3d.coords], srid=4269)
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2009-11-16 18:49:00 +00:00
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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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2012-09-22 09:38:19 +00:00
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def _load_city_data(self):
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for name, pnt_data in city_data:
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2016-06-18 15:10:16 +00:00
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City3D.objects.create(
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name=name,
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point=Point(*pnt_data, srid=4326),
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pointg=Point(*pnt_data, srid=4326),
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)
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2012-09-22 09:38:19 +00:00
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def _load_polygon_data(self):
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bbox_wkt, bbox_z = bbox_data
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bbox_2d = GEOSGeometry(bbox_wkt, srid=32140)
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bbox_3d = Polygon(
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tuple((x, y, z) for (x, y), z in zip(bbox_2d[0].coords, bbox_z)), srid=32140
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)
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Polygon2D.objects.create(name="2D BBox", poly=bbox_2d)
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Polygon3D.objects.create(name="3D BBox", poly=bbox_3d)
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2015-01-19 15:09:41 +00:00
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2017-05-04 14:14:35 +00:00
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@skipUnlessDBFeature("supports_3d_storage")
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2015-01-19 15:09:41 +00:00
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class Geo3DTest(Geo3DLoadingHelper, 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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2017-03-16 18:01:45 +00:00
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https://postgis.net/docs/PostGIS_Special_Functions_Index.html#PostGIS_3D_Functions
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2015-01-19 15:09:41 +00:00
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"""
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2012-09-22 09:38:19 +00:00
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def test_3d_hasz(self):
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"""
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Make sure data is 3D and has expected Z values -- shouldn't change
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because of coordinate system.
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"""
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self._load_interstate_data()
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for name, line, exp_z in interstate_data:
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2009-11-16 18:49:00 +00:00
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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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2011-03-03 15:04:39 +00:00
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self.assertTrue(i.line.hasz)
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2009-11-16 18:49:00 +00:00
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self.assertEqual(exp_z, tuple(i.line.z))
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2012-09-22 09:38:19 +00:00
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self._load_city_data()
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for name, pnt_data in city_data:
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city = City3D.objects.get(name=name)
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2016-06-18 15:10:16 +00:00
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# Testing both geometry and geography fields
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2012-09-22 09:38:19 +00:00
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self.assertTrue(city.point.hasz)
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2016-06-18 15:10:16 +00:00
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self.assertTrue(city.pointg.hasz)
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self.assertEqual(city.point.z, pnt_data[2])
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self.assertEqual(city.pointg.z, pnt_data[2])
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2012-09-22 09:38:19 +00:00
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def test_3d_polygons(self):
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"""
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Test the creation of polygon 3D models.
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"""
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self._load_polygon_data()
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2009-11-16 18:49:00 +00:00
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p3d = Polygon3D.objects.get(name="3D BBox")
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2011-03-03 15:04:39 +00:00
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self.assertTrue(p3d.poly.hasz)
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2012-09-22 09:38:19 +00:00
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self.assertIsInstance(p3d.poly, Polygon)
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self.assertEqual(p3d.poly.srid, 32140)
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2009-11-16 18:49:00 +00:00
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2012-09-22 09:38:19 +00:00
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def test_3d_layermapping(self):
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"""
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Testing LayerMapping on 3D models.
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"""
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2016-06-14 14:18:33 +00:00
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# Import here as GDAL is required for those imports
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2020-07-24 06:25:47 +00:00
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from django.contrib.gis.utils import LayerMapError, LayerMapping
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2016-06-14 14:18:33 +00:00
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2013-10-27 01:27:42 +00:00
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point_mapping = {"point": "POINT"}
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mpoint_mapping = {"mpoint": "MULTIPOINT"}
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2009-11-16 18:49:00 +00:00
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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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2016-01-17 11:26:39 +00:00
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with self.assertRaises(LayerMapError):
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LayerMapping(Point3D, city_file, point_mapping, transform=False)
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2011-10-17 18:45:22 +00:00
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2009-11-16 18:49:00 +00:00
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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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2014-11-03 21:03:59 +00:00
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@skipUnlessDBFeature("supports_3d_functions")
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2012-09-22 09:38:19 +00:00
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def test_union(self):
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"""
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Testing the Union aggregate of 3D models.
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"""
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2009-11-16 18:49:00 +00:00
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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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2012-09-22 09:38:19 +00:00
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self._load_city_data()
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2014-09-04 12:15:09 +00:00
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ref_ewkt = (
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"SRID=4326;MULTIPOINT(-123.305196 48.462611 15,-104.609252 38.255001 1433,"
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"-97.521157 34.464642 380,-96.801611 32.782057 147,-95.363151 29.763374 18,"
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"-95.23506 38.971823 251,-87.650175 41.850385 181,174.783117 -41.315268 14)"
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)
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2009-11-16 18:49:00 +00:00
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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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2011-03-03 15:04:39 +00:00
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self.assertTrue(union.hasz)
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2014-03-27 20:17:10 +00:00
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# Ordering of points in the resulting geometry may vary between implementations
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2017-03-17 11:51:48 +00:00
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self.assertEqual({p.ewkt for p in ref_union}, {p.ewkt for p in union})
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2009-11-16 18:49:00 +00:00
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2014-11-03 21:03:59 +00:00
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@skipUnlessDBFeature("supports_3d_functions")
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2012-09-22 09:38:19 +00:00
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def test_extent(self):
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"""
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Testing the Extent3D aggregate for 3D models.
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"""
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self._load_city_data()
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2009-11-16 18:49:00 +00:00
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# `SELECT ST_Extent3D(point) FROM geo3d_city3d;`
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2013-10-26 17:50:40 +00:00
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ref_extent3d = (-123.305196, -41.315268, 14, 174.783117, 48.462611, 1433)
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2015-09-02 23:55:55 +00:00
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extent = City3D.objects.aggregate(Extent3D("point"))["point__extent3d"]
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2009-11-16 18:49:00 +00:00
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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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2015-09-02 23:55:55 +00:00
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check_extent3d(extent)
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2015-01-14 19:48:55 +00:00
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self.assertIsNone(
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City3D.objects.none().aggregate(Extent3D("point"))["point__extent3d"]
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)
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2009-11-16 18:49:00 +00:00
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2015-01-19 15:09:41 +00:00
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2017-05-04 14:14:35 +00:00
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@skipUnlessDBFeature("supports_3d_functions")
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2017-09-11 15:56:39 +00:00
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class Geo3DFunctionsTests(FuncTestMixin, Geo3DLoadingHelper, TestCase):
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2015-01-19 15:09:41 +00:00
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def test_kml(self):
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"""
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Test KML() function with Z values.
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"""
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self._load_city_data()
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h = City3D.objects.annotate(kml=AsKML("point", 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(
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r"^<Point><coordinates>-95.363\d+,29.763\d+,18</coordinates></Point>$"
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)
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self.assertTrue(ref_kml_regex.match(h.kml))
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def test_geojson(self):
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"""
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Test GeoJSON() function with Z values.
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"""
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self._load_city_data()
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h = City3D.objects.annotate(geojson=AsGeoJSON("point", precision=6)).get(
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name="Houston"
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)
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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(
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r'^{"type":"Point","coordinates":\[-95.363151,29.763374,18(\.0+)?\]}$'
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)
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|
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self.assertTrue(ref_json_regex.match(h.geojson))
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|
|
|
|
|
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|
def test_perimeter(self):
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|
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|
"""
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|
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|
Testing Perimeter() function on 3D fields.
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|
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|
"""
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|
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|
self._load_polygon_data()
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|
|
# Reference query for values below:
|
|
|
|
# `SELECT ST_Perimeter3D(poly), ST_Perimeter2D(poly) FROM geo3d_polygon3d;`
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|
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|
ref_perim_3d = 76859.2620451
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|
|
|
ref_perim_2d = 76859.2577803
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|
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|
tol = 6
|
|
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|
poly2d = Polygon2D.objects.annotate(perimeter=Perimeter("poly")).get(
|
|
|
|
name="2D BBox"
|
|
|
|
)
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|
|
|
self.assertAlmostEqual(ref_perim_2d, poly2d.perimeter.m, tol)
|
|
|
|
poly3d = Polygon3D.objects.annotate(perimeter=Perimeter("poly")).get(
|
|
|
|
name="3D BBox"
|
|
|
|
)
|
|
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|
self.assertAlmostEqual(ref_perim_3d, poly3d.perimeter.m, tol)
|
|
|
|
|
|
|
|
def test_length(self):
|
|
|
|
"""
|
|
|
|
Testing Length() function on 3D fields.
|
|
|
|
"""
|
|
|
|
# ST_Length_Spheroid Z-aware, and thus does not need to use
|
|
|
|
# a separate function internally.
|
|
|
|
# `SELECT ST_Length_Spheroid(line, 'SPHEROID["GRS 1980",6378137,298.257222101]')
|
|
|
|
# FROM geo3d_interstate[2d|3d];`
|
|
|
|
self._load_interstate_data()
|
|
|
|
tol = 3
|
|
|
|
ref_length_2d = 4368.1721949481
|
|
|
|
ref_length_3d = 4368.62547052088
|
|
|
|
inter2d = Interstate2D.objects.annotate(length=Length("line")).get(name="I-45")
|
|
|
|
self.assertAlmostEqual(ref_length_2d, inter2d.length.m, tol)
|
|
|
|
inter3d = Interstate3D.objects.annotate(length=Length("line")).get(name="I-45")
|
|
|
|
self.assertAlmostEqual(ref_length_3d, inter3d.length.m, tol)
|
|
|
|
|
|
|
|
# Making sure `ST_Length3D` is used on for a projected
|
|
|
|
# and 3D model rather than `ST_Length`.
|
|
|
|
# `SELECT ST_Length(line) FROM geo3d_interstateproj2d;`
|
|
|
|
ref_length_2d = 4367.71564892392
|
|
|
|
# `SELECT ST_Length3D(line) FROM geo3d_interstateproj3d;`
|
|
|
|
ref_length_3d = 4368.16897234101
|
|
|
|
inter2d = InterstateProj2D.objects.annotate(length=Length("line")).get(
|
|
|
|
name="I-45"
|
|
|
|
)
|
|
|
|
self.assertAlmostEqual(ref_length_2d, inter2d.length.m, tol)
|
|
|
|
inter3d = InterstateProj3D.objects.annotate(length=Length("line")).get(
|
|
|
|
name="I-45"
|
|
|
|
)
|
|
|
|
self.assertAlmostEqual(ref_length_3d, inter3d.length.m, tol)
|
|
|
|
|
|
|
|
def test_scale(self):
|
|
|
|
"""
|
|
|
|
Testing Scale() function on Z values.
|
|
|
|
"""
|
|
|
|
self._load_city_data()
|
|
|
|
# Mapping of City name to reference Z values.
|
|
|
|
zscales = (-3, 4, 23)
|
|
|
|
for zscale in zscales:
|
|
|
|
for city in City3D.objects.annotate(scale=Scale("point", 1.0, 1.0, zscale)):
|
|
|
|
self.assertEqual(city_dict[city.name][2] * zscale, city.scale.z)
|
|
|
|
|
|
|
|
def test_translate(self):
|
|
|
|
"""
|
|
|
|
Testing Translate() function on Z values.
|
|
|
|
"""
|
|
|
|
self._load_city_data()
|
|
|
|
ztranslations = (5.23, 23, -17)
|
|
|
|
for ztrans in ztranslations:
|
|
|
|
for city in City3D.objects.annotate(
|
|
|
|
translate=Translate("point", 0, 0, ztrans)
|
|
|
|
):
|
|
|
|
self.assertEqual(city_dict[city.name][2] + ztrans, city.translate.z)
|