def test_wkt_vectorize_one_wkt(self):
max_points = GeoVectorizer.max_points(brt_wkt, osm_wkt)
vectorized = []
target_set = SOURCE_DATA['intersection_wkt']
for index in range(len(target_set)):
vectorized.append(
GeoVectorizer.vectorize_wkt(target_set[index], max_points))
self.assertEqual(len(target_set), len(brt_wkt))
def test_interpolate(self):
interpolated = GeoVectorizer.interpolate(input_geom,
len(input_geom) * 2)
for index, _ in enumerate(interpolated):
result = list(interpolated[index])
expected = list(output_geom[index])
self.assertListEqual(result,
expected,
msg='Lists differ at index %i' % index)
def test_wkt_vectorize_two_wkt(self):
vectorized = []
max_points = GeoVectorizer.max_points(brt_wkt, osm_wkt)
for index in range(len(brt_wkt)):
vectorized.append(
GeoVectorizer.vectorize_two_wkts(brt_wkt[index],
osm_wkt[index], max_points))
num_records = len(vectorized)
num_points = len(vectorized[0])
num_features = len(vectorized[0][0])
self.assertEqual(num_records, 13)
self.assertEqual(num_points, 47)
self.assertEqual(num_features, GEO_VECTOR_LEN)
for record in vectorized:
points = [point for point in record if point[0] > 0]
# Every first point should have a "render" code
self.assertEqual(points[0][RENDER_INDEX], 1)
# Every last point should have a "full stop" code
self.assertEqual(points[-1][FULL_STOP_INDEX], 1)
training_data = pandas.read_csv(TOPOLOGY_TRAINING_CSV)
truncated_data = np.array([
record for record in training_data.values
if len(record[0] + ';' + record[1]) <= MAX_SEQUENCE_LEN
])
raw_training_set = training_data['brt_wkt'] + ';' + training_data['osm_wkt']
raw_target_set = training_data['intersection_wkt']
print(len(raw_training_set), 'data points in training set')
brt_wkt = truncated_data[:, 0]
osm_wkt = truncated_data[:, 1]
intersection_set = truncated_data[:, 2]
centroid_distance = truncated_data[:, 3]
geom_distance = truncated_data[:, 4]
brt_centroid = [
GeoVectorizer.vectorize_wkt(point, 1) for point in truncated_data[:, 5]
]
osm_centroid = [
GeoVectorizer.vectorize_wkt(point, 1) for point in truncated_data[:, 6]
]
brt_centroid_rd = [
GeoVectorizer.vectorize_wkt(point, 1) for point in truncated_data[:, 7]
]
osm_centroid_rd = [
GeoVectorizer.vectorize_wkt(point, 1) for point in truncated_data[:, 8]
]
intersection_surface = truncated_data[:, 9]
training_set = brt_wkt + ';' + osm_wkt
print(len(training_set), 'max length data points in training set')
import numpy as np
from model.topoml_util.GeoVectorizer import GeoVectorizer
from shapely.geometry import Polygon
from shapely.wkt import loads
SET_SIZE = 100000
TRIANGLES = '../files/triangles.npz'
print('Creating triangles')
raw_training_vectors = np.random.normal(size=(SET_SIZE, 6, 2))
triangle_sets = np.array([[Polygon(point_set[0:3]).wkt, Polygon(point_set[3:]).wkt]
for point_set in raw_training_vectors])
max_points = GeoVectorizer.max_points(triangle_sets[:, 0], triangle_sets[:, 1])
print('Intersecting triangles and pruning')
intersection_area = []
intersection_vectors = []
for index, (a, b) in enumerate(triangle_sets):
# if loads(a).intersection_surface_area(loads(b)).type == 'Polygon': # constrain to actually intersecting
intersection = loads(a).intersection(loads(b))
intersection_area.append(intersection.area)
intersection_vectors.append(GeoVectorizer.vectorize_wkt(intersection.wkt, 12))
training_vectors = np.reshape(raw_training_vectors, (SET_SIZE, 12))
(_, GEO_VECTOR_LEN) = np.array(training_vectors).shape
intersection_area = np.array(intersection_area)
print('Saving compressed numpy data file', TRIANGLES)
np.savez_compressed(
def test_decypher_gmm_geom(self):
pred = gmm_output.prediction
sample_size = 10
points = GeoVectorizer(gmm_size=5).decypher_gmm_geom(
pred, sample_size=sample_size)
self.assertEqual(len(points), 40)
def test_decypher(self):
self.maxDiff = None
max_points = GeoVectorizer.max_points(brt_wkt, osm_wkt)
target_vector = GeoVectorizer.vectorize_wkt(target_wkt[0], max_points)
decyphered = GeoVectorizer.decypher(target_vector)
self.assertEqual(decyphered, target_wkt[0])
def test_max_points(self):
max_points = GeoVectorizer.max_points(brt_wkt, osm_wkt)
self.assertEqual(max_points, 47)