def collapse_zip_codes(self):
# The ESRI ZIP Code layer breaks ZIP Codes up along county
# boundaries, so we need to collapse them first before
# proceeding
if len(self.zipcodes) > 0:
return
for feature in self.layer:
zipcode = feature.get(self.name_field)
geom = feature.geom.geos
if zipcode not in self.zipcodes:
self.zipcodes[zipcode] = geom
else:
# If it's a MultiPolygon geom we're adding to our
# existing geom, we need to "unroll" it into its
# constituent polygons
if isinstance(geom, MultiPolygon):
subgeoms = list(geom)
else:
subgeoms = [geom]
existing_geom = self.zipcodes[zipcode]
if not isinstance(existing_geom, MultiPolygon):
new_geom = MultiPolygon([existing_geom])
new_geom.extend(subgeoms)
self.zipcodes[zipcode] = new_geom
else:
existing_geom.extend(subgeoms)
def save(self, verbose=False):
# The ESRI ZIP Code layer breaks ZIP Codes up along county
# boundaries, so we need to collapse them first before
# proceeding
zipcodes = {}
for feature in self.layer:
zipcode = feature.get('POSTAL')
geom = feature.geom.geos
if zipcode not in zipcodes:
zipcodes[zipcode] = geom
else:
# If it's a MultiPolygon geom we're adding to our
# existing geom, we need to "unroll" it into its
# constituent polygons
if isinstance(geom, MultiPolygon):
subgeoms = list(geom)
else:
subgeoms = [geom]
existing_geom = zipcodes[zipcode]
if not isinstance(existing_geom, MultiPolygon):
new_geom = MultiPolygon([existing_geom])
new_geom.extend(subgeoms)
zipcodes[zipcode] = new_geom
else:
existing_geom.extend(subgeoms)
sorted_zipcodes = sorted(zipcodes.iteritems(), key=lambda x: int(x[0]))
now = datetime.datetime.now()
num_created = 0
for i, (zipcode, geom) in enumerate(sorted_zipcodes):
if not geom.valid:
geom = geom.buffer(0.0)
if not geom.valid:
print >> sys.stderr, 'Warning: invalid geometry for %s' % zipcode
geom.srid = 4326
zipcode_obj, created = Location.objects.get_or_create(
name=zipcode,
normalized_name=zipcode,
slug=zipcode,
location_type=self.location_type,
location=geom,
centroid=geom.centroid,
display_order=i,
city=self.city,
source='ESRI',
area=geom.transform(3395, True).area,
is_public=True,
creation_date=now,
last_mod_date=now,
)
if created:
num_created += 1
if verbose:
print >> sys.stderr, '%s ZIP Code %s ' % (
created and 'Created' or 'Already had', zipcode_obj.name)
return num_created
def save(self, verbose=False):
# The ESRI ZIP Code layer breaks ZIP Codes up along county
# boundaries, so we need to collapse them first before
# proceeding
zipcodes = {}
for feature in self.layer:
zipcode = feature.get('POSTAL')
geom = feature.geom.geos
if zipcode not in zipcodes:
zipcodes[zipcode] = geom
else:
# If it's a MultiPolygon geom we're adding to our
# existing geom, we need to "unroll" it into its
# constituent polygons
if isinstance(geom, MultiPolygon):
subgeoms = list(geom)
else:
subgeoms = [geom]
existing_geom = zipcodes[zipcode]
if not isinstance(existing_geom, MultiPolygon):
new_geom = MultiPolygon([existing_geom])
new_geom.extend(subgeoms)
zipcodes[zipcode] = new_geom
else:
existing_geom.extend(subgeoms)
sorted_zipcodes = sorted(zipcodes.iteritems(), key=lambda x: int(x[0]))
now = datetime.datetime.now()
num_created = 0
for i, (zipcode, geom) in enumerate(sorted_zipcodes):
if not geom.valid:
geom = geom.buffer(0.0)
if not geom.valid:
print >> sys.stderr, 'Warning: invalid geometry for %s' % zipcode
geom.srid = 4326
zipcode_obj, created = Location.objects.get_or_create(
name = zipcode,
normalized_name = zipcode,
slug = zipcode,
location_type = self.location_type,
location = geom,
centroid = geom.centroid,
display_order = i,
city = self.city,
source = 'ESRI',
area = geom.transform(3395, True).area,
is_public = True,
creation_date = now,
last_mod_date = now,
)
if created:
num_created += 1
if verbose:
print >> sys.stderr, '%s ZIP Code %s ' % (created and 'Created' or 'Already had', zipcode_obj.name)
return num_created
def convert_region_to_polygon(
region_queue_shape: RegionAdiacentCells) -> Polygon:
try:
if not region_queue_shape:
logger.info(
'convert_region_to_polygon region_queue_shape None. Exit')
return None
list_shapesrow_region = region_queue_shape.get_rowshapesvertex()
if not list_shapesrow_region:
return None
list_rectangles = list()
for single_shape in list_shapesrow_region.get_listgroupvertex():
if not single_shape:
continue
list_points = list()
for vertex in single_shape.get_listvertex():
if not vertex:
continue
tuple_point = vertex.to_tuple()
if not tuple_point:
continue
list_points.append(tuple_point)
sub_rectangle = Polygon(list_points)
list_rectangles.append(sub_rectangle)
multi_polygon = MultiPolygon()
multi_polygon.extend(list_rectangles)
merged_polygon = multi_polygon.unary_union
del multi_polygon
logger.debug(
'convert_shapes_to_list_rectangles Created, typeof: {}'.format(
type(merged_polygon).__name__))
# merged_polygon = cascaded_union(list_rectangles)
# FIXME: Check if the operations above gives the same results
return merged_polygon
except Exception as ex:
logger.error(
'convert_shapes_to_list_rectangles Exception {}'.format(ex))
return None
def _combine(geometries):
"""
Try to combine geometries with least computing power necessary.
If there are both lines and polygons, all lines are first buffered
one by one into polygons, and then added to a MultiPolygon together
with the other polygons.
If there are only polygons, they are combined in a single
multipolygon.
If there are only lines, they are combined in a single multilinestring
"""
if len(geometries) == 1:
return geometries[0]
lines = [g for g in geometries
if isinstance(g, (LineString))]
multilines = [g for g in geometries
if isinstance(g, (MultiLineString))]
polygons = [g for g in geometries
if isinstance(g, (Polygon))]
multipolygons = [g for g in geometries
if isinstance(g, (MultiPolygon))]
if polygons or multipolygons:
if lines or multilines:
# All kinds of stuff present
lines.extend([l for ml in multilines for l in ml])
print 'buffering lines'
for l in lines:
polygons.append(l.buffer(0.0001, 2))
result = MultiPolygon(polygons)
for mp in multipolygons:
result.extend(mp)
else:
# Only lines or multilines
result = MultiLineString(lines)
for ml in multilines:
result.extend(ml)
return result
