def to_geojson(regions): # pragma: no cover
features = []
for code, region in regions.items():
# calculate the maximum radius of each polygon
boundary = region.boundary
if isinstance(boundary, shapely.geometry.base.BaseMultipartGeometry):
boundaries = list(boundary.geoms)
else:
boundaries = [boundary]
radii = []
for boundary in boundaries:
# flip x/y aka lon/lat to lat/lon
boundary = numpy.fliplr(numpy.array(boundary))
ctr_lat, ctr_lon = geocalc.centroid(boundary)
radii.append(geocalc.max_distance(ctr_lat, ctr_lon, boundary))
radius = round(max(radii) / 1000.0) * 1000.0
features.append({
'type': 'Feature',
'properties': {
'alpha2': code,
'radius': radius,
},
'geometry': shapely.geometry.mapping(region),
})
def _sort(value):
return value['properties']['alpha2']
features = sorted(features, key=_sort)
lines = ',\n'.join([json.dumps(f, sort_keys=True, separators=(',', ':'))
for f in features])
return '{"type": "FeatureCollection", "features": [\n' + lines + '\n]}\n'
def to_geojson(regions): # pragma: no cover
features = []
for code, region in regions.items():
# calculate the maximum radius of each polygon
boundary = region.boundary
if isinstance(boundary, shapely.geometry.base.BaseMultipartGeometry):
boundaries = list(boundary.geoms)
else:
boundaries = [boundary]
radii = []
for boundary in boundaries:
# flip x/y aka lon/lat to lat/lon
boundary = numpy.fliplr(numpy.array(boundary))
ctr_lat, ctr_lon = geocalc.centroid(boundary)
radii.append(geocalc.max_distance(ctr_lat, ctr_lon, boundary))
radius = round(max(radii) / 1000.0) * 1000.0
features.append({
'type': 'Feature',
'properties': {
'alpha2': code,
'radius': radius,
},
'geometry': shapely.geometry.mapping(region),
})
def _sort(value):
return value['properties']['alpha2']
features = sorted(features, key=_sort)
lines = ',\n'.join([
json.dumps(f, sort_keys=True, separators=(',', ':')) for f in features
])
return '{"type": "FeatureCollection", "features": [\n' + lines + '\n]}\n'
def to_geojson(regions): # pragma: no cover
features = []
features_buffered = []
for code, region in regions.items():
# calculate the maximum radius of each polygon
boundary = region.boundary
if isinstance(boundary, shapely.geometry.base.BaseMultipartGeometry):
boundaries = list(boundary.geoms)
else:
boundaries = [boundary]
radii = []
for boundary in boundaries:
# flip x/y aka lon/lat to lat/lon
boundary = numpy.fliplr(numpy.array(boundary))
# calculate centroid
ctr_lat, ctr_lon = boundary.mean(axis=0)
ctr_lat = float(ctr_lat)
ctr_lon = float(ctr_lon)
radii.append(geocalc.max_distance(ctr_lat, ctr_lon, boundary))
radius = round(max(radii) / 1000.0) * 1000.0
features.append({
'type': 'Feature',
'properties': {
'alpha2': code,
'radius': radius,
},
'geometry': shapely.geometry.mapping(region),
})
# Build up region buffers, to create shapes that include all of
# the coastal areas and boundaries of the regions and anywhere
# a cell signal could still be recorded. The value is in decimal
# degrees (1.0 == ~100km) but calculations don't take projection
# / WSG84 into account.
# After buffering remove any parts that crosses the -180.0/+180.0
# longitude boundary to the east or west.
buffered = (region.buffer(0.5).simplify(0.02).difference(
DATELINE_EAST).difference(DATELINE_WEST))
features_buffered.append({
'type':
'Feature',
'properties': {
'alpha2': code,
},
'geometry':
shapely.geometry.mapping(buffered),
})
def _sort(value):
return value['properties']['alpha2']
def _to_collection(features):
# put each region on a single line to get a diffable output
lines = ',\n'.join([
json.dumps(feature, sort_keys=True, separators=(',', ':'))
for feature in sorted(features, key=_sort)
])
return ('{"type": "FeatureCollection", '
'"features": [\n' + lines + '\n]}\n')
return (_to_collection(features), _to_collection(features_buffered))
def to_geojson(regions): # pragma: no cover
features = []
features_buffered = []
for code, region in regions.items():
# calculate the maximum radius of each polygon
boundary = region.boundary
if isinstance(boundary, shapely.geometry.base.BaseMultipartGeometry):
boundaries = list(boundary.geoms)
else:
boundaries = [boundary]
radii = []
for boundary in boundaries:
# flip x/y aka lon/lat to lat/lon
boundary = numpy.fliplr(numpy.array(boundary))
ctr_lat, ctr_lon = geocalc.centroid(boundary)
radii.append(geocalc.max_distance(ctr_lat, ctr_lon, boundary))
radius = round(max(radii) / 1000.0) * 1000.0
features.append({
'type': 'Feature',
'properties': {
'alpha2': code,
'radius': radius,
},
'geometry': shapely.geometry.mapping(region),
})
# Build up region buffers, to create shapes that include all of
# the coastal areas and boundaries of the regions and anywhere
# a cell signal could still be recorded. The value is in decimal
# degrees (1.0 == ~100km) but calculations don't take projection
# / WSG84 into account.
# After buffering remove any parts that crosses the -180.0/+180.0
# longitude boundary to the east or west.
buffered = (region.buffer(0.5)
.simplify(0.02)
.difference(DATELINE_EAST)
.difference(DATELINE_WEST))
features_buffered.append({
'type': 'Feature',
'properties': {
'alpha2': code,
},
'geometry': shapely.geometry.mapping(buffered),
})
def _sort(value):
return value['properties']['alpha2']
def _to_collection(features):
# put each region on a single line to get a diffable output
lines = ',\n'.join([json.dumps(feature,
sort_keys=True,
separators=(',', ':'))
for feature in sorted(features, key=_sort)])
return ('{"type": "FeatureCollection", '
'"features": [\n' + lines + '\n]}\n')
return (_to_collection(features), _to_collection(features_buffered))
