def target(x, pattern: BaseGeometry, pos: BaseGeometry):
params = _TargetTransformParams(x[0], x[1], x[2], x[3])
pos_trans = _target_affine_transform(pos, params)
neg = box(*pos_trans.bounds).difference(pos_trans)
# neg = box(*pos.bounds).difference(pos)
# neg_trans = _target_affine_transform(neg, params)
pos_overlap = pattern.intersection(pos_trans).area
neg_overlap = pattern.intersection(neg).area
false_pos_overlap = pos_trans.difference(pattern).area
# return neg_overlap+false_pos_overlap-pos_overlap
return false_pos_overlap - 2.0 * pos_overlap + neg_overlap + 0.1 * abs(
x[0]) + 0.1 * abs(x[1])
def find_shape_in_index(shape: BaseGeometry, index):
# (minx, miny, maxx, maxy)
bounds = shape.bounds
lon = []
lat = []
weights = []
for result in index.intersection(bounds, objects="raw"):
point = result['point']
rect = result['bbox']
poly = Polygon([(r[0], r[1]) for r in rect])
inters = shape.intersection(poly)
# Intersection with bounds might not intersect with detailed poly
if inters:
weights.append(inters.area)
lon.append(point[0])
lat.append(point[1])
lon = np.array(lon)
lat = np.array(lat)
weights = np.array(weights)
weights = weights / np.sum(weights)
return GridLookupResults(lon, lat, weights)
def make_geom(geo_frame, voronoi_frame):
#new columns to add
voronoi_frame['area'] = None
#create full continent of europe
euro_geoms = [
geo_frame.loc[index]['geometry'] for index in range(len(geo_frame))
]
all_europe = unary_union(euro_geoms)
#test to see if voronoi shapes intersect with the europe shape
for index in range(len(voronoi_frame)):
current_shape = voronoi_frame.loc[index]['points']
intersect = BaseGeometry.intersection(all_europe.buffer(0),
current_shape.buffer(0))
voronoi_frame.loc[index, 'geometry'] = intersect
voronoi_frame.loc[index, 'area'] = intersect.area
#there is always an error where index 39 should be a part of norway (index 40)
nshape = voronoi_frame.loc[40]['geometry']
missing_part = voronoi_frame.loc[39]['geometry']
voronoi_frame.loc[40]['geometry'] = unary_union([nshape, missing_part])
voronoi_frame.loc[39] = None
return voronoi_frame
def make_geoms(vframe, geo_frame):
vframe['geometry'] = None
poly = geo_frame.unary_union
for index in range(135):
try:
loop_geom = BaseGeometry.intersection(
vframe.loc[index]['points'].buffer(0), poly.buffer(0))
vframe.loc[index, 'geometry'] = loop_geom
except:
True
#set projection as mercator for the new data frame
vframe.crs = {'init': 'epsg = 3395'}
return vframe
x, y = list(zip(*loop_points))
loop_points = list(zip(y, x))
poly = Polygon(loop_points)
voronoi_frame.loc[i, 'geometry'] = []
voronoi_frame.loc[i, 'points'] = poly
i += 1
except (ValueError, TypeError):
True
# PART 3: Make Voronoi shapes fit Brazil's shape
voronoi_frame['area'] = None
br_geoms = [cap.loc[i]['Geometria'] for i in range(len(cap))]
all_br = unary_union(br_geoms)
for i in range(len(voronoi_frame)):
cur_shape = voronoi_frame.loc[i]['points']
intersect = BaseGeometry.intersection(all_br.buffer(0),
cur_shape.buffer(0))
if i == 0: # We have to deal this way with the State of Acre
intersect = (
all_br.buffer(0)
) # This state is known as nowhere land. It's the Brazilian Wyoming.
voronoi_frame.loc[i, 'geometry'] = intersect
voronoi_frame.loc[i, 'area'] = intersect.area
# PART 4: Plot the map
voronoi_frame['map color'] = [
1, 2, 3, 4, 3, 4, 1, 2, 4, 2, 2, 1, 1, 2, 3, 4, 1, 2, 3, 4, 2, 1, 4, 3, 4,
2, 1
]
capital_pts = [(cap.loc[index]['Latitude'], cap.loc[index]['Longitude'])
for index in range(len(cap))]
fig, ax = plt.subplots()
def intersect_geometry_with_feature_class(geometry: BaseGeometry, in_layer_path: str,
output_geom_type: int,
epsg: int = None,
attribute_filter: str = None,
) -> BaseGeometry:
"""[summary]
Args:
geometry (BaseGeometry): [description]
in_layer_path (str): [description]
out_layer_path (str): [description]
output_geom_type (int): [description]
epsg (int, optional): [description]. Defaults to None.
attribute_filter (str, optional): [description]. Defaults to None.
Raises:
VectorBaseException: [description]
VectorBaseException: [description]
Returns:
BaseGeometry: [description]
"""
log = Logger('intersect_geometry_with_feature_class')
if output_geom_type not in [ogr.wkbMultiPoint, ogr.wkbMultiLineString]:
raise VectorBaseException('Unsupported ogr type for geometry intersection: "{}"'.format(output_geom_type))
log.debug('Intersection with feature class: Performing unary union on input: {}'.format(in_layer_path))
geom_union = get_geometry_unary_union(in_layer_path, epsg=epsg, attribute_filter=attribute_filter, clip_shape=geometry)
# Nothing to do if there were no features in the feature class
if not geom_union:
return
log.debug('Finding intersections (may take a few minutes)...')
tmr = Timer()
geom_inter = geometry.intersection(geom_union)
log.debug('Intersection done in {:.1f} seconds'.format(tmr.ellapsed()))
# Nothing to do if the intersection is empty
if geom_inter.is_empty:
return
# Single features and collections need to be converted into Multi-features
if output_geom_type == ogr.wkbMultiPoint and not isinstance(geom_inter, MultiPoint):
if isinstance(geom_inter, Point):
geom_inter = MultiPoint([(geom_inter)])
elif isinstance(geom_inter, LineString):
# Break this linestring down into vertices as points
geom_inter = MultiPoint([geom_inter.coords[0], geom_inter.coords[-1]])
elif isinstance(geom_inter, MultiLineString):
# Break this linestring down into vertices as points
geom_inter = MultiPoint(reduce(lambda acc, ls: acc + [ls.coords[0], ls.coords[-1]], list(geom_inter.geoms), []))
elif isinstance(geom_inter, GeometryCollection):
geom_inter = MultiPoint([geom for geom in geom_inter.geoms if isinstance(geom, Point)])
elif output_geom_type == ogr.wkbMultiLineString and not isinstance(geom_inter, MultiLineString):
if isinstance(geom_inter, LineString):
geom_inter = MultiLineString([(geom_inter)])
else:
raise VectorBaseException('Unsupported ogr type: "{}" does not match shapely type of "{}"'.format(output_geom_type, geom_inter.type))
return geom_inter
def voronoi_tesselation(region = read_gis()):
region_shape = region.unary_union
region['points'] = None
region['city'] = None
#read locations of city from file with pandas
top_cities = pd.read_csv('europe_1mil.csv')
x, y = top_cities['mercx'].tolist(), top_cities['mercy'].tolist()
name = top_cities['city_ascii'].tolist()
city_locs = [(name[index], (float(x[index]), float(y[index]))) for index in range(len(name))]
points = [item[1] for item in city_locs]
#add four extra points to later ignore
points.append((-500000000,-500000000))
points.append((-500000000,500000000))
points.append((500000000,-500000000))
points.append((500000000,500000000))
vor = Voronoi(points)
regions = vor.regions
pts = vor.vertices
i = 0
for part in regions:
loop_points = []
if -1 not in part and part != []:
loop_points = [pts[part[index]] for index in range(len(part))]
poly = Polygon(loop_points)
region.loc[i, 'points'] = poly
name_index = 0
for point in points:
if poly.contains(Point(point)):
region.loc[i, 'city'] = city_locs[name_index][0]
break
name_index += 1
i += 1
#only want to keep the ones that have city data
keep = [index for index in range(len(region))
if isinstance(region.iloc[index]['city'], str)]
keep = [region.index[item] for item in keep]
#filter out the rest
region = region.filter(keep, axis = 0)
#make geometry intersection of region geometry and voronoi tesselation
extras = []
for index in range(len(region)):
current_vor = region.loc[index]['points']
geom = BaseGeometry.intersection(current_vor.buffer(0),
region_shape.buffer(0))
region.at[index, 'geometry'] = geom
current_city = region.loc[index]['city']
color_1 = ['Dublin','London','Hamburg','Warsaw','Mannheim','Munich',
'Marseille', 'Rabat','Rome','Budapest','Athens','Bursa',
'Adana','El Giza','Amman','Karaj','Shiraz','Moscow',
'Yekaterinburg']
color_2 = ['Birmingham','Paris','Essen','Madrid','Milan','Stockholm',
'Kiev','Nizhny Novgorod','Istanbul','Aleppo','Tel Aviv-Yafo',
'Baghdad','Tbilisi','Tehran','Chelyabinsk']
color_3 = ['Lisbon','Copenhagen','Frankfurt','Turin','Algiers','Belgrade',
'Katowice','St. Petersburg','Kharkiv','Kazan','Tabriz',
'Kuwait','Cairo','Beirut','Ankara']
color_4 = ['Brussels','Stuttgart','Tunis','Vienna','Alexandria','Minsk',
'Izmir','Rostov','Yerevan','Damascus','Mashhad']
color_5 = ['Barcelona','Berlin','Bucharest','Naples','Tripoli','Mosul',
'Isfahan','Baku', 'Manchester','Casablanca']
if current_city in color_1:
region.loc[index, 'color'] = 1
elif current_city in color_2:
region.loc[index, 'color'] = 2
elif current_city in color_3:
region.loc[index, 'color'] = 3
elif current_city in color_4:
region.loc[index, 'color'] = 4
elif current_city in color_5:
region.loc[index, 'color'] = 5
else:
region.loc[index, 'color'] = 6
return region.to_crs(epsg = 4326)
def is_inside(a: BaseGeometry,
b: BaseGeometry,
*,
threshold: float = 0.05) -> bool:
""" Checks if one geometry (a) is inside other (b)"""
return a.intersection(b).area / (b.area + 1e-8) >= threshold