def update_geojson_choropleth(self):
geo_data = pygeoj.load(script_file_path + "/central_london.geojson")
avg_area = self.df_disposals.groupby('area_code').mean()
avg_district = self.df_disposals.groupby('district_code').mean()
avg_sector = self.df_disposals.groupby('sector_code').mean()
for feature in geo_data:
ppt = feature.properties
area, district, sector = extract_postcode_stubs(ppt['name'])
ppt['area'] = area
ppt['district'] = district
ppt['sector'] = sector
mkts = [m for m in extract_markets(ppt['name']) if m is not None]
ppt['sub_market'] = str(mkts[0])
ppt['wider_market'] = str(mkts[-1])
ppt.pop('column_1495195118190')
ppt.pop('cartodb_id')
ppt['average_rent'] = self.average_cascade('rent', area, district,
sector, avg_area,
avg_district,
avg_sector)
ppt['average_rates'] = self.average_cascade(
'rates', area, district, sector, avg_area, avg_district,
avg_sector)
ppt['average_size_min'] = self.average_cascade(
'size_min', area, district, sector, avg_area, avg_district,
avg_sector)
ppt['average_size_max'] = self.average_cascade(
'size_max', area, district, sector, avg_area, avg_district,
avg_sector)
geo_data.save("pyg_test.geojson")
def json_to_txt(jsonfile, maskland):
drift_json = pygeoj.load(jsonfile)
lats1 = []
lons1 = []
lats2 = []
lons2 = []
drift_m = []
n = 0
for feature in drift_json:
n += 1
print 'new feature', n
lat1 = feature._data['properties']['lat1']
lon1 = feature._data['properties']['lon1']
if maskland == True:
land = mask_land_basemap(lat1, lon1)
if land != 1:
lats1.append(feature._data['properties']['lat1'])
lons1.append(feature._data['properties']['lon1'])
lats2.append(feature._data['properties']['lat2'])
lons2.append(feature._data['properties']['lon2'])
#drift_m.append(feature._data['properties']['drift_m'])
drift_m.append(np.float(
feature._data['properties']['drift_m']))
else:
print 'land'
else:
lats1.append(feature._data['properties']['lat1'])
lons1.append(feature._data['properties']['lon1'])
lats2.append(feature._data['properties']['lat2'])
lons2.append(feature._data['properties']['lon2'])
drift_m.append(np.float(feature._data['properties']['drift_m']))
return lats1, lons1, lats2, lons2, drift_m
def returnCordinates(path):
files = os.listdir(path)
LongtitudeList = []
LatitudeList = []
for file in files[1:]:
if file.endswith(
"housenumbers.geojson"
): # four geojson files skiped,this line will be change
continue
file = path + '\\' + file
try:
test = pygeoj.load(filepath=file)
except:
continue
citydict = dict()
# print("++++++++++++++",file,"+++++++++++++")#I'll print to see contents in file,it will be deleted
for feature in test:
coordinates = feature.geometry.coordinates
if feature.geometry.type == "Point":
LongtitudeList.append(coordinates[0])
LatitudeList.append(coordinates[1])
elif feature.geometry.type == "LineString":
for coordinate in coordinates:
LongtitudeList.append(coordinate[0])
LatitudeList.append(coordinate[1])
elif feature.geometry.type == "Polygon":
for coordinate in coordinates[0]:
LongtitudeList.append(coordinate[0])
LatitudeList.append(coordinate[1])
return [
np.min(LongtitudeList),
np.max(LongtitudeList),
np.min(LatitudeList),
np.max(LatitudeList)
]
def jsonCase(filepath):
try:
myGeojson = pygeoj.load(filepath=filepath)
pointList = []
def getCoordinates(listInList):
coordinates = []
for sublist in listInList:
if type(sublist) is list:
if type(sublist[0]) is list:
coordinates.extend(getCoordinates(sublist))
else:
coordinates.extend(listInList)
break
else:
coordinates.append(listInList)
break
return coordinates
for features in myGeojson:
pointList.extend(
list(
map(tuple,
getCoordinates(features.geometry.coordinates))))
return (convex_hull(pointList), None)
# errors
except:
return (None, "File Error!")
def update(request, modelo):
datos = request.data.get("data")
if datos is None:
raise ValidationError({"data":"es necesario en geojson"})
if not isinstance(datos, str):
raise ValidationError({"data":"debe ser un str"})
datos = datos.replace("'", "\"")
try:
datos = json.loads(datos)
geo = pygeoj.load(data=datos)
data = []
for i in geo._data["features"]:
nuevo = i["properties"].get("nuevo")
modificar = i["properties"].get("modificar")
eliminar = i["properties"].get("eliminar")
if nuevo is not None or modificar is not None or eliminar is not None:
data.append(i)
geo._data["features"] = data
importer = CapaImporter(geo, None, None, verificar_nombre=False,
verificar_categoria=False)
importer.alterar_registros(modelo)
queryset = modelo.objects.all()
data = serialize('geojson', queryset,
geometry_field='geom')
data = json.loads(data)
return Response(data)
#except json.decoder.JSONDecodeError as e:
# raise ValidationError({"mensaje": "json invalido, "+e})
except ValueError as e:
print(e)
raise ValidationError({"mensaje": "el geojson es invalido"})
def AddRegion2LanLongData(LanLogData, GeojsonRegion, CsvFileName):
from shapely.geometry import shape, Point
import pygeoj
import pandas as pd
import numpy as np
DatosTrain = pd.read_csv(LanLogData, index_col=0)
js = pygeoj.load(GeojsonRegion)
# Seleccionamos las columnas de longitud y latitud
LongLat = DatosTrain.loc[:, ["lng", "lat"]]
DatosTrain["Region"] = pd.Series(np.nan, index=DatosTrain.index)
for i in range(0, len(LongLat.index)):
PuntoCoord = LongLat.iloc[i]
Lng = PuntoCoord.values[0]
Lat = PuntoCoord.values[1]
point1 = Point(Lng, Lat)
# check each polygon to see if it contains the point
for feature in js:
polygon = shape(feature.geometry)
if polygon.contains(point1):
DatosTrain.iloc[i, (len(DatosTrain.columns) - 1)] = feature.properties["name"]
return DatosTrain.to_csv(CsvFileName, sep=";", encoding="UTF-8")
def getBoundingBox(name, path):
filepath = "%s\%s.json" % (path, name)
try:
myGeojson = pygeoj.load(filepath=filepath)
click.echo(myGeojson.bbox)
except ValueError:
myJson = open(filepath, "rb")
myJson = json.load(myJson)
myGeojson = {"type": "FeatureCollection", "features": []}
myGeojson.get("features").append(myJson)
myGeojson = pygeoj.load(data=myGeojson)
click.echo(myGeojson.bbox)
except:
click.echo("File not Found")
def main(argv):
help_message = 'test.py <inputfile> <outputfile>'
if len(argv) < 2:
print(help_message)
sys.exit(2)
else:
inputfile = argv[0]
outputfile = argv[1]
print("Reading data from " + inputfile)
# Setting up the user defined problem in pygmo
prob = pg.problem(TestOptimizer(inputfile))
solution_size = 8
# Start with an initial set of 100 sets
pop = pg.population(prob, size=solution_size)
# Set the algorithm to non-dominated sorting GA
algo = pg.algorithm(pg.nsga2(gen=40))
# Optimize
pop = algo.evolve(pop)
# This returns a set of optimal vectors and corresponding fitness values
fits, vectors = pop.get_f(), pop.get_x()
print("Writing output to " + outputfile)
jsonfile = pygeoj.load(filepath=inputfile)
num_districts = len(jsonfile)
counter = 0
for feature in jsonfile:
for sol in range(solution_size):
feature.properties = {"sol" + str(sol): str(vectors[sol][counter])}
counter += 1
# Save output
jsonfile.save(outputfile)
def ogr2ogrCase(filepath):
"""Method for extracting the crs of a valid GeoJSON file\n
@param filepath Full path to GeoJSON
@returns a boundingbox as an array in a tuple in WGS84, formated like ([minLong, minLat, maxLong, maxLat], None)
"""
try:
myGeojson = pygeoj.load(filepath=filepath)
crs = myGeojson.crs['properties']['name']
if crs.find('EPSG') != -1:
crs = int(crs.split(':')[-1])
else:
return (None, "No reference system found or not as EPSG Code")
pointList = []
for features in myGeojson:
# the coordinates are beeing extracted from the GeoJSON and transformed into wgs84 coordinates
pointList.extend(
list(
map(
lambda point: CRSTransform(point[1], point[0], crs
),
list(
map(
tuple,
getCoordinatesFromGeoJson(
features.geometry.coordinates))))))
return (convex_hull(pointList), None)
except:
return (None, "File Error!")
def geojsonCase(filepath):
"""Method for extracting the boundingbox of a valid GeoJSON file
@param filepath Full path to GeoJSON
@returns a boundingbox as an array in a tuple in WGS84, formated like ([minLong, minLat, maxLong, maxLat], None)
"""
try:
myGeojson = pygeoj.load(filepath=filepath)
return (myGeojson.bbox, None)
# except ValueError: # if geojson is not a featureCollection
# myJson = open(filepath, "rb")
# myJson = json.load(myJson)
# # raw FeatureCollection
# myGeojson = {
# "type": "FeatureCollection",
# "features": []
# }
# myGeojson.get("features").append(myJson)
# myGeojson = pygeoj.load(data=myGeojson)
# return (myGeojson.bbox, None)
# errors
except:
return (None, "File Error!")
def coord_parse(point):
x = []
testfile = pygeoj.load(data=dict(point))
for feature in testfile:
p = feature.geometry.coordinates
x.append(p)
break
return x
def getCRS(filePath):
''' extracts EPSG number of the taken coordinate reference system (short: crs), as standard the crs WGS84 is used. \n
input "filePath": type string, file path to geojson File \n
returns the epsg code of the used coordinate reference system: type int, EPSG number of taken crs
'''
def extractAfterKeyword(searchParam, gjsonContent):
''' searches for the value fo the dict entry with keyword which is given as input \n
input "searchParam": type string, keyword for which is searched in the dict \n
input "gjsonContent": type dict, Content of geojson File
'''
if type(gjsonContent) == dict:
for keyContent, valueContent in gjsonContent.items():
if keyContent == searchParam:
extracted.append(valueContent)
if type(valueContent) == dict or type(valueContent) == list:
extractAfterKeyword(searchParam, valueContent)
if type(gjsonContent) == list:
for element in gjsonContent:
extractAfterKeyword(searchParam, element)
try:
gjsonContent = pygeoj.load(filePath)
crsCode = gjsonContent.crs
if not crsCode:
return hf.WGS84_EPSG_ID
else:
for key, value in crsCode.items():
if key == "properties":
try:
if value["name"] == "urn:ogc:def:crs:OGC:2:84":
return hf.WGS84_EPSG_ID
elif value["name"]:
splittedCrs = value["name"].split(":")
for elem in splittedCrs:
try:
if int(elem) is not None:
crsCode = int(elem)
return crsCode
except:
pass
except:
pass
#formats like urn:ogc:def:crs:EPSG::25832
return hf.WGS84_EPSG_ID
except:
gjsonContent = extractContentFromPath(filePath)
#4326 is the standard epsg after http://wiki.geojson.org/GeoJSON_draft_version_6#Specification
crsCode = hf.WGS84_EPSG_ID
extracted = []
extractAfterKeyword("crs", gjsonContent)
if len(extracted) != 0:
if type(extracted[0]) == dict and "properties" in extracted[
0] and "code" in extracted[0]["properties"]:
crsCode = extracted[0]["properties"]["code"]
return crsCode
def _return_geo_walk_poly(geo_file):
testfile = pygeoj.load(geo_file)
for feature in testfile:
#print (feature.geometry.type)
#print (feature.geometry.coordinates)
foot = {
"type": feature.geometry.type,
"coordinates": feature.geometry.coordinates
}
return (foot)
def geojsonCase(filepath):
"""Method for extracting the boundingbox of a valid GeoJSON file\n
@param filepath Full path to GeoJSON
@returns a boundingbox as an array in a tuple in WGS84, formated like ([minLong, minLat, maxLong, maxLat], None)
"""
try:
myGeojson = pygeoj.load(filepath=filepath)
return (myGeojson.bbox, None)
except:
return (None, "File Error!")
def from_file(filepath, encoding="utf8"):
def decode(value):
if isinstance(value, str):
return value.decode(encoding)
else:
return value
# shapefile
if filepath.lower().endswith(".shp"):
shapereader = pyshp.Reader(filepath)
# load fields, rows, and geometries
# Field name is first value in field, first value in shapereader is delete flag
fields = [decode(field[0]) for field in shapereader.fields[1:]]
rows = [[decode(value) for value in record]
for record in shapereader.iterRecords()]
def getgeoj(obj):
""" Get list of geojson features and capture bbox if alreaday calculated"""
# .__Geo_interface__ returns geojson dict
geoj = obj.__geo_interface__
# Shapefiles store feature bounding boxes - except points obvy
if hasattr(obj, "bbox"):
geoj["bbox"] = obj.bbox
return geoj
geometries = [getgeoj(shape) for shape in shapereader.iterShapes()]
# load projection string from .prj file if exists
if os.path.lexists(filepath[:-4] + ".prj"):
crs = open(filepath[:-4] + ".prj", "r").read()
else:
crs = "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs"
return fields, rows, geometries, crs
# geojson file
elif filepath.lower().endswith((".geojson", ".json")):
geojfile = pygeoj.load(filepath)
# load fields, rows, and geometries
fields = [decode(field) for field in geojfile.common_attributes]
rows = [[decode(feat.properties[field]) for field in fields]
for feat in geojfile]
geometries = [feat.geometry.__geo_interface__ for feat in geojfile]
# load crs
crs = geojfile.crs
return fields, rows, geometries, crs
else:
raise Exception(
"Could not create vector data from the given filepath:"
" the filetype extension is either missing or not supported")
def isValid(filePath):
'''
Checks whether it is valid GML or not. \n
input "path": type string, path to file which shall be extracted \n
output true if file is valid, false if not
'''
try:
ogr2ogr.main(["","-f", "GeoJSON", "outputV.json", filePath])
myGeojson = pygeoj.load(filepath="outputV.json")
return True
except:
raise Exception('The gml file from ' + filePath + ' has no valid gml Attributes')
def parse(**kwargs):
try:
path_file = kwargs.get('p', None)
MASTER_MD_DICT = kwargs.get('md', None)
is_debug = kwargs.get('is_debug', None)
gj = pygeoj.load(filepath=path_file)
if 'spatial' in MASTER_MD_DICT:
if 'files' in MASTER_MD_DICT['spatial']:
MASTER_MD_DICT['spatial']['files'].append({"name": path_file, "bbox": gj.bbox})
return MASTER_MD_DICT
except Exception as exc:
status_note(['! error while parsing geojson ', str(exc)], d=is_debug)
def get_bbox(self):
""" Corrected geometry of campaign.
:return: corrected coordinated
:rtype: [str]
"""
if not self.geometry:
return []
geometry = copy.deepcopy(self.geometry)
geometry['features'][0]['geometry']['coordinates'][0] = \
self.corrected_coordinates()
geojson = pygeoj.load(data=geometry)
return geojson.bbox
def neighborList(filename):
os.chdir('C:\\Users\\galli_000\\Desktop\\gitfolder\\HW1')
testfile = pygeoj.load(filename)
neighborList = []
for feature in testfile:
multipoly = shape(feature.geometry)
name = feature.properties['pri_neigh']
temp = {'Name':name, 'Geometry':multipoly}
neighborList.append(temp)
#print('Checking lasted: ', final - orig)
#print('Data >> Neighborhood\n')
return neighborList
def getBoundingBox(filePath):
'''
extract bounding box from gml \n
input "filepath": type string, file path to gml file \n
returns bounding box of the file: type list, length = 4 , type = float, schema = [min(longs), min(lats), max(longs), max(lats)]
'''
ogr2ogr.main(["","-f", "GeoJSON", "outputB.json", filePath])
myGeojson = pygeoj.load(filepath="outputB.json")
os.remove("outputB.json")
if myGeojson.bbox is not None:
return (myGeojson.bbox)
else:
raise Exception('The gml file from ' + filePath + ' has no BoundingBox')
def sql_single_min(query):
data = pygeoj.load('static/data/states.geojson')
sql = text(query)
result = db.engine.execute(sql)
min_hospital = ""
for row in result:
name = row['name'].encode('UTF-8')
state = row['state'].encode("utf-8")
mincost= float(row['avg_total_payments'])
min_hospital = "%s %s %.2f" % (name.decode("utf-8") , state.decode("utf-8"), mincost)
return min_hospital
def readGeoJSON(self, filename):
jsonfile = pygeoj.load(filepath=filename)
self.num_districts = len(jsonfile)
for feature in jsonfile:
ewz = feature.properties['EWZ']
cases = feature.properties['cases']
deaths = feature.properties['deaths']
recovered = feature.properties['recovered']
self.total_population += ewz
self.population.append(ewz)
self.total_num_positive += cases
self.num_positive.append(cases)
self.total_num_deaths += deaths
self.num_deaths.append(deaths)
def getVectorRepresentation(filePath):
'''
extracts coordinates from gml File (for vector representation) \n
input "filepath": type string, file path to gml file \n
returns extracted coordinates of content: type list, list of lists with length = 2
'''
ogr2ogr.main(["","-f", "GeoJSON", "outputV.json", filePath])
myGeojson = pygeoj.load(filepath="outputV.json")
properties= (myGeojson.get_feature(0).geometry.coordinates[0])
os.remove("outputV.json")
if properties is None:
raise Exception('The gml file from ' + filePath + ' has no VectorRepresentation')
else:
return properties
def getBoundingBox(filePath):
''' extract bounding box from geojson content \n
input "filePath": type string, file path to geojson File \n
returns bounding box: type list, length = 4 , type = float, schema = [min(longs), min(lats), max(longs), max(lats)]
'''
bbox = None
#gjsonContent is a FeatureCollection
try:
gjsonContent = pygeoj.load(data=convert3dto2d(filePath))
bbox = gjsonContent.bbox
#gjsonContent is a single geometrie and has to be converted to a FeatureCollection
except ValueError:
gjsonContent = convert3dto2d(filePath)
gjsonFeatureColl = {"type": "FeatureCollection", "features": []}
gjsonFeatureColl["features"].append(gjsonContent)
gjsonContent_FeatureColl = pygeoj.load(data=gjsonFeatureColl)
bbox = gjsonContent_FeatureColl.bbox
if not bbox:
raise Exception("Bounding box could not be extracted")
return bbox
def load_lsoa_polygons(self):
polygon_data = pygeoj.load(filepath="LondonLSOA.geojson")
spatial_entity_to_coordinates = {}
for feature in polygon_data:
coords = feature.geometry.coordinates
coords = coords[0][0]
lsoa_id = feature.properties['LSOA11CD']
xs = [i for i, j in coords]
ys = [j for i, j in coords]
spatial_entity_to_coordinates[lsoa_id] = [xs, ys]
return spatial_entity_to_coordinates
def merge_geojson(cls, folder, file_name, files):
geojson = pygeoj.new()
for path in files:
f = pygeoj.load(path)
for feature in f:
geojson.add_feature(obj=feature)
full_path = os.path.join(folder, file_name + ".json")
geojson.add_all_bboxes()
geojson.update_bbox()
geojson.save(full_path)
return full_path
def analysis_add_trafficzone(request):
if request.is_ajax() and request.POST:
trafficzone_filename = request.POST.get('trafficzone_filename')
file_path = "media/trafficzones/" + str(trafficzone_filename)
geofile = pygeoj.load(file_path)
zone_tally = 0
for feature in geofile:
zone_tally = zone_tally + 1
data = {}
data['no_trafficzones'] = zone_tally
data['trafficzone_filename'] = trafficzone_filename
data['zone_geojson'] = geojson.dumps(geofile)
return HttpResponse(json.dumps(data), content_type='application/json')
return HttpResponse("Non ajax post request")
def importar(self, request, *args, **kwargs):
def validar(capa):
if capa is None:
raise ValidationError({"data":"es necesario la capa"})
capa = self.request.data.get('data')
validar(capa)
nombre = self.request.data.get("nombre")
categoria = self.request.data.get("categoria")
if nombre is None:
raise ValidationError({"nombre": "es requerido"})
if categoria is None:
categoria = 1
capa = json.loads(capa)
geo = pygeoj.load(data=capa)
importer = CapaImporter(geo, nombre, categoria)
importer.importar_tabla()
return Response()
def stats(args):
if args.country:
france = []
files = [path.join(STATS_PATH, x) for x in os.listdir(STATS_PATH) if x.endswith('.geojson') and x != "france.geojson"]
files.sort()
counter = 0
for json_path in files:
counter += 1
log.info("{:.2f}% Treating {}".format(100 * counter / len(files), json_path))
with open(json_path) as fd:
department = geojson.load(fd)
for city in department.features:
if city.geometry:
[x1, x2, y1, y2] = pygeoj.load(data=FeatureCollection([city])).bbox
city.geometry = Polygon([[(x1, y1), (x1, y2), (x2, y2), (x2, y1)]])
france.append(city)
json_path = path.join(STATS_PATH, "france.geojson")
with open(json_path, 'w') as fd:
fd.write(geojson.dumps(FeatureCollection(france), indent=1))
elif args.department:
vectorized = get_vectorized_insee(args.department)
build_municipality_list(args.department.zfill(2), vectorized, force_download=args.force, umap=args.umap)
elif args.insee:
vectorized = {}
for insee in args.insee:
# Format of INSEE if [0-9]{2-3}[0-9]{3}
# the first part is the department number, the second the city unique id
# We just need to junk the last 3 caracters
department = insee[:-3]
vectorized[department] = get_vectorized_insee(department)
build_municipality_list(department,
vectorized[department],
given_insee=insee,
force_download=args.force,
umap=args.umap)
elif args.name:
# if we got a name, we must find the associated INSEE
args.insee = []
for name in args.name:
args.insee.append(get_insee_for(name))
stats(args)
else:
log.critical("Unhandled case")
def ogr2ogrCase(filepath):
"""Method for extracting the crs of a valid GeoJSON file\n
@param filepath Full path to GeoJSON
@returns a boundingbox as an array in a tuple in WGS84, formated like ([minLong, minLat, maxLong, maxLat], None)
"""
try:
myGeojson = pygeoj.load(filepath=filepath)
crs = myGeojson.crs['properties']['name']
if crs.find('EPSG') != -1:
crs = int(crs.split(':')[-1])
else:
return (None, "No reference system found or not as EPSG Code")
bbox = myGeojson.bbox
wgsBbox = CRSTransform(bbox[1], bbox[0], crs)
wgsBbox.extend(CRSTransform(bbox[3], bbox[2], crs))
return (wgsBbox, None)
except:
return (None, "File Error!")
def GenerateNeighborhoodsAdjacency(CityShapeFileLocation,
CityShapeFile): #Khorshed worked on it
directory = CityShapeFileLocation
files = [CityShapeFile]
for filename in files[:]:
testfile = pygeoj.load(directory + filename)
count = 0
a = []
aa = []
pair = []
for feature in testfile:
a.append(feature.geometry.coordinates)
aa.append(feature.properties['OBJECTID'])
pair.append([
feature.properties['District_N'],
feature.properties['Municipali']
])
count = count + 1
p = []
output = []
for i in aa:
p0 = Polygon(a[i - 1][0])
p = a
intpoly = []
for j in range(len(p)):
if p0.intersects(Polygon(p[j][0])) == True:
if aa[j] != i:
intpoly.append(aa[j])
output.append([i, intpoly])
FArray = []
Adj = []
for ii in range(len(output)):
Adj = []
for k in range(len(output[ii][1])):
Adj.append([
pair[output[ii][1][k] - 1][0],
pair[output[ii][1][k] - 1][1]
])
FArray.append([pair[ii][0], pair[ii][1], Adj])
return FArray
def index(request):
coord = ''
if request.method == "POST":
form = ImportGeojsonfileForm(request.POST, request.FILES)
if form.is_valid():
geoJson = request.FILES['import_file']
data = json.load(geoJson)
a = pygeoj.load(None, data)
for feature in a:
coord = feature.geometry.coordinates
gtype = feature.geometry.type
print(gtype)
# file_ = open(os.path.join(PROJECT_ROOT, 'filename'))
form = ImportGeojsonfileForm()
if (coord != ''):
geometry = ee.Geometry.MultiPolygon(coord)
else:
geometry = ee.Geometry.Polygon(
[[[84.97873462030498, 27.87424989960898],
[84.74527514764873, 27.563032482426987],
[85.20670092889873, 27.385144636789754],
[85.69833911249248, 27.368071821574812],
[85.95102465936748, 27.57277145564543],
[86.04166186639873, 27.840253798218345],
[85.70657885858623, 27.973748526646474],
[85.55826342889873, 27.95676744082692],
[85.29733813592998, 27.910662458572368]]])
context = {
# "tile2020" : getTile2020(geometry),
"tile2019": getTile2019(geometry),
"tile2018": getTile2018(geometry),
"tile2017": getTile2017(geometry),
"band_viz": getVisParam(),
# "form" : form,
"title": "Carbon Monoxide Emission",
"startDate": '2020-04-01',
"endDate": '2020-04-24',
"form": form,
}
return render(request, 'index.html', context)
def __init__(self, random_mode=RandomMode.UNIFORM_DISTRIBUTION_RANDOM, sigma=0.01):
# by default we set UNIFORM_DISTRIBUTION_RANDOM as Point in Polygon.
self._random_mode = random_mode
self.sigma = sigma
self.shelve = shelve.open('geo_tag.shelve')
try:
# self.abbrev_us_state is the relation between the state's full name and abbrev.
with open('us_state_abbrev.json') as json_file:
self._abbrev_us_state = json.load(json_file)
# self.city_datafile is a big json.
self._city_json_file = pygeoj.load(filepath="city.json")
# infer on place
self._init_city_state_mapping()
# infer on coordinate
self._init_coord_tree_cache()
# infer on user
self._init_location_coordinate_mapping()
except (ValueError, FileExistsError, FileNotFoundError) as err:
logger.critical(err)
exit(1)
def readGeoJSON(self, filename):
jsonfile = pygeoj.load(filepath=filename)
self.num_districts = len(jsonfile)
for feature in jsonfile:
residents = feature.properties['EWZ']
cases = feature.properties['cases']
deaths = feature.properties['deaths']
recovered = feature.properties['recovered']
area = feature.properties['KFL'] #in km²
mortality_rate = feature.properties['death_rate']
#t_type = feature.properties['Thünen-Typ'] #indicator if the area is rural and has low economy
self.total_population += residents
self.population.append(residents)
self.total_num_positive += cases
self.num_positive.append(cases)
self.total_num_deaths += deaths
self.num_deaths.append(deaths)
self.total_mortality_rate += mortality_rate
self.mortality_rate.append(mortality_rate)
def sql_min(query):
data = pygeoj.load('static/data/states.geojson')
sql = text(query)
result = db.engine.execute(sql)
for row in result:
state = 'US.' + str(row['state'].encode("utf-8"))
mincost = float(row['min'])
for feature in data:
if feature.properties["code_hasc"] == state:
feature.properties["name"] = "%.2f" % mincost
data.save('static/data/states.geojson')
with open('static/data/states.geojson') as f:
saved = json.load(f)
data_json = json.dumps(saved, ensure_ascii=False)
return data_json
__author__ = 'david'
from shapely.geometry import shape,Point
import pygeoj
import pandas as pd
import numpy as np
DatosTrain=pd.read_csv("data/DatosAValorar.csv",sep=";",index_col=0)
js = pygeoj.load("data/spain-communities.geojson")
#Seleccionamos las columnas de longitud y latitud
LongLat=DatosTrain.loc[:,['lng','lat']]
DatosTrain["Region"]=pd.Series(np.nan,index=DatosTrain.index)
for i in range(0,len(LongLat.index)):
PuntoCoord=LongLat.iloc[i]
Lng=PuntoCoord.values[0]
Lat=PuntoCoord.values[1]
point1 = Point(Lng,Lat)
# check each polygon to see if it contains the point
for feature in js:
polygon = shape(feature.geometry)
if polygon.contains(point1):
DatosTrain.iloc[i,(len(DatosTrain.columns)-1)]=feature.properties['name']
demo_stats = demo_stats.loc[demo_stats["gender"] != 'unknown']
demo_stats = demo_stats.loc[demo_stats["age_interval"] != 'unknown']
demo_stats = demo_stats[demo_stats.category == 'es_barsandrestaurants']
demo_stats["weekday"] = demo_stats["date"].map(lambda d: (d.weekday()))
demo_stats["weekday"] = demo_stats["weekday"].astype('string')
gbcn = demo_stats.groupby(["gender", "age_interval", "weekday", "merchant_zipcode"]).aggregate({ "payments": np.sum })
gbcn = gbcn.reset_index()
total_by_zipcode = gbcn.groupby(["gender" , "age_interval", "weekday"])["payments"].max()
gbcn['payments_proportion'] = gbcn.apply(lambda row: np.true_divide(row.payments, total_by_zipcode[row.gender, row.age_interval, row.weekday]), axis=1)
zip_code_geojson = pygeoj.load(filepath="../dataset/best_bcn.geojson")
geojson = {
"type": "FeatureCollection",
"features": []
}
for feature in zip_code_geojson:
zipcode = feature.properties['merchant_zipcode']
feature = {
"type": "Feature",
"properties": {
"payments_proportion": "0",
"zipcode": zipcode
},
"geometry": {
"type": "MultiPolygon",
other={},
geometry=fullgeom.__geo_interface__)
# Initiate results table
results = ResultsTable()
# Load contemporary table
for feat in pygeoj.load("BaseData/natearthprovs_codeupdates.geojson", encoding="latin1"):
if feat.properties["geonunit"] != "Vietnam": continue
results.add_province(start=None, #datetime.date(year=1946, month=1, day=1),
end=datetime.date(year=2014, month=12, day=31),
ids={"Name": feat.properties["name"],
"HASC": feat.properties["code_hasc"],
"ISO": feat.properties["iso_3166_2"],
"FIPS": feat.properties["fips"]
},
other={},
geometry=feat.geometry)
# Load events table
import sys
bnd_base = bnd['base'] +"/"+ bnd["resources"][0]["path"]
bnd_type = bnd['type']
meta = c_data.find({'name':match['name']})[0]
# dataset base and type
dset_base = meta['base'] +"/"+ meta["resources"][0]["path"]
dset_type = meta['type']
result = False
if meta['file_format'] in ["raster", "release"]:
if bnd_type == "boundary" and dset_type == "raster":
# python raster stats extract
# bnd_geo = cascaded_union([shape(shp) for shp in shapefile.Reader(bnd_base).shapes()])
bnd_geo = cascaded_union([shape(shp.geometry) for shp in pygeoj.load(bnd_base)])
extract = rs.zonal_stats(bnd_geo, dset_base, stats="min max")
if extract[0]['min'] != extract[0]['max']:
result = True
elif bnd_type == "boundary" and dset_type == "release":
result = True
else:
print "Error - Dataset type not yet supported (skipping dataset).\n"
continue
# check results and update tracker
if result == True:
cadastre_f = 'D:/DATA/g.meunier/Desktop/elev/emprise_bati_paris.geojson'
#YOUR ELEVATION FILE AS HDR
# expects to also find bil file in same folder
elevation_f = "elev-decoupe75.hdr"
#IF YOU WANT A SMALL PART OF PARIS (IF YOU DON'T USE ZERO IN radius_around
#THE ADDRESS YOU WANT
address_f = ""
address_f = "20 rue Gasnier-Guy Paris"
#AND THE RADIUS AROUND THIS ADDRESS IN METER (OR ZERO)
radius_around = 400
#CALCULATION
extrude_json = pygeoj.load(cadastre_f)
elevation_file = BilParser(elevation_f)
h = elevation_file.header
v = elevation_file.values
#test if radius_around>0 or exist
if radius_around:
if address_f:
address_coord_lat,address_coord_lon = nominatim(address_f)
extrude(extrude_json, h, v, radius_around, address_coord_lat, address_coord_lon)
else:
print "need an address or no radius"
else:
extrude(extrude_json, h, v)
#COULD USE MULTITHREADING :
csvfile.close()
#create dict variable that will hold only replacement key,value pairs, remove matching key,pair values
#iterate through key,value pairs only select those with spelling variations
LookUp={}
for key,value in lookup_dict_all.iteritems():
if key!=value:
LookUp.update({key:value})
else:
pass
print "lookup table ="
print LookUp
# open template
geoj_template = pygeoj.load(r"C:\Users\shylander\Desktop\ICE\app\ICE_Data\Countries_Template.geojson")
# save copy
geoj_template.save(r"C:\Users\shylander\Desktop\ICE\app\ICE_Data\Countries.geojson")
# open copy
geoj = pygeoj.load(r"C:\Users\shylander\Desktop\ICE\app\ICE_Data\Countries.geojson")
# open csv
csvfile = io.open(r"C:\Users\shylander\Desktop\ICE\app\ICE_Data\CSV\Tabular_Data.csv",'r', encoding='utf-8', errors='ignore')
# intialize reader
reader = csv.DictReader(csvfile)
# dump the tabular data csv into a string of geojson objects
out = geojson.dumps([row for row in reader])
# convert to the geojson object into a list/array
out_list_tab = geojson.loads(out)
#close Tabular Data csv
csvfile.close()
print 'outlist ='
def render_world(crs, savename):
import urllib2
import json
import pygeoj
import pyagg
import pyproj
import random
# load world borders
global raw
if not raw:
raw = urllib2.urlopen("https://raw.githubusercontent.com/johan/world.geo.json/master/countries.geo.json").read()
rawdict = json.loads(raw)
data = pygeoj.load(data=rawdict)
# convert coordinates
fromproj = pyproj.Proj("+init=EPSG:4326")
toproj = pyproj.Proj(crs.to_proj4())
for feat in data:
if feat.geometry.type == "Polygon":
feat.geometry.coordinates = [zip(*pyproj.transform(fromproj, toproj, zip(*ring)[0], zip(*ring)[1]))
for ring in feat.geometry.coordinates]
elif feat.geometry.type == "MultiPolygon":
feat.geometry.coordinates = [
[zip(*pyproj.transform(fromproj, toproj, zip(*ring)[0], zip(*ring)[1]))
for ring in poly]
for poly in feat.geometry.coordinates]
feat.geometry.update_bbox() # important to clear away old bbox
# get zoom area
data.add_all_bboxes()
data.update_bbox()
bbox = data.bbox
## # to avoid inf bounds and no render in satellite view
## xmins, ymins, xmaxs, ymaxs = zip(*(feat.geometry.bbox for feat in data))
## inf = float("inf")
## xmaxs = (xmax for xmax in xmaxs if xmax != inf)
## ymaxs = (ymax for ymax in ymaxs if ymax != inf)
## bbox = (min(xmins), min(ymins), max(xmaxs), max(ymaxs))
# set up drawing
c = pyagg.Canvas(1000,1000)
c.geographic_space()
c.zoom_bbox(*bbox)
c.zoom_out(1.3)
# draw countries
for feat in data:
try: c.draw_geojson(feat.geometry,
fillcolor=tuple(random.randrange(255) for _ in range(3)),
outlinecolor="white")
except:
# NOTE: feat.__geo_interface__ is one level too high maybe??
print("unable to draw?", feat.geometry)
# draw text of the proj4 string used
c.percent_space()
c.draw_text(crs.to_proj4(), (50,10))
# save
c.save("testrenders/"+savename+".png")
def from_file(filepath, encoding="utf8", **kwargs):
# TODO: for geoj and delimited should detect and force consistent field types in similar manner as when saving
select = kwargs.get("select")
def decode(value):
if isinstance(value, str):
return value.decode(encoding)
else: return value
# shapefile
if filepath.endswith(".shp"):
shapereader = pyshp.Reader(filepath, **kwargs) # TODO: does pyshp take kwargs?
# load fields, rows, and geometries
fields = [decode(fieldinfo[0]) for fieldinfo in shapereader.fields[1:]]
rows = ( [decode(value) for value in record] for record in shapereader.iterRecords() )
def getgeoj(obj):
geoj = obj.__geo_interface__
if hasattr(obj, "bbox"): geoj["bbox"] = list(obj.bbox)
return geoj
geometries = (getgeoj(shape) for shape in shapereader.iterShapes())
rowgeoms = itertools.izip(rows, geometries)
# load projection string from .prj file if exists
if os.path.lexists(filepath[:-4] + ".prj"):
crs = open(filepath[:-4] + ".prj", "r").read()
else: crs = "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs"
# geojson file
elif filepath.endswith((".geojson",".json")):
geojfile = pygeoj.load(filepath, encoding=encoding, **kwargs)
# load fields, rows, and geometries
fields = [field for field in geojfile.common_attributes]
rows = ([feat.properties[field] for field in fields] for feat in geojfile)
geometries = (feat.geometry.__geo_interface__ for feat in geojfile)
rowgeoms = itertools.izip(rows, geometries)
# load crs
crs = geojfile.crs
# table files without geometry
elif filepath.endswith((".txt",".csv",".xls",".xlsx")):
# txt or csv
if filepath.endswith((".txt",".csv")):
delimiter = kwargs.get("delimiter")
fileobj = open(filepath, "rU")
if delimiter is None:
dialect = csv.Sniffer().sniff(fileobj.read())
fileobj.seek(0)
rows = csv.reader(fileobj, dialect)
else:
rows = csv.reader(fileobj, delimiter=delimiter)
def parsestring(string):
try:
val = float(string.replace(",","."))
if val.is_integer():
val = int(val)
return val
except:
if string.upper() == "NULL":
return None
else:
return string.decode(encoding)
rows = ([parsestring(cell) for cell in row] for row in rows)
fields = next(rows)
# excel
elif filepath.endswith((".xls",".xlsx")):
if filepath.endswith(".xls"):
import xlrd
wb = xlrd.open_workbook(filepath, encoding_override=encoding, on_demand=True)
if "sheet" in kwargs:
sheet = wb.sheet_by_name(kwargs["sheet"])
else:
sheet = wb.sheet_by_index(0)
rows = ([cell.value for cell in row] for row in sheet.get_rows())
fields = next(rows)
elif filepath.endswith(".xlsx"):
raise NotImplementedError()
geokey = kwargs.get("geokey")
xfield = kwargs.get("xfield")
yfield = kwargs.get("yfield")
if geokey:
rowgeoms = ((row,geokey(dict(zip(fields,row)))) for row in rows)
elif xfield and yfield:
def xygeoj(row):
rowdict = dict(zip(fields,row))
x,y = rowdict[xfield],rowdict[yfield]
try:
x,y = float(x),float(y)
geoj = {"type":"Point", "coordinates":(x,y)}
except:
try:
x,y = float(x.replace(",",".")),float(y.replace(",","."))
geoj = {"type":"Point", "coordinates":(x,y)}
except:
warnings.warn("Could not create point geometry from xfield and yfield values {x} and {y}".format(x=repr(x), y=repr(y)))
geoj = None
return geoj
rowgeoms = ((row,xygeoj(row)) for row in rows)
else:
rowgeoms = ((row,None) for row in rows)
crs = None
else:
raise UnknownFileError("Could not create vector data from the given filepath: the filetype extension is either missing or not supported")
# filter if needed
if select:
rowgeoms = ( (row,geom) for row,geom in rowgeoms if select(dict(zip(fields,row))) )
# load to memory in lists
rows,geometries = itertools.izip(*rowgeoms)
rows = list(rows)
geometries = list(geometries)
return fields, rows, geometries, crs
import maps_api
import geometry as gm
import time
from matplotlib.path import Path
import matplotlib.patches as patches
import pygeoj
import square_meter_price as sqm
sectors = {"Bouches-du-Rhône":[]}
### values given by the formular filled on internet
concurrent_place_type = 'parking'
coeff_demography = 2
coords_communes_list = []
file13 = pygeoj.load("Data/france-geojson/departements/13/communes.geojson")
for feature in file13:
sectors["Bouches-du-Rhône"].append(feature.properties['nom'])
correct_coords = []
for [ln,lat] in feature.geometry.coordinates[0]:
correct_coords.append((ln,lat))
coords_communes_list.append(correct_coords)
def refresh_database():
for departement,commune in sectors.iteritems():
for i in range(len(commune)):
print('refreshing data of '+ commune[i])
if i>=commune.index('Istres'):
