@author: admin
'''
from src.uk.co.riskaware.dggs.enums.shape_string_format import ShapeStringFormat
from src.uk.co.riskaware.dggs.dggs import Dggs
from src.uk.co.riskaware.dggs.enums.model import Model
from src.uk.co.riskaware.dggs.shapes.dggs_cell import DggsCell
from src.uk.co.riskaware.dggs.shapes.dggs_linestring import DggsLinestring
from src.uk.co.riskaware.dggs.shapes.dggs_polygon import DggsPolygon
from src.uk.co.riskaware.dggs.enums.shape_string_format import ShapeStringFormat
#create dggs cells from wkt
wkt_string = ('GEOMETRYCOLLECTION(' 'POINT(2.345 1.234))')
# Convert the shape string
dggs = Dggs(Model.ISEA4T) # change between these two fro hex and tri
#dggs = Dggs(Model.ISEA3H)
dggs_shapes = dggs.convert_shape_string_to_dggs_shapes(wkt_string,
ShapeStringFormat.WKT,
3.884)
dggs_cells_list = []
for item in dggs_shapes:
x = item.get_shape()
print x
y = item.get_shape().get_cell_id()
print y
dggs_cells_list.append(item.get_shape())
#create kml file
kml_filename = "5_ActualKmlFile.kml"
@author: admin
"""
from src.uk.co.riskaware.dggs.enums.shape_string_format import ShapeStringFormat
from src.uk.co.riskaware.dggs.dggs import Dggs
from src.uk.co.riskaware.dggs.enums.model import Model
from src.uk.co.riskaware.dggs.shapes.dggs_cell import DggsCell
from src.uk.co.riskaware.dggs.shapes.dggs_linestring import DggsLinestring
from src.uk.co.riskaware.dggs.shapes.dggs_polygon import DggsPolygon
from src.uk.co.riskaware.dggs.enums.shape_string_format import ShapeStringFormat
# create dggs cells from wkt
wkt_string = "GEOMETRYCOLLECTION(" "POINT(2.345 1.234))"
# Convert the shape string
dggs = Dggs(Model.ISEA4T) # change between these two fro hex and tri
# dggs = Dggs(Model.ISEA3H)
dggs_shapes = dggs.convert_shape_string_to_dggs_shapes(wkt_string, ShapeStringFormat.WKT, 3.884)
dggs_cells_list = []
for item in dggs_shapes:
x = item.get_shape()
print x
y = item.get_shape().get_cell_id()
print y
dggs_cells_list.append(item.get_shape())
# create kml file
kml_filename = "5_ActualKmlFile.kml"
dggs.create_dggs_kml_file(kml_filename, dggs_cells_list) # dggs_cells_list is list of the get shape objects
user = "******"
password = "******"
host = "localhost"
sql_query = "select lat, lon from tweets limit 10;" #this takes about 17 seconds for 1 million, change limit as needed
connection = psycopg2.connect(dbname = dbname, user = user, password = password, host = host)
cursor = connection.cursor()
start_time = time.time()
cursor.execute(sql_query)
result = cursor.fetchall()
for row in result:
lat = str(row[0])
lon = str(row[1])
wkt_string = 'GEOMETRYCOLLECTION(''POINT('+lon+' '+lat+'))'
# Convert the shape string
dggs = Dggs(Model.ISEA3H) # change between this and ISEA4T
dggs_shapes = dggs.convert_shape_string_to_dggs_shapes(wkt_string, ShapeStringFormat.WKT, 1.234)
for item in dggs_shapes:
dggs_cellID = item.get_shape().get_cell_id()
mongo_insert = {"lon": lon, "lat": lat, "cell_id": dggs_cellID}
collection.insert(mongo_insert)
end_time = time.time() - start_time
print end_time
