def initialize(self, db_interface):
# Load blocklot LatLong locations from the database.
self.my_tree = kdtree.create(dimensions=2)
self.latlong_to_blocklot = dict()
offset = 0
while offset >= 0:
results = db_interface.read_rows(
["block_lot", "latitude", "longitude"],
"address",
limit=offset,
limit2=PAGE_SIZE,
ordergroup="ORDER BY block_lot DESC")
# We want to fetch all records for a blocklot, so we read until
# the last blocklot (which may have gotten snipped).
logging.info("Fetched %d results.", len(results))
if len(results) == PAGE_SIZE:
filtered_results = [
r for r in results if r[0] != results[-1][0]
]
offset += len(filtered_results)
results = filtered_results
else:
offset = -1
if not results:
continue
points = []
for i in range(len(results)):
if i != 0:
if results[i][1] == results[i-1][1] and \
results[i][2] == results[i-1][2]:
continue
self.my_tree.add((results[i][1], results[i][2]))
points.append((results[i][1], results[i][2]))
self.latlong_to_blocklot["%10f|%10f" %
(results[i][1],
results[i][2])] = results[i][0]
self.my_tree.rebalance()
def initialize(self, zoning_csv):
self.my_tree = kdtree.create(dimensions=2)
self.headerrow = dict()
self.latlong_to_zoning = dict()
with open(zoning_csv, 'r') as csvfile:
csvreader = csv.reader(csvfile)
for row in csvreader:
if not self.headerrow:
for idx in range(len(row)):
self.headerrow[row[idx]] = idx
continue
if row[self.headerrow['ZONING_SIM']] == 'P':
# There's a bug that causes public land to mark
# neighboring buildings as public land as well.
continue
latitude = float(row[self.headerrow['latitude']])
longitude = float(row[self.headerrow['longitude']])
self.my_tree.add([latitude, longitude])
self.latlong_to_zoning["%10f|%10f" % (
latitude, longitude)] = list(row)
self.my_tree.rebalance()
def initialize(self, zoning_csv):
self.my_tree = kdtree.create(dimensions=2)
self.headerrow = dict()
self.latlong_to_zoning = dict()
with open(zoning_csv, 'r') as csvfile:
csvreader = csv.reader(csvfile)
for row in csvreader:
if not self.headerrow:
for idx in range(len(row)):
self.headerrow[row[idx]] = idx
continue
if row[self.headerrow['ZONING_SIM']] == 'P':
# There's a bug that causes public land to mark
# neighboring buildings as public land as well.
continue
latitude = float(row[self.headerrow['latitude']])
longitude = float(row[self.headerrow['longitude']])
self.my_tree.add([latitude, longitude])
self.latlong_to_zoning["%10f|%10f" %
(latitude, longitude)] = list(row)
self.my_tree.rebalance()
def initialize(self, db_interface):
# Load blocklot LatLong locations from the database.
self.my_tree = kdtree.create(dimensions=2)
self.latlong_to_blocklot = dict()
offset = 0
while offset >= 0:
results = db_interface.read_rows(
["block_lot", "latitude", "longitude"],
"address",
limit = offset,
limit2 = PAGE_SIZE,
ordergroup = "ORDER BY block_lot DESC")
# We want to fetch all records for a blocklot, so we read until
# the last blocklot (which may have gotten snipped).
logging.info("Fetched %d results.", len(results))
if len(results) == PAGE_SIZE:
filtered_results = [r for r in results if r[0] != results[-1][0]]
offset += len(filtered_results)
results = filtered_results
else:
offset = -1
if not results:
continue
points = []
for i in range(len(results)):
if i != 0:
if results[i][1] == results[i-1][1] and \
results[i][2] == results[i-1][2]:
continue
self.my_tree.add((results[i][1], results[i][2]))
points.append((results[i][1], results[i][2]))
self.latlong_to_blocklot["%10f|%10f" % (
results[i][1], results[i][2])] = results[i][0]
self.my_tree.rebalance()
