def __init__(self, fname="./buildings_backup_meters.json", map_fname="./polygon_poznan_meters.json"):
with open(fname, "r") as f:
b_backup = json.load(f)
buildings = b_backup['buildings']
with open(map_fname, "r") as f:
self.map_poly = json.load(f)["boundary"]
self.width, self.height = b_backup["_11"]
self.buildings_dict = {helpers.mean(x): x for x in buildings}
self.bmeans = list(self.buildings_dict.keys())
self.tree = KDTree(list(self.bmeans))
def getPedestral(tDict, vDict, timetupel):
#
# returns dict with timber var as keys and corresponding
# averaged pedestral for time period
#
#
(dtStart, dtEnd, labText) = timetupel
tsStart = stringDateToTimeStamp(dtStart)
tsEnd = stringDateToTimeStamp(dtEnd)
pedList = []
if debug:
print "Starting time", dtStart
print "Ending time", dtEnd
vars = vDict.keys()
for det in vDict.keys():
xarray, yarray = [], []
if debug: print "timber var ", det
detData = tDict[det]
for ts, dt, val in detData:
if ts > tsEnd or ts <= tsStart:
continue
yarray += [val]
meanPedestral = mean(yarray)
stddevPed = stddev(yarray)
pedList += [(det, [meanPedestral, stddevPed])]
pedDict = dict(pedList)
if debug: print "pedDict", pedDict
return pedDict
def meansFromSets3(sets, length, means):
newmeans = []
for i in range(len(sets)):
newmeans.append(helpers.mean(list(sets[i].keys()), length, means[i]))
return newmeans
def meansFromSets(sets, length, means):
newmeans = []
# print sets, means
for i in range(len(sets)):
newmeans.append(helpers.mean(sets[i], length, means[i]))
return newmeans