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