def __init__(self,ini_date, end_date, id_meters = None):
self.__ini_date = ini_date
self.__end_date = end_date
ids = []
if id_meters is None:
ids = Raw_data.get_id_meters()
else:
ids = id_meters
self.insert_update()
# Creates each object and find mininma maxima
for meter in ids:
meter_data_obj = Meter_data(meter,self.__ini_date,self.__end_date,self.__id_meter_data_collection)
min_obj,max_obj = meter_data_obj.get_min_max()
if (min_obj < self.__min_val):
self.__min_val = min_obj
if(max_obj > self.__max_val):
self.__max_val = max_obj
self.__meters_data[meter] = meter_data_obj
# after finding min and max, update
self.insert_update()
# Normalize all the measurements and insert into DB
for meter_id,meter_data_obj in self.__meters_data.items():
meter_data_obj.normalize(self.__min_val,self.__max_val)
meter_data_obj.insert()
def get_full_data(self, cleaned_data = False):
dic = {}
for meter_data in self.get_meters_data():
measurements = []
for normalized_measure in Meter_data.get_normalized_measures(meter_data.id_meter_data):
measurements.append(normalized_measure.normalized_measure)
meter_vals = np.array(measurements)
dic[meter_data.id_meter] = meter_vals
#clean the data
if (cleaned_data):
to_remove = []
for k,v in dic.items():
if(len(v) == 0):
to_remove.append(k)
for d in to_remove:
del dic[d]
return dic
def plot(self, name_plot = None, locator = "Day"):
x = []
y = []
fig = plt.figure()
fig.suptitle("Cluster (" + str(self.__ini_date) + " ~ " + str(self.__end_date) + ")" ,fontsize=14,fontweight='bold')
ax = fig.add_subplot(111)
ax.grid(True)
ax.set_ylabel("kwh ("+str(self.__min_val)+" ~ "+str(self.__max_val)+")")
string = ''
legends = []
#for id_meter,meter_data in self.__m_ids_meters.items():
for md_obj in self.get_meters_data():
for nm_obj in Meter_data.get_normalized_measures(md_obj.id_meter_data):
smd_obj = Smart_meter_date(nm_obj.date)
x.append(smd_obj.get_datetime())
y.append(nm_obj.normalized_measure)
ax.plot(x,y)
string = string + str(md_obj.id_meter) + '_'
x = []
y = []
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%d/%m/%Y %H'))
if (locator == "Day"):
plt.gca().xaxis.set_major_locator(mdates.DayLocator())
else:
plt.gca().xaxis.set_major_locator(mdates.HourLocator(byhour=range(24), interval=4))
plt.gcf().autofmt_xdate()
filename = string if name_plot is None else name_plot
filename = filename + '.png'
fig.savefig(filename)
