def auto_update_charts_wattstopper_plugload(request):
if request.method == 'POST':
print 'inside cassandra auto update wattstopper plugload'
_data = request.body
_data = json.loads(_data)
mac = _data['mac']
if 'from_dt' in _data.keys():
from_date = _data['from_dt']
print from_date
else:
from_date = ''
device_id = get_device_id_from_mac(mac)
if from_date == '':
data_points, rs = retrieve(device_id, ['time', 'status', 'power'])
else:
from_date = datetime.datetime.strptime(from_date, '%Y/%m/%d %H:%M')
data_points, rs = retrieve(device_id, ['time', 'status', 'power'], from_date)
rs_status = parse_resultset(data_points, 'status', rs)
rs_power = parse_resultset(data_points, 'power', rs)
json_result = {
'status': rs_status,
'power': rs_power
}
if request.is_ajax():
return HttpResponse(json.dumps(json_result), mimetype='application/json')
def get_statistics_datetime_wattstopper_plugload(request):
if request.method == 'POST':
print 'inside cassandra get statistics for wattstopper plugload based on given from and to datetime'
_data = request.body
_data = json.loads(_data)
mac = _data['mac']
from_date = _data['from_dt']
to_date = _data['to_dt']
print from_date
device_id = get_device_id_from_mac(mac)
if not from_date and not to_date:
data_points, rs = retrieve(device_id, ['time', 'status', 'power'])
elif not to_date and from_date:
from_date = datetime.datetime.strptime(from_date, '%Y/%m/%d %H:%M')
data_points, rs = retrieve(device_id, ['time', 'status', 'power'], from_date)
else:
from_date = datetime.datetime.strptime(from_date, '%Y/%m/%d %H:%M')
to_date = datetime.datetime.strptime(to_date, '%Y/%m/%d %H:%M')
print from_date, to_date
data_points, rs = retrieve(device_id, ['time', 'status', 'power'], from_date, to_date)
rs_status = parse_resultset(data_points, 'status', rs)
rs_power = parse_resultset(data_points, 'power', rs)
json_result = {
'status': rs_status,
'power': rs_power
}
print 'Got results based on datetime'
if request.is_ajax():
return HttpResponse(json.dumps(json_result), mimetype='application/json')
def auto_update_charts_thermostat(request):
if request.method == 'POST':
print 'inside cassandra auto update thermostat'
_data = request.body
_data = json.loads(_data)
mac = _data['mac']
if 'from_dt' in _data.keys():
from_date = _data['from_dt']
print from_date
else:
from_date = ''
device_id = get_device_id_from_mac(mac)
if from_date == '':
data_points, rs = retrieve(device_id, ['time', 'temperature',
'heat_setpoint', 'cool_setpoint'])
else:
from_date = datetime.datetime.strptime(from_date, '%Y/%m/%d %H:%M')
data_points, rs = retrieve(device_id, ['time', 'temperature',
'heat_setpoint', 'cool_setpoint'], from_date)
rs_temperature = parse_resultset(data_points, 'temperature', rs)
rs_heat_setpoint = parse_resultset(data_points, 'heat_setpoint', rs)
rs_cool_setpoint = parse_resultset(data_points, 'cool_setpoint', rs)
json_result = {
'temperature': rs_temperature,
'heat_setpoint': rs_heat_setpoint,
'cool_setpoint': rs_cool_setpoint
}
print 'test'
if request.is_ajax():
return HttpResponse(json.dumps(json_result), mimetype='application/json')
def retrieve_for_export(agentID, vars=None, startTime=None, endTime=None, tablename=None,weather_agent=False):
if weather_agent:
data = retrieve(agentID=agentID,vars=vars,startTime=startTime,endTime=endTime,export=True,tablename=tablename,weather_agent=settings.weather_agent)
if data is not None:
a,b=data
else:
a, b = retrieve(agentID=agentID, vars=vars, startTime=startTime, endTime=endTime, export=True,
tablename=tablename, weather_agent=None)
else:
a, b = retrieve(agentID=agentID, vars=vars, startTime=startTime, endTime=endTime, export=True,
tablename=tablename, weather_agent=None)
return a,b
def get_statistics_datetime_rtu(request):
if request.method == 'POST':
print 'inside cassandra get statistics for rtu based on given from and to datetime'
_data = request.body
_data = json.loads(_data)
mac = _data['mac']
from_date = _data['from_dt']
to_date = _data['to_dt']
print from_date
device_id = get_device_id_from_mac(mac)
if not from_date and not to_date:
data_points, rs = retrieve(device_id, ['time', 'outside_temperature', 'return_temperature', 'supply_temperature',
'heat_setpoint', 'cool_setpoint', 'cooling_mode', 'heating',
'outside_damper_position', 'bypass_damper_position'])
elif not to_date and from_date:
from_date = datetime.datetime.strptime(from_date, '%Y/%m/%d %H:%M')
data_points, rs = retrieve(device_id, ['time', 'outside_temperature', 'return_temperature', 'supply_temperature',
'heat_setpoint', 'cool_setpoint', 'cooling_mode', 'heating',
'outside_damper_position', 'bypass_damper_position'], from_date)
else:
from_date = datetime.datetime.strptime(from_date, '%Y/%m/%d %H:%M')
to_date = datetime.datetime.strptime(to_date, '%Y/%m/%d %H:%M')
data_points, rs = retrieve(device_id, ['time', 'outside_temperature', 'return_temperature', 'supply_temperature',
'heat_setpoint', 'cool_setpoint', 'cooling_mode', 'heating',
'outside_damper_position', 'bypass_damper_position'], from_date, to_date)
rs_outside_temperature = parse_resultset(data_points, 'outside_temperature', rs)
rs_return_temperature = parse_resultset(data_points, 'return_temperature', rs)
rs_supply_temperature = parse_resultset(data_points, 'supply_temperature', rs)
rs_heat_setpoint = parse_resultset(data_points, 'heat_setpoint', rs)
rs_cool_setpoint = parse_resultset(data_points, 'cool_setpoint', rs)
rs_cooling_mode = parse_resultset(data_points, 'cooling_mode', rs)
rs_heating = parse_resultset(data_points, 'heating', rs)
rs_outside_damper_position = parse_resultset(data_points, 'outside_damper_position', rs)
rs_bypass_damper_position = parse_resultset(data_points, 'bypass_damper_position', rs)
json_result = {'outside_temperature': rs_outside_temperature,
'supply_temperature': rs_supply_temperature,
'return_temperature': rs_return_temperature,
'heating': rs_heating,
'outside_damper_position': rs_outside_damper_position,
'bypass_damper_position': rs_bypass_damper_position,
'cooling_mode': rs_cooling_mode,
'heat_setpoint': rs_heat_setpoint,
'cool_setpoint': rs_cool_setpoint
}
print 'Got results based on datetime'
if request.is_ajax():
return HttpResponse(json.dumps(json_result), mimetype='application/json')
def charts_plugload(request, mac):
print "inside cassandra view method for plugload"
context = RequestContext(request)
if request.method == 'GET':
device_metadata = [ob.device_control_page_info() for ob in DeviceMetadata.objects.filter(mac_address=mac)]
device_id = device_metadata[0]['device_id']
device_type_id = device_metadata[0]['device_model_id']
device_type_id = device_type_id.device_model_id
if device_type_id == '2WL':
device_status = [ob.data_as_json() for ob in Lighting.objects.filter(lighting_id=device_id)]
device_nickname = device_status[0]['nickname']
zone_nickname = device_status[0]['zone']['zone_nickname']
else:
device_status = [ob.data_as_json() for ob in Plugload.objects.filter(plugload_id=device_id)]
device_nickname = device_status[0]['nickname']
zone_nickname = device_status[0]['zone']['zone_nickname']
data_points, rs = retrieve(device_id, ['time', 'status'])
rs_status = parse_resultset(data_points, 'status', rs)
update_context(context)
return render_to_response(
'charts/charts_plugload.html',
{'status': rs_status, 'mac': mac, 'nickname': device_nickname, 'zone_nickname': zone_nickname,
'device_type_id': device_type_id}, context)
def charts_vav(request, mac):
"""Page load definition for VAV statistics."""
print "inside smap view method"
context = RequestContext(request)
if request.method == 'GET':
device_id = get_device_id_from_mac(mac)
device_status = [ob.as_json() for ob in VAV.objects.filter(vav_id=device_id)]
device_nickname = device_status[0]['nickname']
zone_nickname = device_status[0]['zone']['zone_nickname']
data_points, rs = retrieve(device_id, ['time', 'temperature', 'supply_temperature',
'heat_setpoint', 'cool_setpoint', 'flap_position'])
rs_temperature = parse_resultset(data_points, 'temperature', rs)
rs_supply_temperature = parse_resultset(data_points, 'supply_temperature', rs)
rs_heat_setpoint = parse_resultset(data_points, 'heat_setpoint', rs)
rs_cool_setpoint = parse_resultset(data_points, 'cool_setpoint', rs)
rs_flap_position = parse_resultset(data_points, 'flap_position', rs)
context = update_context(context)
return render_to_response(
'charts/charts_vav.html',
{'temperature': rs_temperature, 'supply_temperature': rs_supply_temperature,
'flap_position': rs_flap_position, 'heat_setpoint': rs_heat_setpoint, 'cool_setpoint': rs_cool_setpoint,
'nickname': device_nickname, 'mac': mac,
'zone_nickname': zone_nickname},
context)
def auto_update_charts_rtu(request):
"""Statistics page update for RTU"""
if request.method == 'POST':
print 'inside cassandra auto update RTU'
_data = request.body
_data = json.loads(_data)
mac = _data['mac']
if 'from_dt' in _data.keys():
from_date = _data['from_dt']
print from_date
else:
from_date = ''
device_id = get_device_id_from_mac(mac)
if from_date == '':
data_points, rs = retrieve(device_id, ['time', 'outside_temperature', 'return_temperature', 'supply_temperature',
'heat_setpoint', 'cool_setpoint', 'cooling_mode', 'heating',
'outside_damper_position', 'bypass_damper_position'])
else:
from_date = datetime.datetime.strptime(from_date, '%Y/%m/%d %H:%M')
data_points, rs = retrieve(device_id, ['time', 'outside_temperature', 'return_temperature', 'supply_temperature',
'heat_setpoint', 'cool_setpoint', 'cooling_mode', 'heating',
'outside_damper_position', 'bypass_damper_position'], from_date)
rs_outside_temperature = parse_resultset(data_points, 'outside_temperature', rs)
rs_return_temperature = parse_resultset(data_points, 'return_temperature', rs)
rs_supply_temperature = parse_resultset(data_points, 'supply_temperature', rs)
rs_heat_setpoint = parse_resultset(data_points, 'heat_setpoint', rs)
rs_cool_setpoint = parse_resultset(data_points, 'cool_setpoint', rs)
rs_cooling_mode = parse_resultset(data_points, 'cooling_mode', rs)
rs_heating = parse_resultset(data_points, 'heating', rs)
rs_outside_damper_position = parse_resultset(data_points, 'outside_damper_position', rs)
rs_bypass_damper_position = parse_resultset(data_points, 'bypass_damper_position', rs)
json_result = {'outside_temperature': rs_outside_temperature,
'supply_temperature': rs_supply_temperature,
'return_temperature': rs_return_temperature,
'heating': rs_heating,
'outside_damper_position': rs_outside_damper_position,
'bypass_damper_position': rs_bypass_damper_position,
'cooling_mode': rs_cooling_mode,
'heat_setpoint': rs_heat_setpoint,
'cool_setpoint': rs_cool_setpoint}
print 'test'
if request.is_ajax():
return HttpResponse(json.dumps(json_result), mimetype='application/json')
def returnChartsPage(request, context,mac,data_variables,page,get_weather=False):
'''
:param context: var obtained from RequestContext(request)
:param mac: Device mac ID (table id)
:param data_variables: Dict. Variables in the database that is to be retrieved as value, and varaibles in html as keys
:param page: The html page to be returned to
:param device_type: The device type class
:return: the rendered html page
'''
agent_id = get_agent_id_from_mac(mac)
try:
if not get_weather:
varlist, rs = retrieve(agent_id)
else:
data = retrieve(agent_id, weather_agent=settings.weather_agent)
if data is not None:
varlist, rs=data
else:
varlist, rs = retrieve(agent_id)
except Exception as er:
print er
print 'Cassandra data reading error'
return {}
device_list_side_nav = get_device_list_and_count(request)
data_dict = {}
objects = [ob for ob in DeviceMetadata.objects.filter(mac_address=mac)]
try:
device_nickname = objects[0].nickname
node_name = objects[0].node.node_name
data_dict = {'mac': mac, 'nickname': device_nickname, 'node_name': node_name}
except Exception as er:
print er
print 'get device status failed'
for key,val in data_variables.items():
try:
data_dict[key] = parse_resultset(varlist,val,rs)
except (KeyError, ValueError) as er:
print er
continue
context.update(get_device_list_and_count(request))
data_dict.update(device_list_side_nav)
return render(request, page,data_dict)
def returnsCharts(request,data_variables,get_weather=False):
_data = request.body
_data = json.loads(_data)
mac = _data['mac']
if 'from_dt' in _data.keys():
from_date = _data['from_dt']
if from_date not in [None,'',u'']:
if type(from_date) in [str,unicode]:
from_date = datetime.datetime.strptime(from_date, '%Y/%m/%d %H:%M')
else:
from_date = None
print from_date
else:
from_date = None
if 'to_dt' in _data.keys():
to_date = _data['to_dt']
if to_date not in [None,'',u'']:
if type(to_date) in [str,unicode]:
to_date = datetime.datetime.strptime(to_date, '%Y/%m/%d %H:%M')
else:
to_date = None
else:
to_date = None
if from_date is None and to_date is None:
to_date = datetime.datetime(2017, 2, 4)
from_date = datetime.datetime(2017, 1, 1)
agent_id = get_agent_id_from_mac(mac)
if get_weather:
varlist, rs = retrieve(agent_id,startTime=from_date,endTime=to_date,weather_agent=settings.weather_agent)
else:
varlist, rs = retrieve(agent_id,startTime=from_date,endTime=to_date)
#varlist, rs = retrieve(agent_id, weather_agent="weatheragent22101", )
json_result =dict()
for key,val in data_variables.items():
if key in varlist:
json_result[key] = parse_resultset(varlist,val,rs,to_date)
if request.is_ajax():
return HttpResponse(json.dumps(json_result))
def retrieve_for_export(agentID,
vars=None,
startTime=None,
endTime=None,
tablename=None,
weather_agent=False):
device = DeviceMetadata.objects.get(agent_id=agentID)
if not tablename:
tablename = "B" + str(
device.building.building_id) + "_" + device.device_model.replace(
" ", "_").replace("-", "_")
tablename = re.sub(r'\W', '_', tablename)
weather_agent = 'BEMO_WUG' + device.building.zip_code + '_' + str(
device.building.building_id)
weather_table = "B" + str(device.building.building_id) + "bemossweather"
if weather_agent:
data = retrieve(agentID=agentID,
vars=vars,
startTime=startTime,
endTime=endTime,
export=True,
tablename=tablename,
weather_agent=weather_agent,
weather_table=weather_table)
if data is not None:
a, b = data
else:
a, b = retrieve(agentID=agentID,
vars=vars,
startTime=startTime,
endTime=endTime,
export=True,
tablename=tablename,
weather_agent=None)
else:
a, b = retrieve(agentID=agentID,
vars=vars,
startTime=startTime,
endTime=endTime,
export=True,
tablename=tablename,
weather_agent=None)
return a, b
def auto_update_charts_vav(request):
"""Statistics page load for VAV"""
if request.method == 'POST':
print 'inside smap auto update VAV'
_data = request.body
_data = json.loads(_data)
mac = _data['mac']
print mac
if 'from_dt' in _data.keys():
from_date = _data['from_dt']
print from_date
else:
from_date = ''
device_id = get_device_id_from_mac(mac)
if from_date == '':
data_points, rs = retrieve(device_id, ['time', 'temperature', 'supply_temperature',
'heat_setpoint', 'cool_setpoint', 'flap_position'])
else:
from_date = datetime.datetime.strptime(from_date, '%Y/%m/%d %H:%M')
data_points, rs = retrieve(device_id, ['time', 'temperature', 'supply_temperature',
'heat_setpoint', 'cool_setpoint', 'flap_position'], from_date)
rs_temperature = parse_resultset(data_points, 'temperature', rs)
rs_supply_temperature = parse_resultset(data_points, 'supply_temperature', rs)
rs_heat_setpoint = parse_resultset(data_points, 'heat_setpoint', rs)
rs_cool_setpoint = parse_resultset(data_points, 'cool_setpoint', rs)
rs_flap_position = parse_resultset(data_points, 'flap_position', rs)
json_result = {'temperature': rs_temperature,
'supply_temperature': rs_supply_temperature,
'flap_position': rs_flap_position,
'heat_setpoint': rs_heat_setpoint,
'cool_setpoint': rs_cool_setpoint}
if request.is_ajax():
return HttpResponse(json.dumps(json_result), mimetype='application/json')
def charts_wattstopper_plugload(request, mac):
context = RequestContext(request)
if request.method == 'GET':
device_id = get_device_id_from_mac(mac)
device_status = [ob.data_as_json() for ob in Plugload.objects.filter(plugload_id=device_id)]
device_nickname = device_status[0]['nickname']
zone_nickname = device_status[0]['zone']['zone_nickname']
data_points, rs = retrieve(device_id, ['time', 'status', 'power'])
rs_status = parse_resultset(data_points, 'status', rs)
rs_power = parse_resultset(data_points, 'power', rs)
context = update_context(context)
return render_to_response(
'charts/charts_wtplug.html',
{'status': rs_status, 'power': rs_power, 'nickname': device_nickname, 'zone_nickname': zone_nickname,
'mac': mac}, context)
def charts_rtu(request, mac):
"""Page load definition for RTU statistics."""
print "inside smap view method"
context = RequestContext(request)
if request.method == 'GET':
device_id = get_device_id_from_mac(mac)
device_status = [ob.as_json() for ob in RTU.objects.filter(rtu_id=device_id)]
device_nickname = device_status[0]['nickname']
zone_nickname = device_status[0]['zone']['zone_nickname']
data_points, rs = retrieve(device_id, ['time', 'outside_temperature', 'return_temperature', 'supply_temperature',
'heat_setpoint', 'cool_setpoint', 'cooling_mode', 'heating',
'outside_damper_position', 'bypass_damper_position'])
rs_outside_temperature = parse_resultset(data_points, 'outside_temperature', rs)
rs_return_temperature = parse_resultset(data_points, 'return_temperature', rs)
rs_supply_temperature = parse_resultset(data_points, 'supply_temperature', rs)
rs_heat_setpoint = parse_resultset(data_points, 'heat_setpoint', rs)
rs_cool_setpoint = parse_resultset(data_points, 'cool_setpoint', rs)
rs_cooling_mode = []
rs_heating = parse_resultset(data_points, 'heating', rs)
rs_outside_damper_position = parse_resultset(data_points, 'outside_damper_position', rs)
rs_bypass_damper_position = parse_resultset(data_points, 'bypass_damper_position', rs)
context = update_context(context)
return render_to_response(
'charts/charts_rtu.html',
{'outside_temperature': rs_outside_temperature, 'supply_temperature': rs_supply_temperature,
'return_temperature': rs_return_temperature, 'heating': rs_heating,
'outside_damper_position': rs_outside_damper_position,
'bypass_damper_position': rs_bypass_damper_position, 'cooling_mode': rs_cooling_mode,
'heat_setpoint': rs_heat_setpoint, 'cool_setpoint': rs_cool_setpoint,
'nickname': device_nickname, 'mac': mac,
'zone_nickname': zone_nickname},
context)
def charts_lighting(request, mac):
print "inside cassandra view method for lighting"
context = RequestContext(request)
if request.method == 'GET':
device_id = get_device_id_from_mac(mac)
device_status = [ob.data_as_json() for ob in Lighting.objects.filter(lighting_id=device_id)]
device_nickname = device_status[0]['nickname']
zone_nickname = device_status[0]['zone']['zone_nickname']
data_points, rs = retrieve(device_id, ['time', 'status', 'brightness'])
rs_status = parse_resultset(data_points, 'status', rs)
rs_brightness = parse_resultset(data_points, 'brightness', rs)
context = update_context(context)
return render_to_response(
'charts/charts_lighting.html',
{'status': rs_status, 'brightness': rs_brightness,
'nickname': device_nickname, 'zone_nickname': zone_nickname,
'mac': mac}, context)
def charts_thermostat(request, mac):
"""Page load definition for thermostat statistics."""
print "inside cassandra view method"
context = RequestContext(request)
if request.method == 'GET':
device_id = get_device_id_from_mac(mac)
data_points, rs = retrieve(device_id, ['time', 'temperature',
'heat_setpoint', 'cool_setpoint'])
rs_temperature = parse_resultset(data_points, 'temperature', rs)
rs_heat_setpoint = parse_resultset(data_points, 'heat_setpoint', rs)
rs_cool_setpoint = parse_resultset(data_points, 'cool_setpoint', rs)
device_status = [ob.data_as_json() for ob in Thermostat.objects.filter(thermostat_id=device_id)]
device_nickname = device_status[0]['nickname']
zone_nickname = device_status[0]['zone']['zone_nickname']
context = update_context(context)
return render_to_response(
'charts/charts_thermostat.html',
{'temperature': rs_temperature, 'heat_setpoint': rs_heat_setpoint, 'cool_setpoint': rs_cool_setpoint,
'mac': mac, 'nickname': device_nickname, 'zone_nickname': zone_nickname}, context)
def check_profile_trigger(self):
if not self.trained:
self.train_model()
vars = [
'time', 'cool_setpoint', 'heat_setpoint', 'thermostat_mode',
'thermostat_state', 'temperature'
]
curtime = self.current_time()
look_back_time = curtime - datetime.timedelta(hours=24)
vars, result = cassandraDB.retrieve(
self.data['thermostat'],
vars,
look_back_time,
curtime,
weather_agent=self.data['weather_agent'])
slopes_and_points = self.getSlopesAndPoints(result, vars)
anamoly = False
current_mode = 'Normal setpoint-following'
try:
if slopes_and_points['heating_points']:
current_mode = 'heating'
if self.checkAnamoly(slopes_and_points['heating_points'],
'heating_model'):
anamoly = True
if self.checkDeviation(slopes_and_points['heating_points']):
anamoly = True
elif slopes_and_points['cooling_points']:
current_mode = 'cooling'
if self.checkAnamoly(slopes_and_points['cooling_points'],
'cooling_model'):
anamoly = True
if self.checkDeviation(slopes_and_points['cooling_points']):
anamoly = True
elif slopes_and_points['heatoff_points']:
current_mode = 'heat-off'
if self.checkAnamoly(slopes_and_points['heatoff_points'],
'heatoff_model'):
anamoly = True
elif slopes_and_points['cooloff_points']:
current_mode = 'cool-off'
if self.checkAnamoly(slopes_and_points['cooloff_points'],
'cooloff_model'):
anamoly = True
except ValueError as er:
if str(er) == 'no-outdoor-temp':
anamoly = False
current_mode = "Missing outdoor temperature"
elif str(er) == 'not-enough-data':
anamoly = False
current_mode = "Watching " + current_mode
elif str(er) == 'not-enough-historical-data':
anamoly = False
current_mode = "Watching " + current_mode + ". Insufficient historical data"
else:
raise
return anamoly, current_mode
def train_model(self):
end_time = self.current_time()
start_time = end_time - datetime.timedelta(days=90)
vars = [
'time', 'cool_setpoint', 'heat_setpoint', 'thermostat_mode',
'thermostat_state', 'temperature'
]
vars, result = cassandraDB.retrieve(
self.data['thermostat'],
vars,
start_time,
end_time,
weather_agent=self.data['weather_agent'])
if not len(result):
return
slope_and_points = self.getSlopesAndPoints(result, vars)
def train_models(slope_history):
if len(slope_history) < 3:
return None
#slope_histroy = list of tuples: (avg_outdoor, slope, std_err,temperature_profile[0,0])
sh = np.matrix(slope_history)
lnmodel = LinearRegression()
error_inverse = np.array(1 / sh[:, 2])[:, 0]
lnfit = lnmodel.fit(sh[:, 0], sh[:, 1])
#svr_rbf = SVR(kernel='linear', C=10, epsilon=0.5)
#svrfit = svr_rbf.fit(sh[:, 0], sh[:,1])
ln_residue = []
for i in range(len(slope_history)):
p = lnfit.predict(slope_history[i][0])[0][0]
ln_residue.append((p - slope_history[i][1])**2)
ln_std = stats.tstd(ln_residue)
ln_mean = stats.tmean(ln_residue)
new_sh = None
for i in range(len(ln_residue)):
if ln_residue[i] < ln_mean + 3 * ln_std:
#sh = np.delete(sh,i,axis=0)
if new_sh is None:
new_sh = sh[i, :]
else:
new_sh = np.vstack((new_sh, sh[i, :]))
sh = new_sh
#redo the fit
error_inverse = np.array(1 / sh[:, 2])[:, 0]
slope_mean = stats.tmean(sh[:, 1])
slope_std = stats.tstd(sh[:, 1])
lnfit = lnmodel.fit(sh[:, 0], sh[:, 1])
ln_residue = []
for i in range(len(sh)):
p = lnfit.predict(sh[i, 0])[0][0]
ln_residue.append((p - sh[i, 1])**2)
ln_std = stats.tstd(ln_residue)
ln_mean = stats.tmean(ln_residue)
return {
'ln_model': lnfit,
'ln_residue': ln_residue,
'ln_residue_std': ln_std,
'ln_residue_mean': ln_mean,
'slope_mean': slope_mean,
'slope_std': slope_std,
'data_matrix': sh
}
slope_dict = {
'heating_model': 'heating_slopes',
'cooling_model': 'cooling_slopes',
'heatoff_model': 'heatoff_slopes',
'cooloff_model': 'cooloff_slopes'
}
self.models = dict()
for key, val in slope_dict.items():
slope_history = slope_and_points[val]
if len(slope_history):
self.models[key] = train_models(slope_history)
self.trained = True
def check_profile_trigger(self):
if not self.trained:
self.train_model()
vars = [
'time', 'cool_setpoint', 'heat_setpoint', 'thermostat_mode',
'thermostat_state', 'temperature'
]
curtime = self.current_time()
look_back_time = curtime - datetime.timedelta(hours=24)
vars, result = cassandraDB.retrieve(
self.data['thermostat'],
vars,
look_back_time,
curtime,
weather_agent=self.data['weather_agent'])
last_result = result[-1]
current_result = last_result.copy()
current_result[0] = time.time() * 1000
result = np.vstack([result, current_result])
slopes_and_points = self.getSlopesAndPoints(result, vars)
anamoly = False
current_mode = 'Normal setpoint-following'
#slope based Anamoly detection has been commented out to avoid false positives for now.
try:
if slopes_and_points['heating_points']:
current_mode = 'heating'
# if self.checkAnamoly(slopes_and_points['heating_points'],'heating_model'):
# anamoly = True
if self.checkDeviation(slopes_and_points['heating_points'],
'heating'):
anamoly = True
current_mode = 'Heating Failure'
else:
current_mode = 'Normal Heating'
elif slopes_and_points['cooling_points']:
# if self.checkAnamoly(slopes_and_points['cooling_points'], 'cooling_model'):
# anamoly = True
if self.checkDeviation(slopes_and_points['cooling_points'],
'cooling'):
anamoly = True
current_mode = 'Cooling Failure'
else:
current_mode = 'Normal Cooling'
elif slopes_and_points['heatoff_points']:
# if self.checkAnamoly(slopes_and_points['heatoff_points'], 'heatoff_model'):
# anamoly = True
if self.checkDeviation(slopes_and_points['heatoff_points'],
'heatoff'):
anamoly = True
current_mode = 'Too much cooling'
else:
current_mode = 'Normal cooling'
elif slopes_and_points['cooloff_points']:
# if self.checkAnamoly(slopes_and_points['cooloff_points'], 'cooloff_model'):
# anamoly = True
if self.checkDeviation(slopes_and_points['cooloff_points'],
'cooloff'):
anamoly = True
current_mode = 'Too much heating'
else:
current_mode = 'Normal heating'
except ValueError as er:
if str(er) == 'no-outdoor-temp':
anamoly = False
current_mode = "Missing outdoor temperature"
elif str(er) == 'not-enough-data':
anamoly = False
current_mode = "Watching " + current_mode
elif str(er) == 'not-enough-historical-data':
anamoly = False
current_mode = "Watching " + current_mode + ". Insufficient historical data"
else:
raise
return anamoly, current_mode
def returnChartsPage(request,
context,
mac,
data_variables,
page,
get_weather=False):
'''
:param context: var obtained from RequestContext(request)
:param mac: Device mac ID (table id)
:param data_variables: Dict. Variables in the database that is to be retrieved as value, and varaibles in html as keys
:param page: The html page to be returned to
:param device_type: The device type class
:return: the rendered html page
'''
agent_id = get_agent_id_from_mac(mac)
device = DeviceMetadata.objects.get(agent_id=agent_id)
weather_agent = 'BEMO_WUG' + device.building.zip_code + '_' + str(
device.building.building_id)
weather_table = "B" + str(device.building.building_id) + "_bemossweather"
tablename = getTableName(device.building.building_id, device.device_model)
try:
if not get_weather:
varlist, rs = retrieve(agent_id, tablename=tablename)
else:
data = retrieve(agent_id,
weather_agent=weather_agent,
tablename=tablename,
weather_table=weather_table)
if data is not None:
varlist, rs = data
else:
varlist, rs = retrieve(agent_id, tablename=tablename)
except Exception as er:
print er
print 'Cassandra data reading error'
return HttpResponse("Database fail", status=404)
device_list_side_nav = get_device_list_and_count(request)
data_dict = {}
objects = [ob for ob in DeviceMetadata.objects.filter(mac_address=mac)]
try:
device_nickname = objects[0].nickname
node_name = objects[0].node.node_name
data_dict = {
'mac': mac,
'nickname': device_nickname,
'node_name': node_name
}
except Exception as er:
print er
print 'get device status failed'
for key, val in data_variables.items():
try:
data_dict[key] = parse_resultset(varlist, val, rs)
except (KeyError, ValueError) as er:
print er
continue
context.update(get_device_list_and_count(request))
data_dict.update(device_list_side_nav)
return render(request, page, data_dict)
def returnsCharts(_data, data_variables, get_weather=False):
if 'agent_id' not in _data:
mac = _data['mac']
agent_id = get_agent_id_from_mac(mac)
else:
agent_id = _data['agent_id']
if 'from_dt' in _data.keys():
from_date = _data['from_dt']
if from_date not in [None, '', u'']:
if type(from_date) in [str, unicode]:
from_date = datetime.datetime.strptime(from_date,
'%Y/%m/%d %H:%M')
else:
from_date = None
print from_date
else:
from_date = None
if 'to_dt' in _data.keys():
to_date = _data['to_dt']
if to_date not in [None, '', u'']:
if type(to_date) in [str, unicode]:
to_date = datetime.datetime.strptime(to_date, '%Y/%m/%d %H:%M')
else:
to_date = None
else:
to_date = None
if from_date is None and to_date is None:
to_date = datetime.datetime.now()
from_date = to_date - datetime.timedelta(days=1)
device = DeviceMetadata.objects.get(agent_id=agent_id)
weather_agent = 'BEMO_WUG' + device.building.zip_code + '_' + str(
device.building.building_id)
weather_table = "B" + str(device.building.building_id) + "_bemossweather"
tablename = "B" + str(
device.building.building_id) + "_" + device.device_model.replace(
" ", "_").replace("-", "_")
tablename = re.sub(r'\W', '', tablename)
if get_weather:
varlist, rs = retrieve(agent_id,
startTime=from_date,
endTime=to_date,
weather_agent=weather_agent,
tablename=tablename,
weather_table=weather_table)
else:
varlist, rs = retrieve(agent_id,
startTime=from_date,
endTime=to_date,
tablename=tablename)
#varlist, rs = retrieve(agent_id, weather_agent="weatheragent22101", )
json_result = dict()
for key, val in data_variables.items():
if key in varlist:
json_result[key] = parse_resultset(varlist, val, rs, to_date)
return json_result
