def processAutarcoFile(file):
logger = logging.getLogger('solaroad.autarco')
x = pd.read_csv(file, delimiter=';', skip_blank_lines=True)
index_time = pd.to_datetime(x['time'], format="%Y-%m-%d %H:%M:%S")
x.index = index_time
for key in x.keys():
if 'Unnamed' in key:
del (x[key])
x = x.dropna()
for device in x['device'].unique():
logger.debug('======================== Now processing %s ========================', device)
y = x.loc[x['device'] == device]
del (y['device'])
del (y['time'])
ctr = 0
total_steps = np.round(len(y) / sc.MAX_POINTS) + 1
while ctr < total_steps:
server, auth_token = sc.authenticate()
deviceId = sc.getDeviceId()
sp = ctr * sc.MAX_POINTS
tmp = y.iloc[sp:sp + sc.MAX_POINTS - 1, :]
logger.debug('--------------------- RECORD %s/%s of %s ------------------------------', ctr + 1,
total_steps, device)
if ctr == 0:
sc.addSensor(server, auth_token, deviceId, device, SENSOR_NAME, device, device)
logger.debug('Now uploading ' + device)
for parameter in tmp['parameter'].unique():
param_vals = tmp.loc[tmp['parameter'] == parameter]
del (param_vals['parameter'])
param_vals = param_vals.resample('300S').mean().interpolate(method='linear')
packer = xdrlib.Packer()
packer.pack_int(1) # version 1
packer.pack_enum(sc.SECONDS)
packer.pack_int(300)
POINTS = len(param_vals)
packer.pack_int(POINTS)
channel = '_'.join(parameter.replace('(', '').replace(')', '').split(' '))
if ctr == 0:
sc.addChannel(server, auth_token, deviceId, device, channel, channel, channel)
for item in param_vals['value'].iteritems():
val = item[1]
timestamp = item[0].to_pydatetime().timestamp() * 1000000000
packer.pack_hyper(int(timestamp))
packer.pack_float(float(val))
data = packer.get_buffer()
sc.uploadData(server, auth_token, deviceId, device, channel, data)
ctr = ctr + 1
def processLeGrandFile(file):
logger = logging.getLogger('solaroad.legrand')
x = pd.read_csv(file, delimiter=';', skip_blank_lines=True)
x.columns = ['Date', 'kWh']
index_time = pd.to_datetime(x['Date'], format='%m/%d/%Y %I:%M:%S %p')
x.index = index_time
for key in x.keys():
if 'Unnamed' in key:
del (x[key])
x = x.dropna()
del (x['Date'])
x['kWh'] = pd.to_numeric(x['kWh'])
# Authenticate
server, auth_token = sc.authenticate()
deviceId = sc.getDeviceId()
# Add Sensor
logger.debug('======================== Now processing Legrand ========================')
sc.addSensor(server, auth_token, deviceId, SENSOR_NAME, SENSOR_NAME, SENSOR_NAME, SENSOR_NAME)
# Pre-processing
y = x.resample('12H').mean().interpolate(method='linear')
# Break DataFrame into chunks of 100k
ctr = 0
total_steps = round(len(x) / sc.MAX_POINTS) + 1
while ctr < total_steps:
sp = ctr * sc.MAX_POINTS
tmp = y.iloc[sp:sp + sc.MAX_POINTS - 1, :]
logger.debug('--------------------- RECORD %s/%s ------------------------------', ctr + 1, total_steps)
for key in tmp.keys():
packer = xdrlib.Packer()
packer.pack_int(1) # version 1
packer.pack_enum(sc.SECONDS)
packer.pack_int(43200)
POINTS = len(tmp[key])
packer.pack_int(POINTS)
logger.debug('Now uploading %s', key)
if ctr == 0:
sc.addChannel(server, auth_token, deviceId, SENSOR_NAME, CHANNEL_NAME, CHANNEL_NAME, CHANNEL_NAME)
for item in tmp[key].iteritems():
val = item[1]
timestamp = item[0].to_pydatetime().timestamp() * 1000000000
packer.pack_hyper(int(timestamp))
packer.pack_float(float(val))
data = packer.get_buffer()
sc.uploadData(server, auth_token, deviceId, SENSOR_NAME, CHANNEL_NAME, data)
ctr = ctr + 1
def processDataFrame(y, sensor, sensorId):
logger = logging.getLogger('solaroad.' + sensor)
# Pre-processing
x = y[np.abs(y['Energy (Wh)'] -
y['Energy (Wh)'].mean()) <= (2 * y['Energy (Wh)'].std())]
x = x[(x['Energy (Wh)'] != 0)]
x = x.dropna()
x = x.resample('10S').mean().interpolate(method='linear')
# Break DataFrame into chunks of 100k
ctr = 0
total_steps = np.round(len(x) / sc.MAX_POINTS) + 1
while ctr < total_steps:
# Authenticate
server, auth_token = sc.authenticate()
deviceId = sc.getDeviceId()
sp = ctr * sc.MAX_POINTS
tmp = x.iloc[sp:sp + sc.MAX_POINTS - 1, :]
logger.debug(
'--------------------- RECORD %s/%s of %s ------------------------------',
ctr + 1, total_steps, sensorId)
for key in tmp.keys():
channel = '_'.join(
key.replace('(', '').replace(')', '').split(' '))
packer = xdrlib.Packer()
packer.pack_int(1) # version 1
packer.pack_enum(sc.SECONDS)
packer.pack_int(10)
POINTS = len(tmp[key])
packer.pack_int(POINTS)
logger.debug('Now uploading %s', key)
if ctr == 0:
sc.addChannel(server, auth_token, deviceId, sensorId, channel,
channel, channel)
for item in tmp[key].iteritems():
val = item[1]
timestamp = item[0].to_pydatetime().timestamp() * 1000000000
packer.pack_hyper(int(timestamp))
packer.pack_float(float(val))
data = packer.get_buffer()
sc.uploadData(server, auth_token, deviceId, sensorId, channel,
data)
logger.debug(
'--------------------- FINISHED RECORD %s/%s of %s ------------------------------',
ctr + 1, total_steps, sensorId)
ctr = ctr + 1
def processAPSFile(file):
logger = logging.getLogger('solaroad.aps')
x = pd.read_csv(file, delimiter=';', skip_blank_lines=True)
index_time = pd.to_datetime(x['Date'], format="%Y-%m-%d %H:%M:%S")
x.index = index_time
for key in x.keys():
if 'Unnamed' in key:
del (x[key])
x = x.dropna()
for inverterId in x['Inverter ID'].unique():
logger.debug('======================== Now processing %s ========================', inverterId)
y = x.loc[x['Inverter ID'] == inverterId]
del (y['Inverter ID'])
del (y['Date'])
server, auth_token = sc.authenticate()
deviceId = sc.getDeviceId()
ctr = 0
total_steps = np.round(len(y) / sc.MAX_POINTS) + 1
while ctr < total_steps:
sp = ctr * sc.MAX_POINTS
tmp = y.iloc[sp:sp + sc.MAX_POINTS - 1, :]
logger.debug('--------------------- RECORD %s/%s ------------------------------', ctr + 1, total_steps)
sc.addSensor(server, auth_token, deviceId, inverterId, inverterId, inverterId, inverterId)
packer = xdrlib.Packer()
packer.pack_int(1) # version 1
packer.pack_enum(sc.SECONDS)
packer.pack_int(300)
POINTS = len(tmp)
packer.pack_int(POINTS)
logger.debug('Now uploading %s', inverterId)
for key in tmp.keys():
channel = '_'.join(key.replace('(', '').replace(')', '').split(' '))
sc.addChannel(server, auth_token, deviceId, inverterId, channel, channel, channel)
for item in tmp[key].iteritems():
val = item[1]
timestamp = item[0].to_pydatetime().timestamp() * 1000000000
packer.pack_hyper(int(timestamp))
packer.pack_float(float(val))
data = packer.get_buffer()
sc.uploadData(server, auth_token, deviceId, inverterId, channel, data)
ctr = ctr + 1
def processAgilentFile(file):
logger = logging.getLogger('solaroad.agilent')
numSkipRows = 0
num_lines = sum(1 for line in open(file, encoding="utf-16")) - 1
with open(file, encoding="utf-16") as csvFile:
line = csvFile.readline()
while line[:5] != "Scan,":
if numSkipRows >= num_lines:
logger.debug('There was no data to read from %s! Skipping!',
file)
return
numSkipRows += 1
line = csvFile.readline()
x = pd.read_csv(file,
delimiter=',',
skip_blank_lines=True,
skiprows=numSkipRows,
encoding="utf-16")
index_time = pd.to_datetime(x['Time'], format="%d-%m-%Y %H:%M:%S:%f")
x.index = index_time
for key in x.keys():
if 'Unnamed' in key:
del (x[key])
x = x.dropna()
del (x['Time'])
del (x['Scan'])
server, auth_token = sc.authenticate()
deviceId = sc.getDeviceId()
# Add Sensor
logger.debug(
'======================== Now processing Agilent ========================'
)
sc.addSensor(server, auth_token, deviceId, SENSOR_NAME, SENSOR_NAME,
SENSOR_NAME, SENSOR_NAME)
# Pre-processing
y = x.resample('120S').mean().interpolate(method='linear')
# Break DataFrame into chunks of 100k
ctr = 0
total_steps = np.round(len(x) / sc.MAX_POINTS) + 1
while ctr < total_steps:
sp = ctr * sc.MAX_POINTS
tmp = y.iloc[sp:sp + sc.MAX_POINTS - 1, :]
logger.debug(
'--------------------- RECORD %s/%s ------------------------------',
str(ctr + 1), str(total_steps))
for key in tmp.keys():
channel = '_'.join(
key.replace('(',
'').replace(')',
'').replace('<',
'').replace('>',
'').split(' '))
packer = xdrlib.Packer()
packer.pack_int(1) # version 1
packer.pack_enum(sc.SECONDS)
packer.pack_int(120)
POINTS = len(tmp[key])
packer.pack_int(POINTS)
logger.debug('Now uploading %s', key)
if ctr == 0:
sc.addChannel(server, auth_token, deviceId, SENSOR_NAME,
channel, channel, channel)
for item in tmp[key].iteritems():
val = item[1]
timestamp = item[0].to_pydatetime().timestamp() * 1000000000
packer.pack_hyper(int(timestamp))
packer.pack_float(float(val))
data = packer.get_buffer()
sc.uploadData(server, auth_token, deviceId, SENSOR_NAME, channel,
data)
ctr = ctr + 1
def processFlirBicycleFile(file):
logger = logging.getLogger('solaroad.flirbicycle')
x = pd.read_csv(file,
delimiter=',',
skip_blank_lines=True,
skipinitialspace=True)
index_time = pd.to_datetime(x['Time'], format="%d/%m/%Y %H:%M:%S")
x.index = index_time
for key in x.keys():
if 'Unnamed' in key:
del (x[key])
del (x['Time'])
x = x.dropna()
for zone in x['Zone'].unique():
# Authenticate
server, auth_token = sc.authenticate()
deviceId = sc.getDeviceId()
# Add Sensor
logger.debug(
'======================== Now processing Zone %s ========================',
zone)
sc.addSensor(server, auth_token, deviceId, str(zone), 'Flir-Bicycle',
str(zone), str(zone))
# Pre-processing
y = x.resample('3600S').mean().interpolate(method='linear')
del (y['Zone'])
# Break DataFrame into chunks of 100k
ctr = 0
total_steps = np.round(len(x) / sc.MAX_POINTS) + 1
while ctr < total_steps:
sp = ctr * sc.MAX_POINTS
tmp = y.iloc[sp:sp + sc.MAX_POINTS - 1, :]
logger.debug(
'--------------------- RECORD %s/%s of %s ------------------------------',
ctr + 1, total_steps, zone)
for key in tmp.keys():
channel = '_'.join(
key.replace('(', '').replace(')',
'').replace('#',
'').split(' '))
packer = xdrlib.Packer()
packer.pack_int(1) # version 1
packer.pack_enum(sc.SECONDS)
packer.pack_int(3600)
POINTS = len(tmp[key])
packer.pack_int(POINTS)
logger.debug('Now uploading %s', key)
if ctr == 0:
sc.addChannel(server, auth_token, deviceId, str(zone),
channel, channel, channel)
for item in tmp[key].iteritems():
val = item[1]
timestamp = item[0].to_pydatetime().timestamp(
) * 1000000000
packer.pack_hyper(int(timestamp))
packer.pack_float(float(val))
data = packer.get_buffer()
sc.uploadData(server, auth_token, deviceId, str(zone), channel,
data)
ctr = ctr + 1
def processGillFile(file):
logger = logging.getLogger('solaroad.gill')
x = pd.read_csv(file,
delimiter=',',
skiprows=1,
header=None,
skip_blank_lines=True)
x.columns = [
'SlNo', 'Reporting Time', 'Node', 'Pressure', 'Relative Humidity',
'Temperature', 'Dew Point', 'Solar Radiation', 'Measured Time',
'Voltage', 'Status', 'EndChar'
]
x.index = pd.to_datetime(x['Measured Time'], format="%Y-%m-%dT%H:%M:%S.%f")
x.index.name = 'Timestamp'
del (x['SlNo'])
del (x['Node'])
del (x['Reporting Time'])
del (x['Measured Time'])
del (x['Voltage'])
del (x['Status'])
del (x['EndChar'])
x = x.dropna()
sensorName = 'GillMaximetGMX301'
logger.debug(
'======================== Now processing %s ========================',
sensorName)
server, auth_token = sc.authenticate()
deviceId = sc.getDeviceId()
x = x.resample('5min').mean().interpolate(method='linear')
ctr = 0
total_steps = np.round(len(x) / sc.MAX_POINTS) + 1
while ctr < total_steps:
sp = ctr * sc.MAX_POINTS
tmp = x.iloc[sp:sp + sc.MAX_POINTS - 1, :]
logger.debug(
'--------------------- RECORD %s/%s ------------------------------',
ctr + 1, total_steps)
sc.addSensor(server, auth_token, deviceId, sensorName, sensorName,
sensorName, sensorName)
logger.debug('Now uploading %s', sensorName)
for key in tmp.keys():
packer = xdrlib.Packer()
packer.pack_int(1) # version 1
packer.pack_enum(sc.SECONDS)
packer.pack_int(300)
POINTS = len(tmp)
packer.pack_int(POINTS)
channel = '_'.join(
key.replace('(', '').replace(')', '').split(' '))
sc.addChannel(server, auth_token, deviceId, sensorName, channel,
channel, channel)
logger.debug('Now uploading %s', channel)
for item in tmp[key].iteritems():
val = item[1]
timestamp = item[0].to_pydatetime().timestamp() * 1000000000
packer.pack_hyper(int(timestamp))
packer.pack_float(float(val))
data = packer.get_buffer()
sc.uploadData(server, auth_token, deviceId, sensorName, channel,
data)
ctr = ctr + 1
