def find_mean(self, startUTCTimeStr, endUTCTimeStr):
startTime = btrdb.date(startUTCTimeStr) # returns nanoseconds since the epoch
endTime = btrdb.date(endUTCTimeStr) # returns nanoseconds since the epoch
summation = 0
count = 0
pw = int(math.ceil(math.log(endTime-startTime, 2)))-11
overview = self.connection.get_stat(self.uuid, startTime, endTime, pw)
for x in overview:
summation += x[2]*x[4]
count += x[4]
return summation/count, count
def find_mean(self, startUTCTimeStr, endUTCTimeStr):
startTime = btrdb.date(
startUTCTimeStr) # returns nanoseconds since the epoch
endTime = btrdb.date(
endUTCTimeStr) # returns nanoseconds since the epoch
summation = 0
count = 0
pw = int(math.ceil(math.log(endTime - startTime, 2))) - 11
overview = self.connection.get_stat(self.uuid, startTime, endTime, pw)
for x in overview:
summation += x[2] * x[4]
count += x[4]
return summation / count, count
def multi_resolution_search(self,
startUTCTimeStr,
endUTCTimeStr,
ylabel,
threshold=0.1,
plotFlag=False,
benchmarkFlag=False):
startTime = btrdb.date(
startUTCTimeStr) # returns nanoseconds since the epoch
endTime = btrdb.date(
endUTCTimeStr) # returns nanoseconds since the epoch
return self.visitor.traverse(self.uuid,
self.connection,
startTime,
endTime,
threshold,
ylabel,
plotFlag=plotFlag,
benchmarkFlag=benchmarkFlag)
def get_upmu_data(inputdt, upmu_path):
""" Retrieves instantaneous P, Q, and voltage magnitude for specified datetime.
Args:
inputdt (datetime): timezone aware datetime object
upmu_path (str): e.g., '/LBNL/grizzly_bus1/'
Returns:
{'P_A': , 'Q_A': , 'P_B': , 'Q_B': , 'P_C': , 'Q_C': ,
'units': ('kW', 'kVAR'),
'VMAG_A': , 'VMAG_B': , 'VMAG_C': }
"""
bc = btrdb.HTTPConnection("miranda.cs.berkeley.edu")
ur = btrdb.UUIDResolver("miranda.cs.berkeley.edu", "uuidresolver", "uuidpass", "upmu")
# convert dt to nanoseconds since epoch
epochns = btrdb.date(inputdt.strftime('%Y-%m-%dT%H:%M:%S'))
# retrieve raw data from btrdb
upmu_data = {}
streams = ['L1MAG', 'L2MAG', 'L3MAG', 'C1MAG', 'C2MAG', 'C3MAG', 'L1ANG', 'L2ANG', 'L3ANG', 'C1ANG', 'C2ANG', 'C3ANG']
for s in streams:
pt = bc.get_stat(ur.resolve(upmu_path + s), epochns, epochns + int(9e6))
upmu_data[s] = pt[0][2]
output_dict = {}
output_dict['P_A'] = (upmu_data['L1MAG']*upmu_data['C1MAG']*np.cos(upmu_data['L1ANG'] - upmu_data['C1ANG']))*1e-3
output_dict['Q_A'] = (upmu_data['L1MAG']*upmu_data['C1MAG']*np.sin(upmu_data['L1ANG'] - upmu_data['C1ANG']))*1e-3
output_dict['P_B'] = (upmu_data['L2MAG']*upmu_data['C2MAG']*np.cos(upmu_data['L2ANG'] - upmu_data['C2ANG']))*1e-3
output_dict['Q_B'] = (upmu_data['L2MAG']*upmu_data['C2MAG']*np.sin(upmu_data['L2ANG'] - upmu_data['C2ANG']))*1e-3
output_dict['P_C'] = (upmu_data['L3MAG']*upmu_data['C3MAG']*np.cos(upmu_data['L3ANG'] - upmu_data['C3ANG']))*1e-3
output_dict['Q_C'] = (upmu_data['L3MAG']*upmu_data['C3MAG']*np.sin(upmu_data['L3ANG'] - upmu_data['C3ANG']))*1e-3
output_dict['units'] = ('kW', 'kVAR', 'V')
output_dict['VMAG_A'] = upmu_data['L1MAG']
output_dict['VMAG_B'] = upmu_data['L2MAG']
output_dict['VMAG_C'] = upmu_data['L3MAG']
return output_dict
def multi_resolution_search_fw(self, startUTCTimeStr, endUTCTimeStr, ylabel, threshold=0.1, final_res=26, plotFlag=False, benchmarkFlag=False):
startTime = btrdb.date(startUTCTimeStr) # returns nanoseconds since the epoch
endTime = btrdb.date(endUTCTimeStr) # returns nanoseconds since the epoch
return self.visitor.traverse(self.uuid, self.connection, startTime, endTime, threshold, ylabel, final_res, plotFlag=plotFlag, benchmarkFlag=benchmarkFlag)
