def getObsStatsForDate(self, platform, obsName, uom, sOrder, beginDate, endDate):
obsStats = stats()
sensorID = self.dbConnection.sensorExists(obsName, uom, platform, sOrder);
if(sensorID != None and sensorID != -1):
sql = "SELECT m_date,m_value FROM multi_obs WHERE (m_date >= '%s' AND m_date <= '%s') AND sensor_id=%d"\
%(beginDate,endDate,sensorID)
dbCursor = self.dbConnection.executeQuery(sql)
if(dbCursor != None):
for row in dbCursor:
m_value = float(row['m_value'])
obsStats.addValue(m_value)
#Calculate the statistics.
obsStats.doCalculations()
dbCursor.close()
return(obsStats)
def getObsStatsForDate(self, platform, obsName, uom, sOrder, beginDate, endDate):
obsStats = stats()
sensorID = self.dbConnection.sensorExists(obsName, uom, platform, sOrder)
if sensorID != None and sensorID != -1:
sql = "SELECT m_date,m_value FROM multi_obs WHERE (m_date >= '%s' AND m_date <= '%s') AND sensor_id=%d" % (
beginDate,
endDate,
sensorID,
)
dbCursor = self.dbConnection.executeQuery(sql)
if dbCursor != None:
for row in dbCursor:
m_value = float(row["m_value"])
obsStats.addValue(m_value)
# Calculate the statistics.
obsStats.doCalculations()
dbCursor.close()
return obsStats
def computeMonthlyDataPoints(self, platformList, beginYear, endYear, QAQCFlags, outputFilePath, writeRawDataPoints):
import calendar
# If we want to use the qc_level to determine which data to include, let's build the SQL for this.
# qaqcWHERE = ''
# if(len(QAQCFlags)):
# for qcLevel in QAQCFlags:
# if(len(qaqcWHERE)):
# qaqcWHERE += 'OR '
# qaqcWHERE += "qc_level=%d " % (qcLevel)
# qaqcWHERE = "AND (%s)" %(qaqcWHERE)
for platformHandle in platformList:
# Get all the observations on the platform
platformNfoCur = self.dbConnection.getPlatformInfo(platformHandle)
# Platform doesn't seem to exist, so move on.
if platformNfoCur == None:
continue
platformNfo = platformNfoCur.fetchone()
platformID = int(platformNfo["row_id"])
platformNfoCur.close()
sql = (
"SELECT\
obs_type.standard_name \
,uom_type.standard_name as uom \
,sensor.row_id as sensor_id\
,sensor.m_type_id as m_type_id\
,sensor.s_order as s_order\
FROM sensor \
left join m_type on m_type.row_id=sensor.m_type_id \
left join m_scalar_type on m_scalar_type.row_id=m_type.m_scalar_type_id \
left join obs_type on obs_type.row_id=m_scalar_type.obs_type_id \
left join uom_type on uom_type.row_id=m_scalar_type.uom_type_id \
WHERE sensor.platform_id = %d ORDER BY obs_type.standard_name ASC"
% (platformID)
)
sensorCur = self.dbConnection.executeQuery(sql)
# No sensors available on the platform.
if sensorCur == None:
continue
sensorNfo = recursivedefaultdict()
for row in sensorCur:
sensorNfo[row["standard_name"]]["uom"] = row["uom"]
sensorNfo[row["standard_name"]]["sensor_id"] = int(row["sensor_id"])
sensorNfo[row["standard_name"]]["m_type_id"] = int(row["m_type_id"])
sensorNfo[row["standard_name"]]["sorder"] = int(row["s_order"])
sensorCur.close()
outputFile = "%s/%s-yearly-stats-%s_%s.csv" % (outputFilePath, platformHandle, beginYear, endYear)
statsFile = open(outputFile, "w")
statsFile.write("Observation,StartDate,EndDate,Min,Max,Average,StdDev,90thPercentile,TotalRecordCount\n")
rawDataPoints = None
if writeRawDataPoints:
outputFile = "%s/%s-yearly-raw.csv" % (outputFilePath, platformHandle)
rawDataPoints = open(outputFile, "w")
if rawDataPoints != None:
rawDataPoints.write("Observation,StartDate,EndDate,Data\n")
yearList = []
if beginYear == None:
# Get the distinct years
if self.dbConnection.dbType == dbTypes.PostGRES:
sql = (
"SELECT DISTINCT(EXTRACT(YEAR FROM m_date)) as year FROM multi_obs WHERE platform_handle='%s'"
% (platformHandle)
)
else:
sql = (
"SELECT DISTINCT(strftime('%%Y', m_date)) as year FROM multi_obs WHERE platform_handle='%s'"
% (platformHandle)
)
dbCursor = self.dbConnection.executeQuery(sql)
if dbCursor != None:
for row in dbCursor:
yearList.append(int(row["year"]))
dbCursor.close()
else:
for i in range(beginYear, endYear + 1):
yearList.append(i)
# This is a dictionary we use to hold all the months of data for the years. We use it as a collection
# of stats() objects so we can calculate some overall stats for each month over the years.
# obsOverallMonthStats = recursivedefaultdict()
print("Processing: %s" % (platformHandle))
for year in yearList:
for obsName in sensorNfo:
uom = sensorNfo[obsName]["uom"]
sensorID = sensorNfo[obsName]["sensor_id"]
mTypeID = sensorNfo[obsName]["m_type_id"]
# sOrder = sensorNfo[obsName]['sorder']
# Now for each month, we calc stats on the data.
for month in range(1, 13):
print("Obs: %s(%s) Year: %d Month: %d" % (obsName, uom, year, month))
monthStats = stats()
dayCnt = calendar.monthrange(year, month)
startDate = "%d-%02d-%02dT00:00:00" % (year, month, 1)
endDate = "%d-%02d-%2dT24:00:00" % (year, month, dayCnt[1])
if rawDataPoints != None:
rawDataPoints.write("%s,%s,%s" % (obsName, startDate, endDate))
# mTypeID = self.dbConnection.getMTypeFromObsName(obsName, uom, platformHandle, sOrder)
# sql = "SELECT m_date,m_value FROM multi_obs WHERE (m_date >= '%s' AND m_date <= '%s')\
# AND sensor_id=%d %s;"\
# %(startDate,endDate,sensorID,qaqcWHERE)
sql = (
"SELECT m_date,m_value,qc_level FROM multi_obs WHERE (m_date >= '%s' AND m_date <= '%s')\
AND sensor_id=%d;"
% (startDate, endDate, sensorID)
)
dbCursor = self.dbConnection.executeQuery(sql)
if dbCursor != None:
for row in dbCursor:
goodVal = False
# Use all data.
if len(QAQCFlags) == 0:
goodVal = True
elif row["qc_level"] != None:
for qaqcFlag in QAQCFlags:
if qaqcFlag == row["qc_level"]:
goodVal = True
break
if goodVal:
m_value = row["m_value"]
if m_value != None:
m_value = float(m_value)
monthStats.addValue(m_value)
if rawDataPoints != None:
rawDataPoints.write(",%f" % (m_value))
monthStats.doCalculations()
avg = monthStats.average
if avg == None:
avg = -1.0
stdDev = monthStats.stdDev
if stdDev == None:
stdDev = -1.0
popStdDev = monthStats.populationStdDev
if popStdDev == None:
popStdDev = -1.0
UpperPercentile = monthStats.getValueAtPercentile(90)
if UpperPercentile == None:
UpperPercentile = -1.0
min = monthStats.minVal
if min == None:
min = -1.0
max = monthStats.maxVal
if max == None:
max = -1.0
statsFile.write(
"%s,%s,%s,%f,%f,%f,%f,%f,%d\n"
% (
obsName,
startDate,
endDate,
min,
max,
avg,
stdDev,
UpperPercentile,
len(monthStats.items),
)
)
if rawDataPoints != None:
rawDataPoints.write("\n")
else:
i = 0
statsFile.close()
if rawDataPoints != None:
rawDataPoints.close()
def computeMonthlyDataPoints(self, platformList, beginYear, endYear, QAQCFlags, outputFilePath,writeRawDataPoints):
import calendar
#If we want to use the qc_level to determine which data to include, let's build the SQL for this.
#qaqcWHERE = ''
#if(len(QAQCFlags)):
# for qcLevel in QAQCFlags:
# if(len(qaqcWHERE)):
# qaqcWHERE += 'OR '
# qaqcWHERE += "qc_level=%d " % (qcLevel)
# qaqcWHERE = "AND (%s)" %(qaqcWHERE)
for platformHandle in platformList:
#Get all the observations on the platform
platformNfoCur = self.dbConnection.getPlatformInfo(platformHandle)
#Platform doesn't seem to exist, so move on.
if(platformNfoCur == None):
continue
platformNfo = platformNfoCur.fetchone()
platformID = int(platformNfo['row_id'])
platformNfoCur.close()
sql= "SELECT\
obs_type.standard_name \
,uom_type.standard_name as uom \
,sensor.row_id as sensor_id\
,sensor.m_type_id as m_type_id\
,sensor.s_order as s_order\
FROM sensor \
left join m_type on m_type.row_id=sensor.m_type_id \
left join m_scalar_type on m_scalar_type.row_id=m_type.m_scalar_type_id \
left join obs_type on obs_type.row_id=m_scalar_type.obs_type_id \
left join uom_type on uom_type.row_id=m_scalar_type.uom_type_id \
WHERE sensor.platform_id = %d ORDER BY obs_type.standard_name ASC"\
%(platformID)
sensorCur = self.dbConnection.executeQuery(sql)
#No sensors available on the platform.
if(sensorCur == None):
continue
sensorNfo = recursivedefaultdict()
for row in sensorCur:
sensorNfo[row['standard_name']]['uom'] = row['uom']
sensorNfo[row['standard_name']]['sensor_id'] = int(row['sensor_id'])
sensorNfo[row['standard_name']]['m_type_id'] = int(row['m_type_id'])
sensorNfo[row['standard_name']]['sorder'] = int(row['s_order'])
sensorCur.close()
outputFile = "%s/%s-yearly-stats-%s_%s.csv" %(outputFilePath,platformHandle,beginYear,endYear)
statsFile = open(outputFile,'w')
statsFile.write('Observation,StartDate,EndDate,Min,Max,Average,StdDev,90thPercentile,TotalRecordCount\n')
rawDataPoints = None
if(writeRawDataPoints):
outputFile = "%s/%s-yearly-raw.csv" %(outputFilePath,platformHandle)
rawDataPoints = open(outputFile, 'w')
if(rawDataPoints != None):
rawDataPoints.write('Observation,StartDate,EndDate,Data\n')
yearList = []
if(beginYear == None):
# Get the distinct years
if(self.dbConnection.dbType == dbTypes.PostGRES):
sql = "SELECT DISTINCT(EXTRACT(YEAR FROM m_date)) as year FROM multi_obs WHERE platform_handle='%s'" %(platformHandle)
else:
sql = "SELECT DISTINCT(strftime('%%Y', m_date)) as year FROM multi_obs WHERE platform_handle='%s'" %(platformHandle)
dbCursor = self.dbConnection.executeQuery(sql)
if(dbCursor != None):
for row in dbCursor:
yearList.append(int(row['year']))
dbCursor.close()
else:
for i in range(beginYear, endYear+1):
yearList.append(i)
#This is a dictionary we use to hold all the months of data for the years. We use it as a collection
#of stats() objects so we can calculate some overall stats for each month over the years.
#obsOverallMonthStats = recursivedefaultdict()
print("Processing: %s" % (platformHandle))
for year in yearList:
for obsName in sensorNfo:
uom = sensorNfo[obsName]['uom']
sensorID = sensorNfo[obsName]['sensor_id']
mTypeID = sensorNfo[obsName]['m_type_id']
#sOrder = sensorNfo[obsName]['sorder']
#Now for each month, we calc stats on the data.
for month in range( 1,13 ):
print("Obs: %s(%s) Year: %d Month: %d" %(obsName, uom, year, month))
monthStats = stats()
dayCnt = calendar.monthrange(year, month)
startDate = "%d-%02d-%02dT00:00:00" %(year,month,1)
endDate = "%d-%02d-%2dT24:00:00" %(year,month,dayCnt[1])
if(rawDataPoints != None):
rawDataPoints.write("%s,%s,%s" %(obsName,startDate,endDate))
#mTypeID = self.dbConnection.getMTypeFromObsName(obsName, uom, platformHandle, sOrder)
#sql = "SELECT m_date,m_value FROM multi_obs WHERE (m_date >= '%s' AND m_date <= '%s')\
# AND sensor_id=%d %s;"\
# %(startDate,endDate,sensorID,qaqcWHERE)
sql = "SELECT m_date,m_value,qc_level FROM multi_obs WHERE (m_date >= '%s' AND m_date <= '%s')\
AND sensor_id=%d;"\
%(startDate,endDate,sensorID)
dbCursor = self.dbConnection.executeQuery(sql)
if(dbCursor != None):
for row in dbCursor:
goodVal = False
#Use all data.
if(len(QAQCFlags) == 0):
goodVal = True
elif(row['qc_level'] != None):
for qaqcFlag in QAQCFlags:
if(qaqcFlag == row['qc_level']):
goodVal = True
break
if(goodVal):
m_value = row['m_value']
if(m_value != None):
m_value = float(m_value)
monthStats.addValue(m_value)
if(rawDataPoints != None):
rawDataPoints.write(",%f" %(m_value))
monthStats.doCalculations()
avg = monthStats.average
if(avg == None):
avg = -1.0
stdDev = monthStats.stdDev
if(stdDev == None):
stdDev = -1.0
popStdDev = monthStats.populationStdDev
if(popStdDev == None):
popStdDev = -1.0
UpperPercentile = monthStats.getValueAtPercentile(90)
if(UpperPercentile == None):
UpperPercentile = -1.0
min = monthStats.minVal
if(min == None):
min = -1.0
max = monthStats.maxVal
if(max == None):
max = -1.0
statsFile.write('%s,%s,%s,%f,%f,%f,%f,%f,%d\n'\
%(obsName,startDate,endDate,min,max,avg,stdDev,UpperPercentile,len(monthStats.items)))
if(rawDataPoints != None):
rawDataPoints.write("\n")
else:
i = 0
statsFile.close()
if(rawDataPoints != None):
rawDataPoints.close()