def readWindFile(self, file):
"""
Parsing this file is straight forward: we'll need the timestamp
and *scalar* quantities from each row.
"""
# read cleo forecast (ground)
print 'Process cleo forecast data (ground) ...', file
f = open(file, 'r')
lines = f.readlines()
header = lines[0]
assert header.strip() == windFileHeader.strip()
for line in lines[1:]:
row = line.split(' ')
timestamp = TimeAgent.hour(TimeAgent.mjd2dt(float(row[0]))) #mjd
self.data[timestamp] = {}
# what forecast type will this be?
self.data[timestamp]['forecast_type_id'] = \
self.getForecastTypeIdFromTimestamp(timestamp)
self.readWindFileValues(header, timestamp, row)
# Note: we'll stop doing this eventually, but for now:
# need to insert a corrected wind speed into the DB.
speed_mph = self.data[timestamp]['speed_mph']
self.data[timestamp]['speed_ms'] = \
self.dbimport.correctWindSpeed(timestamp
, self.mph2mps(speed_mph))
f.close()
def readWindFile(self, file):
"""
Parsing this file is straight forward: we'll need the timestamp
and *scalar* quantities from each row.
"""
# read cleo forecast (ground)
print 'Process cleo forecast data (ground) ...', file
f = open(file, 'r')
lines = f.readlines()
header = lines[0]
assert header.strip() == windFileHeader.strip()
for line in lines[1:]:
row = line.split(' ')
timestamp = TimeAgent.hour(TimeAgent.mjd2dt(float(row[0]))) #mjd
self.data[timestamp] = {}
# what forecast type will this be?
self.data[timestamp]['forecast_type_id'] = \
self.getForecastTypeIdFromTimestamp(timestamp)
self.readWindFileValues(header, timestamp, row)
# Note: we'll stop doing this eventually, but for now:
# need to insert a corrected wind speed into the DB.
speed_mph = self.data[timestamp]['speed_mph']
self.data[timestamp]['speed_ms'] = \
self.dbimport.correctWindSpeed(timestamp
, self.mph2mps(speed_mph))
f.close()
def readAtmoFile(self, file):
"""
Parsing this file is more complicated, because each row contains
*vector* quantities.
"""
# read cleo forecast (atmosphere)
print 'Process cleo forecast data (atmosphere) ... ', file
f = open(file, 'r')
lines = f.readlines()
header = lines[0]
assert header.strip() == freqFileHeader.strip()
first = lines[0].split(' ')
lines = lines[1:]
for line in lines:
row = line.split(' ')
timestamp = TimeAgent.hour(TimeAgent.mjd2dt(float(row[0]))) #mjdt1
if not self.data.has_key(timestamp):
self.reportLine("ERROR: No wind data for %s\n" % timestamp)
continue
# frequencies
self.data[timestamp]['freqs'] = []
# OpacityTime<freq>List_avrg
self.data[timestamp]['tauCleo'] = []
# TsysTime<freq>List_avrg
self.data[timestamp]['tSysCleo'] = []
# TatmTime<freq>List_avrg
self.data[timestamp]['tAtmCleo'] = []
num = self.numAtmoFreqs
for i in range(num):
#print first[ifreq+1], first[ifreq+51], first[ifreq+101]
self.data[timestamp]['freqs'].append(self.atmoFreqs[i])
self.data[timestamp]['tauCleo'].append(float(row[i + 1]))
self.data[timestamp]['tSysCleo'].append(float(row[i + num +
1]))
self.data[timestamp]['tAtmCleo'].append(
float(row[i + (num * 2) + 1]))
f.close()
def readAtmoFile(self, file):
"""
Parsing this file is more complicated, because each row contains
*vector* quantities.
"""
# read cleo forecast (atmosphere)
print 'Process cleo forecast data (atmosphere) ... ', file
f = open(file, 'r')
lines = f.readlines()
header = lines[0]
assert header.strip() == freqFileHeader.strip()
first = lines[0].split(' ')
lines = lines[1:]
for line in lines:
row = line.split(' ')
timestamp = TimeAgent.hour(TimeAgent.mjd2dt(float(row[0]))) #mjdt1
if not self.data.has_key(timestamp):
self.reportLine("ERROR: No wind data for %s\n" % timestamp)
continue
# frequencies
self.data[timestamp]['freqs'] = []
# OpacityTime<freq>List_avrg
self.data[timestamp]['tauCleo'] = []
# TsysTime<freq>List_avrg
self.data[timestamp]['tSysCleo'] = []
# TatmTime<freq>List_avrg
self.data[timestamp]['tAtmCleo'] = []
num = self.numAtmoFreqs
for i in range(num):
#print first[ifreq+1], first[ifreq+51], first[ifreq+101]
self.data[timestamp]['freqs'].append(self.atmoFreqs[i])
self.data[timestamp]['tauCleo'].append(float(row[i+1]))
self.data[timestamp]['tSysCleo'].append(float(row[i+num+1]))
self.data[timestamp]['tAtmCleo'].append(float(row[i+(num*2)+1]))
f.close()
