if args.data and (len(args.data) != len(args.legend)):
sys.exit('Number of legend items must equal the number of data files')
elif args.behavioralData and (len(args.behavioralData) != len(
args.legend)):
sys.exit('Number of legend items must equal the number of data files')
# Open data and align to observed
obs_align = None
data = []
max_x = min_x = 0
if args.data:
# Open observed data
obs_file = open(args.obs, 'r')
(obs_datetime,
obs_data) = RHESSysOutput.readObservedDataFromFile(obs_file,
readHour=False)
obs_file.close()
obs = pd.Series(obs_data, index=obs_datetime)
for d in args.data:
mod_file = open(d, 'r')
(tmp_datetime,
tmp_data) = RHESSysOutput.readColumnFromFile(mod_file,
args.column,
startHour=0)
tmp_mod = pd.Series(tmp_data, index=tmp_datetime)
# Align timeseries
(mod_align, obs_align) = tmp_mod.align(obs, join='inner')
tmp_max_x = max(mod_align.max(), obs_align.max())
if tmp_max_x > max_x:
max_x = tmp_max_x
sys.exit('A secondary data file was specified, but the secondary column to use was not')
if args.data and ( len(args.data) != len(args.legend) ):
sys.exit('Number of legend items must equal the number of data files')
elif args.behavioralData and ( len(args.behavioralData) != len(args.legend) ):
sys.exit('Number of legend items must equal the number of data files')
# Open data and align to observed
obs_align = None
data = []
max_x = min_x = 0
if args.data:
# Open observed data
obs_file = open(args.obs, 'r')
(obs_datetime, obs_data) = RHESSysOutput.readObservedDataFromFile(obs_file,
readHour=False)
obs_file.close()
obs = pd.Series(obs_data, index=obs_datetime)
for d in args.data:
mod_file = open(d, 'r')
(tmp_datetime, tmp_data) = RHESSysOutput.readColumnFromFile(mod_file, args.column, startHour=0)
tmp_mod = pd.Series(tmp_data, index=tmp_datetime)
# Align timeseries
(mod_align, obs_align) = tmp_mod.align(obs, join='inner')
tmp_max_x = max(mod_align.max(), obs_align.max())
if tmp_max_x > max_x:
max_x = tmp_max_x
min_x = max(min_x, mod_align.min())
mod_file.close()
def readBehavioralData(
self, basedir, session_id, variable="streamflow", observed_file=None, behavioral_filter=None, end_date=None
):
dbPath = RHESSysCalibrator.getDBPath(basedir)
if not os.access(dbPath, os.R_OK):
raise IOError(errno.EACCES, "The database at %s is not readable" % dbPath)
self.logger.debug("DB path: %s" % dbPath)
outputPath = RHESSysCalibrator.getOutputPath(basedir)
if not os.access(outputPath, os.R_OK):
raise IOError(errno.EACCES, "The output directory %s is not readable" % outputPath)
self.logger.debug("Output path: %s" % outputPath)
rhessysPath = RHESSysCalibrator.getRhessysPath(basedir)
calibratorDB = ModelRunnerDB(RHESSysCalibrator.getDBPath(basedir))
# Make sure the session exists
session = calibratorDB.getSession(session_id)
if None == session:
raise Exception("Session %d was not found in the calibration database %s" % (session_id, dbPath))
if session.status != "complete":
print "WARNING: session status is: %s. Some model runs may not have completed." % (session.status,)
else:
self.logger.debug("Session status is: %s" % (session.status,))
# Determine observation file path
if observed_file:
obs_file = observed_file
else:
# Get observered file from session
assert session.obs_filename != None
obs_file = session.obs_filename
obsPath = RHESSysCalibrator.getObsPath(basedir)
obsFilePath = os.path.join(obsPath, obs_file)
if not os.access(obsFilePath, os.R_OK):
raise IOError(errno.EACCES, "The observed data file %s is not readable" % obsFilePath)
self.logger.debug("Obs path: %s" % obsFilePath)
# Get runs in session
runs = calibratorDB.getRunsInSession(session.id, where_clause=behavioral_filter)
numRuns = len(runs)
if numRuns == 0:
raise Exception("No runs found for session %d" % (session.id,))
response = raw_input(
"%d runs selected for plotting from session %d in basedir '%s', continue? [yes | no] "
% (numRuns, session_id, os.path.basename(basedir))
)
response = response.lower()
if response != "y" and response != "yes":
# Exit normally
return 0
self.logger.debug("%d behavioral runs" % (numRuns,))
# Read observed data from file
obsFile = open(obsFilePath, "r")
(obs_datetime, obs_data) = RHESSysOutput.readObservedDataFromFile(obsFile)
obsFile.close()
obs = pd.Series(obs_data, index=obs_datetime)
if end_date:
obs = obs[:end_date]
self.logger.debug("Observed data: %s" % obs_data)
likelihood = np.empty(numRuns)
ysim = None
x = None
runsProcessed = False
for (i, run) in enumerate(runs):
if "DONE" == run.status:
runOutput = os.path.join(rhessysPath, run.output_path)
self.logger.debug(">>>\nOutput dir of run %d is %s" % (run.id, runOutput))
tmpOutfile = RHESSysCalibrator.getRunOutputFilePath(runOutput)
if not os.access(tmpOutfile, os.R_OK):
print "Output file %s for run %d not found or not readable, unable to calculate fitness statistics for this run" % (
tmpOutfile,
run.id,
)
continue
tmpFile = open(tmpOutfile, "r")
(tmp_datetime, tmp_data) = RHESSysOutput.readColumnFromFile(tmpFile, "streamflow")
tmp_mod = pd.Series(tmp_data, index=tmp_datetime)
# Align timeseries to observed
(mod, obs) = tmp_mod.align(obs, join="inner")
# Stash date for X values (assume they are the same for all runs
if x == None:
x = [datetime.strptime(str(d), "%Y-%m-%d %H:%M:%S") for d in mod.index]
# Put data in matrix
dataLen = len(mod)
if ysim == None:
# Allocate matrix for results
ysim = np.empty((numRuns, dataLen))
assert np.shape(ysim)[1] == dataLen
ysim[i,] = mod
# Store fitness parameter
likelihood[i] = run.nse
tmpFile.close()
runsProcessed = True
return (runsProcessed, obs, x, ysim, likelihood)