From bc392c94ce4cffa6dda3d63225aa1cdd570aa9dc Mon Sep 17 00:00:00 2001
From: karolina <amvdw95@gmail.com>
Date: Thu, 6 Jun 2013 15:43:45 +0000
Subject: [PATCH] removed checking for rc filetype, as it is always pycasso
---
gridded/da/tm5/observationoperator.py | 105 +++++++++-----------------
1 file changed, 34 insertions(+), 71 deletions(-)
diff --git a/gridded/da/tm5/observationoperator.py b/gridded/da/tm5/observationoperator.py
index 994164a..5d62cdb 100755
--- a/gridded/da/tm5/observationoperator.py
+++ b/gridded/da/tm5/observationoperator.py
@@ -63,26 +63,18 @@ class TM5ObservationOperator(ObservationOperator):
"""
- def __init__(self, RcFileName, DaCycle=None):
+ def __init__(self, filename):
""" The instance of an TMObservationOperator is application dependent """
self.Identifier = identifier # the identifier gives the model name
self.Version = version # the model version used
self.RestartFileList = []
self.OutputFileList = []
- self.RcFileType = 'None'
+
self.outputdir = None # Needed for opening the samples.nc files created
- self.load_rc(RcFileName) # load the specified rc-file
+ self.load_rc(filename) # load the specified rc-file
self.validate_rc() # validate the contents
- # The following code allows the object to be initialized with a DaCycle object already present. Otherwise, it can
- # be added at a later moment.
-
- if DaCycle != None:
- self.DaCycle = DaCycle
- else:
- self.DaCycle = {}
-
logging.info('Observation Operator initialized: %s (%s)' % (self.Identifier, self.Version))
def initialize(self, DaCycle):
@@ -101,7 +93,7 @@ class TM5ObservationOperator(ObservationOperator):
# Create the TM5 run directory to hold a copy of the modified rc-file
- tm5compiledir = self.tm_settings[self.rundirkey]
+ tm5compiledir = self.tm_settings['my.run.dir']
create_dirs(tm5compiledir)
rcfilename = os.path.join(tm5compiledir, 'tm5_setup_init.rc')
@@ -125,7 +117,7 @@ class TM5ObservationOperator(ObservationOperator):
logging.debug('Reloading the da.obsoperator.rc file for this DaCycle')
- self.load_rc(self.DaCycle['da.obsoperator.rc']) #LU czy tutaj jest to kiedykolwiek zapisywane? chyba tak, jak zapisujemy daCycle...
+ self.load_rc(self.DaCycle['da.obsoperator.rc'])
logging.debug('Note that the obsoperator is not recompiled if this is a recovery from a crash!!!')
@@ -178,8 +170,8 @@ class TM5ObservationOperator(ObservationOperator):
NewItems = {
'submit.options': DaPlatForm.give_blocking_flag(),
- self.timestartkey: self.DaCycle['time.sample.start'],
- self.timefinalkey: self.DaCycle['time.sample.end'],
+ 'timerange.start': self.DaCycle['time.sample.start'],
+ 'timerange.end': self.DaCycle['time.sample.end'],
'jobstep.timerange.start': self.DaCycle['time.sample.start'],
'jobstep.timerange.end': self.DaCycle['time.sample.end'],
'jobstep.length': 'inf',
@@ -190,10 +182,10 @@ class TM5ObservationOperator(ObservationOperator):
}
if self.DaCycle['time.restart']: # If this is a restart from a previous cycle, the TM5 model should do a restart
- NewItems[self.istartkey] = self.restartvalue
+ NewItems['istart'] = self.restartvalue
logging.debug('Resetting TM5 to perform restart')
else:
- NewItems[self.istartkey] = self.coldstartvalue # if not, start TM5 'cold'
+ NewItems['istart'] = self.coldstartvalue # if not, start TM5 'cold'
logging.debug('Resetting TM5 to perform cold start')
#LU to ponizej: po prostu jesli to jest inny lag niz pierwszy
#LU czyli: restart wtedy kiedy albo time.restart = true czyli w kazdym nastepnym cyklu, albo kiedy jest to nie pierwszy step w sample step. tylko wtedy to skad robimy restart sie rozni...czy nie , bo robimy po advance?
@@ -201,7 +193,7 @@ class TM5ObservationOperator(ObservationOperator):
#LU ale: nowy RC zapisywany jst przy koncu cyklu. czyli time. sample.window bedzie zawsze 0.
if self.DaCycle['time.sample.window'] != 0: # If this is a restart from a previous time step within the filter lag, the TM5 model should do a restart
- NewItems[self.istartkey] = self.restartvalue
+ NewItems['istart'] = self.restartvalue
logging.debug('Resetting TM5 to perform restart')
# If neither one is true, simply take the istart value from the tm5.rc file that was read
@@ -209,20 +201,16 @@ class TM5ObservationOperator(ObservationOperator):
self.modify_rc(NewItems)
self.write_rc(self.RcFileName)
- def load_rc(self, RcFileName):#LU tutaj bylo wczesniej rcfIletype. to znaczy ze pewnie zawsze bylo pycasso. bo wpp byloby blad.
+ def load_rc(self, name):#LU tutaj bylo wczesniej rcfIletype. to znaczy ze pewnie zawsze bylo pycasso. bo wpp byloby blad.
"""
This method loads a TM5 rc-file with settings for this simulation
"""
import da.tools.rcn as rc
- self.rcfile = rc.RcFile(RcFileName)
+ self.rcfile = rc.RcFile(name)
self.tm_settings = self.rcfile.values
- self.RcFileName = RcFileName
- self.Tm5RcLoaded = True #LU to wyglada na zupelnie niepotrzebne
- if 'my.source.dirs' in self.tm_settings.keys():
- self.RcFileType = 'pycasso'
- else:
- self.RcFileType = 'pre-pycasso'
+ self.RcFileName = name
+
logging.debug('TM5 rc-file loaded successfully')
def validate_rc(self):
@@ -230,40 +218,18 @@ class TM5ObservationOperator(ObservationOperator):
Validate the contents of the tm_settings dictionary and add extra values. The required items for the TM5 rc-file
are specified in the tm5_tools module, as dictionary variable "needed_rc_items".
"""
-
-
- if self.RcFileType == 'pycasso':
- self.projectkey = 'my.project.dir'
- self.rundirkey = 'my.run.dir'
- self.outputdirkey = 'output.dir'
- self.savedirkey = 'restart.write.dir'
- self.timestartkey = 'timerange.start'
- self.timefinalkey = 'timerange.end'
- self.timelengthkey = 'jobstep.length'
- self.istartkey = 'istart'
- self.restartvalue = 33
- self.coldstartvalue = 9
- else:
- self.projectkey = 'runid'
- self.rundirkey = 'rundir'
- self.outputdirkey = 'outputdir'
- self.savedirkey = 'savedir'
- self.timestartkey = 'time.start'
- self.timefinalkey = 'time.final'
- self.timelengthkey = 'time.break.nday'
- self.istartkey = 'istart'
- self.restartvalue = 3
- self.coldstartvalue = 9
+ self.restartvalue = 33
+ self.coldstartvalue = 9
needed_rc_items = [
- self.projectkey,
- self.rundirkey,
- self.outputdirkey,
- self.savedirkey,
- self.timestartkey,
- self.timefinalkey,
- self.timelengthkey,
- self.istartkey
+ 'my.project.dir',
+ 'my.run.dir',
+ 'output.dir',
+ 'restart.write.dir',
+ 'timerange.start',
+ 'timerange.end',
+ 'jobstep.length',
+ 'istart'
]
for k, v in self.tm_settings.iteritems():
@@ -280,7 +246,6 @@ class TM5ObservationOperator(ObservationOperator):
self.tm_settings[k] = to_datetime(v)
for key in needed_rc_items:
-
if not self.tm_settings.has_key(key):
msg = 'Missing a required value in rc-file : %s' % key
logging.error(msg)
@@ -357,12 +322,10 @@ class TM5ObservationOperator(ObservationOperator):
# Next, make sure there is an actual model version compiled and ready to execute
- targetdir = os.path.join(self.tm_settings[self.rundirkey])
+ targetdir = os.path.join(self.tm_settings['my.run.dir'])
- if self.RcFileType == 'pycasso':
- self.Tm5Executable = os.path.join(targetdir, self.tm_settings['my.basename'] + '.x')
- else:
- self.Tm5Executable = os.path.join(targetdir, 'tm5.x')
+
+ self.Tm5Executable = os.path.join(targetdir, self.tm_settings['my.basename'] + '.x')
if not os.path.exists(self.Tm5Executable):
logging.error("Required TM5 executable was not found %s" % self.Tm5Executable)
@@ -386,8 +349,8 @@ class TM5ObservationOperator(ObservationOperator):
# First get the restart data for TM5 from the current restart dir of the filter
sourcedir = self.DaCycle['dir.restart']
- targetdir = self.tm_settings[self.savedirkey]
- self.outputdir = self.tm_settings[self.outputdirkey] #IV test
+ targetdir = self.tm_settings['restart.write.dir']
+ self.outputdir = self.tm_settings['output.dir'] #IV test
for f in os.listdir(sourcedir):
fpath = os.path.join(sourcedir, f)
@@ -458,7 +421,7 @@ class TM5ObservationOperator(ObservationOperator):
""" Method handles the case where a shell runs an MPI process that forks into N TM5 model instances """
DaPlatForm = self.DaCycle.DaPlatForm
- targetdir = os.path.join(self.tm_settings[self.rundirkey])
+ targetdir = os.path.join(self.tm_settings['my.run.dir'])
if not os.path.exists(os.path.join(mpi_shell_location, mpi_shell_filename)):
logging.error("Cannot find the mpi_shell wrapper needed for completion (%s) in (%s)" % (mpi_shell_filename, mpi_shell_location))
@@ -513,7 +476,7 @@ class TM5ObservationOperator(ObservationOperator):
""" Method handles the case where one TM5 model instance with N tracers does the sampling of all ensemble members"""
- tm5submitdir = os.path.join(self.tm_settings[self.rundirkey])
+ tm5submitdir = os.path.join(self.tm_settings['my.run.dir'])
logging.info('tm5submitdir', tm5submitdir)
# Go to executable directory and start the subprocess, using a new logfile
@@ -558,8 +521,8 @@ class TM5ObservationOperator(ObservationOperator):
Note 2: also adding the weekly mean flux output to the OutputFileList for later collection
"""
- sourcedir = os.path.join(self.tm_settings[self.savedirkey])
- filterlist = ['%s' % self.tm_settings[self.timefinalkey].strftime('%Y%m%d')]
+ sourcedir = os.path.join(self.tm_settings['restart.write.dir'])
+ filterlist = ['%s' % self.tm_settings['timerange.end'].strftime('%Y%m%d')]
logging.debug("Creating a new list of TM5 restart data")
logging.debug(" from directory: %s " % sourcedir)
@@ -591,7 +554,7 @@ class TM5ObservationOperator(ObservationOperator):
self.RestartFileList.append(fil)
logging.debug(" [added to restart list] .... %s " % fil)
- sourcedir = os.path.join(self.tm_settings[self.outputdirkey])
+ sourcedir = os.path.join(self.tm_settings['output.dir'])
sd_ed = self.DaCycle['time.sample.stamp']
filterlist = ['flask_output.%s' % sd_ed, 'flux1x1_%s' % sd_ed]
--
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