removed StateVector.isOptimized and replaced with an "optimized" parameter in...

removed StateVector.isOptimized and replaced with an "optimized" parameter in StateVector.write_to_file call

in obs and obspack_geocarbon adding some parameters to function calls

da/baseclasses/optimizer.py

@@ -148,7 +148,6 @@ class Optimizer(object):
             for m, mem in enumerate(members):
                 members[m].ParameterValues[:] = self.X_prime[n * self.nparams:(n + 1) * self.nparams, m] + self.x[n * self.nparams:(n + 1) * self.nparams]     
 
-        StateVector.isOptimized = True
         logging.debug('Returning optimized data to the StateVector, setting "StateVector.isOptimized = True" ')
 
     def write_diagnostics(self, DaCycle, StateVector, type='prior'):

da/baseclasses/statevector.py

@@ -143,7 +143,6 @@ class StateVector(object):
         self.nparams = int(self.DaCycle.DaSystem['nparameters'])
         self.nobs = 0
         
-        self.isOptimized = False
         self.ObsToAssimmilate = ()  # empty containter to hold observations to assimilate later on
 
         # These list objects hold the data for each time step of lag in the system. Note that the ensembles for each time step consist 
@@ -308,7 +307,7 @@ class StateVector(object):
         logging.info('The state vector has been propagated by one cycle')
 
 
-    def write_to_file(self, filename):
+    def write_to_file(self, filename, optimized):
         """
         :param filename: the full filename for the output NetCDF file
         :rtype: None
@@ -326,7 +325,7 @@ class StateVector(object):
         #import da.tools.io4 as io
         #import da.tools.io as io
 
-        if not self.isOptimized:
+        if not optimized:
             f = io.CT_CDF(filename, method='create')
             logging.debug('Creating new StateVector output file (%s)' % filename)
             qual = 'prior'

da/ct/obs.py

@@ -241,7 +241,7 @@ class CtObservations(Observation):
         return obsinputfile
 
 
-    def add_model_data_mismatch(self):
+    def add_model_data_mismatch(self, filename):
         """ 
             Get the model-data mismatch values for this cycle.
 
@@ -253,7 +253,7 @@ class CtObservations(Observation):
         """
         import da.tools.rc as rc
 
-        filename = self.DaCycle.DaSystem['obs.sites.rc']
+        
 
         if not os.path.exists(filename):
             msg = 'Could not find  the required sites.rc input file (%s)' % filename
@@ -314,7 +314,7 @@ class CtObservations(Observation):
 
             self.SiteInfo = SiteInfo
 
-    def write_obs_to_file(self):
+    def write_obs_to_file(self, outdir, timestamp):
         """ 
             Write selected information contained in the Observation object to a file. 
 
@@ -322,7 +322,8 @@ class CtObservations(Observation):
         import da.tools.io4 as io
 
         outfile = os.path.join(self.DaCycle['dir.output'], 'sampleinfo_%s.nc' % (self.DaCycle['time.sample.stamp']))
-
+        outfile = os.path.join(outdir, 'sampleinfo_%s.nc' % timestamp)
+        
         f = io.CT_CDF(outfile, method='create')
         logging.debug('Creating new Sample output file for postprocessing (%s)' % outfile)
 

da/ct/obspack_geocarbon.py

@@ -253,7 +253,7 @@ class ObsPackObservations(Observation):
 
         return obsinputfile
 
-    def add_model_data_mismatch(self):
+    def add_model_data_mismatch(self, filename):
         """ 
             Get the model-data mismatch values for this cycle.
 
@@ -265,7 +265,7 @@ class ObsPackObservations(Observation):
         """
         import da.tools.rc as rc
 
-        filename = self.DaCycle.DaSystem['obs.sites.rc']
+        
 
         if not os.path.exists(filename):
             msg = 'Could not find  the required sites.rc input file (%s) ' % filename
@@ -360,7 +360,7 @@ class ObsPackObservations(Observation):
 
         logging.debug("Added Model Data Mismatch to all samples ")
 
-    def write_obs_to_file(self):
+    def write_obs_to_file(self, outdir, timestamp):
         """ 
             Write selected information contained in the Observation object to a file. 
 
@@ -368,6 +368,8 @@ class ObsPackObservations(Observation):
         import da.tools.io4 as io
 
         outfile = os.path.join(self.DaCycle['dir.output'], 'sampleinfo_%s.nc' % (self.DaCycle['time.sample.stamp']))
+        outfile = os.path.join(outdir, 'sampleinfo_%s.nc' % timestamp)
+
 
         f = io.CT_CDF(outfile, method='create')
         logging.debug('Creating new Sample output file for postprocessing (%s)' % outfile)

da/tools/pipeline.py

@@ -56,12 +56,12 @@ def forward_pipeline(DaCycle, PlatForm, DaSystem, Samples, StateVector, ObsOpera
     else: 
         prepare_state(DaCycle, StateVector)
 
-    StateVector.isOptimized = False
+    
 
     # Write as prior fluxes to output dir
 
     savefilename = os.path.join(DaCycle['dir.output'], 'savestate.nc')   #LU to jest state vector po zoptymalizowaniu.
-    StateVector.write_to_file(savefilename)
+    StateVector.write_to_file(savefilename, False)
 
     # Now read optimized fluxes to propagate
     
@@ -70,7 +70,6 @@ def forward_pipeline(DaCycle, PlatForm, DaSystem, Samples, StateVector, ObsOpera
     else: 
         StateVector.read_from_file(savefilename, 'prior')
 
-    StateVector.isOptimized = True
 
     # Run forward with these parameters
 
@@ -131,7 +130,7 @@ def prepare_state(DaCycle, StateVector):
     # Finally, also write the StateVector to a file so that we can always access the a-priori information
 
     filename = os.path.join(DaCycle['dir.output'], 'savestate.nc')
-    StateVector.write_to_file(filename)  # write prior info because StateVector.Isoptimized == False for now
+    StateVector.write_to_file(filename, False)  # write prior info because StateVector.Isoptimized == False for now
 
 def sample_state(DaCycle, Samples, StateVector, ObservationOperator):
     """ Sample the filter state for the inversion """
@@ -162,7 +161,7 @@ def sample_state(DaCycle, Samples, StateVector, ObservationOperator):
         logging.debug("StateVector now carries %d samples" % StateVector.nobs)
 
 
-def sample_step(DaCycle, Samples, StateVector, ObservationOperator, lag, isadvance=False):
+def sample_step(DaCycle, Samples, StateVector, ObservationOperator, lag):
     """ Perform all actions needed to sample one cycle """
     
 
@@ -190,7 +189,7 @@ def sample_step(DaCycle, Samples, StateVector, ObservationOperator, lag, isadvan
 
     # Add model-data mismatch to all samples, this *might* use output from the ensemble in the future??
 
-    Samples.add_model_data_mismatch() 
+    Samples.add_model_data_mismatch(DaCycle.DaSystem['obs.sites.rc']) 
     filename = Samples.write_sample_info() #LU observations.nc 
 
     # Write filename to DaCycle, and to output collection list
@@ -201,11 +200,6 @@ def sample_step(DaCycle, Samples, StateVector, ObservationOperator, lag, isadvan
 
     run_forecast_model(DaCycle, ObservationOperator)
 
-    # Add model-data mismatch to all samples, this *might* use output from the ensemble in the future??
-
-    #Samples.add_model_data_mismatch()
-
-    #msg = "Added Model Data Mismatch to all samples " ; logging.debug(msg)
 
     # Read forecast model samples that were written to NetCDF files by each member. Add them to the exisiting
     # Observation object for each sample loop. This data fill be written to file in the output folder for each sample cycle. 
@@ -280,7 +274,7 @@ def advance(DaCycle, Samples, StateVector, ObservationOperator):
 
     ObservationOperator.get_initial_data()
 
-    sample_step(DaCycle, Samples, StateVector, ObservationOperator, 0, True) #LU w srodku zmienia zawartosc obiektu samples
+    sample_step(DaCycle, Samples, StateVector, ObservationOperator, 0) #LU w srodku zmienia zawartosc obiektu samples
     #LU ale z drugiej strony dodaje tez pozniej samples, to tak jakby chcial na nowo dodac ...
     #LU a to dlatego ze samples jest inicjalizowane na nowo.
 #LU skoro w srodku sample step jest inicjalizowanie samples przez przypisanie datalist=[], to czy ten obiekt samples ma jkaies podobiekty ktore kaza mu byc przekazywanym?
@@ -293,7 +287,7 @@ def advance(DaCycle, Samples, StateVector, ObservationOperator):
     logging.debug("Appended Observation filename to DaCycle for collection ")
 
 
-    Samples.write_obs_to_file()
+    Samples.write_obs_to_file(DaCycle['dir.output'], DaCycle['time.sample.stamp'])
 
 
 def save_and_submit(DaCycle, StateVector):
@@ -302,7 +296,7 @@ def save_and_submit(DaCycle, StateVector):
     savedir = DaCycle['dir.output']
     filename = os.path.join(savedir, 'savestate.nc')   #LU to jest state vector po zoptymalizowaniu.
 
-    StateVector.write_to_file(filename)
+    StateVector.write_to_file(filename, True)
     DaCycle.RestartFileList.append(filename) # write optimized info because StateVector.Isoptimized == False for now
     DaCycle.finalize()