added extra logic to deal with TM5 release/trunk differences, and pycasso TM5

gridded/da/tm5/observationoperator.py

@@ -93,7 +93,7 @@ class TM5ObservationOperator(ObservationOperator):
 
             # Create the TM5 run directory to hold a copy of the modified rc-file
 
-            tm5compiledir = self.tm_settings['my.run.dir']
+            tm5compiledir = self.tm_settings[self.rundirkey]
             create_dirs(tm5compiledir)
 
             rcfilename = os.path.join(tm5compiledir, 'tm5_setup_init.rc')
@@ -165,8 +165,8 @@ class TM5ObservationOperator(ObservationOperator):
 
         new_items = {
                     'submit.options': self.dacycle.daplatform.give_blocking_flag(),
-                    'timerange.start': self.dacycle['time.sample.start'],
-                    'timerange.end': self.dacycle['time.sample.end'],
+                    self.timestartkey: self.dacycle['time.sample.start'],
+                    self.timefinalkey: self.dacycle['time.sample.end'],
                     'jobstep.timerange.start': self.dacycle['time.sample.start'],
                     'jobstep.timerange.end': self.dacycle['time.sample.end'],
                     'jobstep.length': 'inf',
@@ -177,14 +177,14 @@ class TM5ObservationOperator(ObservationOperator):
                     }
 
         if self.dacycle['time.restart']:  # If this is a restart from a previous cycle, the TM5 model should do a restart
-            new_items['istart'] = self.restartvalue
+            new_items[self.istartkey] = self.restartvalue
             logging.debug('Resetting TM5 to perform restart')
         else:
-            new_items['istart'] = self.coldstartvalue  # if not, start TM5 'cold'
+            new_items[self.istartkey] = self.coldstartvalue  # if not, start TM5 'cold'
             logging.debug('Resetting TM5 to perform cold start')
 
         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
-            new_items['istart'] = self.restartvalue
+            new_items[self.istartkey] = 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
@@ -202,6 +202,10 @@ class TM5ObservationOperator(ObservationOperator):
         self.tm_settings = self.rcfile.values
         self.rc_filename = name
 
+        if 'my.source.dirs' in self.tm_settings.keys():
+            self.rcfiletype = 'pycasso'
+        else:
+            self.rcfiletype = 'pre-pycasso'
         logging.debug('TM5 rc-file loaded successfully')
 
     def validate_rc(self):
@@ -209,18 +213,39 @@ 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".
         """
-        self.restartvalue = 33
-        self.coldstartvalue = 9
+
+        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
 
         needed_rc_items = [
-                            'my.project.dir',
-                            'my.run.dir',
-                            'output.dir',
-                            'restart.write.dir',
-                            'timerange.start',
-                            'timerange.end',
-                            'jobstep.length',
-                            'istart'
+                            self.projectkey,
+                            self.rundirkey,
+                            self.outputdirkey,
+                            self.savedirkey,
+                            self.timestartkey,
+                            self.timefinalkey,
+                            self.timelengthkey,
+                            self.istartkey
                           ]
 
         for k, v in self.tm_settings.iteritems():
@@ -313,10 +338,12 @@ class TM5ObservationOperator(ObservationOperator):
 
         # Next, make sure there is an actual model version compiled and ready to execute
 
-        targetdir = os.path.join(self.tm_settings['my.run.dir'])
+        targetdir = os.path.join(self.tm_settings[self.rundirkey])
 
-        
-        self.tm5_exec = os.path.join(targetdir, self.tm_settings['my.basename'] + '.x')
+        if self.rcfiletype == 'pycasso':
+            self.tm5_exec = os.path.join(targetdir, self.tm_settings['my.basename'] + '.x')
+        else:
+            self.tm5_exec = os.path.join(targetdir, 'tm5.x')
 
         if not os.path.exists(self.tm5_exec):
             logging.error("Required TM5 executable was not found %s" % self.tm5_exec)
@@ -340,7 +367,7 @@ 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['restart.write.dir']
+        targetdir = self.tm_settings[self.savedirkey]
         self.outputdir = self.tm_settings[self.outputdirkey]  # Needed further downstream to collect output data from TM5
 
         filterlist = '%s' % self.tm_settings['timerange.start']
@@ -416,7 +443,7 @@ class TM5ObservationOperator(ObservationOperator):
         """ Method handles the case where a shell runs an MPI process that forks into N TM5 model instances """
 
         da_platform = self.dacycle.daplatform
-        targetdir = os.path.join(self.tm_settings['my.run.dir'])
+        targetdir = os.path.join(self.tm_settings[self.rundirkey])
 
         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))
@@ -471,7 +498,7 @@ 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['my.run.dir'])
+        tm5submitdir = os.path.join(self.tm_settings[self.rundirkey])
         logging.info('tm5submitdir', tm5submitdir)
 
         # Go to executable directory and start the subprocess, using a new logfile
@@ -516,8 +543,8 @@ class TM5ObservationOperator(ObservationOperator):
             Note 2: also adding the weekly mean flux output to the output_filelist for later collection
          """
 
-        sourcedir = os.path.join(self.tm_settings['restart.write.dir'])
-        filterlist = ['%s' % self.tm_settings['timerange.end'].strftime('%Y%m%d')]
+        sourcedir = os.path.join(self.tm_settings[self.savedirkey])
+        filterlist = ['%s' % self.tm_settings[self.timefinalkey].strftime('%Y%m%d')]
 
         logging.debug("Creating a new list of TM5 restart data")
         logging.debug("           from directory: %s " % sourcedir)
@@ -549,7 +576,7 @@ class TM5ObservationOperator(ObservationOperator):
             self.restart_filelist.append(fil)
             logging.debug("           [added to restart list] .... %s " % fil)
 
-        sourcedir = os.path.join(self.tm_settings['output.dir'])
+        sourcedir = os.path.join(self.tm_settings[self.outputdirkey])
         sd_ed = self.dacycle['time.sample.stamp']
         filterlist = ['flask_output.%s' % sd_ed, 'flux1x1_%s' % sd_ed]