now propagating obs_nums into the optimizer.nc file. Note: requires obspack.py!

da/baseclasses/optimizer.py

@@ -64,6 +64,8 @@ class Optimizer(object):
         self.HX_prime        = np.zeros( (self.nobs,self.nmembers), float)
         # observations
         self.obs             =  np.zeros( (self.nobs,), float)
+        # observation ids
+        self.obs_ids         =  np.zeros( (self.nobs,), float)
         # covariance of observations
         self.R               =  np.zeros( (self.nobs,self.nobs,), float)
         # localization of obs
@@ -93,6 +95,7 @@ class Optimizer(object):
         allobs=[]      # collect all obs for n=1,..,nlag
         allmdm=[]      # collect all mdm for n=1,..,nlag
         allsamples=[]  # collect all model samples for n=1,..,nlag
+        allids=[]  # collect all model samples for n=1,..,nlag
         allreject=[]  # collect all model samples for n=1,..,nlag
         alllocalize=[]  # collect all model samples for n=1,..,nlag
         allflags=[]  # collect all model samples for n=1,..,nlag
@@ -116,6 +119,7 @@ class Optimizer(object):
                 allobs.extend(                                    members[0].ModelSample.Data.getvalues('obs') )
                 allsamples.extend(                                members[0].ModelSample.Data.getvalues('simulated') )
                 allmdm.extend(                                    members[0].ModelSample.Data.getvalues('mdm')  )
+                allids.extend(                                    members[0].ModelSample.Data.getvalues('id')  )
 
                 memsamples=[]
                 for mem in members:
@@ -130,6 +134,7 @@ class Optimizer(object):
         self.HX_prime[:,:]                                      = np.transpose(allmemsamples)
 
         self.obs[:]                                             = np.array(allobs)
+        self.obs_ids[:]                                         = np.array(allids)
         self.Hx[:]                                              = np.array(allsamples)
 
         self.may_reject[:]                                      = np.array(allreject)
@@ -260,6 +265,18 @@ class Optimizer(object):
             savedict['comment']     = 'Observations used in optimization'
             dummy                   = f.AddData(savedict)
 
+            data =  self.obs_ids
+
+            savedict                = io.std_savedict.copy()
+            savedict['name']        = "obspack_num"
+            savedict['dtype']       = "int64"
+            savedict['long_name']   = "Unique_ObsPack_observation_number"
+            savedict['units']       = ""
+            savedict['dims']        = dimobs
+            savedict['values']      = data.tolist()
+            savedict['comment']     = 'Unique observation number across the entire ObsPack distribution'
+            dummy                   = f.AddData(savedict)
+
 
             data =  self.R