added site codes to optimizer file, just for convenience...

da/baseclasses/optimizer.py

@@ -76,6 +76,8 @@ class Optimizer(object):
         self.flags         = np.zeros(self.nobs,int)
         # species type
         self.species       = np.zeros(self.nobs,str)
+        # species type
+        self.sitecode      = np.zeros(self.nobs,str)
 
         # species mask
         self.speciesmask    = {}
@@ -92,6 +94,7 @@ class Optimizer(object):
         except:
             pass
 
+        allsites=[]      # collect all obs for n=1,..,nlag
         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
@@ -118,6 +121,7 @@ class Optimizer(object):
                 allflags.extend(                                  Samples.Data.getvalues('flag') )
                 allspecies.extend(                                Samples.Data.getvalues('species') )
                 allobs.extend(                                    Samples.Data.getvalues('obs') )
+                allsites.extend(                                  Samples.Data.getvalues('code') )
                 allmdm.extend(                                    Samples.Data.getvalues('mdm')  )
                 allids.extend(                                    Samples.Data.getvalues('id')  )
 
@@ -132,7 +136,6 @@ class Optimizer(object):
 
         self.obs[:]                                             = np.array(allobs)
         self.obs_ids[:]                                         = np.array(allids)
-        print self.HX_prime[:,:].shape,np.array(allsimulated).shape
         self.HX_prime[:,:]                                      = np.array(allsimulated)
         self.Hx[:]                                              = self.HX_prime[:,0]
 
@@ -140,7 +143,7 @@ class Optimizer(object):
         self.may_localize[:]                                    = np.array(alllocalize)
         self.flags[:]                                           = np.array(allflags)
         self.species[:]                                         = np.array(allspecies)
-
+        self.sitecode                                           = allsites
 
         self.X_prime                                            = self.X_prime - self.x[:,np.newaxis] # make into a deviation matrix
         self.HX_prime                                           = self.HX_prime - self.Hx[:,np.newaxis] # make a deviation matrix
@@ -202,6 +205,7 @@ class Optimizer(object):
         dimlag          = f.AddLagDim(self.nlag, unlimited=False)
         dimobs          = f.AddObsDim(self.nobs)
         dimstate        = f.AddDim('nstate',self.nparams*self.nlag)
+        dim200char      = f.AddDim('string_of200chars',200)
 
         # Add data, first the ones that are written both before and after the optimization
 
@@ -249,10 +253,23 @@ class Optimizer(object):
         savedict['comment']     = '%s mixing ratio deviations based on %s state vector'% (type,type,)
         dummy                   = f.AddData(savedict)
 
+
         # Continue with prior only data
 
         if type == 'prior':
 
+            data = self.sitecode
+
+            savedict                = io.std_savedict.copy()
+            savedict['name']        = "sitecode"
+            savedict['long_name']   = "site code propagated from observation file"
+            savedict['dtype']       = "char"
+            savedict['dims']        = dimobs+dim200char
+            savedict['values']      = data
+            savedict['missing_value'] = '!'
+            status                   = f.AddData(savedict)
+
+
             data =  self.obs
 
             savedict                = io.std_savedict.copy()