started to add diagnostic filter output to optimizer class

da/baseclasses/optimizer.py

@@ -114,10 +114,50 @@ class Optimizer(object):
 
         return None
 
+    def WriteDiagnostics(self,DaCycle, StateVector):
+        """
+            Open a NetCDF file and write diagnostic output from optimization process:
+
+                - calculated residuals
+                - model-data mismatches
+                - HPH^T
+                - prior ensemble of samples
+                - posterior ensemble of samples
+                - prior ensemble of fluxes
+                - posterior ensemble of fluxes
+        """
+        from da.tools.io import CT_CDF, std_savedict
+
+        outdir          = DaCycle['dir.output']
+        filename        = os.path.join(outdir,'optimizer.%s.nc'% DaCycle['time.start'].strftime('%Y%m%d') )
+
+        f               = CT_CDF(filename,'create')
+
+        dimparams       = f.AddParamsDim(self.nparams)
+        dimmembers      = f.AddMembersDim(self.nmembers)
+        dimlag          = f.AddLagDim(self.nlag, unlimited=False)
+        dimobs          = f.AddObsDim(self.nobs)
+        dimstate        = f.file.create_dimension('nstate',self.nparams*self.nlag)
+        dimstate        = ('nstate',)
+
+        data =  self.x
+
+        savedict                = std_savedict.copy()
+        savedict['name']        = "statevector"
+        savedict['long_name']   = "statevector"
+        savedict['units']       = "unitless"
+        savedict['dims']        = dimstate 
+        savedict['values']      = data.tolist()
+        savedict['comment']     = 'blablabla'
+        dummy                   = f.AddData(savedict)
+
+
+        return None
+
     def SerialMinimumLeastSquares(self):
         """ Make minimum least squares solution by looping over obs"""
         import numpy as np
-        import numpy .linalg as la
+        import numpy.linalg as la
 
         tvalue=1.97591
         for n in range(self.nobs):