lambdas are not 0

da/cosmo/base_optimizer.py

@@ -347,11 +347,23 @@ class Optimizer(object):
 
             alpha = np.double(1.0) / (np.double(1.0) + np.sqrt((self.R[n]) / self.HPHR[n]))
 
+#            if all(self.x[:] + self.KG[:] * res >= 0.):
             self.x[:] = self.x + self.KG[:] * res
             self.x[self.x<0.] = 0.    # cut off negative values, COSMO don't like negative fluxes # pavle
 
             for r in range(self.nmembers):
-                self.X_prime[:, r] = self.X_prime[:, r] - alpha * self.KG[:] * (self.HX_prime[n, r])
+                X_prime_temp = self.X_prime[:, r] - alpha * self.KG[:] * (self.HX_prime[n, r])
+                X_prime_temp[X_prime_temp+self.x < 0.] = 0.
+#                if all(self.X_prime[:, r] - alpha * self.KG[:] * (self.HX_prime[n, r]) + self.x[:] >= 0.):
+                self.X_prime[:, r] = X_prime_temp
+                #self.X_prime[:, r] = self.X_prime[:, r] - alpha * self.KG[:] * (self.HX_prime[n, r])
+#                    continue
+ #               else:
+  #                  self.X_prime[:, r] = self.X_prime[:, r] - alpha * self.KG[:] * (self.HX_prime[n, r])
+
+#                for p in range(self.nparams):
+ #                   if self.X_prime[p, r]+self.x[p]<0.:
+  #                       self.X_prime[p, r]=0.
 
 #WP !!!! Very important to first do all obervations from n=1 through the end, and only then update 1,...,n. The current observation
 #WP      should always be updated last because it features in the loop of the adjustments !!!!

da/cosmo/pipeline.py

@@ -266,7 +266,7 @@ def prepare_state(dacycle, statevector):
 
     current_sv = os.path.join(dacycle['dir.restart'], 'savestate_%s.nc' % dacycle['time.start'].strftime('%Y%m%d'))
     statevector.write_to_file(current_sv, 'prior')  # write prior info 
-    nlag = int(dacycle['time.nlag'])
+#    nlag = int(dacycle['time.nlag'])
 #    for l in range(0,nlag):                      # pavle added from here
 ##        statevector.write_members_to_file(l, dacycle['restartmap.dir'])
   #      statevector.write_members_for_cosmo(l, dacycle['restartmap.dir'])

da/cosmo/statevector_read_from_output.py

@@ -290,8 +290,7 @@ class StateVector(object):
         newmember.param_values = newmean.flatten()  # no deviations
         self.ensemble_members[lag].append(newmember)
 
-#        ifile = Dataset('/scratch/snx3000/parsenov/40_9reg/bckp/output/20130401/lambda.nc', mode='r')
-        ifile = Dataset('/scratch/snx3000/parsenov/9reg/optimizer.20130401.nc', mode='r')
+        ifile = Dataset('/scratch/snx3000/parsenov/octe/optimizer.20130401.nc', mode='r')
 #        par = ifile.variables['lambda'][:]
         par = ifile.variables['statevectordeviations_prior'][:]
         par = par.reshape(181,2,21)
@@ -313,8 +312,8 @@ class StateVector(object):
      #       newmember.param_values[newmember.param_values>2.] = 2.
             newmember.param_values = par[:, lag, member]
 #            newmember.param_values = par[lag, member, :]
-            if member==1:
-                print(par[:, lag, member])
+#            if member==1:
+#                print(par[:, lag, member])
             self.ensemble_members[lag].append(newmember)
 
         logging.debug('%d new ensemble members were added to the state vector # %d' % (self.nmembers, (lag + 1)))

octe.rc

@@ -38,7 +38,7 @@ abs.time.start          : 2013-04-01 00:00:00
 ! Whether to restart the CTDAS system from a previous cycle, or to start the sequence fresh. Valid entries are T/F/True/False/TRUE/FALSE
 
 time.restart        : F
-da.restart.tstamp   : 2013-01-01 00:00:00
+da.restart.tstamp   : 2013-04-01 00:00:00
 
 ! The length of a cycle is given in days, such that the integer 7 denotes the typically used weekly cycle. Valid entries are integers > 1