CHIMERE seems to be fixed as well

pycif/plugins/models/chimere/ini_periods.py

@@ -76,4 +76,8 @@ def ini_periods(self, **kwargs):
     self.iniobs = {ddi: False for ddi in self.subsimu_dates}
     self.reset_obs = {ddi: True for ddi in self.subsimu_dates}
     
+    # Keep in memory whether a given period has a successor period
+    # The info is used by the adjoint to fetch or not the aend file
+    self.chain = {ddi: True for ddi in self.subsimu_dates[:-1]}
+    self.chain[self.subsimu_dates[-2]] = False
     
\ No newline at end of file

pycif/plugins/models/chimere/io/inputs/params.py

-def make_nml(self, runsubdir, sdc, mode):
+def make_nml(self, runsubdir, sdc, mode, ddi):
     # Default values
     nvegtype = getattr(self, "nvegtype", 16)
 
@@ -136,7 +136,7 @@ def make_nml(self, runsubdir, sdc, mode):
 
         f.write("afnout = '{}/aout.'\n".format(runsubdir))
 
-        ainit = 1 if (mode == "adj" and hasattr(self, "chain")) else 0
+        ainit = 1 if (mode == "adj" and self.chain[ddi]) else 0
         f.write("iopainit = {}\n".format(ainit))
 
         netcdfoutput = 1 if self.dumpncoutput else 0

pycif/plugins/models/chimere/io/native2inputs.py

@@ -75,7 +75,7 @@ def native2inputs(
 
     # Deals with the nml file
     elif input_type == "nml":
-        make_nml(self, runsubdir, sdc, mode)
+        make_nml(self, runsubdir, sdc, mode, ddi)
 
     # Deals with fluxes
     # WARNING: Not specified emissions are set to zero??

pycif/plugins/obsoperators/standard/obsoper.py

@@ -150,10 +150,6 @@ def obsoper(
         info("The run was correctly initialized")
         return
 
-    # Re-initalizing the chain argument
-    if hasattr(model, "chain"):
-        del model.chain
-
     # Dump observation vector for later use in fwd and tl modes
     # Otherwise dumps the control vector
     if mode in ["fwd", "tl"]:

pycif/plugins/transforms/system/fromcontrol/__init__.py

@@ -70,13 +70,13 @@ def ini_mapper(
         mapper["subsimus"] = {}
         for di in input_dates:
             outdates = np.sort(np.unique(np.append(
-                                    default_dict["input_dates"][di],
+                input_dates[di],
                                     transform.orig_parameter_plg.dates
                                 )))
             outdates = outdates[
-                outdates >= np.min(default_dict["input_dates"][di])]
+                outdates >= np.min(input_dates[di])]
             outdates = outdates[
-                outdates <= np.max(default_dict["input_dates"][di])]
+                outdates <= np.max(input_dates[di])]
             outdates = pd.DatetimeIndex(outdates).to_pydatetime()
             mapper["subsimus"][di] = {
                 "inputs": {},
@@ -90,4 +90,5 @@ def ini_mapper(
                 mapper["subsimus"][di]["outputs"][trid][di]
 
     mapper["fixed_subsimus"] = True
+    
     return mapper

pycif/plugins/transforms/system/fromcontrol/adjoint.py

@@ -154,7 +154,7 @@ def adjoint(
                     model=transform.model,
                     **kwargs
                 ).data
-
+            
             # Vertical aggregation
             vdata = np.sum(sensit_data[mask] * phys, axis=0)
             vaggreg = vmap2vaggreg(vdata[np.newaxis], tracer, tracer.domain)
@@ -168,4 +168,9 @@ def adjoint(
                 * tracer.hresoldim
                 * tracer.vresoldim
             ] += map2scale(vaggreg, tracer, tracer.domain).flatten()
+            
+
+            print(ddi, k, period, control_slice, data_slice,
+                  map2scale(vaggreg, tracer, tracer.domain).flatten().sum(),
+                  controlvect.dx.sum())
             
\ No newline at end of file

pycif/plugins/transforms/system/fromcontrol/forward.py

@@ -111,11 +111,11 @@ def forward(
                 
                 scale = reindex(
                     xmod_out["scale"],
-                    levels={"time": outdates, "lev": inputs.lev},
+                    levels={"time": outdates[:-1], "lev": inputs.lev},
                 )
                 inputs = reindex(
                     inputs,
-                    levels={"time": outdates},
+                    levels={"time": outdates[:-1]},
                 )
                 
                 xmod_out["spec"] = inputs * scale
@@ -123,7 +123,7 @@ def forward(
                 if mode == "tl":
                     incr = reindex(
                         xmod_out["incr"],
-                        levels={"time": outdates, "lev": inputs.lev},
+                        levels={"time": outdates[:-1], "lev": inputs.lev},
                     )
                     xmod_out["incr"] = incr * inputs
                 

pycif/plugins/transforms/system/fromcontrol/utils/dates.py

@@ -23,13 +23,13 @@ def dateslice(tracer, di, df):
     ddi = min(di, df)
     ddf = max(di, df)
 
-    if hasattr(tracer, "dates") and hasattr(tracer, "period"):
+    if hasattr(tracer, "dates") and hasattr(tracer, "tresol"):
         dates = np.append(
             tracer.dates, tracer.dates[-1] + datetime.timedelta(1)
         )
         chunk = np.where((dates[1:] > ddi) & (dates[:-1] <= ddf))[0]
 
-    # When no period is specified and/or no date,
+    # When no tresol is specified and/or no date,
     # just take all the first element
     else:
         chunk = [0]

pycif/plugins/transforms/system/run_model/adjoint.py

@@ -19,7 +19,4 @@ def adjoint(
     if not onlyinit:
         transform.model.run(runsubdir, mode, workdir, min(di, df),
                             do_simu=do_simu, **kwargs)
-        
-        # Keep in memory the fact that it is (or not) a chained simulation
-        transform.model.chain = min(di, df)
-    
\ No newline at end of file
+        
\ No newline at end of file

pycif/plugins/transforms/system/run_model/forward.py

@@ -18,7 +18,3 @@ def forward(
     if not onlyinit:
         transform.model.run(runsubdir, mode, workdir, min(di, df),
                             do_simu=do_simu, **kwargs)
-
-        # Keep in memory the fact that it is (or not) a chained simulation
-        transform.model.chain = min(di, df)
-