Handle start and stop dates for the models as well.

Goutte
1 parent 60b73eb1
Showing 1 changed file with 55 additions and 70 deletions Show diff stats
web/run.py
@@ -427,44 +427,24 @@ def get_data_for_target(target_config, started_at, stopped_at):
         abort(500, "Invalid orbit configuration for '%s' : %s"
               % (target_config['slug'], str(e)))
  
-    # try:
-    #     started_at = datetime.datetime.strptime(started_at, FILE_DATE_FMT)
-    # except:
-    #     abort(400, "Invalid started_at config : '%s'." % started_at)
-    # try:
-    #     stopped_at = datetime.datetime.strptime(stopped_at, FILE_DATE_FMT)
-    # except:
-    #     abort(400, "Invalid stopped_at config : '%s'." % stopped_at)
-
-    # Grab the list of netCDF files from Myriam's API
-    model_files = []
-    for model in models:
-        model_files = model_files + retrieve_amda_netcdf(
-            target_config['slug'], model['slug'], started_at, stopped_at
-        )
-    # Remove possible duplicates
-    model_files = set(model_files)
-
-    # Let's return an empty dict when there's no data instead of crashing
-    # if not len(model_files):
-    #     abort(500, "No model files found for '%s'." % target_config['slug'])
-    # if not len(orbit_files):
-    #     abort(500, "No orbit files found for '%s'." % target_config['slug'])
+    def _sta_sto(_cnf, _sta, _sto):
+        if 'started_at' in _cnf:
+            _s0 = datetime.datetime.strptime(_cnf['started_at'], FILE_DATE_FMT)
+            _s0 = max(_s0, _sta)
+        else:
+            _s0 = _sta
+        if 'stopped_at' in _cnf:
+            _s1 = datetime.datetime.strptime(_cnf['stopped_at'], FILE_DATE_FMT)
+            _s1 = min(_s1, _sto)
+        else:
+            _s1 = _sto
+        return _s1, _s0
  
     precision = "%Y-%m-%dT%H"  # model and orbits times are only equal-ish
     orbit_data = {}  # keys are datetime as str, values arrays of XY
  
     for orbit in orbits:
-        if 'started_at' in orbit:
-            s0 = datetime.datetime.strptime(orbit['started_at'], FILE_DATE_FMT)
-            s0 = max(s0, started_at)
-        else:
-            s0 = started_at
-        if 'stopped_at' in orbit:
-            s1 = datetime.datetime.strptime(orbit['stopped_at'], FILE_DATE_FMT)
-            s1 = min(s1, stopped_at)
-        else:
-            s1 = stopped_at
+        s0, s1 = _sta_sto(orbit, started_at, stopped_at)
  
         orbit_files = retrieve_amda_netcdf(
             target_config['slug'], orbit['slug'], s0, s1
@@ -493,43 +473,48 @@ def get_data_for_target(target_config, started_at, stopped_at):
             cdf_handle.close()
  
     all_data = {}  # keys are datetime as str, values tuples of data
-    for model_file in model_files:
-        # Time, StartTime, StopTime, V, B, N, T, Delta_angle, P_dyn
-        log.debug("%s: opening model NETCDF4 '%s'..." %
-                  (target_config['name'], model_file))
-        cdf_handle = Dataset(model_file, "r", format="NETCDF4")
-        times = cdf_handle.variables['Time']  # YYYY DOY HH MM SS .ms
-        data_v = cdf_handle.variables['V']
-        data_b = cdf_handle.variables['B']
-        data_t = cdf_handle.variables['T']
-        data_n = cdf_handle.variables['N']
-        data_p = cdf_handle.variables['P_dyn']
-        data_d = cdf_handle.variables['Delta_angle']
-        log.debug("%s: aggregating data from '%s'..." %
-                  (target_config['name'], model_file))
-        for time, datum_v, datum_b, datum_t, datum_n, datum_p, datum_d \
-                in zip(times, data_v, data_b, data_t, data_n, data_p, data_d):
-            vrad = datum_v[0]
-            vtan = datum_v[1]
-            try:
-                dtime = datetime_from_list(time)
-            except Exception as e:
-                log.error("Failed to parse time from %s." % time)
-                raise e
-            if started_at <= dtime <= stopped_at:
-                dkey = round_time(dtime, 60*60).strftime(precision)
-                x_hee = None
-                y_hee = None
-                if dkey in orbit_data:
-                    x_hee = orbit_data[dkey][0]
-                    y_hee = orbit_data[dkey][1]
-                all_data[dkey] = (
-                    dtime.strftime("%Y-%m-%dT%H:%M:%S+00:00"),
-                    vrad, vtan, sqrt(vrad * vrad + vtan * vtan),
-                    datum_b, datum_t, datum_n, datum_p, datum_d,
-                    x_hee, y_hee
-                )
-        cdf_handle.close()
+    for model in models:
+        s0, s1 = _sta_sto(model, started_at, stopped_at)
+        model_files = retrieve_amda_netcdf(
+            target_config['slug'], model['slug'], s0, s1
+        )
+        for model_file in model_files:
+            # Time, StartTime, StopTime, V, B, N, T, Delta_angle, P_dyn
+            log.debug("%s: opening model NETCDF4 '%s'..." %
+                      (target_config['name'], model_file))
+            cdf_handle = Dataset(model_file, "r", format="NETCDF4")
+            times = cdf_handle.variables['Time']  # YYYY DOY HH MM SS .ms
+            data_v = cdf_handle.variables['V']
+            data_b = cdf_handle.variables['B']
+            data_t = cdf_handle.variables['T']
+            data_n = cdf_handle.variables['N']
+            data_p = cdf_handle.variables['P_dyn']
+            data_d = cdf_handle.variables['Delta_angle']
+            log.debug("%s: aggregating data from '%s'..." %
+                      (target_config['name'], model_file))
+            for time, datum_v, datum_b, datum_t, datum_n, datum_p, datum_d \
+                    in zip(times, data_v, data_b, data_t, data_n, data_p, data_d):
+                vrad = datum_v[0]
+                vtan = datum_v[1]
+                try:
+                    dtime = datetime_from_list(time)
+                except Exception as e:
+                    log.error("Failed to parse time from %s." % time)
+                    raise e
+                if s0 <= dtime <= s1:
+                    dkey = round_time(dtime, 60*60).strftime(precision)
+                    x_hee = None
+                    y_hee = None
+                    if dkey in orbit_data:
+                        x_hee = orbit_data[dkey][0]
+                        y_hee = orbit_data[dkey][1]
+                    all_data[dkey] = (
+                        dtime.strftime("%Y-%m-%dT%H:%M:%S+00:00"),
+                        vrad, vtan, sqrt(vrad * vrad + vtan * vtan),
+                        datum_b, datum_t, datum_n, datum_p, datum_d,
+                        x_hee, y_hee
+                    )
+            cdf_handle.close()
  
     return all_data