Json bdd and scheduler

Alain Klotz
1 parent 0e1d4d92
Showing 2 changed files with 63 additions and 17 deletions Show diff stats
src/core/pyros_django/scheduling/A_Scheduler.py
src/core/pyros_django/scheduling/models.py
@@ -39,6 +39,7 @@ for short_path in short_paths:
 from src.core.pyros_django.majordome.agent.Agent import Agent, build_agent, log, parse_args
 from seq_submit.models import Sequence
 from user_mgmt.models import Period, ScientificProgram, SP_Period
+from scheduling.models import PredictiveSchedule, EffectiveSchedule
 # = Specials
 import glob
 import shutil
@@ -85,7 +86,7 @@ class A_Scheduler(Agent):
     _TEST_COMMANDS_LIST = [
         # Format : ("self cmd_name cmd_args", timeout, "expected_result", expected_status),
         (True, "self do_create_seq_1 6", 200, '', Agent.CMD_STATUS.CMD_EXECUTED),
-        (True, "self do_stop asap", 500, "STOPPING", Agent.CMD_STATUS.CMD_EXECUTED),
+        #(True, "self do_stop asap", 500, "STOPPING", Agent.CMD_STATUS.CMD_EXECUTED),
     ]
     """
@@ -232,6 +233,35 @@ class A_Scheduler(Agent):
         schedule_order = np.zeros(86400, dtype=int) -1
         schedule_jd = np.zeros(86400, dtype=float)
         schedule_scientific_programm_id = np.zeros(86400, dtype=int) -1
+        # ---
+        # --- Get the numpy matrix in database (via Json)
+        # --- Get the effective schedule matrix
+        print("STEP 2000")
+        time.sleep(5)
+        input_matrix = EffectiveSchedule.objects.last().conv_numpy()
+        # input_matrix = EffectiveSchedule.objects.get(id=10).scheduler_matrix
+        print(f"STEP 2500 {type(input_matrix)=}")
+        print(f"STEP 2600 {input_matrix=}")
+       
+        print(f"STEP 3000 {input_matrix.shape=}")
+        time.sleep(10)
+        # --- Get the effective schedule arrays
+        schedule_eff_jd, schedule_eff_binary, schedule_eff_sequence_id, schedule_eff_scientific_programm_id, schedule_eff_order, schedule_eff_visibility = input_matrix
+        print(f"{schedule_eff_jd=}")
+        # --- Get the index in the night
+        night, index = self._fn.date2night("now", 86400)
+        print(f"{night=} {index=}")
+        schedule_sequence_id[0:index] = schedule_eff_sequence_id[0:index]
+        schedule_binary[0:index] = schedule_eff_binary[0:index]
+        schedule_visibility[0:index] = schedule_eff_visibility[0:index]
+        schedule_order[0:index] = schedule_eff_order[0:index]
+        schedule_jd[0:index] = schedule_eff_jd[0:index]
+        schedule_scientific_programm_id[0:index] = schedule_eff_scientific_programm_id[0:index]  
+        try:
+            pass
+        except:
+            pass
+        print(f"{schedule_jd=}")
         # ===================================================================
         # --- Loop over the sequences of the night to extract useful infos
@@ -288,7 +318,10 @@ class A_Scheduler(Agent):
             else:
                 sequence_info['error'] = f"File {ephfile} not exists"
             sequence_infos.append(sequence_info)
-        schedule_jd = eph_info['jd']
+        try:
+            schedule_jd = eph_info['jd']
+        except:
+            pass
         # ===================================================================
         # --- Get informations of priority and quota from scientific programs
@@ -456,8 +489,21 @@ class A_Scheduler(Agent):
         self.dprint("\n" + "="*70 + "\n=== Save the schedule\n" + "="*70 + "\n")
         self.dprint("Order ID_seq K_start ID_sp Priority Duration Status\n")
         self.dprint(f"{seqs=}")
+        # --- Prepare the output matrix
+        ouput_matrix = np.array([schedule_jd, schedule_binary, schedule_sequence_id, schedule_scientific_programm_id, schedule_order, schedule_visibility])
+        # --- Save the numpy matrix in ASCII
         fpathname = os.path.join(rootdir, subdir, "scheduler_schedule.txt")
-        np.savetxt(fpathname, np.array([schedule_jd, schedule_binary, schedule_sequence_id, schedule_scientific_programm_id, schedule_order, schedule_visibility]).T)
+        np.savetxt(fpathname, ouput_matrix.T)
+        # --- Save the numpy matrix in database (via Json)
+        v = PredictiveSchedule()
+        v.scheduler_matrix = ouput_matrix
+        v.save()
+        # --- Save the numpy matrix in database (via Json)
+        v = EffectiveSchedule()
+        v.scheduler_matrix = ouput_matrix
+        v.save()
+
+        print(f"{schedule_jd=}")
         # --- Update the running state
         self._routine_running = self.RUNNING_NOTHING
         print(f"_compute_schedule_1 finished in {time.time() - t0:.2f} seconds")
@@ -7,6 +7,7 @@ import numpy as np
 import json
 from json import JSONEncoder
 import numpy
+import ast
 class NumpyArrayEncoder(JSONEncoder):
     def default(self, obj):
@@ -15,40 +16,39 @@ class NumpyArrayEncoder(JSONEncoder):
         return JSONEncoder.default(self, obj)
+    
 class EffectiveSchedule(models.Model):
     scheduler_matrix = JSONField(blank=True, null=True)    
-
+    
+    
     def save(self, *args, **kwargs):
         # Transform numpy matrix to JSON
-        scheduler_matrix_as_json = json.dumps(self.scheduler_matrix, cls=NumpyArrayEncoder)
+        scheduler_matrix_as_json = json.dumps({"array":self.scheduler_matrix}, cls=NumpyArrayEncoder)
         self.scheduler_matrix = scheduler_matrix_as_json
         super(EffectiveSchedule, self).save(*args, **kwargs)
-    def get(self, *args, **kwargs):
+    def conv_numpy(self):
         # Transform JSON to numpy matrix 
         matrix_as_json = json.loads(self.scheduler_matrix)
-
-        self.scheduler_matrix = numpy.asarray(matrix_as_json["array"]) 
-        return super().get(**kwargs)
-    
+      
+        return numpy.array(matrix_as_json)
+        
 class PredictiveSchedule(models.Model):
     scheduler_matrix = JSONField(blank=True, null=True)    
-
+    
     def save(self, *args, **kwargs):
         # Transform numpy matrix to JSON
         scheduler_matrix_as_json = json.dumps(self.scheduler_matrix, cls=NumpyArrayEncoder)
         self.scheduler_matrix = scheduler_matrix_as_json
         super(PredictiveSchedule, self).save(*args, **kwargs)
-    def get(self, *args, **kwargs):
+    def conv_numpy(self, *args, **kwargs):
         # Transform JSON to numpy matrix 
         matrix_as_json = json.loads(self.scheduler_matrix)
-
-        self.scheduler_matrix = numpy.asarray(matrix_as_json["array"]) 
-        return super().get(**kwargs)
-    
-
+     
+        return numpy.array(matrix_as_json) 
+         
 class SchedulerHistory(EffectiveSchedule):
     night_datetime = models.DateTimeField(blank=True, null=True)
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