Develop: update to result folder naming

.github/workflows/unit_testing_linux.yml

@@ -11,10 +11,10 @@ on:
 
 jobs:
   test:
-    runs-on: ubuntu-20.04
+    runs-on: ubuntu-24.04
     strategy:
       matrix:
-        python-version: [ '3.6', '3.7', '3.8', '3.9', '3.10', '3.11', '3.12', '3.13' ]
+        python-version: [ '3.8', '3.9', '3.10', '3.11', '3.12', '3.13' ]
 
     steps:
       - uses: actions/checkout@v4

src/quocslib/__init__.py

@@ -1,3 +1,3 @@
 from __future__ import absolute_import, division, print_function, unicode_literals
 
-__VERSION__ = "0.0.63"
+__VERSION__ = "0.0.64"

src/quocslib/communication/AllInOneCommunication.py

@@ -16,6 +16,7 @@
 
 import os
 import time
+import datetime
 from typing import List
 
 from quocslib.utils.AbstractFoM import AbstractFoM
@@ -59,18 +60,28 @@ def __init__(self,
         # Pre job name
         pre_job_name = interface_job_name
         # Datetime for 1-1 association
-        self.date_time = str(time.strftime("%Y%m%d_%H%M%S"))
+        self.date_time = datetime.datetime.now().strftime("%Y%m%d_%H%M%S_%f")
         # Client job name to send to the Server
         self.client_job_name = self.date_time + "_" + pre_job_name
         ###
         # Logging, Results, Figure of merit evaluation ...
         ###
         # Optimization folder
         optimization_folder = "QuOCS_Results"
-        self.results_path = os.path.join(os.getcwd(), optimization_folder, self.client_job_name)
         if not os.path.isdir(os.path.join(os.getcwd(), optimization_folder)):
             os.makedirs(os.path.join(os.getcwd(), optimization_folder))
         # Create the folder for logging and results
+        self.results_path = os.path.join(os.getcwd(), optimization_folder, self.client_job_name)
+        # # check if folder already exists
+        # if os.path.isdir(self.results_path):
+        #     # if it exists, include microseconds of time
+        #     self.date_time = datetime.datetime.now().strftime("%Y%m%d_%H%M%S_%f")
+        #     self.client_job_name = self.date_time + "_" + pre_job_name
+        #     self.results_path = os.path.join(os.getcwd(), optimization_folder, self.client_job_name)
+        # check if it already exists
+        if os.path.isdir(self.results_path):
+            raise FileExistsError("The folder {0} already exists. Please change the job name.".format(self.results_path))
+        # Create the folder for logging and results
         os.makedirs(self.results_path)
         # Write the current quocs lib version in the file
         with open(os.path.join(self.results_path, "quocs_version.txt"), "w") as version_file:
@@ -81,7 +92,6 @@ def __init__(self,
         self.print_general_log = True
         # Figure of merit object
         self.FoM_obj = FoM_obj
-        # TODO Thinks whether it is a good idea dumping the results
         # Dumping data object
         self.dump_obj = dump_attribute(self.results_path, self.date_time, dump_format)
         # Handle exit object

src/quocslib/optimizationalgorithms/ADAlgorithm.py

@@ -77,13 +77,13 @@ def __init__(self, optimization_dict: dict = None, communication_obj=None, FoM_o
                 self.rng = RandomNumberGenerator(seed_number=seed_number)
             except (TypeError, KeyError):
                 default_seed_number = np.random.randint(0, 10000)
-                message = "Seed number must be an integer value. Set {0} as a seed numer for this optimization".format(
+                message = "Seed number must be an integer value. Set {0} as a seed number for this optimization".format(
                     default_seed_number)
                 self.rng = RandomNumberGenerator(seed_number=default_seed_number)
                 self.comm_obj.print_logger(message, level=30)
         else:
             default_seed_number = np.random.randint(0, 10000)
-            message = "Seed number must be an integer value. Set {0} as a seed numer for this optimization".format(
+            message = "Seed number must be an integer value. Set {0} as a seed number for this optimization".format(
                 default_seed_number)
             self.rng = RandomNumberGenerator(seed_number=default_seed_number)
             self.comm_obj.print_logger(message, level=30)

src/quocslib/optimizationalgorithms/GRAPEAlgorithm.py

@@ -73,7 +73,7 @@ def __init__(self, optimization_dict: dict = None, communication_obj=None, FoM_o
                 seed_number = alg_parameters["random_number_generator"]["seed_number"]
             except (TypeError, KeyError):
                 seed_number = 2022
-                message = "Seed number must be an integer value. Set {0} as a seed numer for this optimization".format(
+                message = "Seed number must be an integer value. Set {0} as a seed number for this optimization".format(
                     seed_number)
                 self.comm_obj.print_logger(message, level=30)
         self.rng = RandomNumberGenerator(seed_number=seed_number)

src/quocslib/optimizationalgorithms/dCRABAlgorithm.py

@@ -112,7 +112,7 @@ def __init__(self, optimization_dict: dict = None, communication_obj=None, **kwa
                 self.rng = RandomNumberGenerator(seed_number=seed_number)
             except (TypeError, KeyError):
                 default_seed_number = 2022
-                message = "Seed number must be an integer value. Set {0} as a seed numer for this optimization".format(
+                message = "Seed number must be an integer value. Set {0} as a seed number for this optimization".format(
                     default_seed_number)
                 self.rng = RandomNumberGenerator(seed_number=default_seed_number)
                 self.comm_obj.print_logger(message, level=30)

tests/test_quick_parallel_jobs.py

@@ -0,0 +1,66 @@
+from quocslib.utils.AbstractFoM import AbstractFoM
+from quocslib.utils.inputoutput import readjson
+from quocslib.Optimizer import Optimizer
+from scipy.optimize import rosen
+import numpy as np
+import os
+import pytest
+import threading
+
+
+class RosenFoM(AbstractFoM):
+    def __init__(self, args_dict: dict = None):
+        if args_dict is None:
+            args_dict = {}
+
+        self.FoM_list = []
+        self.param_list = []
+        self.save_path = ""
+
+    def save_FoM(self):
+        np.savetxt(os.path.join(self.save_path, 'FoM.txt'), self.FoM_list)
+        np.savetxt(os.path.join(self.save_path, 'params.txt'), self.param_list)
+
+    def set_save_path(self, save_path: str = ""):
+        self.save_path = save_path
+
+    def get_FoM(self, pulses: list = [], parameters: list = [], timegrids: list = []) -> dict:
+
+        FoM = rosen(np.asarray(parameters))
+
+        self.FoM_list.append(FoM)
+        self.param_list.append(parameters)
+
+        return {"FoM": FoM}
+
+
+def main(optimization_dictionary: dict):
+
+    FoM_object = RosenFoM()
+
+    optimization_obj = Optimizer(optimization_dictionary, FoM_object)
+
+    FoM_object.set_save_path(optimization_obj.results_path)
+
+    optimization_obj.execute()
+
+    FoM_object.save_FoM()
+
+
+def test_parameter_optimization():
+    # get the optimization settings from the json dictionary
+    folder = os.path.dirname(os.path.realpath(__file__))
+    optimization_dictionary = readjson(os.path.join(folder, "opt_Rosen_NM.json"))
+    opt_dict_1 = optimization_dictionary.copy()
+    opt_dict_2 = optimization_dictionary.copy()
+    opt_dict_1["optimization_client_name"] = "Check_quick_parallel_job_1"
+    opt_dict_2["optimization_client_name"] = "Check_quick_parallel_job_2"
+
+    t1 = threading.Thread(target=main, args=(opt_dict_1, ))
+    t2 = threading.Thread(target=main, args=(opt_dict_2, ))
+
+    t1.start()
+    t2.start()
+
+    t1.join(timeout=10)
+    t2.join(timeout=10)