creat scripts/ folder, move parallel calculation folder to scripts, rename markdown as README.md

Author: haitao-ZCU

doc/parallel_ansys_sweeps.md scripts/parallel_calculation/README.mddoc/parallel_ansys_sweeps.md renamed to scripts/parallel_calculation/README.md

@@ -1,8 +1,11 @@
 # Running a parameter grid across parallel Ansys sessions
 
-This documents the pattern originally in `machine_design/parallel_calculation/`
-(`runner_parallel.py` , `calculate_combination.py`, added by Jan Laksar), kept
-here after that folder was removed in issue #21.
+This is the parallel Ansys computation pattern originally in
+`machine_design/parallel_calculation/` (added by Jan Laksar), moved here in
+issue #21 along with the two scripts (`runner_parallel.py`,
+`calculate_combination.py`). The large `SynRM_orig.aedt` example project was
+dropped since it does not belong in git. Running these scripts requires your
+own base `.aedt` project.
 
 ## Problem
 
@@ -15,8 +18,8 @@ roughly by the number of workers.
 ## Method
 
 1. Split the full grid of tasks into `N_WORKERS` contiguous chunks.
-2. For each worker, copy the base `.aedt` project file to its own file before 
-   opening it. Ansys locks a project file while it is open, so every worker 
+2. For each worker, copy the base `.aedt` project file to its own file before
+   opening it. Ansys locks a project file while it is open, so every worker
    needs its own copy rather than sharing one file.
 3. Start `multiprocessing.Pool(N_WORKERS)` and run one worker function per
    chunk. Each worker opens its own `Desktop(non_graphical=True,
@@ -36,7 +39,7 @@ roughly by the number of workers.
 
 ## Example
 
-The removed `runner_parallel.py` swept a 16x16 grid of `Id`/`Iq` values (0.0
-to 3.2 A in 0.2 A steps) and recorded flux linkages, inductances, and torque
-for each point, with `calculate_combination.py` doing the per-point solve
-and extraction described above.
+`runner_parallel.py` swept a 16x16 grid of `Id`/`Iq` values (0.0 to 3.2 A
+in 0.2 A steps) and recorded flux linkages, inductances, and torque for
+each point, with `calculate_combination.py` doing the per-point solve and
+extraction described above.

scripts/parallel_calculation/calculate_combination.py

@@ -0,0 +1,40 @@
+import numpy as np
+
+
+def main(m2d, task_chunk, setup_name):
+
+    def run_simulation(Id, Iq):
+        m2d.variable_manager["Id"] = f"{Id}A"
+        m2d.variable_manager["Iq"] = f"{Iq}A"
+
+        m2d.save_project()
+        m2d.analyze_setup(setup_name, use_auto_settings=False, cores=1, tasks=1)
+
+        expressions = ["I_d1", "I_q1", "Flux_d1", "Flux_q1", "Flux_e_d1", "Flux_e_q1", "Ld1", "Lq1", "Ld1q1", "Lq1d1", "Moving1.Torque"]
+
+        sols = m2d.post.get_solution_data(expressions=expressions, primary_sweep_variable="Time")
+
+        out = np.zeros(len(expressions))
+
+        for i, expr in enumerate(expressions):
+            data = sols.data_real(expr)[:-1]
+            val = float(np.mean(data))
+
+            if expr.startswith("L"):
+                val /= 1e9
+
+            out[i] = val
+
+        return out
+
+    # --- chunk processing ---
+    results_local = []
+    total = len(task_chunk)
+    for k, (Id, Iq, i, j) in enumerate(task_chunk, start=1):
+        print(f"[INFO] {k}/{total} | Id={Id:.3f} A | Iq={Iq:.3f} A")
+
+        res = run_simulation(Id, Iq)
+
+        results_local.append((i, j, res))
+
+    return results_local

scripts/parallel_calculation/runner_parallel.py

@@ -0,0 +1,113 @@
+import os
+import shutil
+import time
+from multiprocessing import Pool
+
+import calculate_combination
+import h5py
+import numpy as np
+from ansys.aedt.core import Desktop, Maxwell2d
+
+from machine_design.config import load_config
+
+# =========================================================
+# CONFIGURATION
+# =========================================================
+config = load_config()
+AEDT_VERSION = config["aedt_version"]
+
+PROJECT_DIR = os.path.join(os.getcwd(), config["project_dir"])
+BASE_PROJECT = "SynRM_orig"
+DESIGN_NAME = "Design02_def_Idq"
+SETUP_NAME = "Setup1"
+
+N_WORKERS = config["n_workers"]  # less then number of logical processors
+
+
+# =========================================================
+# PROJECT COPY
+# =========================================================
+def copy_project(worker_id):
+    src = os.path.join(PROJECT_DIR, BASE_PROJECT + ".aedt")
+    dst_name = f"SynRM_worker_{worker_id}.aedt"
+    dst = os.path.join(PROJECT_DIR, dst_name)
+
+    shutil.copyfile(src, dst)
+
+    return dst_name
+
+
+# =========================================================
+# WORKER
+# =========================================================
+def worker(args):
+
+    worker_id, task_chunk = args
+
+    project_name = copy_project(worker_id)
+
+    desktop = Desktop(specified_version=AEDT_VERSION, non_graphical=True, new_desktop=True, close_on_exit=False)
+
+    app = Maxwell2d(project=project_name, design=DESIGN_NAME)
+
+    results = calculate_combination.main(app, task_chunk, SETUP_NAME)
+
+    desktop.release_desktop(close_projects=True, close_on_exit=False)
+
+    return results
+
+
+# =========================================================
+# MAIN
+# =========================================================
+def run():
+
+    Id_vec = np.arange(0.0, 3.2, 0.2)  # 16 values
+    Iq_vec = np.arange(0.0, 3.2, 0.2)  # 16 values
+
+    tasks = []
+    for i, Id in enumerate(Id_vec):
+        for j, Iq in enumerate(Iq_vec):
+            tasks.append((Id, Iq, i, j))
+
+    chunk_size = int(np.ceil(len(tasks) / N_WORKERS))
+    chunks = [tasks[i : i + chunk_size] for i in range(0, len(tasks), chunk_size)]
+
+    args = [(i, chunk) for i, chunk in enumerate(chunks)]
+
+    results = np.zeros((len(Id_vec), len(Iq_vec), 11))
+
+    with Pool(N_WORKERS) as pool:
+        outputs = pool.map(worker, args)
+
+    rows = []
+    for chunk in outputs:
+        for i, j, res in chunk:
+            results[i, j, :] = res
+            rows.append(list(results[i, j, :]))
+    data_out = np.array(rows)
+
+    header = "Id,Iq,Flux_d,Flux_q,Flux_e_d,Flux_e_q,L_d,L_q,L_dq,L_qd,Torque"
+    np.savetxt("results_grid.csv", data_out, delimiter=",", header=header, comments="")
+
+    with h5py.File("results_grid.h5", "w") as f:
+        f.create_dataset("Id", data=Id_vec)
+        f.create_dataset("Iq", data=Iq_vec)
+        f.create_dataset("results", data=results)
+
+    print("[INFO] DONE")
+
+    return results
+
+
+# =========================================================
+# ENTRY POINT
+# =========================================================
+if __name__ == "__main__":
+    start = time.perf_counter()
+
+    run()
+
+    end = time.perf_counter()
+
+    print(f"Time of calculation: {end - start:.6f} s")