Modified em_trame console window

em_trame.py

@@ -367,7 +367,7 @@ def _refresh_qpu_plot_figures():
         state.qpu_ts_other_ready = False
         state.qpu_other_plot_style = "display: none; width: 900px; height: 660px; margin: 0 auto;"
 
-def _build_qpu_timeseries_plotly_multi(configs, nx: int, T: float, snapshot_dt: float, impulse_pos):
+def _build_qpu_timeseries_plotly_multi(configs, nx: int, T: float, snapshot_dt: float, impulse_pos, progress_callback=None):
     times = qutils.create_time_frames(T, snapshot_dt)
     fig = go.Figure()
     # Gather all validated positions across configs (after expanding 'All') to compute color normalization
@@ -408,10 +408,20 @@ def _build_qpu_timeseries_plotly_multi(configs, nx: int, T: float, snapshot_dt:
     dashes = ["solid", "dash", "dot", "dashdot"]
     markers = ["circle", "square", "diamond", "triangle-up", "x"]
 
-    for field_type, valid_positions in cfg_expanded:
+    total_configs = len(cfg_expanded)
+    for idx, (field_type, valid_positions) in enumerate(cfg_expanded):
+        # Create a sub-callback for this config's portion of progress
+        def _sub_progress(p):
+            if progress_callback:
+                # Map p (0-100) to the slice for this config
+                base = (idx / total_configs) * 100
+                fraction = (1 / total_configs) * 100
+                total_p = base + (p / 100.0) * fraction
+                progress_callback(total_p)
+
         # Fetch time series from QPU for this field and the validated positions
         try:
-            series_map_field = qutils.run_qpu(field_type, valid_positions, None, float(T), float(snapshot_dt), int(nx), None, impulse_pos)
+            series_map_field = qutils.run_qpu(field_type, valid_positions, None, float(T), float(snapshot_dt), int(nx), None, impulse_pos, progress_callback=_sub_progress)
         except Exception as e:
             print(f"QPU error for {field_type} positions {valid_positions}: {e}")
             continue
@@ -753,6 +763,15 @@ def run_simulation_only():
     state.show_progress = True
     state.simulation_progress = 0
     
+    last_logged_percent = 0
+    def _progress_callback(percent):
+        nonlocal last_logged_percent
+        state.simulation_progress = percent
+        # Log every 10%
+        if percent - last_logged_percent >= 10:
+            log_to_console(f"Simulation progress: {int(percent)}%")
+            last_logged_percent = percent
+
     # Reset stop flag and enable Stop button at start
     stop_simulation = False
     state.stop_button_disabled = False
@@ -817,7 +836,7 @@ def run_simulation_only():
             state.status_message = "Building QPU time series..."
             state.simulation_progress = 60
             # Build and render Plotly chart (multi-config)
-            fig = _build_qpu_timeseries_plotly_multi(configs, nx, T, snapshot_dt, impulse_pos)
+            fig = _build_qpu_timeseries_plotly_multi(configs, nx, T, snapshot_dt, impulse_pos, progress_callback=_progress_callback)
             qpu_ts_cache["fig"] = fig
             try:
                 ctrl.qpu_ts_update(fig)
@@ -827,6 +846,7 @@ def run_simulation_only():
             state.run_button_text = "Successful!"
             state.simulation_progress = 100
             state.status_message = "QPU simulation completed successfully!"
+            log_to_console("Simulation Completed")
             state.status_type = "success"
             state.show_progress = False
             # Show chart only if it has data
@@ -867,8 +887,9 @@ def run_simulation_only():
         return stop_simulation
     
     state.simulation_progress = 50
-    simulation_data, snapshot_times = run_sim(nx, na, R, initial_state, T, snapshot_dt=snapshot_dt, stop_check=_stop_check)
+    simulation_data, snapshot_times = run_sim(nx, na, R, initial_state, T, snapshot_dt=snapshot_dt, stop_check=_stop_check, progress_callback=_progress_callback)
     print("Simulation complete.")
+    log_to_console("Simulation complete.")
     
     state.simulation_progress = 80
     state.status_message = "Processing simulation results..."
@@ -1211,7 +1232,7 @@ def generate_plot():
             points_str = state.timeseries_gridpoints or ""
             positions = [tuple(map(int, match)) for match in re.findall(r'\((\d+)\s*,\s*(\d+)\)', points_str)]
             if not positions and (state.timeseries_points or "").strip():
-                raise ValueError("No valid monitor positions found. Enter (x, y) pairs in [0,1].")
+                raise ValueError("No valid monitor positions found. Enter (x, y) pairs in [0,1] x [0,1].")
             fig = _build_sim_timeseries_plotly(state.timeseries_field, positions, nx, snapshot_times, simulation_data)
             if fig is not None:
                 try:
@@ -1554,7 +1575,7 @@ def _snap_samples_to_grid(sample_str: str, nx: int):
         return "", ""
     matches = _SAMPLE_PAIR_RE.findall(str(sample_str))
     if not matches:
-        return "", "Enter sample position(s) as (x, y) pairs in [0,1]."
+        return "", "Enter sample position(s) as (x, y) pairs in [0,1] x [0,1]."
 
     nx_int = int(nx)
     denom = float(max(nx_int - 1, 1))