adding tordoidal simulator and drawing

model.py

@@ -1,5 +1,6 @@
 from dataclasses import dataclass, field
 from typing import List, Tuple, Optional, Dict
+from core import core_loss_Pv
 
 
 @dataclass
@@ -18,6 +19,9 @@ class TransformerModel:
     # Turn counts (total)
     Np_total: int
     Ns_total: int
+    # Core loss model parameters (optional)
+    Ve_mm3: float = 0.0          # effective core volume in mm^3 (for core loss calculation)
+    use_core_loss_model: bool = False  # if True, calculate core loss from B and f
     # Tap positions in turns counted from a common reference (e.g. one end of the bobbin)
     # Must include 0 and total turns if you want to be able to use full winding.
     primary_taps: List[int] = field(default_factory=lambda: [0])
@@ -173,8 +177,26 @@ class TransformerModel:
         # Output power (resistive load)
         P_out = Vs_rms_ideal**2 / load_ohms
 
+        # Core loss calculation
+        if self.use_core_loss_model and self.Ve_mm3 > 0:
+            # Calculate core loss from B and f using the model
+            # Convert volume to m^3
+            Ve_m3 = self.Ve_mm3 * 1e-9  # mm^3 to m^3
+
+            # Get core loss density in kW/m^3
+            try:
+                Pv_kW_m3 = core_loss_Pv(B_peak_T, freq_hz)
+                # Convert to watts
+                core_loss_calculated = Pv_kW_m3 * Ve_m3 * 1000  # kW/m^3 * m^3 * 1000 = W
+            except (ValueError, Exception) as e:
+                # If core loss model fails (e.g., B or f out of range), fall back to provided value
+                core_loss_calculated = core_loss_W
+        else:
+            # Use provided core loss value
+            core_loss_calculated = core_loss_W
+
         # Total input power (approx)
-        P_in = P_out + P_cu_total + core_loss_W
+        P_in = P_out + P_cu_total + core_loss_calculated
 
         efficiency = P_out / P_in if P_in > 0 else 1.0
 
@@ -191,7 +213,7 @@ class TransformerModel:
             "P_cu_W": P_cu_total,
             "P_cu_primary_W": P_cu_p,
             "P_cu_secondary_W": P_cu_s,
-            "P_core_W": core_loss_W,
+            "P_core_W": core_loss_calculated,
             "P_in_W": P_in,
             "efficiency": efficiency,
             "primary_tap": primary_tap,