final rebase changes

Author: mahlau-flex

tests/test_components/test_heat_charge.py

@@ -1927,7 +1927,7 @@ def test_gaussian_doping_sigma_calculation():
     expected_sigma = np.sqrt(-(0.1**2) / (2 * np.log(1e15 / 1e18)))
     assert np.isclose(box.sigma, expected_sigma), "Sigma calculation is incorrect."
 
-    with pytest.raises(pd.ValidationError, match="must be less than.*concentration"):
+    with pytest.raises(ValidationError, match="must be less than.*concentration"):
         _ = td.GaussianDoping(
             size=(1, 1, 1), ref_con=1e19, concentration=1e18, width=0.1, source="xmin"
         )
@@ -1988,7 +1988,7 @@ def test_gaussian_doping_validator_source():
             size=(1, 1, 1), ref_con=1e15, concentration=1e18, width=0.1, source=source
         )
 
-    with pytest.raises(pd.ValidationError):
+    with pytest.raises(ValidationError):
         _ = td.GaussianDoping(
             size=(1, 1, 1), ref_con=1e15, concentration=1e18, width=0.1, source="invalid"
         )

tidy3d/components/tcad/doping.py

@@ -2,7 +2,7 @@
 
 from __future__ import annotations
 
-from typing import Literal, TYPE_CHECKING, Union
+from typing import TYPE_CHECKING, Literal, Union
 
 import numpy as np
 import xarray as xr
@@ -195,32 +195,32 @@ class GaussianDoping(AbstractDopingBox):
         "are [``xmin``, ``xmax``, ``ymin``, ``ymax``, ``zmin``, ``zmax``]",
     )
 
-    @pd.validator("concentration")
-    def _validate_ref_con_less_than_concentration(cls, val, values):
+    @model_validator(mode="after")
+    def _validate_ref_con_less_than_concentration(self: Self) -> Self:
         """Ensure ref_con < concentration to avoid negative sqrt in sigma calculation."""
-        if "ref_con" in values:
-            if values["ref_con"] >= val:
-                raise ValueError(
-                    f"'ref_con' ({values['ref_con']}) must be less than 'concentration' ({val}) "
-                    "for GaussianDoping. The reference concentration at the edges must be lower "
-                    "than the peak concentration at the center."
-                )
-        return val
+        val = self.concentration
+        if self.ref_con >= val:
+            raise ValueError(
+                f"'ref_con' ({self.ref_con}) must be less than 'concentration' ({val}) "
+                "for GaussianDoping. The reference concentration at the edges must be lower "
+                "than the peak concentration at the center."
+            )
+        return self
 
-    @pd.validator("width")
-    def _validate_width_vs_size(cls, val, values):
+    @model_validator(mode="after")
+    def _validate_width_vs_size(self: Self) -> Self:
         """Warn if box size may be too small for the specified transition width."""
-        if "size" in values:
-            size = values["size"]
-            for i, s in enumerate(size):
-                if not np.isinf(s) and s < 2 * val:
-                    dim_name = ["x", "y", "z"][i]
-                    log.warning(
-                        f"Box size in '{dim_name}' direction ({s} μm) is less than "
-                        f"'2*width' ({2 * val} μm) for 'GaussianDoping'. "
-                        "This may result in unexpected behavior in the transition region."
-                    )
-        return val
+        val = self.width
+        size = self.size
+        for i, s in enumerate(size):
+            if not np.isinf(s) and s < 2 * val:
+                dim_name = ["x", "y", "z"][i]
+                log.warning(
+                    f"Box size in '{dim_name}' direction ({s} μm) is less than "
+                    f"'2*width' ({2 * val} μm) for 'GaussianDoping'. "
+                    "This may result in unexpected behavior in the transition region."
+                )
+        return self
 
     @cached_property
     def sigma(self) -> float: