chore: add GaussianDoping frontend validators

CHANGELOG.md

@@ -10,6 +10,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Added
 
 ### Changed
+- Added validation to `GaussianDoping` to ensure `ref_con < concentration`, validate `source` face identifier, and warn the user when the box size is not sufficient for the specified transition width.
 
 ### Fixed
 

schemas/EMESimulation.json

@@ -5916,6 +5916,14 @@
         },
         "source": {
           "default": "xmin",
+          "enum": [
+            "xmax",
+            "xmin",
+            "ymax",
+            "ymin",
+            "zmax",
+            "zmin"
+          ],
           "type": "string"
         },
         "type": {

schemas/HeatChargeSimulation.json

@@ -3894,6 +3894,14 @@
         },
         "source": {
           "default": "xmin",
+          "enum": [
+            "xmax",
+            "xmin",
+            "ymax",
+            "ymin",
+            "zmax",
+            "zmin"
+          ],
           "type": "string"
         },
         "type": {

schemas/HeatSimulation.json

@@ -3894,6 +3894,14 @@
         },
         "source": {
           "default": "xmin",
+          "enum": [
+            "xmax",
+            "xmin",
+            "ymax",
+            "ymin",
+            "zmax",
+            "zmin"
+          ],
           "type": "string"
         },
         "type": {

schemas/ModeSimulation.json

@@ -5116,6 +5116,14 @@
         },
         "source": {
           "default": "xmin",
+          "enum": [
+            "xmax",
+            "xmin",
+            "ymax",
+            "ymin",
+            "zmax",
+            "zmin"
+          ],
           "type": "string"
         },
         "type": {

schemas/Simulation.json

@@ -8473,6 +8473,14 @@
         },
         "source": {
           "default": "xmin",
+          "enum": [
+            "xmax",
+            "xmin",
+            "ymax",
+            "ymin",
+            "zmax",
+            "zmin"
+          ],
           "type": "string"
         },
         "type": {

schemas/TerminalComponentModeler.json

@@ -8640,6 +8640,14 @@
         },
         "source": {
           "default": "xmin",
+          "enum": [
+            "xmax",
+            "xmin",
+            "ymax",
+            "ymin",
+            "zmax",
+            "zmin"
+          ],
           "type": "string"
         },
         "type": {

tests/test_components/test_heat_charge.py

@@ -1878,13 +1878,18 @@ def test_gaussian_doping_initialization():
 
 
 def test_gaussian_doping_sigma_calculation():
-    """Test sigma calculation in GaussianDoping."""
+    """Test sigma calculation in GaussianDoping and ref_con validator."""
     box = td.GaussianDoping(
         size=(1, 1, 1), ref_con=1e15, concentration=1e18, width=0.1, source="xmin"
     )
     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"):
+        _ = td.GaussianDoping(
+            size=(1, 1, 1), ref_con=1e19, concentration=1e18, width=0.1, source="xmin"
+        )
+
 
 def test_gaussian_doping_get_contrib():
     """Test _get_contrib method in GaussianDoping."""
@@ -1933,6 +1938,44 @@ def test_gaussian_doping_bounds_behavior():
     assert box.bounds == box_coords, "Bounds should match provided box_coords."
 
 
+def test_gaussian_doping_validator_source():
+    """Test validator for source face."""
+    valid_sources = ["xmin", "xmax", "ymin", "ymax", "zmin", "zmax"]
+    for source in valid_sources:
+        _ = td.GaussianDoping(
+            size=(1, 1, 1), ref_con=1e15, concentration=1e18, width=0.1, source=source
+        )
+
+    with pytest.raises(pd.ValidationError):
+        _ = td.GaussianDoping(
+            size=(1, 1, 1), ref_con=1e15, concentration=1e18, width=0.1, source="invalid"
+        )
+
+
+def test_gaussian_doping_validator_width():
+    """Test validator for width vs size."""
+    width = 0.1
+    _ = td.GaussianDoping(
+        size=(0.2, 0.2, 0.2), ref_con=1e15, concentration=1e18, width=width, source="xmin"
+    )
+    _ = td.GaussianDoping(
+        size=(np.inf, 1, 1), ref_con=1e15, concentration=1e18, width=width, source="xmin"
+    )
+
+    with AssertLogLevel("WARNING", contains_str="'x' direction"):
+        _ = td.GaussianDoping(
+            size=(0.15, 1, 1), ref_con=1e15, concentration=1e18, width=width, source="xmin"
+        )
+    with AssertLogLevel("WARNING", contains_str="'y' direction"):
+        _ = td.GaussianDoping(
+            size=(1, 0.15, 1), ref_con=1e15, concentration=1e18, width=width, source="xmin"
+        )
+    with AssertLogLevel("WARNING", contains_str="'z' direction"):
+        _ = td.GaussianDoping(
+            size=(1, 1, 0.15), ref_con=1e15, concentration=1e18, width=width, source="xmin"
+        )
+
+
 def test_2D_doping_box():
     """Check that the doping boxes can handle 2D cases correctly."""
 

tidy3d/components/tcad/doping.py

@@ -2,7 +2,7 @@
 
 from __future__ import annotations
 
-from typing import Union
+from typing import Literal, Union
 
 import numpy as np
 import pydantic.v1 as pd
@@ -14,6 +14,7 @@
 from tidy3d.components.geometry.base import Box
 from tidy3d.constants import MICROMETER, PERCMCUBE, inf
 from tidy3d.exceptions import SetupError
+from tidy3d.log import log
 
 
 class AbstractDopingBox(Box):
@@ -171,7 +172,7 @@ class GaussianDoping(AbstractDopingBox):
         units=MICROMETER,
     )
 
-    source: str = pd.Field(
+    source: Literal["xmin", "xmax", "ymin", "ymax", "zmin", "zmax"] = pd.Field(
         "xmin",
         title="Source face",
         description="Specifies the side of the box acting as the source, i.e., "
@@ -180,6 +181,33 @@ class GaussianDoping(AbstractDopingBox):
         "are [``xmin``, ``xmax``, ``ymin``, ``ymax``, ``zmin``, ``zmax``]",
     )
 
+    @pd.validator("concentration")
+    def _validate_ref_con_less_than_concentration(cls, val, values):
+        """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
+
+    @pd.validator("width")
+    def _validate_width_vs_size(cls, val, values):
+        """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
+
     @cached_property
     def sigma(self):
         """The sigma parameter of the pseudo-gaussian"""