Add _validation_data property to Metric classes

CHANGELOG.md

@@ -13,11 +13,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - `tidy3d.plugins.pytorch` to wrap autograd functions for interoperability with PyTorch via the `to_torch` wrapper.
 
 ### Changed
-- Renamed `Metric.freqs` --> `Metric.f` and made frequency argument optional, in which case all frequencies from the relevant monitor will be extracted.
+- Renamed `Metric.freqs` --> `Metric.f` and made frequency argument optional, in which case all frequencies from the relevant monitor will be extracted. Metrics can still be initialized with both `f` or `freqs`.
 
 ### Fixed
 - Some validation fixes for design region.
 - Bug in adjoint source creation that included empty sources for extraneous `FieldMonitor` objects, triggering unnecessary errors.
+- Correct sign in objective function history depending on `Optimizer.maximize`.
 
 ## [2.7.4] - 2024-09-25
 

tests/test_plugins/test_invdes.py

@@ -6,7 +6,7 @@
 import pytest
 import tidy3d as td
 import tidy3d.plugins.invdes as tdi
-from tidy3d.plugins.expressions import ModePower
+from tidy3d.plugins.expressions import ModeAmp, ModePower
 from tidy3d.plugins.invdes.initialization import (
     CustomInitializationSpec,
     RandomInitializationSpec,
@@ -606,3 +606,11 @@ def test_validate_invdes_metric():
     invdes = invdes.updated_copy(simulation=simulation.updated_copy(monitors=[monitor]))
     with pytest.raises(ValueError, match="single frequency"):
         invdes.updated_copy(metric=metric)
+
+    metric = ModeAmp(monitor_name=MNT_NAME2, mode_index=0) + ModePower(
+        monitor_name=MNT_NAME2, mode_index=0
+    )
+    monitor = mnt2.updated_copy(freqs=[FREQ0])
+    invdes = invdes.updated_copy(simulation=simulation.updated_copy(monitors=[monitor]))
+    with pytest.raises(ValueError, match="must return a real"):
+        invdes.updated_copy(metric=metric)

tidy3d/plugins/expressions/__init__.py

@@ -1,6 +1,6 @@
 from .base import Expression
 from .functions import Cos, Exp, Log, Log10, Sin, Sqrt, Tan
-from .metrics import ModeAmp, ModePower
+from .metrics import ModeAmp, ModePower, generate_validation_data
 from .variables import Constant, Variable
 
 __all__ = [
@@ -9,6 +9,7 @@
     "Variable",
     "ModeAmp",
     "ModePower",
+    "generate_validation_data",
     "Sin",
     "Cos",
     "Tan",

tidy3d/plugins/expressions/metrics.py

@@ -1,23 +1,49 @@
+from abc import ABC, abstractmethod
 from typing import Any, Optional, Union
 
 import autograd.numpy as np
 import pydantic.v1 as pd
+import xarray as xr
 
 from tidy3d.components.monitor import ModeMonitor
 from tidy3d.components.types import Direction, FreqArray
 
+from .base import Expression
 from .types import NumberType
 from .variables import Variable
 
 
-class Metric(Variable):
+def generate_validation_data(expr: Expression) -> dict[str, xr.Dataset]:
+    """Generate combined dummy simulation data for all metrics in the expression.
+
+    Parameters
+    ----------
+    expr : Expression
+        The expression containing metrics.
+
+    Returns
+    -------
+    dict[str, xr.Dataset]
+        The combined validation data.
+    """
+    metrics = set(expr.filter(target_type=Metric))
+    combined_data = {k: v for metric in metrics for k, v in metric._validation_data.items()}
+    return combined_data
+
+
+class Metric(Variable, ABC):
     """
     Base class for all metrics.
 
     To subclass Metric, you must implement an evaluate() method that takes a SimulationData
     object and returns a scalar value.
     """
 
+    @property
+    @abstractmethod
+    def _validation_data(self) -> Any:
+        """Return dummy data for this metric."""
+
     def __repr__(self) -> str:
         return f'{self.type}("{self.monitor_name}")'
 
@@ -43,6 +69,7 @@ class ModeAmp(Metric):
         None,
         title="Frequency Array",
         description="The frequency array. If None, all frequencies in the monitor will be used.",
+        alias="freqs",
     )
     direction: Direction = pd.Field(
         "+",
@@ -63,6 +90,21 @@ def from_mode_monitor(
             monitor_name=monitor.name, f=monitor.freqs, mode_index=mode_index, direction=direction
         )
 
+    @property
+    def _validation_data(self) -> Any:
+        """Return dummy data for this metric (complex array of mode amplitudes)."""
+        f = list(self.f) if self.f is not None else [1.0]
+        amps_data = np.random.rand(len(f)) + 1j * np.random.rand(len(f))
+        amps = xr.DataArray(
+            amps_data.reshape(1, 1, -1),
+            coords={
+                "direction": [self.direction],
+                "mode_index": [self.mode_index],
+                "f": f,
+            },
+        )
+        return {self.monitor_name: xr.Dataset({"amps": amps})}
+
     def evaluate(self, *args: Any, **kwargs: Any) -> NumberType:
         data = super().evaluate(*args, **kwargs)
         amps = data[self.monitor_name].amps.sel(

tidy3d/plugins/invdes/design.py

@@ -12,7 +12,7 @@
 import tidy3d as td
 from tidy3d.components.autograd import get_static
 from tidy3d.exceptions import ValidationError
-from tidy3d.plugins.expressions.metrics import Metric
+from tidy3d.plugins.expressions.metrics import Metric, generate_validation_data
 from tidy3d.plugins.expressions.types import ExpressionType
 
 from .base import InvdesBaseModel
@@ -151,6 +151,7 @@ def _validate_metric(values: dict) -> dict:
             InverseDesign._validate_metric_monitor_name(metric, simulation)
             InverseDesign._validate_metric_mode_index(metric, simulation)
             InverseDesign._validate_metric_f(metric, simulation)
+        InverseDesign._validate_metric_data(metric_expr, simulation)
         return values
 
     @staticmethod
@@ -192,6 +193,23 @@ def _validate_metric_f(metric: Metric, simulation: td.Simulation) -> None:
                     f"Monitor '{metric.monitor_name}' must contain only a single frequency when metric.f is None."
                 )
 
+    @staticmethod
+    def _validate_metric_data(expr: ExpressionType, simulation: td.Simulation) -> None:
+        """Validate that expression can be evaluated and returns a real scalar."""
+        data = generate_validation_data(expr)
+        try:
+            result = expr(data)
+        except Exception as e:
+            raise ValidationError(f"Failed to evaluate the metric expression: {str(e)}") from e
+        if len(np.ravel(result)) > 1:
+            raise ValidationError(
+                f"The expression must return a scalar value or an array of length 1 (got {result})."
+            )
+        if not np.all(np.isreal(result)):
+            raise ValidationError(
+                f"The expression must return a real (not complex) value (got {result})."
+            )
+
     def is_output_monitor(self, monitor: td.Monitor) -> bool:
         """Whether a monitor is added to the ``JaxSimulation`` as an ``output_monitor``."""
 

tidy3d/plugins/invdes/optimizer.py

@@ -203,7 +203,7 @@ def continue_run(
             params = anp.clip(params, a_min=0.0, a_max=1.0)
 
             # save the history of scalar values
-            history["objective_fn_val"].append(val)
+            history["objective_fn_val"].append(aux_data["objective_fn_val"])
             history["penalty"].append(penalty)
             history["post_process_val"].append(post_process_val)