feat: Adding gaussian monitors

Author: momchil-flex

schemas/Simulation.json

@@ -344,6 +344,14 @@ def test_diffraction_validators():
 FREQS = np.array([1, 2, 3]) * 1e12
 
 
+def test_gaussian_overlap_monitors_basic():
+    g = td.GaussianOverlapMonitor(size=(1, 1, 0), name="g", freqs=FREQS)
+    a = td.AstigmaticGaussianOverlapMonitor(size=(1, 1, 0), name="a", freqs=FREQS)
+    for m in (g, a):
+        s = m.storage_size(num_cells=10, tmesh=[0.0, 1.0])
+        assert isinstance(s, int) and s > 0
+
+
 def test_monitor():
     size = (1, 2, 3)
     center = (1, 2, 3)
@@ -381,10 +389,14 @@ def test_monitor():
     m10 = td.PermittivityMonitor(size=size, center=center, freqs=FREQS, name="perm")
     m11 = td.AuxFieldTimeMonitor(size=size, center=center, name="aux_field_time", fields=("Nfx",))
     m12 = td.MediumMonitor(size=size, center=center, freqs=FREQS, name="mat")
+    m13 = td.GaussianOverlapMonitor(size=(1, 1, 0), center=center, freqs=FREQS, name="gauss")
+    m14 = td.AstigmaticGaussianOverlapMonitor(
+        size=(1, 1, 0), center=center, freqs=FREQS, name="astigauss"
+    )
 
     tmesh = np.linspace(0, 1, 10)
 
-    for m in [m1, m2, m3, m4, m5, m6, m7, m8, m9, m10, m12]:
+    for m in [m1, m2, m3, m4, m5, m6, m7, m8, m9, m10, m11, m12, m13, m14]:
         m.storage_size(num_cells=100, tmesh=tmesh)
 
     for m in [m2, m4]:

schemas/TerminalComponentModeler.json

@@ -18,6 +18,7 @@
     DiffractionData,
     DirectivityData,
     FieldData,
+    FieldOverlapData,
     FieldTimeData,
     FluxData,
     FluxTimeData,
@@ -223,6 +224,16 @@ def make_mode_data():
     return ModeData(monitor=MODE_MONITOR, amps=AMPS.copy(), n_complex=N_COMPLEX.copy())
 
 
+def make_field_overlap_data():
+    monitor = td.GaussianOverlapMonitor(
+        size=(0, 2, 2),
+        freqs=[1e14, 1.1e14],
+        name="gaussian_overlap_monitor",
+        store_fields_direction="+",
+    )
+    return FieldOverlapData(monitor=monitor, amps=AMPS)
+
+
 def make_flux_data():
     return FluxData(monitor=FLUX_MONITOR, flux=FLUX.copy())
 
@@ -412,6 +423,11 @@ def test_mode_data():
     _ = data.k_eff
 
 
+def test_overlap_data():
+    data = make_field_overlap_data()
+    _ = data.amps
+
+
 def test_flux_data():
     data = make_flux_data()
     _ = data.flux

tests/test_components/test_monitor.py

@@ -345,6 +345,7 @@
 
 # monitors
 from .components.monitor import (
+    AstigmaticGaussianOverlapMonitor,
     AuxFieldTimeMonitor,
     DiffractionMonitor,
     DirectivityMonitor,
@@ -356,6 +357,7 @@
     FieldTimeMonitor,
     FluxMonitor,
     FluxTimeMonitor,
+    GaussianOverlapMonitor,
     MediumMonitor,
     ModeMonitor,
     ModeSolverMonitor,
@@ -492,6 +494,7 @@ def set_logging_level(level: str) -> None:
     "ApodizationSpec",
     "AstigmaticGaussianBeam",
     "AstigmaticGaussianBeamProfile",
+    "AstigmaticGaussianOverlapMonitor",
     "AugerRecombination",
     "AutoGrid",
     "AutoImpedanceSpec",
@@ -631,6 +634,7 @@ def set_logging_level(level: str) -> None:
     "GaussianBeam",
     "GaussianBeamProfile",
     "GaussianDoping",
+    "GaussianOverlapMonitor",
     "GaussianPulse",
     "Geometry",
     "GeometryGroup",

tests/test_data/test_monitor_data.py

@@ -19,6 +19,7 @@
 from tidy3d.components.grid.grid import Coords, Grid
 from tidy3d.components.medium import Medium, MediumType
 from tidy3d.components.monitor import (
+    AstigmaticGaussianOverlapMonitor,
     AuxFieldTimeMonitor,
     DiffractionMonitor,
     DirectivityMonitor,
@@ -30,6 +31,7 @@
     FieldTimeMonitor,
     FluxMonitor,
     FluxTimeMonitor,
+    GaussianOverlapMonitor,
     MediumMonitor,
     ModeMonitor,
     ModeSolverMonitor,
@@ -1596,7 +1598,58 @@ class MediumData(MediumDataset, AbstractFieldData):
     )
 
 
-class ModeData(ModeSolverDataset, ElectromagneticFieldData):
+class AbstractOverlapData(ElectromagneticFieldData):
+    amps: ModeAmpsDataArray = pd.Field(
+        ...,
+        title="Amplitudes",
+        description="Complex-valued amplitudes of the overlap decomposition.",
+    )
+
+    def normalize(self, source_spectrum_fn) -> AbstractOverlapData:
+        """Return copy of self after normalization is applied using source spectrum function."""
+        if self.amps is None:
+            return self.copy()
+        source_freq_amps = source_spectrum_fn(self.amps.f)[None, :, None]
+        new_amps = (self.amps / source_freq_amps).astype(self.amps.dtype)
+        return self.copy(update={"amps": new_amps})
+
+    @property
+    def time_reversed_copy(self) -> FieldData:
+        """Make a copy of the data with direction-reversed fields. In lossy or gyrotropic systems,
+        the time-reversed fields will not be the same as the backward-propagating modes."""
+
+        # Time reversal
+        new_data = {}
+        for comp, field in self.field_components.items():
+            if comp[0] == "H":
+                new_data[comp] = -np.conj(field)
+            else:
+                new_data[comp] = np.conj(field)
+
+        # switch direction in the monitor
+        mnt = self.monitor
+        new_dir = "+" if mnt.store_fields_direction == "-" else "-"
+        update_dict = {"store_fields_direction": new_dir}
+        if hasattr(mnt, "direction"):
+            update_dict["direction"] = new_dir
+        new_data["monitor"] = mnt.updated_copy(**update_dict)
+        return self.copy(update=new_data)
+
+
+class FieldOverlapData(AbstractOverlapData):
+    monitor: Union[GaussianOverlapMonitor, AstigmaticGaussianOverlapMonitor] = pd.Field(
+        ..., title="Monitor", description="Monitor associated with the data."
+    )
+
+    def _make_adjoint_sources(
+        self, dataset_names: list[str], fwidth: float
+    ) -> list[Union[CustomCurrentSource, PointDipole]]:
+        """Converts a :class:`.FieldData` to a list of adjoint current or point sources."""
+
+        raise NotImplementedError("Could not formulate adjoint source for overlap monitor output.")
+
+
+class ModeData(ModeSolverDataset, AbstractOverlapData):
     """
     Data associated with a :class:`.ModeMonitor`: modal amplitudes, propagation indices and mode profiles.
 
@@ -1636,11 +1689,7 @@ class ModeData(ModeSolverDataset, ElectromagneticFieldData):
     """
 
     monitor: ModeMonitor = pd.Field(
-        ..., title="Monitor", description="Mode monitor associated with the data."
-    )
-
-    amps: ModeAmpsDataArray = pd.Field(
-        ..., title="Amplitudes", description="Complex-valued amplitudes associated with the mode."
+        ..., title="Monitor", description="Monitor associated with the data."
     )
 
     eps_spec: list[EpsSpecType] = pd.Field(
@@ -1662,12 +1711,6 @@ def eps_spec_match_mode_spec(cls, val, values):
                 )
         return val
 
-    def normalize(self, source_spectrum_fn) -> ModeData:
-        """Return copy of self after normalization is applied using source spectrum function."""
-        source_freq_amps = source_spectrum_fn(self.amps.f)[None, :, None]
-        new_amps = (self.amps / source_freq_amps).astype(self.amps.dtype)
-        return self.copy(update={"amps": new_amps})
-
     def overlap_sort(
         self,
         track_freq: TrackFreq,
@@ -1965,25 +2008,6 @@ def _group_index_post_process(self, frequency_step: float) -> ModeData:
 
         return self.copy(update=update_dict)
 
-    @property
-    def time_reversed_copy(self) -> FieldData:
-        """Make a copy of the data with direction-reversed fields. In lossy or gyrotropic systems,
-        the time-reversed fields will not be the same as the backward-propagating modes."""
-
-        # Time reversal
-        new_data = {}
-        for comp, field in self.field_components.items():
-            if comp[0] == "H":
-                new_data[comp] = -np.conj(field)
-            else:
-                new_data[comp] = np.conj(field)
-
-        # switch direction in the monitor
-        mnt = self.monitor
-        new_dir = "+" if mnt.store_fields_direction == "-" else "-"
-        new_data["monitor"] = mnt.updated_copy(store_fields_direction=new_dir)
-        return self.copy(update=new_data)
-
     def _colocated_propagation_axes_field(self, field_name: Literal["E", "H"]) -> DataArray:
         """Collect a field DataArray containing all 3 field components and rotate from frame
         with normal axis along z to frame with propagation axis along z.
@@ -2262,29 +2286,6 @@ class ModeSolverData(ModeData):
         None, title="Amplitudes", description="Unused for ModeSolverData."
     )
 
-    def normalize(self, source_spectrum_fn: Callable[[float], complex]) -> ModeSolverData:
-        """Return copy of self after normalization is applied using source spectrum function."""
-        return self.copy()
-
-    @property
-    def time_reversed_copy(self) -> FieldData:
-        """Make a copy of the data with direction-reversed fields. In lossy or gyrotropic systems,
-        the time-reversed fields will not be the same as the backward-propagating modes."""
-
-        # Time reversal
-        new_data = {}
-        for comp, field in self.field_components.items():
-            if comp[0] == "H":
-                new_data[comp] = -np.conj(field)
-            else:
-                new_data[comp] = np.conj(field)
-
-        # switch direction in the monitor
-        mnt = self.monitor
-        new_dir = "+" if mnt.store_fields_direction == "-" else "-"
-        new_data["monitor"] = mnt.updated_copy(direction=new_dir, store_fields_direction=new_dir)
-        return self.copy(update=new_data)
-
     def _check_fields_stored(self, components: list[str]):
         """Check that all requested field components are stored in the data."""
         missing_comps = [comp for comp in components if comp not in self.field_components.keys()]