Upload, but not run, simulation for write_sparameters routine

gplugins/tidy3d/component.py

@@ -23,11 +23,13 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import tidy3d as td
+import tidy3d.web.api.webapi as web
 from gdsfactory.component import Component
 from gdsfactory.pdk import get_layer_stack
 from gdsfactory.technology import LayerStack
 from pydantic import NonNegativeFloat
 from tidy3d.components.geometry.base import from_shapely
+from tidy3d.components.monitor import FieldMonitor
 from tidy3d.components.types import Symmetry
 from tidy3d.plugins.smatrix import ComponentModeler, Port
 
@@ -277,7 +279,7 @@ def get_component_modeler(
 
         cz = np.round(cz, abs(int(np.log10(grid_eps)))).item()
 
-        freqs = td.C_0 / np.linspace(
+        freqs = td.constants.C_0 / np.linspace(
             wavelength - bandwidth / 2, wavelength + bandwidth / 2, num_freqs
         )
 
@@ -445,6 +447,7 @@ def write_sparameters(
     plot_epsilon: bool = False,
     filepath: PathType | None = None,
     overwrite: bool = False,
+    upload_only: bool = False,
     **kwargs: Any,
 ) -> Sparameters:
     """Writes the S-parameters for a component.
@@ -490,7 +493,7 @@ def write_sparameters(
         filepath: Optional file path for the S-parameters. If None, uses hash of simulation.
         overwrite: Whether to overwrite existing S-parameters. Defaults to False.
         kwargs: Additional keyword arguments for the tidy3d Simulation constructor.
-
+        upload_only: Whether to upload the simulation to the cloud only. Defaults to False.
     """
     layer_stack = layer_stack or get_layer_stack()
 
@@ -591,25 +594,53 @@ def write_sparameters(
         return dict(np.load(filepath))
     else:
         time.sleep(0.2)
-        s = modeler.run()
-        for port_in in s.port_in.values:
-            for port_out in s.port_out.values:
-                for mode_index_in in s.mode_index_in.values:
-                    for mode_index_out in s.mode_index_out.values:
-                        sp[f"{port_in}@{mode_index_in},{port_out}@{mode_index_out}"] = (
-                            s.sel(
-                                port_in=port_in,
-                                port_out=port_out,
-                                mode_index_in=mode_index_in,
-                                mode_index_out=mode_index_out,
-                            ).values
-                        )
-
-        frequency = s.f.values
-        sp["wavelengths"] = td.constants.C_0 / frequency
-        np.savez_compressed(filepath, **sp)
-        print(f"Simulation saved to {filepath!r}")
-        return sp
+        if upload_only:
+            plot_sources = [
+                modeler.to_source(port=p, mode_index=0) for p in modeler.ports
+            ]
+            plot_monitors = [modeler.to_monitor(port=p) for p in modeler.ports]
+
+            cz = c.get_layer_center("core")[2]
+            birdseye = FieldMonitor(
+                name="birdseye",
+                interval_space=(4, 4, 1),
+                freqs=td.constants.C_0 / wavelength,
+                center=(c.center[0], c.center[1], cz),
+                size=(c.size[0], c.size[1], 0),
+            )
+
+            sim_with_sources = modeler.simulation.copy(
+                update={
+                    "sources": plot_sources,
+                    "monitors": list(modeler.simulation.monitors)
+                    + plot_monitors
+                    + [birdseye],
+                }
+            )
+
+            s = web.upload(sim_with_sources, task_name=folder_name)
+            return s
+        if not upload_only:
+            s = modeler.run()
+            if s.status != "completed":
+                for port_in in s.port_in.values:
+                    for port_out in s.port_out.values:
+                        for mode_index_in in s.mode_index_in.values:
+                            for mode_index_out in s.mode_index_out.values:
+                                sp[
+                                    f"{port_in}@{mode_index_in},{port_out}@{mode_index_out}"
+                                ] = s.sel(
+                                    port_in=port_in,
+                                    port_out=port_out,
+                                    mode_index_in=mode_index_in,
+                                    mode_index_out=mode_index_out,
+                                ).values
+
+                frequency = s.f.values
+                sp["wavelengths"] = td.constants.C_0 / frequency
+                np.savez_compressed(filepath, **sp)
+                print(f"Simulation saved to {filepath!r}")
+                return sp
 
 
 def write_sparameters_batch(