fix: outer_dot output frequencies order not matching input

Author: momchil-flex

CHANGELOG.md

@@ -17,6 +17,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Added optional `max_results` handling to the kLayout `DRCLoader` and `DRCRunner` and speeded up parsing of big result sets.
 
 ### Fixed
+- Fix to `outer_dot` when frequencies stored in the data were not in increasing order. Previously, the result would be provided with re-sorted frequencies, which would not match the order of the original data.
 - Fixed bug where an extra spatial coordinate could appear in `complex_flux` and `ImpedanceCalculator` results.
 
 ## [2.10.0rc3] - 2025-11-26

tests/test_data/test_monitor_data.py

@@ -850,7 +850,22 @@ def isel(data, freqs):
 
     dot = mode_data.outer_dot(field_data)
 
-    assert len(dot.f) == 2
+    expected_freqs = [freq for freq in mode_data.Ex.f.values if freq in field_data.Ex.f.values]
+    assert dot.sizes["f"] == len(expected_freqs)
+    assert np.array_equal(dot.f.values, np.array(expected_freqs))
+
+    # ensure frequency order follows the first dataset when the other is unordered
+    field_data_full = make_field_data_2d()
+    reversed_inds = list(range(field_data_full.Ex.sizes["f"] - 1, -1, -1))
+    field_data_reordered = field_data_full.copy(
+        update={
+            name: component.isel(f=reversed_inds)
+            for name, component in field_data_full.field_components.items()
+        }
+    )
+
+    dot_ordered = field_data_full.outer_dot(field_data_reordered)
+    assert np.array_equal(dot_ordered.f.values, field_data_full.Ex.f.values)
 
 
 def test_translated_copy():
@@ -1118,7 +1133,7 @@ def test_tozbf_modedata(
 
     def test_tozbf_modedata_fails(self, tmp_path, mode_data):
         """Asserts that Modedata.to_zbf() fails if mode_index is not specified"""
-        with pytest.raises(ValueError) as e:
+        with pytest.raises(ValueError):
             _ = mode_data.to_zbf(
                 fname=tmp_path / "testzbf_modedata_fail.zbf",
                 background_refractive_index=1,
@@ -1133,7 +1148,7 @@ def test_tozbf_modedata_fails(self, tmp_path, mode_data):
     @pytest.mark.parametrize("n_y", [16, 2**14, 33])
     def test_tozbf_nxny_fails(self, tmp_path, field_data, n_x, n_y):
         """Asserts that to_zbf() fails when n_x and n_y are invalid values."""
-        with pytest.raises(ValueError) as e:
+        with pytest.raises(ValueError):
             _ = field_data.to_zbf(
                 fname=tmp_path / "testzbf_nxny_fail.zbf",
                 background_refractive_index=1,
@@ -1146,7 +1161,7 @@ def test_tozbf_nxny_fails(self, tmp_path, field_data, n_x, n_y):
     @pytest.mark.parametrize("units", ["mmm", "123"])
     def test_tozbf_units_fails(self, tmp_path, field_data, units):
         """Asserts that to_zbf() fails when units are invalid."""
-        with pytest.raises(ValueError) as e:
+        with pytest.raises(ValueError):
             _ = field_data.to_zbf(
                 fname=tmp_path / "testzbf_nxny_fail.zbf",
                 background_refractive_index=1,
@@ -1190,7 +1205,7 @@ def test_from_zbf_dimsfail(self, tmp_path, field_data, dim1, dim2):
             units="mm",
         )
         # this should fail
-        with pytest.raises(ValueError) as e:
+        with pytest.raises(ValueError):
             _ = td.FieldDataset.from_zbf(filename=zbf_filename, dim1=dim1, dim2=dim2)
 
 

tidy3d/components/data/monitor_data.py

@@ -12,7 +12,7 @@
 import autograd.numpy as np
 import pydantic.v1 as pd
 import xarray as xr
-from pandas import DataFrame
+from pandas import DataFrame, Index
 
 from tidy3d.components.base import cached_property, skip_if_fields_missing
 from tidy3d.components.base_sim.data.monitor_data import AbstractMonitorData
@@ -916,9 +916,13 @@ def outer_dot(
         coords = (arrays[0].coords, arrays[1].coords)
 
         # Common frequencies to both data arrays
-        f = np.array(sorted(set(coords[0]["f"].values).intersection(coords[1]["f"].values)))
-        isel1 = [list(coords[0]["f"].values).index(freq) for freq in f]
-        isel2 = [list(coords[1]["f"].values).index(freq) for freq in f]
+        freq_self = Index(coords[0]["f"].values)
+        freq_other = Index(coords[1]["f"].values)
+        common_freqs = freq_self.intersection(freq_other, sort=False)
+        f = common_freqs.to_numpy()
+        # Keep frequency order consistent with the current data while aligning the other dataset.
+        isel1 = freq_self.get_indexer(common_freqs)
+        isel2 = freq_other.get_indexer(common_freqs)
 
         # Mode indices, if available
         modes_in_self = "mode_index" in coords[0]