Drop non-dimensional coordinates for now in stft.

tests/test_signal.py

@@ -215,6 +215,7 @@ def test_compare_with_scipy(self):
                         nfft=nfft,
                         return_onesided=return_onesided,
                         boundary=None,
+                        padded=False,
                         axis=0,
                         scaling=scaling,
                     )
@@ -231,8 +232,9 @@ def test_compare_with_scipy(self):
                         / np.timedelta64(1, "s"),
                         t,
                     )
+                    assert result["distance"].equals(da["distance"])
 
-    def test_signal(self):
+    def test_retrieve_frequency_peak(self):
         fs = 10e3
         N = 1e5
         fc = 3e3
@@ -276,3 +278,37 @@ def test_parrallel(self):
             parallel=True,
         )
         assert serial.equals(parallel)
+
+    def test_last_dimension_with_non_dimensional_coordinates(self):
+        starttime = np.datetime64("2023-01-01T00:00:00")
+        endtime = starttime + 99 * np.timedelta64(10, "ms")
+        da = xdas.DataArray(
+            data=np.random.rand(100, 1001),
+            coords={
+                "time": {"tie_indices": [0, 99], "tie_values": [starttime, endtime]},
+                "distance": {"tie_indices": [0, 1000], "tie_values": [0.0, 10_000.0]},
+                "channel": ("distance", np.arange(1001)),
+            },
+        )
+        result = xs.stft(
+            da,
+            nperseg=100,
+            noverlap=50,
+            window="hamming",
+            dim={"distance": "wavenumber"},
+        )
+        f, t, Zxx = sp.stft(
+            da.values,
+            fs=1 / xs.get_sampling_interval(da, "distance"),
+            window="hamming",
+            nperseg=100,
+            noverlap=50,
+            boundary=None,
+            padded=False,
+            axis=1,
+        )
+        assert np.allclose(result.values, np.transpose(Zxx, (0, 2, 1)))
+        assert result["time"].equals(da["time"])
+        assert np.allclose(result["distance"].values, t)
+        assert np.allclose(result["wavenumber"].values, np.sort(f))
+        assert "channel" not in result.coords  # TODO: keep non-dimensional coordinates

xdas/spectral.py

@@ -71,8 +71,14 @@ def func(x):
         "tie_values": [starttime, endtime],
     }
 
-    coords = da.coords.copy()
-    coords[input_dim] = time
+    coords = {}
+    for name in da.coords:
+        if name == input_dim:
+            coords[input_dim] = time
+        elif name == output_dim:
+            coords[output_dim] = freqs
+        elif da[name].dim != input_dim:  # TODO: keep non-dimensional coordinates
+            coords[name] = da.coords[name]
     coords[output_dim] = freqs
 
     dims = da.dims + (output_dim,)