Fix failing NX tables test

cheetah/converters/nxtables.py

@@ -53,10 +53,10 @@ def translate_element(row: list[str], header: list[str]) -> Optional[Dict]:
     elif class_name == "MCXG":  # TODO: Check length with Willi
         assert name[6] == "X"
         horizontal_coil = cheetah.HorizontalCorrector(
-            name=name[:6] + "H" + name[6 + 1 :], length=torch.tensor(5e-05)
+            name=name[:6] + "H" + name[6 + 1 :], length=torch.tensor([5e-05])
         )
         vertical_coil = cheetah.VerticalCorrector(
-            name=name[:6] + "V" + name[6 + 1 :], length=torch.tensor(5e-05)
+            name=name[:6] + "V" + name[6 + 1 :], length=torch.tensor([5e-05])
         )
         element = cheetah.Segment(elements=[horizontal_coil, vertical_coil], name=name)
     elif class_name == "BSCX":
@@ -115,57 +115,57 @@ def translate_element(row: list[str], header: list[str]) -> Optional[Dict]:
     elif class_name == "SLHG":
         element = cheetah.Aperture(  # TODO: Ask for actual size and shape
             name=name,
-            x_max=torch.tensor(float("inf")),
-            y_max=torch.tensor(float("inf")),
+            x_max=torch.tensor([float("inf")]),
+            y_max=torch.tensor([float("inf")]),
             shape="elliptical",
         )
     elif class_name == "SLHB":
         element = cheetah.Aperture(  # TODO: Ask for actual size and shape
             name=name,
-            x_max=torch.tensor(float("inf")),
-            y_max=torch.tensor(float("inf")),
+            x_max=torch.tensor([float("inf")]),
+            y_max=torch.tensor([float("inf")]),
             shape="rectangular",
         )
     elif class_name == "SLHS":
         element = cheetah.Aperture(  # TODO: Ask for actual size and shape
             name=name,
-            x_max=torch.tensor(float("inf")),
-            y_max=torch.tensor(float("inf")),
+            x_max=torch.tensor([float("inf")]),
+            y_max=torch.tensor([float("inf")]),
             shape="rectangular",
         )
     elif class_name == "MCHM":
-        element = cheetah.HorizontalCorrector(name=name, length=torch.tensor(0.02))
+        element = cheetah.HorizontalCorrector(name=name, length=torch.tensor([0.02]))
     elif class_name == "MCVM":
-        element = cheetah.VerticalCorrector(name=name, length=torch.tensor(0.02))
+        element = cheetah.VerticalCorrector(name=name, length=torch.tensor([0.02]))
     elif class_name == "MBHL":
-        element = cheetah.Dipole(name=name, length=torch.tensor(0.322))
+        element = cheetah.Dipole(name=name, length=torch.tensor([0.322]))
     elif class_name == "MBHB":
-        element = cheetah.Dipole(name=name, length=torch.tensor(0.22))
+        element = cheetah.Dipole(name=name, length=torch.tensor([0.22]))
     elif class_name == "MBHO":
         element = cheetah.Dipole(
             name=name,
-            length=torch.tensor(0.43852543421396856),
-            angle=torch.tensor(0.8203047484373349),
-            e2=torch.tensor(-0.7504915783575616),
+            length=torch.tensor([0.43852543421396856]),
+            angle=torch.tensor([0.8203047484373349]),
+            e2=torch.tensor([-0.7504915783575616]),
         )
     elif class_name == "MQZM":
-        element = cheetah.Quadrupole(name=name, length=torch.tensor(0.122))
+        element = cheetah.Quadrupole(name=name, length=torch.tensor([0.122]))
     elif class_name == "RSBL":
         element = cheetah.Cavity(
             name=name,
-            length=torch.tensor(4.139),
-            frequency=torch.tensor(2.998e9),
-            voltage=torch.tensor(76e6),
+            length=torch.tensor([4.139]),
+            frequency=torch.tensor([2.998e9]),
+            voltage=torch.tensor([76e6]),
         )
     elif class_name == "RXBD":
         element = cheetah.Cavity(  # TODO: TD? and tilt?
             name=name,
-            length=torch.tensor(1.0),
-            frequency=torch.tensor(11.9952e9),
-            voltage=torch.tensor(0.0),
+            length=torch.tensor([1.0]),
+            frequency=torch.tensor([11.9952e9]),
+            voltage=torch.tensor([0.0]),
         )
     elif class_name == "UNDA":  # TODO: Figure out actual length
-        element = cheetah.Undulator(name=name, length=torch.tensor(0.25))
+        element = cheetah.Undulator(name=name, length=torch.tensor([0.25]))
     elif class_name in [
         "SOLG",
         "BCMG",
@@ -252,7 +252,7 @@ def read_nx_tables(filepath: Path) -> "cheetah.Element":
             filled_with_drifts.append(
                 cheetah.Drift(
                     name=f"DRIFT_{previous['element'].name}_{current['element'].name}",
-                    length=torch.as_tensor(drift_length),
+                    length=torch.as_tensor([drift_length]),
                 )
             )