Fixing mag tests, removing temp fix (#1142)

* Fixing mag tests, removing temp fix

* Fix type error

imap_processing/mag/l0/decom_mag.py

@@ -171,4 +171,4 @@ def generate_dataset(
                 attrs=attribute_manager.get_variable_attributes(key),
             )
 
-    return output.drop_duplicates("epoch")
+    return output

imap_processing/mag/l1b/mag_l1b.py

@@ -158,7 +158,7 @@ def rescale_vector(
     if not compression_flags[0]:
         return input_vector
     else:
-        factor = float(2 ** (16 - compression_flags[1]))
+        factor = np.float_power(2, (16 - compression_flags[1]))
         return input_vector * factor  # type: ignore
 
 

imap_processing/tests/mag/test_mag_l1b.py

@@ -18,7 +18,9 @@ def mag_l1a_dataset():
         dims=["epoch", "direction"],
         coords={"epoch": epoch, "direction": direction},
     )
-    compression_flags = xr.DataArray(np.zeros((20, 2)), dims=["epoch", "compression"])
+    compression_flags = xr.DataArray(
+        np.zeros((20, 2), dtype=np.int8), dims=["epoch", "compression"]
+    )
 
     vectors[0, :] = np.array([1, 1, 1, 0])
 
@@ -69,10 +71,9 @@ def test_mag_attributes(mag_l1a_dataset):
     assert output.attrs["Data_level"] == "L1B"
 
 
-@pytest.mark.skip(reason="Epoch variable data need to be monotonically increasing")
 def test_cdf_output():
     l1a_cdf = load_cdf(
-        Path(__file__).parent / "imap_mag_l1a_burst-magi_20231025_v001.cdf"
+        Path(__file__).parent / "imap_mag_l1a_norm-magi_20251017_v001.cdf"
     )
     l1b_dataset = mag_l1b(l1a_cdf, "v001")
 
@@ -94,10 +95,10 @@ def test_mag_compression_scale(mag_l1a_dataset):
     mag_l1a_dataset["vectors"][2, :] = np.array([1, 1, 1, 0])
     mag_l1a_dataset["vectors"][3, :] = np.array([1, 1, 1, 0])
 
-    mag_l1a_dataset["compression_flags"][0, :] = np.array([1, 16])
-    mag_l1a_dataset["compression_flags"][1, :] = np.array([0, 0])
-    mag_l1a_dataset["compression_flags"][2, :] = np.array([1, 18])
-    mag_l1a_dataset["compression_flags"][3, :] = np.array([1, 14])
+    mag_l1a_dataset["compression_flags"][0, :] = np.array([1, 16], dtype=np.int8)
+    mag_l1a_dataset["compression_flags"][1, :] = np.array([0, 0], dtype=np.int8)
+    mag_l1a_dataset["compression_flags"][2, :] = np.array([1, 18], dtype=np.int8)
+    mag_l1a_dataset["compression_flags"][3, :] = np.array([1, 14], dtype=np.int8)
 
     mag_l1a_dataset.attrs["Logical_source"] = ["imap_mag_l1a_norm-mago"]
     output = mag_l1b(mag_l1a_dataset, "v001")