upscale int8 to int16 for numpy 2.0

pocean/dsg/trajectoryProfile/cr.py

@@ -20,6 +20,7 @@
     get_ncdata_from_series,
     nativize_times,
     normalize_countable_array,
+    upscale_int8,
 )
 
 
@@ -323,6 +324,7 @@ def to_dataframe(self, clean_cols=True, clean_rows=True, **kwargs):
             df_data[dnam] = vdata
 
         df = pd.DataFrame(df_data)
+        df = upscale_int8(df)
 
         # Drop all data columns with no data
         if clean_cols:

pocean/tests/test_utils.py

@@ -138,7 +138,7 @@ def test_generic_masked_bad_min_max_value(self):
             # to make sure it doesn't error
             b = ncd.createVariable('imabyte', 'b')
             b.valid_min = 0
-            b.valid_max = 600  # this is over a byte and thus invalid
+            b.valid_max = np.int16(600)  # this is over a byte and thus invalid
             b[:] = 3
             r = generic_masked(b[:], attrs=ncd.vatts(b.name))
             assert np.all(r.mask == False)  # noqa

pocean/utils.py

@@ -458,6 +458,13 @@ def dict_update(d, u):
     return d
 
 
+def upscale_int8(df):
+    """Numpy 2.0 no linger upcast dtypes.
+    In order to preserve the data's original dtype we upcast it here after reading it.
+
+    """
+    return df.astype({col: "int16" for col in df.columns[df.dtypes == "int8"]})
+
 class JSONEncoder(json.JSONEncoder):
 
     def default(self, obj):