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Make sure FCI L2 reader returns cloud type and other categorical data as int #3339

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Make sure FCI L2 reader returns cloud type and other categorical data as int #3339

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db6626a
Add test case for cloud type as float
gerritholl Feb 17, 2026
752fafd
FCI L2: Don't turn categorical data into float
gerritholl Feb 18, 2026
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2 changes: 1 addition & 1 deletion satpy/readers/fci_l2_nc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -233,7 +233,7 @@
if dataset_info["file_type"] == "nc_fci_test_clm":
variable = self._decode_clm_test_data(variable, dataset_info)

if "fill_value" in dataset_info:
if "fill_value" in dataset_info and np.issubdtype(variable.dtype, np.inexact):

Check warning on line 236 in satpy/readers/fci_l2_nc.py

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CodeScene Delta Analysis / CodeScene Code Health Review (main)

❌ New issue: Complex Method 

FciL2NCFileHandler.get_dataset has a cyclomatic complexity of 9, threshold = 9. This function has many conditional statements (e.g. if, for, while), leading to lower code health. Avoid adding more conditionals and code to it without refactoring.
variable = self._mask_data(variable, dataset_info["fill_value"])

variable = self._set_attributes(variable, dataset_info)
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12 changes: 11 additions & 1 deletion satpy/tests/reader_tests/test_fci_l2_nc.py
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Expand Up @@ -222,7 +222,7 @@ def test_dataset_with_scalar(self):
with pytest.raises(NotImplementedError):
self.fh.get_area_def(None)

def test_emumerations(self):
def test_enumerations(self):
"""Test the conversion of enumerated type information into flag_values and flag_meanings."""
dataset = self.fh.get_dataset(make_dataid(name="test_enum", resolution=2000),
{"name": "quality_flag",
Expand All @@ -235,6 +235,16 @@ def test_emumerations(self):
assert "flag_meanings" in attributes
assert attributes["flag_meanings"] == ["False","True"]

def test_enum_with_fill_value_remains_int(self):
"""Test that enum with a fill value (such as cloud type) remains uint8."""
dataset = self.fh.get_dataset(make_dataid(name="test_enum", resolution=2000),
{"name": "quality_flag",
"nc_key": "quality_flag",
"file_type": "test_file_type",
"import_enum_information": True,
"fill_value": -127})
assert np.issubdtype(dataset.dtype, np.integer)

def test_units_from_file(self):
"""Test units extraction from NetCDF file."""
dataset = self.fh.get_dataset(make_dataid(name="test_units_from_file", resolution=2000),
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