def test_path_input(tmp_path):
file_path = tmp_path/"test.asdf"
with asdf.AsdfFile() as af:
af["meta"] = {"telescope": "magnifying glass"}
af.write_to(file_path)
# Test with PurePath input:
with datamodels.open(file_path) as model:
assert model.meta.telescope == "magnifying glass"
af = model._asdf
# When open creates the file pointer, it should be
# closed when the model is closed:
assert af._closed
# Test with string input:
with datamodels.open(str(file_path)) as model:
assert model.meta.telescope == "magnifying glass"
af = model._asdf
assert af._closed
# Appropriate error when file is missing:
with pytest.raises(FileNotFoundError):
with datamodels.open(tmp_path/"missing.asdf"):
pass
def test_core_schema(tmp_path):
# Set temporary asdf file
file_path = tmp_path / "test.asdf"
# Define meta dictionary of required key / value pairs
meta = {
"meta": {
"instrument": {
"detector": "WFI01",
"name": "WFI"
},
"telescope":
"ROMAN",
"model_type":
"RomanDataModel",
"date":
Time('2021-02-20T02:20:00.123456789', format='isot', scale='utc')
}
}
# Testing bad core asdf file
with asdf.AsdfFile(meta) as af:
# Test for invalid entry
af["meta"]["telescope"] = "NOTROMAN"
af.write_to(file_path)
with datamodels.open(file_path) as model:
with pytest.warns(ValidationWarning):
model.validate()
assert model["meta"]["telescope"] == "NOTROMAN"
def test_memmap(tmp_path):
file_path = tmp_path/"test.asdf"
with asdf.AsdfFile() as af:
af["data"] = np.zeros((1024,))
af["meta"] = {}
af.write_to(file_path)
with datamodels.open(file_path, memmap=True) as model:
assert isinstance(model.data.base, np.memmap)
with datamodels.open(file_path, memmap=False) as model:
assert not isinstance(model.data.base, np.memmap)
# Default should be false:
with datamodels.open(file_path) as model:
assert not isinstance(model.data.base, np.memmap)
def test_core_schema(tmp_path):
# Set temporary asdf file
file_path = tmp_path / "test.asdf"
# Define meta dictionary of required key / value pairs
meta = {"meta":
{"instrument": {
"detector": "WFI01",
"optical_element": "F158",
"name": "WFI"
},
"telescope": "ROMAN",
"model_type": "RomanDataModel",
"date": "2020-12-20"
}
}
# Testing bad core asdf file
with asdf.AsdfFile(meta) as af:
# Test for invalid entry
af["meta"]["telescope"] = "NOTROMAN"
af.write_to(file_path)
with datamodels.open(file_path) as model:
model.validate()
with pytest.warns(ValidationWarning):
model.validate()
assert model["meta"]["telescope"] == "NOTROMAN"
def test_model_input(tmp_path):
file_path = tmp_path/"test.asdf"
data = np.random.uniform(size=(1024, 1024))
with asdf.AsdfFile() as af:
af["meta"] = {"telescope": "jeweler's loupe"}
af["data"] = data
af.write_to(file_path)
original_model = datamodels.open(file_path)
reopened_model = datamodels.open(original_model)
# It's essential that we get a new instance so that the original
# model can be closed without impacting the new model.
assert reopened_model is not original_model
assert_array_equal(original_model.data, data)
original_model.close()
assert_array_equal(reopened_model.data, data)
reopened_model.close()
def test_asdf_file_input():
with asdf.AsdfFile() as af:
af["meta"] = {"telescope": "binoculars"}
model = datamodels.open(af)
assert model.meta.telescope == "binoculars"
# When an already open file is passed in, the model
# is not responsible for closing it.
model.close()
assert not af._closed
def test_reference_file_model_base(tmp_path):
# Set temporary asdf file
file_path = tmp_path / "test.asdf"
# Get reference dictionary base
meta = REFERENCEFILE_SCHEMA_DICT
# Testing referencefile asdf file
with asdf.AsdfFile(meta) as af:
af.write_to(file_path)
# Ensure that base referencefile schema contains core schema
assert_referenced_schema(datamodels.reference_files.referencefile.ReferenceFileModel.schema_url,
datamodels.core.RomanDataModel.schema_url)
# Test that asdf file opens properly
assert datamodels.open(file_path)
# Confirm that asdf file is opened as base referencefile model
with datamodels.open(file_path) as model:
assert isinstance(model, datamodels.reference_files.referencefile.ReferenceFileModel)
def get_data_model_flat_dict(filepath):
"""Get the header from `filepath` using the roman data model. Data model
dotted object paths are reduced to capitalized dot-separated FITS-like
keyword strings and a simple key,value dictionary format vs. nested objects.
e.g. meta.instrument.name --> "META.INSTRUMENT.NAME'
Returns { file_keyword : keyword_value, ... }
"""
datamodels = get_datamodels()
log.info("Checking Roman datamodels.")
try:
with datamodels.open(filepath) as d_model:
flat_dict = d_model.to_flat_dict(include_arrays=False)
except Exception as exc:
raise exceptions.ValidationError("Roman Data Models:", str(exc).replace("u'","'")) from exc
return flat_dict
def test_flat_model(tmp_path):
# Set temporary asdf file
file_path = tmp_path / "test.asdf"
# Get reference dictionary base
meta = REFERENCEFILE_SCHEMA_DICT
# Testing flat file asdf file
with asdf.AsdfFile(meta) as af:
# Add required flat file elements
af["meta"]["reftype"] = "FLAT"
af["meta"]["model_type"] = "FlatModel"
af["data"] = np.zeros((4096, 4096))
af["dq"] = np.zeros((4096, 4096))
af["derr"] = np.zeros((4096, 4096))
af.write_to(file_path)
# Test that asdf file opens properly
with datamodels.open(file_path) as model:
with pytest.warns(None):
model.validate()
# Confirm that asdf file is opened as flat file model
assert isinstance(model, datamodels.reference_files.flat.FlatModel)
def test_invalid_input():
with pytest.raises(TypeError):
datamodels.open(fits.HDUList())
