def test_integer_attribute(self):
i = IntegerAttribute(44)
self.assertEqual(i.value, 44)
i = IntegerAttribute(-3)
self.assertEqual(i.value, -3)
i = IntegerAttribute(None, allow_null=True)
with self.assertRaises(AttributeValueError):
i = IntegerAttribute(None)
with self.assertRaises(AttributeValueError):
i = IntegerAttribute(settings.POSITIVE_INF_MARKER)
def test_metadata_correct(self):
resource_path = os.path.join(TESTDIR, 'gene_annotations.tsv')
t = FeatureTable()
column_dict = {}
feature_list = []
for i, line in enumerate(open(resource_path)):
if i == 0:
contents = line.strip().split('\t')
for j,c in enumerate(contents[1:]):
column_dict[j] = c
else:
contents = line.strip().split('\t')
gene_name = contents[0]
attr_dict = {}
for j,v in enumerate(contents[1:]):
try:
v = int(v)
attr = IntegerAttribute(v)
except ValueError:
attr = StringAttribute(v)
attr_dict[column_dict[j]] = attr
f = Feature(gene_name, attr_dict)
feature_list.append(f)
expected_feature_set = FeatureSetSerializer(FeatureSet(feature_list)).data
metadata = t.extract_metadata(resource_path)
self.assertEqual(metadata[FEATURE_SET_KEY], expected_feature_set)
self.assertIsNone(metadata[OBSERVATION_SET_KEY])
self.assertIsNone(metadata[PARENT_OP_KEY])
def test_metadata_correct(self):
resource_path = os.path.join(TESTDIR, 'gene_annotations.tsv')
t = FeatureTable()
column_dict = {}
feature_list = []
for i, line in enumerate(open(resource_path)):
if i == 0:
contents = line.strip().split('\t')
for j, c in enumerate(contents[1:]):
column_dict[j] = c
else:
contents = line.strip().split('\t')
gene_name = contents[0]
attr_dict = {}
for j, v in enumerate(contents[1:]):
try:
v = int(v)
attr = IntegerAttribute(v)
except ValueError:
attr = StringAttribute(v)
attr_dict[column_dict[j]] = attr
f = Feature(gene_name, attr_dict)
feature_list.append(f)
expected_feature_set = FeatureSetSerializer(
FeatureSet(feature_list)).data
metadata = t.extract_metadata(resource_path, 'tsv')
# Commented out when we removed the automatic creation of Feature metadata
# for FeatureTable resource types. For large files, it was causing issues
# with exceptionally large JSON failing to store in db table.
#self.assertEqual(metadata[FEATURE_SET_KEY], expected_feature_set)
self.assertIsNone(metadata[FEATURE_SET_KEY])
self.assertIsNone(metadata[OBSERVATION_SET_KEY])
self.assertIsNone(metadata[PARENT_OP_KEY])
def setUp(self):
float_attr = FloatAttribute(0.01)
int_attr = IntegerAttribute(3)
self.demo_element = Feature('my_identifier', {
'keyA': float_attr,
'keyB': int_attr
})
# the class that will execute the tests
self.tester_class = ElementTester(Feature)
def test_adding_ovewrite_attribute(self, testcase):
'''
Test overwriting an existing attribute
'''
float_attr = FloatAttribute(0.01)
int_attr = IntegerAttribute(3)
element = self.element_class('some_identifier', {
'keyA': float_attr,
'keyB': int_attr
})
element.add_attribute('keyA', {
'attribute_type': 'Float',
'value': 2.3
},
overwrite=True)
expected_attr = FloatAttribute(2.3)
testcase.assertEqual(element.attributes['keyA'], expected_attr)
def test_adding_new_attribute(self, testcase):
'''
Test adding a new attribute
'''
float_attr = FloatAttribute(0.01)
int_attr = IntegerAttribute(3)
element = self.element_class('some_identifier', {
'keyA': float_attr,
'keyB': int_attr
})
element.add_attribute('keyC', {
'attribute_type': 'String',
'value': 'abc'
})
expected_attr = StringAttribute('abc')
testcase.assertEqual(element.attributes['keyC'], expected_attr)
expected_keys = set(['keyA', 'keyB', 'keyC'])
existing_keys = set(element.attributes.keys())
testcase.assertTrue(expected_keys == existing_keys)
def setUp(self):
float_attr = FloatAttribute(0.01)
int_attr = IntegerAttribute(3)
boolean_attr = BooleanAttribute(True)
bounded_float_attr = BoundedFloatAttribute(0.1, min=0.0, max=1.0)
self.demo_element = Feature('my_identifier', {
'keyA': float_attr,
'keyB': int_attr
})
self.demo_element2 = Feature('my_identifier', {})
self.demo_element_data = {
'id': 'my_identifier',
'attributes': {
'keyA': {
'attribute_type': 'Float',
'value': 0.01
},
'keyB': {
'attribute_type': 'Integer',
'value': 3
}
}
}
self.demo_element_data2 = {'id': 'my_identifier', 'attributes': {}}
self.bad_element_data = {
'id': 'my_identifier',
'attributes': {
'keyA': {
'attribute_type': 'Float',
'value': 'abc'
},
'keyB': {
'attribute_type': 'Integer',
'value': 3
}
}
}
self.demo_element_data_w_bounds = {
'id': 'my_identifier',
'attributes': {
'pvalue': {
'attribute_type': 'BoundedFloat',
'value': 0.1,
'min': 0.0,
'max': 1.0
},
'keyB': {
'attribute_type': 'Integer',
'value': 3
}
}
}
self.demo_element_w_bounds = Feature('my_identifier', {
'pvalue': bounded_float_attr,
'keyB': int_attr
})
self.bad_demo_element_data_w_bounds = {
'id': 'my_identifier',
'attributes': {
'pvalue': {
'attribute_type': 'BoundedFloat',
'value': 1.1, # out of bounds!!
'min': 0.0,
'max': 1.0
},
'keyB': {
'attribute_type': 'Integer',
'value': 3
}
}
}
self.demo_element_w_bool = Feature('my_identifier', {
'keyA': int_attr,
'some_bool': boolean_attr
})
self.demo_element_data_w_bool1 = {
'id': 'my_identifier',
'attributes': {
'keyA': {
'attribute_type': 'Integer',
'value': 3
},
'some_bool': {
'attribute_type': 'Boolean',
'value': 'true'
}
}
}
self.demo_element_data_w_bool2 = {
'id': 'my_identifier',
'attributes': {
'keyA': {
'attribute_type': 'Integer',
'value': 3
},
'some_bool': {
'attribute_type': 'Boolean',
'value': 1
}
}
}
self.demo_element_data_w_bool3 = {
'id': 'my_identifier',
'attributes': {
'keyA': {
'attribute_type': 'Integer',
'value': 3
},
'some_bool': {
'attribute_type': 'Boolean',
'value': True
}
}
}
self.bad_demo_element_data_w_bool = {
'id': 'my_identifier',
'attributes': {
'keyA': {
'attribute_type': 'Integer',
'value': 3
},
'some_bool': {
'attribute_type': 'Boolean',
'value': -1
}
}
}
# the class that will execute the tests
self.tester_class = ElementSerializerTester(FeatureSerializer)
def test_int_string_rejected_for_integer(self):
with self.assertRaises(AttributeValueError):
IntegerAttribute('2')
def test_float_rejected_for_integer(self):
with self.assertRaises(AttributeValueError):
IntegerAttribute(1.2)
def convert(self, input_key, user_input, op_dir, staging_dir):
i = IntegerAttribute(user_input)
return {input_key: i.value}
def setUp(self):
float_attr = FloatAttribute(0.01)
int_attr = IntegerAttribute(3)
bounded_float_attr = BoundedFloatAttribute(0.1, min=0.0, max=1.0)
self.demo_element = Observation('my_identifier', {
'keyA': float_attr,
'keyB': int_attr
})
self.demo_element2 = Observation('my_identifier', {})
self.demo_element_data = {
'id': 'my_identifier',
'attributes': {
'keyA': {
'attribute_type': 'Float',
'value': 0.01
},
'keyB': {
'attribute_type': 'Integer',
'value': 3
}
}
}
self.demo_element_data2 = {'id': 'my_identifier', 'attributes': {}}
self.bad_element_data = {
'id': 'my_identifier',
'attributes': {
'keyA': {
'attribute_type': 'Float',
'value': 'abc'
},
'keyB': {
'attribute_type': 'Integer',
'value': 3
}
}
}
self.demo_element_data_w_bounds = {
'id': 'my_identifier',
'attributes': {
'pvalue': {
'attribute_type': 'BoundedFloat',
'value': 0.1,
'min': 0.0,
'max': 1.0
},
'keyB': {
'attribute_type': 'Integer',
'value': 3
}
}
}
self.demo_element_w_bounds = Observation('my_identifier', {
'pvalue': bounded_float_attr,
'keyB': int_attr
})
self.bad_demo_element_data_w_bounds = {
'id': 'my_identifier',
'attributes': {
'pvalue': {
'attribute_type': 'BoundedFloat',
'value': 1.1, # out of bounds!!
'min': 0.0,
'max': 1.0
},
'keyB': {
'attribute_type': 'Integer',
'value': 3
}
}
}
# the class that will execute the tests
self.tester_class = ElementSerializerTester(ObservationSerializer)
