def buildConcepts(self):
cc = ConcreteConcept('hareitosis', 'i', ['hareitosis'], ['B02.34'],
[''])
cc2 = ConcreteConcept('inflammed hair cancer', 'a',
['hairitis', 'hairiatic cancer'],
['A12.23.45', 'B01.23'], [''])
self.storage = {'c12345': cc, 'c98765': cc2}
Concept.init_storage(self.storage)
return (Concept('c12345'), Concept('c98765'))
def testWrongMappingType(self):
c1, c2 = self.buildConcepts()
cc3 = ConcreteConcept('hairosis', 'g/p', ['hairotic hairisis'],
['C1.2.3'], [''])
# Add it in a roundabout way to the original storage
self.storage['c2468'] = cc3
c3 = Concept('c2468')
self.assertEqual([], self.ruleless_converter.convert(c3).utterance)
def convert(self, a_ranked_result_set):
"""Convert a ranked result set into a RankedConversionResult.
In other words, convert a ranked term list to its MeSH equivalents."""
result = RankedConversionResult()
self._my_converter.start_conversion()
for incoming_term, incoming_score in a_ranked_result_set:
converted = self._my_converter.convert(
Concept(incoming_term.node_id))
if converted.utterance != []:
result.add_term_score(converted, incoming_score)
converted = self._my_converter.end_conversion()
if converted.utterance != []:
result.add_term_score(converted,
incoming_score + self._checktag_boost)
logging.log(ULTRADEBUG, "RankedConverter results: %r", result)
return result
def testTermNotInTreeRaisesException(self):
c1, c2 = self.buildConcepts()
cc3 = ConcreteConcept(
'hairosis',
'i',
[
'hairotic hairisis',
'hair-raising hair', # <--This'll be a descriptor
'hurry'
],
['Q12345678', 'D123456', 'Q987564'],
[''])
# Add it in a roundabout way to the original storage
self.storage['c2468'] = cc3
c3 = Concept('c2468')
self.ruleless_converter._skip_unknown = False
self.assertRaises(TermNotInTree, self.ruleless_converter.convert, c3)
def testDeepestOnePreferred(self):
c1, c2 = self.buildConcepts()
cc3 = ConcreteConcept(
'hair-raising hair',
'i',
[
'hairitis', # <-- a descriptor
'hairiatic cancer', # <-- a descriptor
'hareitosis'
], # <-- a descriptor
['D12345678', 'D123456', 'D987564'],
[''])
# Add it in a roundabout way to the original storage
self.storage['c2468'] = cc3
c3 = Concept('c2468')
# Should choose the deepest one (hairiatic cancer, according to
# self.my_tree)
self.assertEqual([Term('hairiatic cancer')],
self.ruleless_converter.convert(c3).utterance)
def testDescriptorNamedLikeConceptPreferred(self):
c1, c2 = self.buildConcepts()
cc3 = ConcreteConcept(
'hair-raising hair',
'i',
[
'hairotic hairisis', # <-- a descriptor
'hair-raising hair', # <-- a descriptor
'hurry'
], # <-- not a descriptor
['D12345678', 'D123456', 'Q987564'],
[''])
# Add it in a roundabout way to the original storage
self.storage['c2468'] = cc3
c3 = Concept('c2468')
# Make sure the tree knows about this concept
self.my_tree._tree['hair-raising hair'] = TreeNode(
'hair-raising hair', 'MH', 'Q', set(['B12.34']))
self.assertEqual([Term('hair-raising hair')],
self.ruleless_converter.convert(c3).utterance)
def __init__(self, original_line, converter):
RelationLine.__init__(self, original_line)
self._mesh1 = converter.convert(Concept(self.CUI1))
self._mesh2 = converter.convert(Concept(self.CUI2))
dummy = converter.end_conversion() # Discard extra terms generated by
def __init__(self, original_line, converter):
EntityLine.__init__(self, original_line)
self._mesh = converter.convert(Concept(self.CUI))
dummy = converter.end_conversion() # Discard extra terms generated by
