def test_compare_ui_score():
## GIVEN three sets
a = set(["a", "b"])
b = set(["b", "a", "d"])
c = set(["b", "c", "d"])
## WHEN finding the similarity
similarity_ab = ui_score(a, b)
similarity_ac = ui_score(a, c)
## THEN assert a and b are more similar than a and c
assert similarity_ab > similarity_ac
def test_compare_ui_score():
## GIVEN three sets
a = set(['a', 'b'])
b = set(['b', 'a', 'd'])
c = set(['b', 'c', 'd'])
## WHEN finding the similarity
similarity_ab = ui_score(a, b)
similarity_ac = ui_score(a, c)
## THEN assert a and b are more similar than a and c
assert similarity_ab > similarity_ac
def test_get_one_empty_ui_score():
## GIVEN one empty sets
a = set(["a", "b"])
b = set()
## WHEN finding the similarity
similarity = ui_score(a, b)
## THEN assert similarity is 0
assert similarity == 0
def test_get_disjunct_ui_score():
## GIVEN two disjunct sets
a = set(["a", "b"])
b = set(["c", "d"])
## WHEN finding the similarity
similarity = ui_score(a, b)
## THEN assert similarity is 0
assert similarity == 0
def test_get_identical_ui_score():
## GIVEN two disjunct sets
a = set(["a", "b"])
b = set(["b", "a"])
## WHEN finding the similarity
similarity = ui_score(a, b)
## THEN assert similarity is 1
assert similarity == 1
def test_get_disjunct_ui_score():
## GIVEN two disjunct sets
a = set(['a', 'b'])
b = set(['c', 'd'])
## WHEN finding the similarity
similarity = ui_score(a, b)
## THEN assert similarity is 0
assert similarity == 0
def test_get_two_empty_ui_score():
## GIVEN two empty sets
a = set()
b = set()
## WHEN finding the similarity
similarity = ui_score(a, b)
## THEN assert similarity is 0
assert similarity == 0
def test_get_almost_identical_ui_score():
## GIVEN two disjunct sets
a = set(['a', 'b'])
b = set(['b', 'a', 'd'])
## WHEN finding the similarity
similarity = ui_score(a, b)
## THEN assert 0 < similarity < 1
assert 0 < similarity
assert similarity < 1
def cases_by_phenotype(self, phenotype_terms, owner, case_id=None):
"""Take a case obj and return a iterable with the most phenotypically similar cases
Args:
phenotype_terms(list):[ "HP:0001250", "HP:0000707",.. ]
owner(str): institute id
case_id(str): Id of a case, when searching for cases similar to another
Returns:
scores(list(tuple)): Returns a list of tuples like (case_id, score) with the most
similar case first
"""
scores = {}
set_1 = set()
if len(phenotype_terms) == 0:
LOG.warning("No phenotype terms provided, please provide ar least one HPO term")
return None
# Add all ancestors of all terms
for term in phenotype_terms:
hpo_term = self.hpo_term(term)
if not hpo_term:
continue
set_1 = set_1.union(set(hpo_term.get("all_ancestors", [])))
# Need to control what cases to look for here
# Fetch all cases with phenotypes
for case in self.cases(phenotype_terms=True, owner=owner):
set_2 = set()
if case["_id"] == case_id:
continue
# Add all ancestors if all terms
for term in case["phenotype_terms"]:
hpo_term = self.hpo_term(term["phenotype_id"])
if not hpo_term:
continue
set_2 = set_2.union(set(hpo_term.get("all_ancestors", [])))
LOG.debug(
f"Check phenotypic similarity between terms:{phenotype_terms} and case {case['_id']}"
)
scores[case["_id"]] = ui_score(set_1, set_2)
# Returns a list of tuples with highest score first
return sorted(scores.items(), key=operator.itemgetter(1), reverse=True)
def get_similar_cases(self, case_obj):
"""Take a case obj and return a iterable with the most phenotypically similar cases
Args:
case_obj(models.Case)
Returns:
scores(list(tuple)): Returns a list of tuples like (case_id, score) with the most
similar case first
"""
scores = {}
set_1 = set()
if not case_obj.get("phenotype_terms"):
LOG.warning("No phenotypes could be found for case %s",
case_obj["_id"])
return None
# Add all ancestors of all terms
for term in case_obj["phenotype_terms"]:
hpo_term = self.hpo_term(term["phenotype_id"])
if not hpo_term:
continue
set_1 = set_1.union(set(hpo_term.get("all_ancestors", [])))
# Need to control what cases to look for here
# Fetch all cases with phenotypes
for case in self.cases(phenotype_terms=True, owner=case_obj["owner"]):
set_2 = set()
if case["_id"] == case_obj["_id"]:
continue
# Add all ancestors if all terms
for term in case["phenotype_terms"]:
hpo_term = self.hpo_term(term["phenotype_id"])
if not hpo_term:
continue
set_2 = set_2.union(set(hpo_term.get("all_ancestors", [])))
LOG.debug("Check phenotypic similarity of %s and %s",
case_obj["_id"], case["_id"])
scores[case["_id"]] = ui_score(set_1, set_2)
# Returns a list of tuples with highest score first
return sorted(scores.items(), key=operator.itemgetter(1), reverse=True)
