def test_structure_normalization(self):
gen = read('mzid_snippet.xml').iterfind("SpectraData")
datum = next(gen)
index = aux.cvquery(datum)
assert index['MS:1000768'] == 'Thermo nativeID format'
datum = next(gen)
index = aux.cvquery(datum)
assert index['MS:1000774'] == 'multiple peak list nativeID format'
def test_cv_query(self):
with MzML(self.path) as handle:
scan = next(handle)
index = aux.cvquery(scan)
self.assertEqual(index['MS:1000511'], 1)
self.assertEqual(aux.cvquery(scan, "MS:1000511"), 1)
# test deep traversal
self.assertEqual(index['MS:1000016'], 0.004935)
self.assertEqual(aux.cvquery(scan, 'MS:1000016'), 0.004935)
def format_tolerance(self, tol, tp):
if not tol:
return None
term_dict = cvquery(tol)
value = term_dict.get('MS:1001413')
low = {
"accession": 'MS:1001413',
"value": value,
'unit_name': getattr(value, 'unit_info', None)
}
value = term_dict.get('MS:1001412')
high = {
"accession": 'MS:1001412',
"value": value,
'unit_name': getattr(value, 'unit_info', None)
}
return tp(low, high)
def format_search_modification(self, mod):
temp = dict(mod)
d = dict()
d['fixed'] = temp.pop("fixedMod", False)
d['mass_delta'] = temp.pop("massDelta")
d['specificity'] = temp.pop('SpecificityRules', [])
d['residues'] = temp.pop("residues")
term_dict = cvquery(temp)
crosslinking_donor_or_receiver = None
has_identity = False
params = []
d['params'] = params
for key, value in list(term_dict.items()):
term = self.writer.term(key)
if term.is_of_type('UNIMOD:0'):
d['name'] = term.name
has_identity = True
term_dict.pop(key)
elif term.is_of_type("MS:1001460"):
d['name'] = value
d['accession'] = "MS:1001460"
term_dict.pop(key)
has_identity = True
# crosslinking donor
elif term.is_of_type("MS:1002508"):
crosslinking_donor_or_receiver = {
"name": term.name,
'accession': term.id,
'value': int(value)
}
term_dict.pop(key)
elif term.is_of_type("XLMOD:00001") or term.is_of_type(
"XLMOD:00002"):
d['name'] = term.name
has_identity = True
term_dict.pop(key)
if not has_identity and crosslinking_donor_or_receiver:
d.update(crosslinking_donor_or_receiver)
elif crosslinking_donor_or_receiver:
params.append(crosslinking_donor_or_receiver)
# return d
return self.writer.SearchModification.ensure(d)
def format_modification(self, mod):
temp = dict(mod)
d = dict()
d['location'] = temp.pop("location", None)
d['monoisotopic_mass_delta'] = temp.pop("monoisotopicMassDelta", None)
d['avg_mass_delta'] = temp.pop("avgMassDelta", None)
d['residues'] = temp.pop("residues", None)
term_dict = cvquery(temp)
crosslinking_donor_or_receiver = None
has_identity = False
params = []
d['params'] = params
for key, value in list(term_dict.items()):
term = self.writer.term(key)
if term.is_of_type('UNIMOD:0'):
d['name'] = term.name
has_identity = True
term_dict.pop(key)
elif term.is_of_type("MS:1001460"):
d['name'] = value
d['accession'] = "MS:1001460"
term_dict.pop(key)
has_identity = True
# crosslinking donor
elif term.is_of_type("MS:1002508"):
crosslinking_donor_or_receiver = {
"name": term.name,
'accession': term.id,
'value': int(value)
}
term_dict.pop(key)
elif term.is_of_type("XLMOD:00001") or term.is_of_type(
"XLMOD:00002"):
d['name'] = term.name
has_identity = True
term_dict.pop(key)
if not has_identity and crosslinking_donor_or_receiver:
d.update(crosslinking_donor_or_receiver)
elif crosslinking_donor_or_receiver:
params.append(crosslinking_donor_or_receiver)
return self.writer.Modification.ensure(d)
