def mint_guid(name, birth_date=None, age=None, reference_date=None, sex="U"):
mint = GUIDMint()
sham = mint.get_sham_id(name=name,
dob=birth_date,
age=age,
reference_date=reference_date,
gender=sex)
resp = {
"name": dicom_name(sham['Name']),
"birth_date": dicom_date(sham["BirthDate"]),
"id": sham["ID"],
"time_offset": sham["TimeOffset"]
}
return resp
def test_guids():
M = GUIDMint()
expected = {
'ID': 'JGHVCZSDBOFIA2QZ4H6EI43K4HAPB3IM',
'Name': ['JACKSITS', 'GENE', 'H'],
'BirthDate': datetime.date(2007, 10, 8),
'TimeOffset': datetime.timedelta(-86, 3040)
}
# expected = ('JGHVCZSDBOFIA2QZ4H6EI43K4HAPB3IM', 'JAMESON^GRAHAM^H', '20080209')
s = "FOO^BAR^Z^^"
age = 10
reference_date = "2018-01-01"
out = M.get_sham_id(name=s, age=age, reference_date=reference_date)
logging.debug(out)
assert (out == expected)
s = "Foo, Bar Z"
age = 10
reference_date = "1/1/2018"
out = M.get_sham_id(name=s, age=age, reference_date=reference_date)
logging.debug(out)
s = "Bar Z Foo"
age = 10
reference_date = "January 1, 2018"
out = M.get_sham_id(name=s, age=age, reference_date=reference_date)
logging.debug(out)
assert (out == expected)
def guid(ctx, name, dob, gender, age, reference_date):
"""Generate a globally unique sham ID from NAME, DOB, and GENDER."""
click.echo(click.style('Generating GUID', underline=True, bold=True))
sham = GUIDMint.get_sham_id(name=name, dob=dob, gender=gender,
age=age, reference_date=reference_date)
resp = {
"name": dicom_name(sham['Name']),
"birth_date": dicom_date(sham["BirthDate"]),
"id": sham["ID"],
"time_offset": sham["TimeOffset"].__str__()
}
click.echo(pformat(resp))
def test_guid_genders():
M = GUIDMint()
expected = {
'ID': 'WHLOKMAGICLQGYKC3ZQLLMFKMOX3ZAP2',
'Name': ['WAGENAAR', 'HERIBERTO', 'L'],
'BirthDate': datetime.date(1999, 10, 8),
'TimeOffset': datetime.timedelta(-86, 85464)
}
s = "Bar Z Foo"
dob = "2000-01-01"
out = M.get_sham_id(name=s, dob=dob)
assert (out == expected)
out = M.get_sham_id(name=s, dob=dob, gender="U")
assert (out == expected)
out = M.get_sham_id(name=s, dob=dob, gender="u")
assert (out == expected)
out = M.get_sham_id(name=s, dob=dob, gender="UNKNOWN")
assert (out == expected)
out = M.get_sham_id(name=s, dob=dob, gender="unknown")
assert (out == expected)
out = M.get_sham_id(name=s, dob=dob, gender="")
assert (out == expected)
out = M.get_sham_id(name=s, dob=dob, gender="ABCD")
assert (out == expected)
expected = {
'BirthDate': datetime.date(2000, 2, 19),
'ID': 'HNG54O6PWWEIVTTQCYCVIYBENW4RK64G',
'Name': ['HOWDESHELL', 'NELSON', 'G'],
'TimeOffset': datetime.timedelta(48, 84883)
}
out = M.get_sham_id(name=s, dob=dob, gender="M")
assert (out == expected)
out = M.get_sham_id(name=s, dob=dob, gender="male")
assert (out == expected)
expected = {
'BirthDate': datetime.date(1999, 10, 19),
'ID': 'SIDYPTGPM27TDCMQOPSXFOAXECXJGOZZ',
'Name': ['SARSON', 'IRENA', 'D'],
'TimeOffset': datetime.timedelta(-74, 1033)
}
out = M.get_sham_id(name=s, dob=dob, gender="F")
assert (out == expected)
out = M.get_sham_id(name=s, dob=dob, gender="female")
assert (out == expected)
def __attrs_post_init__(self):
name_seed = _R.random()
gender = _R.choice(["M", "F"])
age = _R.randint(18, 85)
# logging.debug(name_seed)
# logging.debug(gender)
# logging.debug(age)
patient_info = GUIDMint.get_sham_id(name=name_seed,
age=age,
gender=gender,
reference_date=self.study_datetime)
hash_str = patient_info["ID"] + self.study_datetime.isoformat()
accession_num = md5(hash_str.encode("UTF-8")).hexdigest()
self.stuid = dcm_mint.uid(patient_info["ID"], accession_num)
self.meta = {"StudyDateTime": self.study_datetime}
self.tags = {
"AccessionNumber": accession_num,
"PatientName": dicom_name(patient_info["Name"]),
"PatientID": patient_info["ID"],
"PatientSex": gender,
"PatientBirthDate": dicom_date(patient_info["BirthDate"]),
"StudyInstanceUID": self.stuid,
"StudyDescription": self.study_description,
"StationName": self.station_name,
"Manufacturer": "Device Manufacturer",
"ManufacturerModelName": "Device Model Name",
"Institution": self.site_name,
"Modality": self.modality,
"StudyDate": dicom_date(self.study_datetime),
"StudyTime": dicom_time(self.study_datetime)
}
distribution = {
# Mod SeriesDesc NSer NInst P of at least one
"CT": [("Localizer", 2, 2, 1, 1), ("Volume", 1, 3, 30, 200),
("Fluoro", 0, 1, 10, 50, 0.2),
("Reformat", 0, 2, 100, 200, 0.2),
("Dose Report", 1, 1, 1, 1)],
"MR": [("Localizer", 1, 3, 1, 1), ("Sequence", 3, 6, 10, 50),
("Diffusion Map", 0, 1, 1, 1, 0.2)],
"CR": [("PA", 1, 1, 1, 1), ("Lateral", 1, 1, 1, 1),
("Bx", 0, 1, 1, 2, 0.2)],
"US": [("Transverse", 3, 6, 1, 1), ("Sagittal", 3, 6, 1, 1),
("Cine", 1, 3, 30, 50), ("Doppler", 0, 3, 1, 3, 0.2),
("Bx", 0, 2, 3, 5, 0.2)]
}
series_defs = distribution[self.modality]
ser_num = 0
for s in series_defs:
if s[0] == 0:
if _R.random() < s[5]:
num_series_this_type = 1
else:
num_series_this_type = 0
else:
num_series_this_type = _R.randint(s[1], s[2])
for i in range(1, num_series_this_type + 1):
ser_num += 1
if num_series_this_type > 1:
ser_desc = "{} {}".format(s[0], i)
else:
ser_desc = s[0]
n_instances = _R.randint(s[3], s[4])
S = MockSeries(parent=self,
ser_num=ser_num,
ser_desc=ser_desc,
n_instances=n_instances)
self.children.append(S)