def cal_table(file_number, mammo_breast):
import helper_function.pccm_names as pccm_names
table = "calcification_mammography"
mass_number = gf.get_number_lt(1, 3)
try:
number_calc = int(mass_number)
except ValueError:
number_calc = 1
location, calc_type, calicification_comments = [list([]) for _ in range(3)]
for index in range(0, number_calc):
mass_id = index + 1
if mammo_breast == "Bilateral":
mass_location = gf.get_choice(["Right Breast", "Left Breast"])
else:
mass_location = mammo_breast
location.append(mass_location)
mammo_calcification = gf.get_choice([
"Skin", "Vascular", "Coarse or 'Popcorn-like'", "Large Rod-like",
"Round and punctate", "Eggshell or Rim", "Dystrophic", "Suture",
"Amorphous", "Coarse Heterogeneous", "Fine Pleomorphic",
"Fine Linear or Fine Linear Branching", "Other"
])
calc_type.append(mammo_calcification)
mass_id = "Group " + str(index + 1)
comment = 'na'
calicification_comments.append(comment)
data_list = [
file_number, mass_id,
str(mass_location), mammo_calcification, comment
]
col_list = pccm_names.names_radio_mass(table)
all_data = [[str(mass_number)], location, calc_type,
calicification_comments]
data_return = ask.join_lists(all_data, "; ")
return tuple(data_return)
class TestRadiology(TestCase):
def __init__(self, table, col_list):
super().__init__()
self.table = table
self.col_list = col_list
def test_function(self):
with mock.patch.object(__builtins__, 'input', lambda: 'some_input'):
assert module == 'expected_output'
if __name__ == "__main__":
import helper_function.pccm_names as pccm_names
table = 'mammography'
col_list = pccm_names.names_radio_mass(table)
# execute only if run as a script
masscalc = MassCalcification(table,
mammo_breast='right_breast',
file_number='test',
user_name='dk')
masscalc.mammo_mass('1')
masscalc.multiple_mass()
TestCase.assertIs(self)
pass
def __init__(self, table, mammo_breast, file_number, user_name):
self.table = table
self.mammo_breast = mammo_breast
self.col_list = pccm_names.names_radio_mass(self.table)
self.file_number = file_number
self.user_name = user_name
def cal_table(file_number, mammo_breast):
import helper_function.pccm_names as pccm_names
table = "calcification_mammography"
mass_number = ask.check_number_input("Number of groups of calcifications"
" detected? ", error='Please enter'
'number of calcification groups'
'detected only')
try:
number_calc = int(mass_number)
except ValueError:
number_calc = 1
location, calc_type, calicification_comments = [list([]) for _ in range(3)]
for index in range(0, number_calc):
check = False
while not check:
mass_id = index + 1
if mammo_breast == "Bilateral":
mass_location = ask.ask_option("Location of calcification"
"group " + str(mass_id),
["Right Breast", "Left Breast"])
else:
mass_location = mammo_breast
location.append(mass_location)
mammo_calcification = ask.ask_option("Calcification Type ",
["Skin", "Vascular",
"Coarse or 'Popcorn-like'",
"Large Rod-like",
"Round and punctate",
"Eggshell or Rim",
"Dystrophic", "Suture",
"Amorphous",
"Coarse Heterogeneous",
"Fine Pleomorphic",
"Fine Linear or"
"Fine Linear Branching",
"Other"])
calc_type.append(mammo_calcification)
mass_id = "Group " + str(index + 1)
comment = input('Additional comments for calcification: ')
calicification_comments.append(comment)
data_list = [file_number, mass_id, str(mass_location),
mammo_calcification, comment]
col_list = pccm_names.names_radio_mass(table)
check = sql.review_input(file_number, col_list, data_list)
all_data = [[str(mass_number)], location, calc_type,
calicification_comments]
data_return = ask.join_lists(all_data, "; ")
return tuple(data_return)
@staticmethod
def lesion_size():
mass_size = ask.check_size_input("Mass dimensions (without unit): ")
mass_size_unit = 'NA'
if mass_size != 'NA':
mass_size_unit = ask.ask_list("Mass dimensions unit: ",
RadioTables.mass_units)
mass_name = "lesion_" + str(mass_id)
mass_dimension, mass_longest_dimension = mass_size
mass_longest_dimension = ask.convert_mm_to_cm(
mass_longest_dimension, mass_size_unit)
return mass_size, mass_size_unit, mass_longest_dimension