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