def test_complete_demographics_data():
pid = "003"
df = get_csv_as_df('follow_up', pid)
data = compile_data.compile_demographic_data(df)
expected_answers = [
('age', '22'),
('dob', '03/1993'),
('sex', 'Female'),
('edu_year', 'Graduated'),
('edu_plan', 'PhD'),
('eng_first_lang', 'Yes'),
('eng_years', 'All my life'),
('mother_edu', 'Professional degree (e.g., law)'),
('mother_job', 'lawyer'),
('father_edu', 'MA/MSc degree'),
('father_job', 'computer scientist'),
('high_school_avg', '90'),
('uni_avg', 'n/a'),
('num_uni_stats', '1'),
('num_hs_stats', 'None'),
('num_hs_math', '4'),
('num_uni_math', 'None'),
('math_enjoy', '5'),
('adhd_diag', 'Yes'),
('uni_major', 'n/a'),
('elect_survey_1', 'No'),
('elect_survey_2', 'Yes'),
('elect_survey_3', 'Yes'),
('elect_survey_4', 'Yes'),
('elect_survey_5', 'Yes'),
('elect_survey_6', 'Yes'),
('elect_survey_7', '1'),
('behav_survey_1', 'N/A'),
('behav_survey_2', 'N/A'),
('behav_survey_3', '2'),
('behav_survey_4', 'N/A'),
('behav_survey_5', '2'),
('behav_survey_6', 'N/A'),
('behav_survey_7', 'N/A'),
('behav_survey_8', 'N/A'),
('behav_survey_9', 'N/A'),
('behav_survey_10', 'N/A'),
('behav_survey_11', 'N/A'),
('behav_survey_12', 'N/A'),
('behav_survey_13', 'N/A'),
('behav_survey_14', 'N/A'),
('behav_survey_15', 'N/A'),
('behav_survey_16', 'N/A'),
('behav_survey_17', 'N/A'),
('behav_survey_18', 'N/A'),
('time_delay_b4_retrospect_ms', 196373),
('time_follow_up_ms', 220848),
]
for label, answer in expected_answers:
assert data[label] == answer
def test_complete_demographics_data():
df = get_csv_as_df('follow_up', 1)
data = compile_data.compile_demographic_data(df)
expected_answers = [
('age', '20'),
('dob', '01/1995'),
('sex', 'Male'),
('edu_year', 'Graduated'),
('edu_plan', 'PhD'),
('first_lang', 'Yes'),
('years_eng', 'All my life'),
('mother_edu', 'Professional degree (e.g., law)'),
('mother_job', 'lawyer'),
('father_edu', 'MA/MSc degree'),
('father_job', 'computer scientist'),
('high_school_avg', '85'),
('uni_avg', '85'),
('num_uni_stats', '1'),
('num_hs_stats', 'None'),
('num_hs_math', '4'),
('num_uni_math', 'None'),
('math_enjoy', '4'),
('adhd_diag', 'Yes'),
('uni_major', 'psych'),
('elect_survey_1', 'No'),
('elect_survey_2', 'No'),
('elect_survey_3', 'No'),
('elect_survey_4', 'No'),
('elect_survey_5', 'No'),
('elect_survey_6', 'No'),
('elect_survey_7', '0'),
('behav_survey_1', 'N/A'),
('behav_survey_2', 'N/A'),
('behav_survey_3', '3'),
('behav_survey_4', '2'),
('behav_survey_5', '1'),
('behav_survey_6', '0'),
('behav_survey_7', 'N/A'),
('behav_survey_8', '3'),
('behav_survey_9', '2'),
('behav_survey_10', '1'),
('behav_survey_11', '0'),
('behav_survey_12', 'N/A'),
('behav_survey_13', '3'),
('behav_survey_14', '2'),
('behav_survey_15', '1'),
('behav_survey_16', '0'),
('behav_survey_17', 'N/A'),
('behav_survey_18', '3'),
('time_pwmt_delay_ms', 205396),
('time_follow_up_ms', 223823),
]
for label, answer in expected_answers:
assert data[label] == answer
