def test_extract_sart_blocks_with_4_practice_and_survey():
df = get_csv_as_df('experiment', '104')
blocks = compile_data.extract_sart_blocks(df, with_survey=True)
# basic structure
assert len(blocks) == 8
for b in blocks:
assert isinstance(b, compile_data.pd.DataFrame)
# number of trials
assert len(blocks[0].index.values) == 84
assert len(blocks[1].index.values) == 84
assert len(blocks[2].index.values) == 84
assert len(blocks[3].index.values) == 84
assert len(blocks[4].index.values) == 84
assert len(blocks[5].index.values) == 84
assert len(blocks[6].index.values) == 84
assert len(blocks[7].index.values) == 74
# trial structure
trial_type_mc = 'survey-multi-choice'
trial_type_msmr = 'multi-stim-multi-response'
b7 = blocks[7]
b7_last_idx = b7.last_valid_index()
b7_first_idx = b7.first_valid_index()
assert b7.ix[b7_first_idx]['trial_type'] == trial_type_msmr
assert b7.ix[b7_last_idx-1]['trial_type'] == trial_type_mc
assert b7.ix[b7_last_idx]['trial_type'] == trial_type_mc
def test_summarize_sart_chunk():
pid = "011"
df = get_csv_as_df('experiment', pid)
blocks = compile_data.extract_sart_blocks(df, with_survey=True)
# first block
b1 = blocks[0]
b1s = compile_data.summarize_sart_chunk(b1)
assert b1s['anticipated'] == 0.0
assert b1s['accuracy'] == 0.731707317
assert b1s['effort'] == 4
assert b1s['discomfort'] == 5
assert b1s['ratings_time_min'] == 26.783333333
assert b1s['num_trials'] == 82
assert b1s['nogo_prev4_avg'] == 381.444444444
assert b1s['nogo_next4_avg'] == 391.875
# last block
lb = blocks[-1]
lbs = compile_data.summarize_sart_chunk(lb)
assert lbs['num_trials'] == 68
assert lbs['anticipated'] == 0.014705882
assert lbs['accuracy'] == 0.911764706
assert lbs['effort'] == 3
assert lbs['discomfort'] == 5
assert lbs['ratings_time_min'] == 37.7
def test_extract_sart_blocks_with_2_practice():
# NOTE: tests out get_csv_as_dataframe() from compile_data
csv_path = _csv_path('practice', '003')
df = compile_data.get_csv_as_dataframe(csv_path)
blocks = compile_data.extract_sart_blocks(df)
assert len(blocks) == 2
for b in blocks:
assert isinstance(b, compile_data.pd.DataFrame)
# number of trials
assert len(blocks[0].index.values) == 5
assert len(blocks[1].index.values) == 15
def test_extract_sart_blocks_with_4_practice():
df = get_csv_as_df('practice', 'fail1')
blocks = compile_data.extract_sart_blocks(df)
assert len(blocks) == 4
# number of trials
assert len(blocks[0].index.values) == 29
assert len(blocks[1].index.values) == 72
assert len(blocks[2].index.values) == 72
assert len(blocks[3].index.values) == 72
for b in blocks:
# class
assert isinstance(b, compile_data.pd.DataFrame)
# trials
for idx, series in b.iterrows():
series['trial_type'] == 'multi-stim-multi-response'
def get_sart_trial_block(pid, block_index=0):
df = get_csv_as_df('experiment', pid)
blocks = compile_data.extract_sart_blocks(df, with_survey=True)
b = blocks[block_index]
trial_block = b.loc[b['trial_type'] == 'multi-stim-multi-response']
return trial_block
