code stringlengths 3 6.57k |
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fit(cls, *args, **kwargs) |
dict() |
isinstance(scheduler_options, dict) |
isinstance(search_strategy, str) |
dict() |
copy.copy(scheduler_options) |
searcher_for_hyperband_strategy.get(search_strategy) |
dict() |
isinstance(scheduler_options, dict) |
copy.copy(scheduler_options) |
isinstance(search_strategy, str) |
dict() |
update(scheduler_options['resource']) |
copy() |
scheduler_params.update(scheduler_options) |
searcher_for_hyperband_strategy.get(scheduler_params['searcher']) |
missing_options.append(option) |
AssertionError(f'Missing required keys in scheduler_options: {missing_options}') |
load_pheno_file(pheno_file) |
os.path.isfile(pheno_file) |
Exception(err) |
open(os.path.abspath(pheno_file) |
pd.read_csv(f) |
load_group_participant_list(group_participant_list_file) |
os.path.isfile(group_participant_list_file) |
Exception(err) |
open(group_participant_list_file,"r") |
pd.read_csv(f) |
Exception(err) |
isinstance(pheno_file_dataframe, pd.DataFrame) |
Exception(err) |
isinstance(group_subs_dataframe, pd.DataFrame) |
Exception(err) |
isinstance(participant_id_label, str) |
list(group_subs_dataframe.participant) |
str(i) |
list(group_subs_dataframe.session) |
str(i) |
list(group_subs_dataframe.series) |
str(i) |
range(0,len(subjects) |
full_id.append(subject) |
full_id.append(session) |
full_id.append(scan) |
int(subject) |
full_id.append(session) |
int(subject) |
full_id.append(scan) |
int(subject) |
full_id.append(subject) |
int(subject) |
len(row) |
str(full_id) |
Exception(err) |
len(row) |
df_rows.append(row) |
pd.concat(df_rows) |
new_pheno_df.to_dict("records") |
create_pheno_dict(pheno_file_rows, ev_selections, participant_id_label) |
line.values() |
line.keys() |
CSV (such as ",,,,,") |
len(line[key]) |
pheno_data_dict.keys() |
ev_selections.keys() |
append(key + str(line[key]) |
elif (key == subject_id_label) |
or (key == "session") |
append(line[key]) |
append(float(line[key]) |
elif (key == subject_id_label) |
or (key == "session") |
append(line[key]) |
append(float(line[key]) |
pheno_data_dict.keys() |
ev_selections.keys() |
float(val) |
len(pheno_data_dict[key]) |
new_demeaned_evs.append(float(val) |
ev_selections.keys() |
np.array(pheno_data_dict[key]) |
get_measure_dict(param_file) |
os.path.isfile(param_file) |
Exception(err) |
open(param_file,"r") |
pd.read_csv(f, index_col=False) |
list(motion_params["Subject"]) |
str(i) |
list(motion_params["Scan"]) |
str(i) |
list(motion_params[m]) |
float(i) |
zip(part_ids, scan_ids, measure_vals) |
get_custom_roi_info(roi_means_dict) |
Exception(err_string) |
len(roi_means_dict.values() |
range(0,roi_num) |
int(num+1) |
roi_means_dict.keys() |
ev_selections.keys() |
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