def generate_param_config(ticks, isindex, look_back, num_features, start_date,
data_source):
ins = GetPriceData(sid=ticks, index=isindex, data_source=data_source)
data = ins.batch_get_n_days_backward(start_date, look_back)
data = [(tick, dta.drop(['tick'], axis=1)) for tick, dta in
data.groupby(['tick'])]
proc = partial(generate_features_and_labels, ta_factors=const.ta_factors,
predict_type='next_day')
ret = [proc(dta) for dta in data]
ret2 = get_best_features(ret[0], num_features)
params = batch_find_best_params(ret2)
if not isinstance(params, list):
params = [params]
df = pd.DataFrame(params)
return df
