In [2]: %run classif_cosp.py
cosp classif_
rare theta
(10395, 41, 41)
Classification...
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
~/pCloudDrive/science/sfanx/scripts/classif_cosp.py in <module>
     91     TIMELAPSE_START = time()
     92     for freq, conds in product(FREQ_DICT, COND_GROUPS):
---> 93         main(conds, freq)
     94     print("total time lapsed : %s" % elapsed_time(TIMELAPSE_START, time()))

~/pCloudDrive/science/sfanx/scripts/classif_cosp.py in main(conds, freq)
     74         #     clf, crossval, data, labels, groups, N_PERM, n_jobs=1
     75         # )
---> 76         perm_result = cross_val_score(clf, X=data, y=labels, groups=groups, cv=crossval, n_jobs=1)
     77
     78         print(save["acc_score"])

~/electrophy/lib/python3.6/site-packages/sklearn/model_selection/_validation.py in cross_val_score(estimator, X, y, groups, scoring, cv, n_jobs, verbose, fit_params, pre_dispatch, error_score)
    400                                 fit_params=fit_params,
    401                                 pre_dispatch=pre_dispatch,
--> 402                                 error_score=error_score)
    403     return cv_results['test_score']
    404

~/electrophy/lib/python3.6/site-packages/sklearn/model_selection/_validation.py in cross_validate(estimator, X, y, groups, scoring, cv, n_jobs, verbose, fit_params, pre_dispatch, return_train_score, return_estimator, error_score)
    246     if return_estimator:
    247         fitted_estimators = zipped_scores.pop()
--> 248     test_scores, fit_times, score_times = zipped_scores
    249     test_scores = _aggregate_score_dicts(test_scores)
    250

ValueError: not enough values to unpack (expected 3, got 0)