Found array with 0 sample(s) (shape=(0,)) while a minimum of 1 is required

一个数据放进去跑没问题，另一组数据放进去跑就报这个错误，是我这组数据有问题吗
（这两组数据的处理方式是一样的

```
initial training of underlying models...
CV.. 1/10

ValueError Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_21088/761714535.py in
1 model_sq = SurvivalQuilts()
----> 2 model_sq.train(tr_X, tr_T, tr_Y)

D:\修改后的survivalquilts\SurvivalQuilts-master\class_SurvivalQuilts.py in train(self, X, T, Y)
55 for cv_idx in range(self.num_cv):
56 print('CV.. {}/{}'.format(cv_idx+1, self.num_cv))
---> 57 pulled_models, tmp_CINDEX, tmp_BRIER = self._get_models_pulled_CV(X, T, Y, seed=cv_idx)
58
59 metric_CINDEX[cv_idx,:,:] = tmp_CINDEX

D:\修改后的survivalquilts\SurvivalQuilts-master\class_SurvivalQuilts.py in _get_models_pulled_CV(self, X, T, Y, seed)
290
291 for t, eval_time in enumerate(self.time_horizons):
--> 292 tmp_C, tmp_B = calc_metrics(T_tr, Y_tr, T_va, Y_va, pred[:, t], eval_time)
293 metric_CINDEX[m, t] = tmp_C
294 metric_BRIER[m, t] = tmp_B

D:\修改后的survivalquilts\SurvivalQuilts-master\utils_eval.py in calc_metrics(tr_t_, tr_y_, te_t_, te_y_, preds, eval_time)
50 test_y_ = np.array(test_y_, dtype=[('status', 'bool'),('time','<f8')])
51
---> 52 c_index, , , , _ = concordance_index_ipcw(train_y, test_y, preds, int(eval_time))
53 brier_score = weighted_brier_score(np.asarray(tr_t), np.asarray(tr_y_), preds,
54 np.asarray(te_t_), np.asarray(te_y_), int(eval_time))

D:\ProgramData\Anaconda3\lib\site-packages\sksurv\metrics.py in concordance_index_ipcw(survival_train, survival_test, estimate, tau, tied_tol)
326 cens = CensoringDistributionEstimator()
327 cens.fit(survival_train)
--> 328 ipcw_test = cens.predict_ipcw(survival_test)
329 if tau is None:
330 ipcw = ipcw_test

D:\ProgramData\Anaconda3\lib\site-packages\sksurv\nonparametric.py in predict_ipcw(self, y)
442 Inverse probability of censoring weights.
443 """
--> 444 event, time = check_y_survival(y)
445 Ghat = self.predict_proba(time[event])
446

D:\ProgramData\Anaconda3\lib\site-packages\sksurv\util.py in check_y_survival(y_or_event, allow_all_censored, *args)
142 time_args = args
143
--> 144 event = check_array(y_event, ensure_2d=False)
145 if not numpy.issubdtype(event.dtype, numpy.bool_):
146 raise ValueError('elements of event indicator must be boolean, but found {0}'.format(event.dtype))

D:\ProgramData\Anaconda3\lib\site-packages\sklearn\utils\validation.py in inner_f(*args, **kwargs)
61 extra_args = len(args) - len(all_args)
62 if extra_args <= 0:
---> 63 return f(*args, **kwargs)
64
65 # extra_args > 0

D:\ProgramData\Anaconda3\lib\site-packages\sklearn\utils\validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator)
724 n_samples = _num_samples(array)
725 if n_samples < ensure_min_samples:
--> 726 raise ValueError("Found array with %d sample(s) (shape=%s) while a"
727 " minimum of %d is required%s."
728 % (n_samples, array.shape, ensure_min_samples,

ValueError: Found array with 0 sample(s) (shape=(0,)) while a minimum of 1 is required.

```）