---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-5-608b6c0006b7> in <module>()
      1 run = 16808
----> 2 hax.minitrees.load(run, treemakers=treemakers)

/project/lgrandi/anaconda3/envs/pax_v6.10.1/lib/python3.4/site-packages/hax-2.5.0-py3.4.egg/hax/minitrees.py in load(datasets, treemakers, preselection, force_reload, delayed, num_workers, compute_options, cache_file, remake_cache, event_list)
    531     df_example, _ = load_single_dataset(
    532         first_dset,
--> 533         treemakers, preselection, force_reload=force_reload, event_list=event_list)
    534
    535     partial_results = []

/project/lgrandi/anaconda3/envs/pax_v6.10.1/lib/python3.4/site-packages/hax-2.5.0-py3.4.egg/hax/minitrees.py in load_single_dataset(run_id, treemakers, preselection, force_reload, event_list, bypass_blinding)
    390         try:
    391             dataset_frame = load_single_minitree(
--> 392                 run_id, treemaker, force_reload=force_reload, event_list=event_list)
    393         except NoMinitreeAvailable as e:
    394             log.debug(str(e))

/project/lgrandi/anaconda3/envs/pax_v6.10.1/lib/python3.4/site-packages/hax-2.5.0-py3.4.egg/hax/minitrees.py in load_single_minitree(run_id, treemaker, force_reload, return_metadata, save_file, event_list)
    331     # We have to make the minitree file
    332     # This will raise FileNotFoundError if the root file is not found
--> 333     skimmed_data = treemaker().get_data(run_id, event_list=event_list)
    334
    335     log.debug(

/project/lgrandi/anaconda3/envs/pax_v6.10.1/lib/python3.4/site-packages/hax-2.5.0-py3.4.egg/hax/treemakers/pattern.py in get_data(self, dataset, event_list)
     80         self.indices = list(data.event_number.values)
     81
---> 82         return hax.minitrees.TreeMaker.get_data(self, dataset, event_list)
     83
     84     def load_run_doc(self, run):

/project/lgrandi/anaconda3/envs/pax_v6.10.1/lib/python3.4/site-packages/hax-2.5.0-py3.4.egg/hax/minitrees.py in get_data(self, dataset, event_list)
     99                           event_lists=event_list,
    100                           branch_selection=self.branch_selection,
--> 101                           desc='Making %s minitree' % self.__class__.__name__)
    102         self.check_cache(force_empty=True)
    103         if not len(self.data):

/project/lgrandi/anaconda3/envs/pax_v6.10.1/lib/python3.4/site-packages/hax-2.5.0-py3.4.egg/hax/paxroot.py in loop_over_datasets(*args, **kwargs)
    163     See function_results_datasets for possible options.
    164     """
--> 165     for _ in function_results_datasets(*args, **kwargs):
    166         # do nothing with the results
    167         pass

/project/lgrandi/anaconda3/envs/pax_v6.10.1/lib/python3.4/site-packages/hax-2.5.0-py3.4.egg/hax/paxroot.py in function_results_datasets(datasets_names, event_function, event_lists, branch_selection, kwargs, desc)
    155         except Exception as e:
    156             rootfile.Close()
--> 157             raise e
    158
    159

/project/lgrandi/anaconda3/envs/pax_v6.10.1/lib/python3.4/site-packages/hax-2.5.0-py3.4.egg/hax/paxroot.py in function_results_datasets(datasets_names, event_function, event_lists, branch_selection, kwargs, desc)
    149                 t.GetEntry(event_i)
    150                 event = t.events
--> 151                 yield event_function(event, **kwargs)
    152
    153         except StopEventLoop:

/project/lgrandi/anaconda3/envs/pax_v6.10.1/lib/python3.4/site-packages/hax-2.5.0-py3.4.egg/hax/minitrees.py in process_event(self, event)
     81
     82     def process_event(self, event):
---> 83         result = self.extract_data(event)
     84         if not isinstance(result, dict):
     85             raise ValueError("TreeMakers must always extract dictionary")

/project/lgrandi/anaconda3/envs/pax_v6.10.1/lib/python3.4/site-packages/hax-2.5.0-py3.4.egg/hax/treemakers/pattern.py in extract_data(self, event)
    171             # Create PMT array of booleans for use in likelihood calculation
    172             is_pmt_in = np.ones(len(self.tpc_channels), dtype=bool)  # Default True
--> 173             is_pmt_in[confused_s1_channels] = False  # Ignore saturated channels
    174
    175             event_data['s1_pattern_fit_hax'] = self.s1_pattern_fitter.compute_gof(

IndexError: index 249 is out of bounds for axis 1 with size 248