Coverage for ibllib/io/extractors/opto_trials.py: 59%

1import logging (empty)

2import numpy as np (empty)

3 

4from ibllib.io.extractors import biased_trials (empty)

5from ibllib.io.extractors.base import BaseBpodTrialsExtractor (empty)

6 

7_logger = logging.getLogger(__name__) (empty)

8 

9 

10class LaserBool(BaseBpodTrialsExtractor): (empty)

11 """ 

12 Extracts the laser probabilities from the bpod jsonable 

13 """ 

14 save_names = ('_ibl_trials.laserStimulation.npy', '_ibl_trials.laserProbability.npy') (empty)

15 var_names = ('laserStimulation', 'laserProbability') (empty)

16 

17 def _extract(self, **kwargs): (empty)

18 _logger.info('Extracting laser datasets') 3 ctx1cdb

19 # reference pybpod implementation 

20 lstim = np.array([float(t.get('laser_stimulation', np.NaN)) for t in self.bpod_trials]) 3 ctx1cdb

21 lprob = np.array([float(t.get('laser_probability', np.NaN)) for t in self.bpod_trials]) 3 ctx1cdb

22 

23 # Karolina's choice world legacy implementation - from Slack message: 

24 # it is possible that some versions I have used: 

25 # 1) opto_ON_time (NaN - no laser or some number-laser) 

26 # opto_ON_time=~isnan(opto_ON_time) 

27 # laserON_trials=(opto_ON_time==1); 

28 # laserOFF_trials=(opto_ON_time==0); 

29 # 2) optoOUT (0 - no laser or 255 - laser): 

30 # laserON_trials=(optoOUT ==255); 

31 # laserOFF_trials=(optoOUT ==0); 

32 if 'PROBABILITY_OPTO' in self.settings.keys() and np.all(np.isnan(lstim)): 3 ctx1cdb

33 lprob = np.zeros_like(lprob) + self.settings['PROBABILITY_OPTO'] 

34 lstim = np.array([float(t.get('opto_ON_time', np.NaN)) for t in self.bpod_trials]) 

35 if np.all(np.isnan(lstim)): 

36 lstim = np.array([float(t.get('optoOUT', np.NaN)) for t in self.bpod_trials]) 

37 lstim[lstim == 255] = 1 

38 else: 

39 lstim[~np.isnan(lstim)] = 1 

40 lstim[np.isnan(lstim)] = 0 

41 

42 if np.all(np.isnan(lprob)): 3 ctx1cdb

43 # this prevents the file from being saved when no data 

44 self.save_names = ('_ibl_trials.laserStimulation.npy', None) 1 ctx1b

45 _logger.warning('No laser probability found in bpod data') 1 ctx1b

46 if np.all(np.isnan(lstim)): 3 ctx1cdb

47 # this prevents the file from being saved when no data 

48 self.save_names = (None, '_ibl_trials.laserProbability.npy') 

49 _logger.warning('No laser stimulation found in bpod data') 

50 return lstim, lprob 3 ctx1cdb

51 

52 

53def extract_all(*args, extra_classes=None, **kwargs): (empty)

54 """ 

55 Extracts the biased trials for a training session 

56 """ 

57 if extra_classes is not None: 

58 extra_classes.append(LaserBool) 

59 else: 

60 extra_classes = [LaserBool] 

61 return biased_trials.extract_all(*args, **kwargs, extra_classes=extra_classes)