def pick_trial_numbers(trials_info, outcome='hit', nonrandom=0,
isnotnull=None, **kwargs):
"""Returns trial numbers satisfying condition
This convenience method provides common defaults for me
isnotnull : asserts that the provided column is not Null
"""
return utility.panda_pick(trials_info, outcome=outcome,
nonrandom=nonrandom, isnotnull=isnotnull, **kwargs)
def pick_trial_numbers(trials_info,
outcome='hit',
nonrandom=0,
isnotnull=None,
**kwargs):
"""Returns trial numbers satisfying condition
This convenience method provides common defaults for me
isnotnull : asserts that the provided column is not Null
"""
return utility.panda_pick(trials_info,
outcome=outcome,
nonrandom=nonrandom,
isnotnull=isnotnull,
**kwargs)
def pick(self, trials_info, labels=None, label_kwargs=None,
**all_kwargs):
"""Returns list of trial numbers satisfying list of constraints.
trials_info : DataFrame containing information about each trial,
indexed by trial_number
labels : list of length N, labeling each set of constraints
label_kwargs : list of length N, consisting of kwargs to pass to
panda_pick on trials_info (the constraints)
all_kwargs : added to each label_kwarg
Returns: list of length N
Each entry is a tuple (label, val) where label is the constraint
label and val is the picked trial numbers satisfying that constraint.
Example
labels = ['LB', 'PB']
label_kwargs = [{'block':2}, {'block':4}]
all_kwargs = {'outcome':'hit'}
The return value would be:
[('LB', list_of_LB_trials), ('PB', list_of_PB_trials)]
"""
if labels is None:
labels = self.labels
if label_kwargs is None:
label_kwargs = self.label_kwargs
assert len(labels) == len(label_kwargs)
res = []
for label, kwargs in zip(labels, label_kwargs):
kk = kwargs.copy()
kk.update(all_kwargs)
val = utility.panda_pick(trials_info, **kk)
res.append((label, val))
return res
def pick(self, trials_info, labels=None, label_kwargs=None, **all_kwargs):
"""Returns list of trial numbers satisfying list of constraints.
trials_info : DataFrame containing information about each trial,
indexed by trial_number
labels : list of length N, labeling each set of constraints
label_kwargs : list of length N, consisting of kwargs to pass to
panda_pick on trials_info (the constraints)
all_kwargs : added to each label_kwarg
Returns: list of length N
Each entry is a tuple (label, val) where label is the constraint
label and val is the picked trial numbers satisfying that constraint.
Example
labels = ['LB', 'PB']
label_kwargs = [{'block':2}, {'block':4}]
all_kwargs = {'outcome':'hit'}
The return value would be:
[('LB', list_of_LB_trials), ('PB', list_of_PB_trials)]
"""
if labels is None:
labels = self.labels
if label_kwargs is None:
label_kwargs = self.label_kwargs
assert len(labels) == len(label_kwargs)
res = []
for label, kwargs in zip(labels, label_kwargs):
kk = kwargs.copy()
kk.update(all_kwargs)
val = utility.panda_pick(trials_info, **kk)
res.append((label, val))
return res
