def run(self):
pattern = PATHS['data'] + '%s.csv'
df = self.exp.get_behav_df(pattern=pattern)
agg_acc = stats.accuracy(df,
cols='context',
values='accuracy',
yerr='subjid',
order='sorted')
agg_rt = stats.aggregate(df[df.accuracy == 'correct'],
cols='context',
values='rt',
yerr='subjid',
order='sorted')
plt = plot.Plot(ncols=2)
if len(df.subjid.unique()) == 1:
kind = 'bar'
else:
kind = 'bean'
plt.plot(agg_acc, kind=kind, title='accuracy', ylabel='% correct')
plt.plot(agg_rt, kind=kind, title='response time', ylabel='seconds')
print agg_acc
print agg_rt
plt.show()
def test(self):
"""Analysis of the test phase data
"""
pattern = self.paths['data'] + '%s_test.csv'
df = exp.get_behav_df(self.info['subjid'], pattern=pattern)
agg_acc = stats.accuracy(df, rows='session', cols='pos',
values='accuracy', yerr='subjid')
plt = plot.Plot()
plt.plot(agg_acc)
plt.show()
def test(self):
"""Analysis of the test phase data (for 2AFC task)
"""
pattern = self.paths['data'] + '%s_test.csv'
df = exp.get_behav_df(self.info['subjid'], pattern=pattern)
agg_acc = stats.accuracy(df,
rows='session',
cols='pos',
values='accuracy',
yerr='subjid')
plt = plot.Plot()
plt.plot(agg_acc)
plt.show()
def train(self):
pattern = self.paths['data'] + '%s_train.csv'
df = exp.get_behav_df(self.info['subjid'], pattern=pattern)
dfs = []
for session in df.session.unique():
sdf = df[df.session == session]
dfs.append(self._train_acc(sdf))
df = pandas.concat(dfs)
agg_acc = stats.accuracy(df,
cols='session',
values='accuracy',
yerr='subjid',
incorrect='miss')
self.plot(agg_acc)
def run(self):
pattern = PATHS['data'] + '%s.csv'
df = self.exp.get_behav_df(pattern=pattern)
agg_acc = stats.accuracy(df, cols='context', values='accuracy',
yerr='subjid', order='sorted')
agg_rt = stats.aggregate(df[df.accuracy=='correct'], cols='context',
values='rt', yerr='subjid', order='sorted')
plt = plot.Plot(ncols=2)
if len(df.subjid.unique()) == 1:
kind = 'bar'
else:
kind = 'bean'
plt.plot(agg_acc, kind=kind, title='accuracy', ylabel='% correct')
plt.plot(agg_rt, kind=kind, title='response time', ylabel='seconds')
print agg_acc
print agg_rt
plt.show()
