def anal_kR2(self, dataset, key='valid', steps=10):
"""
Compute the k-steps ahead R2 between the data produced by the Generative
Model and the Observations
"""
zpath = self.eval(dataset, 'Recognition:loc', key=key)
dataset[key + '_StateSeq'] = zpath
zpath = self.eval(dataset, 'Posterior:loc', key=key)
dataset[key + '_StateSeq'] = zpath
zpath = self.eval(dataset, 'Posterior:loc', key=key)
dataset[key + '_StateSeq'] = zpath
zpath = self.eval(dataset, 'Posterior:loc', key=key)
dataset[key + '_StateSeq'] = zpath
kR2 = np.zeros(10)
obs = dataset[key + '_Observation']
preds = self.eval(dataset, 'Generative:prediction', key=key)
R2 = compute_R2_from_sequences(obs[:, :], preds[:, :])
kR2[0] = R2
for k in range(1, steps):
preds = self.eval(dataset, 'Generative:prediction', key=key)
R2 = compute_R2_from_sequences(obs[:, k:], preds[:, k:])
zpath = self.eval(dataset, 'LLDS:loc', key=key)
dataset[key + '_StateSeq'] = zpath
kR2[k] = R2
return kR2
def anal_R2(self, dataset, subdset='valid', axis=None):
"""
"""
data = dataset[subdset + '_' + 'Observation_0']
preds = self.eval('Generative:loc', dataset,
key=subdset)[0] # eval returns a list
R2 = compute_R2_from_sequences(data, preds, axis=axis)
return R2
def anal_R2(self, dataset, key='valid'):
"""
Compute the R2 between the data produced by the Generative Model and the
Observations
"""
obs = dataset[key + '_Observation']
preds = self.eval(dataset, 'Generative:loc', key='valid')
R2 = compute_R2_from_sequences(obs, preds)
return R2