From 3ba405eca0a8d00f222d8470dc7a850281eb5085 Mon Sep 17 00:00:00 2001
From: Scott Linderman <scott.linderman@gmail.com>
Date: Sat, 24 Sep 2016 10:04:17 -0400
Subject: [PATCH] python 3 imports
---
pyhsmm/internals/hmm_states.py | 16 ++++++++--------
pyhsmm/internals/hsmm_states.py | 6 +++---
pyhsmm/util/plot.py | 3 ++-
3 files changed, 13 insertions(+), 12 deletions(-)
diff --git a/pyhsmm/internals/hmm_states.py b/pyhsmm/internals/hmm_states.py
index 30ce024..abbf50a 100644
--- a/pyhsmm/internals/hmm_states.py
+++ b/pyhsmm/internals/hmm_states.py
@@ -605,20 +605,20 @@ class HMMStatesEigen(HMMStatesPython):
@staticmethod
def _messages_backwards_log(trans_matrix,log_likelihoods):
- from hmm_messages_interface import messages_backwards_log
+ from pyhsmm.internals.hmm_messages_interface import messages_backwards_log
return messages_backwards_log(
trans_matrix,log_likelihoods,
np.empty_like(log_likelihoods))
@staticmethod
def _messages_forwards_log(trans_matrix,init_state_distn,log_likelihoods):
- from hmm_messages_interface import messages_forwards_log
+ from pyhsmm.internals.hmm_messages_interface import messages_forwards_log
return messages_forwards_log(trans_matrix,log_likelihoods,
init_state_distn,np.empty_like(log_likelihoods))
@staticmethod
def _messages_forwards_normalized(trans_matrix,init_state_distn,log_likelihoods):
- from hmm_messages_interface import messages_forwards_normalized
+ from pyhsmm.internals.hmm_messages_interface import messages_forwards_normalized
return messages_forwards_normalized(trans_matrix,log_likelihoods,
init_state_distn,np.empty_like(log_likelihoods))
@@ -640,19 +640,19 @@ class HMMStatesEigen(HMMStatesPython):
@staticmethod
def _sample_forwards_log(betal,trans_matrix,init_state_distn,log_likelihoods):
- from hmm_messages_interface import sample_forwards_log
+ from pyhsmm.internals.hmm_messages_interface import sample_forwards_log
return sample_forwards_log(trans_matrix,log_likelihoods,
init_state_distn,betal,np.empty(log_likelihoods.shape[0],dtype='int32'))
@staticmethod
def _sample_backwards_normalized(alphan,trans_matrix_transpose):
- from hmm_messages_interface import sample_backwards_normalized
+ from pyhsmm.internals.hmm_messages_interface import sample_backwards_normalized
return sample_backwards_normalized(trans_matrix_transpose,alphan,
np.empty(alphan.shape[0],dtype='int32'))
@staticmethod
def _resample_multiple(states_list):
- from hmm_messages_interface import resample_normalized_multiple
+ from pyhsmm.internals.hmm_messages_interface import resample_normalized_multiple
if len(states_list) > 0:
loglikes = resample_normalized_multiple(
states_list[0].trans_matrix,states_list[0].pi_0,
@@ -666,7 +666,7 @@ class HMMStatesEigen(HMMStatesPython):
def _expected_statistics_from_messages(
trans_potential,likelihood_log_potential,alphal,betal,
expected_states=None,expected_transcounts=None):
- from hmm_messages_interface import expected_statistics_log
+ from pyhsmm.internals.hmm_messages_interface import expected_statistics_log
expected_states = np.zeros_like(alphal) \
if expected_states is None else expected_states
expected_transcounts = np.zeros_like(trans_potential) \
@@ -678,7 +678,7 @@ class HMMStatesEigen(HMMStatesPython):
### Vitberbi
def Viterbi(self):
- from hmm_messages_interface import viterbi
+ from pyhsmm.internals.hmm_messages_interface import viterbi
self.stateseq = viterbi(self.trans_matrix,self.aBl,self.pi_0,
np.empty(self.aBl.shape[0],dtype='int32'))
diff --git a/pyhsmm/internals/hsmm_states.py b/pyhsmm/internals/hsmm_states.py
index a4b4108..a37303e 100644
--- a/pyhsmm/internals/hsmm_states.py
+++ b/pyhsmm/internals/hsmm_states.py
@@ -500,7 +500,7 @@ class HSMMStatesEigen(HSMMStatesPython):
def messages_backwards(self):
# NOTE: np.maximum calls are because the C++ code doesn't do
# np.logaddexp(-inf,-inf) = -inf, it likes nans instead
- from hsmm_messages_interface import messages_backwards_log
+ from pyhsmm.internals.hsmm_messages_interface import messages_backwards_log
betal, betastarl = messages_backwards_log(
np.maximum(self.trans_matrix,1e-50),self.aBl,np.maximum(self.aDl,-1000000),
self.aDsl,np.empty_like(self.aBl),np.empty_like(self.aBl),
@@ -519,7 +519,7 @@ class HSMMStatesEigen(HSMMStatesPython):
return super(HSMMStatesEigen,self).messages_backwards()
def sample_forwards(self,betal,betastarl):
- from hsmm_messages_interface import sample_forwards_log
+ from pyhsmm.internals.hsmm_messages_interface import sample_forwards_log
if self.left_censoring:
raise NotImplementedError
caBl = np.vstack((np.zeros(betal.shape[1]),np.cumsum(self.aBl[:-1],axis=0)))
@@ -533,7 +533,7 @@ class HSMMStatesEigen(HSMMStatesPython):
@staticmethod
def _resample_multiple(states_list):
- from hsmm_messages_interface import resample_log_multiple
+ from pyhsmm.internals.hsmm_messages_interface import resample_log_multiple
if len(states_list) > 0:
Ts = [s.T for s in states_list]
longest = np.argmax(Ts)
diff --git a/pyhsmm/util/plot.py b/pyhsmm/util/plot.py
index 47c1248..dc508ac 100644
--- a/pyhsmm/util/plot.py
+++ b/pyhsmm/util/plot.py
@@ -1,7 +1,8 @@
from __future__ import division
import numpy as np
from matplotlib import pyplot as plt
-from stats import cov
+
+from pyhsmm.util.stats import cov
def plot_gaussian_2D(mu, lmbda, color='b', centermarker=True,label='',alpha=1.,ax=None,artists=None):
'''
--
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