FIX unit tests

pomegranate/__init__.py

@@ -1,7 +1 @@
-from .bayes_classifier import BayesClassifier
-from .gmm import GeneralMixtureModel
-from .kmeans import KMeans
-
-from .distributions import *
-
-__version__ = "0.5.0"
+__version__ = "1.0.0"

pomegranate/bayesian_network.py

@@ -160,7 +160,7 @@ def add_distribution(self, distribution):
 		
 		Parameters
 		----------
-		distribution: torchegranate.distributions.Distribution
+		distribution: pomegranate.distributions.Distribution
 			A distribution object to include as a node. Currently must be a
 			Categorical or a ConditionalCategorical distribution.
 		"""
@@ -225,10 +225,10 @@ def add_edge(self, parent, child):
 
 		Parameters
 		----------
-		parent: torchegranate.distributions.Distribution
+		parent: pomegranate.distributions.Distribution
 			The distribution that the edge begins at.
 
-		child: torchegranate.distributions.Distribution
+		child: pomegranate.distributions.Distribution
 			The distribution that the edge points to.
 		"""
 
@@ -630,7 +630,7 @@ def _from_structure(X, sample_weight=None, structure=None, pseudocount=0.0):
 
 	Returns
 	-------
-	model: torchegranate.bayesian_network.BayesianNetwork
+	model: pomegranate.bayesian_network.BayesianNetwork
 		The fit Bayesian network.
 	"""
 

pomegranate/distributions/__init__.py

@@ -6,7 +6,6 @@
 from .gamma import Gamma
 from .independent_components import IndependentComponents
 from .joint_categorical import JointCategorical
-from .lognormal import LogNormal
 from .normal import Normal
 from .poisson import Poisson
 from .student_t import StudentT

pomegranate/distributions/zero_inflated.py

@@ -1,4 +1,4 @@
-# zeroinflated.py
+# zero_inflated.py
 # Contact: Jacob Schreiber <jmschreiber91@gmail.com>
 
 import time
@@ -32,8 +32,8 @@ class ZeroInflated(Distribution):
 
 	Parameters
 	----------
-	distribution: torchegranate.distributions._distribution.Distribution
-		A torchegranate distribution object. It should probably be a discrete
+	distribution: pomegranate.distributions.Distribution
+		A pomegranate distribution object. It should probably be a discrete
 		distribution, but does not technically have to be.
 
 	priors: tuple, numpy.ndarray, torch.Tensor, or None. shape=(2,), optional

pomegranate/factor_graph.py

@@ -158,7 +158,7 @@ def add_factor(self, distribution):
 		
 		Parameters
 		----------
-		distribution: torchegranate.distributions.Distribution
+		distribution: pomegranate.distributions.Distribution
 			A distribution object to include as a node.
 		"""
 
@@ -180,7 +180,7 @@ def add_marginal(self, distribution):
 
 		Parameters
 		----------
-		distribution: torchegranate.distributions.Distribution
+		distribution: pomegranate.distributions.Distribution
 			A distribution object to include as a node.
 		"""
 
@@ -202,10 +202,10 @@ def add_edge(self, marginal, factor):
 
 		Parameters
 		----------
-		marginal: torchegranate.distributions.Distribution
+		marginal: pomegranate.distributions.Distribution
 			The marginal distribution to include in the edge.
 
-		factor: torchegranate.distributions.Distribution
+		factor: pomegranate.distributions.Distribution
 			The factor distribution to include in the edge.
 		"""
 

tests/distributions/test_bernoulli.py

@@ -6,7 +6,7 @@
 import torch
 import pytest
 
-from torchegranate.distributions import Bernoulli
+from pomegranate.distributions import Bernoulli
 
 from ._utils import _test_initialization_raises_one_parameter
 from ._utils import _test_initialization

tests/distributions/test_categorical.py

@@ -6,7 +6,7 @@
 import torch
 import pytest
 
-from torchegranate.distributions import Categorical
+from pomegranate.distributions import Categorical
 
 from ._utils import _test_initialization_raises_one_parameter
 from ._utils import _test_predictions

tests/distributions/test_conditional_categorical.py

@@ -5,7 +5,7 @@
 import torch
 import pytest
 
-from torchegranate.distributions import ConditionalCategorical
+from pomegranate.distributions import ConditionalCategorical
 
 from ._utils import _test_initialization_raises_one_parameter
 from ._utils import _test_initialization

tests/distributions/test_dirac_delta.py

@@ -6,7 +6,7 @@
 import torch
 import pytest
 
-from torchegranate.distributions import DiracDelta
+from pomegranate.distributions import DiracDelta
 
 from ._utils import _test_initialization_raises_one_parameter
 from ._utils import _test_initialization

tests/distributions/test_exponential.py

@@ -6,7 +6,7 @@
 import torch
 import pytest
 
-from torchegranate.distributions import Exponential
+from pomegranate.distributions import Exponential
 
 from ._utils import _test_initialization_raises_one_parameter
 from ._utils import _test_initialization

tests/distributions/test_gamma.py

@@ -6,7 +6,7 @@
 import torch
 import pytest
 
-from torchegranate.distributions import Gamma
+from pomegranate.distributions import Gamma
 
 from ._utils import _test_initialization_raises_two_parameters
 from ._utils import _test_initialization

tests/distributions/test_independent_component.py

@@ -6,10 +6,10 @@
 import torch
 import pytest
 
-from torchegranate.distributions import Exponential
-from torchegranate.distributions import Gamma
-from torchegranate.distributions import Categorical
-from torchegranate.distributions import IndependentComponents
+from pomegranate.distributions import Exponential
+from pomegranate.distributions import Gamma
+from pomegranate.distributions import Categorical
+from pomegranate.distributions import IndependentComponents
 
 from ._utils import _test_initialization_raises_one_parameter
 from ._utils import _test_initialization

tests/distributions/test_joint_categorical.py

@@ -1,11 +1,11 @@
-# test_JointCategorical.py
+# test_joint_categorical.py
 # Contact: Jacob Schreiber <jmschreiber91@gmail.com>
 
 import numpy
 import torch
 import pytest
 
-from torchegranate.distributions import JointCategorical
+from pomegranate.distributions import JointCategorical
 
 from ._utils import _test_initialization_raises_one_parameter
 from ._utils import _test_initialization

tests/distributions/test_normal_diagonal.py

@@ -6,7 +6,7 @@
 import torch
 import pytest
 
-from torchegranate.distributions import Normal
+from pomegranate.distributions import Normal
 
 from ._utils import _test_initialization_raises_two_parameters
 from ._utils import _test_initialization

tests/distributions/test_normal_full.py

@@ -6,7 +6,7 @@
 import torch
 import pytest
 
-from torchegranate.distributions import Normal
+from pomegranate.distributions import Normal
 
 from ._utils import _test_initialization_raises_two_parameters
 from ._utils import _test_initialization

tests/distributions/test_poisson.py

@@ -6,7 +6,7 @@
 import torch
 import pytest
 
-from torchegranate.distributions import Poisson
+from pomegranate.distributions import Poisson
 
 from ._utils import _test_initialization_raises_one_parameter
 from ._utils import _test_initialization

tests/distributions/test_student_t.py

@@ -6,7 +6,7 @@
 import torch
 import pytest
 
-from torchegranate.distributions import StudentT
+from pomegranate.distributions import StudentT
 
 from ._utils import _test_initialization_raises_two_parameters
 from ._utils import _test_initialization

tests/distributions/test_uniform.py

@@ -6,7 +6,7 @@
 import torch
 import pytest
 
-from torchegranate.distributions import Uniform
+from pomegranate.distributions import Uniform
 
 from ._utils import _test_initialization_raises_two_parameters
 from ._utils import _test_initialization

tests/hmm/test_dense_hmm.py

@@ -5,9 +5,9 @@
 import torch
 import pytest
 
-from torchegranate.hmm import DenseHMM
-from torchegranate.distributions import Exponential
-from torchegranate.distributions import Gamma
+from pomegranate.hmm import DenseHMM
+from pomegranate.distributions import Exponential
+from pomegranate.distributions import Gamma
 
 from ..distributions._utils import _test_initialization_raises_one_parameter
 from ..distributions._utils import _test_initialization

tests/hmm/test_sparse_hmm.py

@@ -5,9 +5,9 @@
 import torch
 import pytest
 
-from torchegranate.hmm import SparseHMM
-from torchegranate.distributions import Exponential
-from torchegranate.distributions import Gamma
+from pomegranate.hmm import SparseHMM
+from pomegranate.distributions import Exponential
+from pomegranate.distributions import Gamma
 
 from ..distributions._utils import _test_initialization_raises_one_parameter
 from ..distributions._utils import _test_initialization

tests/test_bayes_classifier.py

@@ -6,8 +6,8 @@
 import torch
 import pytest
 
-from torchegranate.bayes_classifier import BayesClassifier
-from torchegranate.distributions import Exponential
+from pomegranate.bayes_classifier import BayesClassifier
+from pomegranate.distributions import Exponential
 
 from .distributions._utils import _test_initialization_raises_one_parameter
 from .distributions._utils import _test_initialization

tests/test_bayesian_network.py

@@ -5,10 +5,10 @@
 import torch
 import pytest
 
-from torchegranate.bayesian_network import BayesianNetwork
-from torchegranate.distributions import Exponential
-from torchegranate.distributions import Categorical
-from torchegranate.distributions import ConditionalCategorical
+from pomegranate.bayesian_network import BayesianNetwork
+from pomegranate.distributions import Exponential
+from pomegranate.distributions import Categorical
+from pomegranate.distributions import ConditionalCategorical
 
 
 from nose.tools import assert_raises

tests/test_bayesian_network_structure_learning.py

@@ -5,15 +5,15 @@
 import torch
 import pytest
 
-from torchegranate.bayesian_network import BayesianNetwork
+from pomegranate.bayesian_network import BayesianNetwork
 
-from torchegranate.bayesian_network import _from_structure
-from torchegranate.bayesian_network import _learn_structure
-from torchegranate.bayesian_network import _categorical_exact
-from torchegranate.bayesian_network import _categorical_chow_liu
+from pomegranate.bayesian_network import _from_structure
+from pomegranate.bayesian_network import _learn_structure
+from pomegranate.bayesian_network import _categorical_exact
+from pomegranate.bayesian_network import _categorical_chow_liu
 
-from torchegranate.distributions import Categorical
-from torchegranate.distributions import ConditionalCategorical
+from pomegranate.distributions import Categorical
+from pomegranate.distributions import ConditionalCategorical
 
 from nose.tools import assert_raises
 from numpy.testing import assert_array_almost_equal

tests/test_factor_graph.py

@@ -5,11 +5,10 @@
 import torch
 import pytest
 
-from torchegranate.factor_graph import FactorGraph
-from torchegranate.distributions import Exponential
-from torchegranate.distributions import Categorical
-from torchegranate.distributions import JointCategorical
-
+from pomegranate.factor_graph import FactorGraph
+from pomegranate.distributions import Exponential
+from pomegranate.distributions import Categorical
+from pomegranate.distributions import JointCategorical
 
 from nose.tools import assert_raises
 from numpy.testing import assert_array_almost_equal

tests/test_gmm.py

@@ -6,8 +6,8 @@
 import torch
 import pytest
 
-from torchegranate.gmm import GeneralMixtureModel
-from torchegranate.distributions import Exponential
+from pomegranate.gmm import GeneralMixtureModel
+from pomegranate.distributions import Exponential
 
 from .distributions._utils import _test_initialization_raises_one_parameter
 from .distributions._utils import _test_initialization

tests/test_kmeans.py

@@ -6,7 +6,7 @@
 import torch
 import pytest
 
-from torchegranate.kmeans import KMeans
+from pomegranate.kmeans import KMeans
 
 from .distributions._utils import _test_initialization_raises_one_parameter
 from .distributions._utils import _test_initialization

tests/test_markov_chain.py

@@ -5,9 +5,9 @@
 import torch
 import pytest
 
-from torchegranate.markov_chain import MarkovChain
-from torchegranate.distributions import Categorical
-from torchegranate.distributions import ConditionalCategorical
+from pomegranate.markov_chain import MarkovChain
+from pomegranate.distributions import Categorical
+from pomegranate.distributions import ConditionalCategorical
 
 from .distributions._utils import _test_initialization_raises_one_parameter
 from .distributions._utils import _test_initialization

tests/test_semisupervised.py

@@ -6,9 +6,9 @@
 import torch
 import pytest
 
-from torchegranate.gmm import GeneralMixtureModel
-from torchegranate.hmm import DenseHMM
-from torchegranate.distributions import Exponential
+from pomegranate.gmm import GeneralMixtureModel
+from pomegranate.hmm import DenseHMM
+from pomegranate.distributions import Exponential
 
 from nose.tools import assert_raises
 from numpy.testing import assert_array_equal

tests/test_utils.py

@@ -5,10 +5,10 @@
 import torch
 import pytest
 
-from torchegranate._utils import _cast_as_tensor
-from torchegranate._utils import _update_parameter
-from torchegranate._utils import _check_parameter
-from torchegranate._utils import partition_sequences
+from pomegranate._utils import _cast_as_tensor
+from pomegranate._utils import _update_parameter
+from pomegranate._utils import _check_parameter
+from pomegranate._utils import partition_sequences
 
 from nose.tools import assert_almost_equal
 from nose.tools import assert_equal