Merge pull request #37 from bab2min/develop

bug #36 fixed
bab2min · Mar 28, 2020 · 3830c3d · 3830c3d
2 parents 084b190 + ef510ca
commit 3830c3d
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diff --git a/.github/workflows/pull_request_test.yml b/.github/workflows/pull_request_test.yml
@@ -72,7 +72,7 @@ jobs:
     strategy:
       max-parallel: 4
       matrix:
-        python-version: [3.6, 3.7, 3.8]
+        python-version: [3.5, 3.6, 3.7, 3.8]
         architecture: [x86, x64]
 
     steps:

diff --git a/README.kr.rst b/README.kr.rst
@@ -30,7 +30,7 @@ tomotopy 란?
 
 더 자세한 정보는 https://bab2min.github.io/tomotopy/index.kr.html 에서 확인하시길 바랍니다.
 
-tomotopy의 가장 최신버전은 0.6.1 입니다.
+tomotopy의 가장 최신버전은 0.6.2 입니다.
 
 시작하기
 ---------------
@@ -39,7 +39,13 @@ tomotopy의 가장 최신버전은 0.6.1 입니다.
 
     $ pip install tomotopy
 
-Linux에서는 c++11 코드를 컴파일하기 위해 gcc 5 이상이 필수적으로 설치되어 있어야 합니다. 
+지원하는 운영체제 및 Python 버전은 다음과 같습니다:
+
+* Python 3.5 이상이 설치된 Linux (x86-64)
+* Python 3.5 이상이 설치된 macOS 10.13나 그 이후 버전
+* Python 3.5 이상이 설치된 Windows 7이나 그 이후 버전 (x86, x86-64)
+* Python 3.5 이상이 설치된 다른 운영체제: 이 경우는 c++11 호환 컴파일러를 통한 소스코드 컴파일이 필요합니다.
+
 설치가 끝난 뒤에는 다음과 같이 Python3에서 바로 import하여 tomotopy를 사용할 수 있습니다.
 ::
 
@@ -210,10 +216,13 @@ tomotopy의 Python3 예제 코드는 https://github.com/bab2min/tomotopy/blob/ma
 
 역사
 -------
-* 0.6.1 (2020-03-22)
+* 0.6.2 (2020-03-28)
+    * `save`와 `load`에 관련된 치명적인 버그가 수정되었습니다. 해당 버그로 0.6.0 및 0.6.1 버전은 릴리즈에서 삭제되었습니다.
+
+* 0.6.1 (2020-03-22) (삭제됨)
     * 모듈 로딩과 관련된 버그가 수정되었습니다.
 
-* 0.6.0 (2020-03-22)
+* 0.6.0 (2020-03-22) (삭제됨)
     * 대량의 문헌을 관리하기 위한 `tomotopy.utils.Corpus`가 추가되었습니다.
     * 어휘-주제 분포의 사전 확률을 조절할 수 있는 `tomotopy.LDAModel.set_word_prior` 메소드가 추가되었습니다.
     * 문헌 빈도를 기반으로 어휘를 필터링할 수 있도록 토픽 모델의 생성자에 `min_df`가 추가되었습니다.

diff --git a/README.rst b/README.rst
@@ -31,7 +31,7 @@ The current version of `tomoto` supports several major topic models including
 
 Please visit https://bab2min.github.io/tomotopy to see more information.
 
-The most recent version of tomotopy is 0.6.1.
+The most recent version of tomotopy is 0.6.2.
 
 Getting Started
 ---------------
@@ -40,7 +40,13 @@ You can install tomotopy easily using pip. (https://pypi.org/project/tomotopy/)
 
     $ pip install tomotopy
 
-For Linux, it is neccesary to have gcc 5 or more for compiling C++11 codes.
+The supported OS and Python versions are:
+
+* Linux (x86-64) with Python >= 3.5 
+* macOS >= 10.13 with Python >= 3.5
+* Windows 7 or later (x86, x86-64) with Python >= 3.5
+* Other OS with Python >= 3.5: Compilation from source code required (with c++11 compatible compiler)
+
 After installing, you can start tomotopy by just importing.
 ::
 
@@ -215,10 +221,13 @@ meaning you can use it for any reasonable purpose and remain in complete ownersh
 
 History
 -------
-* 0.6.1 (2020-03-22)
+* 0.6.2 (2020-03-28)
+    * A critical bug related to `save` and `load` was fixed. Version 0.6.0 and 0.6.1 have been removed from releases.
+
+* 0.6.1 (2020-03-22) (removed)
     * A bug related to module loading was fixed.
 
-* 0.6.0 (2020-03-22)
+* 0.6.0 (2020-03-22) (removed)
     * `tomotopy.utils.Corpus` class that manages multiple documents easily was added.
     * `tomotopy.LDAModel.set_word_prior` method that controls word-topic priors of topic models was added.
     * A new argument `min_df` that filters words based on document frequency was added into every topic model's __init__.

diff --git a/setup.py b/setup.py
@@ -52,7 +52,7 @@
 setup(
     name='tomotopy',
 
-    version='0.6.1',
+    version='0.6.2',
 
     description='Tomoto, The Topic Modeling Tool for Python',
     long_description=long_description,

diff --git a/src/TopicModel/CT.h b/src/TopicModel/CT.h
@@ -3,11 +3,11 @@
 
 namespace tomoto
 {
-    template<TermWeight _TW, size_t _Flags = 0>
-	struct DocumentCTM : public DocumentLDA<_TW, _Flags>
+    template<TermWeight _tw, size_t _Flags = 0>
+	struct DocumentCTM : public DocumentLDA<_tw, _Flags>
 	{
-		using BaseDocument = DocumentLDA<_TW, _Flags>;
-		using DocumentLDA<_TW, _Flags>::DocumentLDA;
+		using BaseDocument = DocumentLDA<_tw, _Flags>;
+		using DocumentLDA<_tw, _Flags>::DocumentLDA;
 		Eigen::Matrix<Float, -1, -1> beta; // Dim: (K, betaSample)
 		Eigen::Matrix<Float, -1, 1> smBeta; // Dim: K
 		DEFINE_SERIALIZER_AFTER_BASE_WITH_VERSION(BaseDocument, 0, smBeta);

diff --git a/src/TopicModel/CTModel.hpp b/src/TopicModel/CTModel.hpp
@@ -11,28 +11,28 @@ Implementation of CTM using Gibbs sampling by bab2min
 
 namespace tomoto
 {
-	template<TermWeight _TW>
-	struct ModelStateCTM : public ModelStateLDA<_TW>
+	template<TermWeight _tw>
+	struct ModelStateCTM : public ModelStateLDA<_tw>
 	{
 	};
 
-	template<TermWeight _TW, size_t _Flags = flags::partitioned_multisampling,
+	template<TermWeight _tw, size_t _Flags = flags::partitioned_multisampling,
 		typename _Interface = ICTModel,
 		typename _Derived = void,
-		typename _DocType = DocumentCTM<_TW>,
-		typename _ModelState = ModelStateCTM<_TW>>
-	class CTModel : public LDAModel<_TW, _Flags, _Interface,
-		typename std::conditional<std::is_same<_Derived, void>::value, CTModel<_TW, _Flags>, _Derived>::type,
+		typename _DocType = DocumentCTM<_tw>,
+		typename _ModelState = ModelStateCTM<_tw>>
+	class CTModel : public LDAModel<_tw, _Flags, _Interface,
+		typename std::conditional<std::is_same<_Derived, void>::value, CTModel<_tw, _Flags>, _Derived>::type,
 		_DocType, _ModelState>
 	{
 	protected:
-		using DerivedClass = typename std::conditional<std::is_same<_Derived, void>::value, CTModel<_TW>, _Derived>::type;
-		using BaseClass = LDAModel<_TW, _Flags, _Interface, DerivedClass, _DocType, _ModelState>;
+		using DerivedClass = typename std::conditional<std::is_same<_Derived, void>::value, CTModel<_tw>, _Derived>::type;
+		using BaseClass = LDAModel<_tw, _Flags, _Interface, DerivedClass, _DocType, _ModelState>;
 		friend BaseClass;
 		friend typename BaseClass::BaseClass;
 		using WeightType = typename BaseClass::WeightType;
 
-		const char* TMID = "CTM\0";
+		static constexpr char TMID[] = "CTM\0";
 
 		size_t numBetaSample = 10;
 		size_t numTMNSample = 5;

diff --git a/src/TopicModel/DMR.h b/src/TopicModel/DMR.h
@@ -3,11 +3,11 @@
 
 namespace tomoto
 {
-	template<TermWeight _TW, size_t _Flags = 0>
-	struct DocumentDMR : public DocumentLDA<_TW, _Flags>
+	template<TermWeight _tw, size_t _Flags = 0>
+	struct DocumentDMR : public DocumentLDA<_tw, _Flags>
 	{
-		using BaseDocument = DocumentLDA<_TW, _Flags>;
-		using DocumentLDA<_TW, _Flags>::DocumentLDA;
+		using BaseDocument = DocumentLDA<_tw, _Flags>;
+		using DocumentLDA<_tw, _Flags>::DocumentLDA;
 		size_t metadata = 0;
 
 		DEFINE_SERIALIZER_AFTER_BASE_WITH_VERSION(BaseDocument, 0, metadata);

diff --git a/src/TopicModel/DMRModel.hpp b/src/TopicModel/DMRModel.hpp
@@ -10,29 +10,29 @@ Implementation of DMR using Gibbs sampling by bab2min
 
 namespace tomoto
 {
-	template<TermWeight _TW>
-	struct ModelStateDMR : public ModelStateLDA<_TW>
+	template<TermWeight _tw>
+	struct ModelStateDMR : public ModelStateLDA<_tw>
 	{
 		Eigen::Matrix<Float, -1, 1> tmpK;
 	};
 
-	template<TermWeight _TW, size_t _Flags = flags::partitioned_multisampling,
+	template<TermWeight _tw, size_t _Flags = flags::partitioned_multisampling,
 		typename _Interface = IDMRModel,
 		typename _Derived = void,
-		typename _DocType = DocumentDMR<_TW>,
-		typename _ModelState = ModelStateDMR<_TW>>
-	class DMRModel : public LDAModel<_TW, _Flags, _Interface,
-		typename std::conditional<std::is_same<_Derived, void>::value, DMRModel<_TW, _Flags>, _Derived>::type,
+		typename _DocType = DocumentDMR<_tw>,
+		typename _ModelState = ModelStateDMR<_tw>>
+	class DMRModel : public LDAModel<_tw, _Flags, _Interface,
+		typename std::conditional<std::is_same<_Derived, void>::value, DMRModel<_tw, _Flags>, _Derived>::type,
 		_DocType, _ModelState>
 	{
 	protected:
-		using DerivedClass = typename std::conditional<std::is_same<_Derived, void>::value, DMRModel<_TW>, _Derived>::type;
-		using BaseClass = LDAModel<_TW, _Flags, _Interface, DerivedClass, _DocType, _ModelState>;
+		using DerivedClass = typename std::conditional<std::is_same<_Derived, void>::value, DMRModel<_tw>, _Derived>::type;
+		using BaseClass = LDAModel<_tw, _Flags, _Interface, DerivedClass, _DocType, _ModelState>;
 		friend BaseClass;
 		friend typename BaseClass::BaseClass;
 		using WeightType = typename BaseClass::WeightType;
 
-		const char* TMID = "DMR\0";
+		static constexpr char TMID[] = "DMR\0";
 
 		Eigen::Matrix<Float, -1, -1> lambda;
 		Eigen::Matrix<Float, -1, -1> expLambda;
@@ -362,11 +362,11 @@ namespace tomoto
 	};
 
 	/* This is for preventing 'undefined symbol' problem in compiling by clang. */
-	template<TermWeight _TW, size_t _Flags,
+	template<TermWeight _tw, size_t _Flags,
 		typename _Interface, typename _Derived, typename _DocType, typename _ModelState>
-		constexpr Float DMRModel<_TW, _Flags, _Interface, _Derived, _DocType, _ModelState>::maxLambda;
+		constexpr Float DMRModel<_tw, _Flags, _Interface, _Derived, _DocType, _ModelState>::maxLambda;
 
-	template<TermWeight _TW, size_t _Flags,
+	template<TermWeight _tw, size_t _Flags,
 		typename _Interface, typename _Derived, typename _DocType, typename _ModelState>
-		constexpr size_t DMRModel<_TW, _Flags, _Interface, _Derived, _DocType, _ModelState>::maxBFGSIteration;
+		constexpr size_t DMRModel<_tw, _Flags, _Interface, _Derived, _DocType, _ModelState>::maxBFGSIteration;
 }
diff --git a/src/TopicModel/DTM.h b/src/TopicModel/DTM.h
@@ -4,12 +4,12 @@
 
 namespace tomoto
 {
-	template<TermWeight _TW, size_t _Flags = 0>
-	struct DocumentDTM : public DocumentLDA<_TW, _Flags>
+	template<TermWeight _tw, size_t _Flags = 0>
+	struct DocumentDTM : public DocumentLDA<_tw, _Flags>
 	{
-		using BaseDocument = DocumentLDA<_TW, _Flags>;
-		using DocumentLDA<_TW, _Flags>::DocumentLDA;
-		using WeightType = typename std::conditional<_TW == TermWeight::one, int32_t, float>::type;
+		using BaseDocument = DocumentLDA<_tw, _Flags>;
+		using DocumentLDA<_tw, _Flags>::DocumentLDA;
+		using WeightType = typename std::conditional<_tw == TermWeight::one, int32_t, float>::type;
 	};
 
     class IDTModel : public ILDAModel

diff --git a/src/TopicModel/DTModel.hpp b/src/TopicModel/DTModel.hpp
@@ -12,29 +12,29 @@ Implementation of Dynamic Topic Model using Gibbs sampling by bab2min
 
 namespace tomoto
 {
-	template<TermWeight _TW>
+	template<TermWeight _tw>
 	struct ModelStateDTM
 	{
-		using WeightType = typename std::conditional<_TW == TermWeight::one, int32_t, float>::type;
+		using WeightType = typename std::conditional<_tw == TermWeight::one, int32_t, float>::type;
 
 		Eigen::Matrix<Float, -1, 1> zLikelihood;
 		Eigen::Matrix<WeightType, -1, -1> numByTopic; // Dim: (Topic, T)
 		Eigen::Matrix<WeightType, -1, -1> numByTopicWord; // Dim: (Topic, Vocabs * T)
 		DEFINE_SERIALIZER(numByTopic, numByTopicWord);
 	};
 
-	template<TermWeight _TW, size_t _Flags = flags::partitioned_multisampling,
+	template<TermWeight _tw, size_t _Flags = flags::partitioned_multisampling,
 		typename _Interface = IDTModel,
 		typename _Derived = void,
-		typename _DocType = DocumentDTM<_TW>,
-		typename _ModelState = ModelStateDTM<_TW>>
-		class DTModel : public LDAModel<_TW, _Flags, _Interface,
-		typename std::conditional<std::is_same<_Derived, void>::value, DTModel<_TW, _Flags>, _Derived>::type,
+		typename _DocType = DocumentDTM<_tw>,
+		typename _ModelState = ModelStateDTM<_tw>>
+		class DTModel : public LDAModel<_tw, _Flags, _Interface,
+		typename std::conditional<std::is_same<_Derived, void>::value, DTModel<_tw, _Flags>, _Derived>::type,
 		_DocType, _ModelState>
 	{
 	protected:
-		using DerivedClass = typename std::conditional<std::is_same<_Derived, void>::value, DTModel<_TW>, _Derived>::type;
-		using BaseClass = LDAModel<_TW, _Flags, _Interface, DerivedClass, _DocType, _ModelState>;
+		using DerivedClass = typename std::conditional<std::is_same<_Derived, void>::value, DTModel<_tw>, _Derived>::type;
+		using BaseClass = LDAModel<_tw, _Flags, _Interface, DerivedClass, _DocType, _ModelState>;
 		friend BaseClass;
 		friend typename BaseClass::BaseClass;
 		using WeightType = typename BaseClass::WeightType;

diff --git a/src/TopicModel/GDMR.h b/src/TopicModel/GDMR.h
@@ -3,11 +3,11 @@
 
 namespace tomoto
 {
-    template<TermWeight _TW, size_t _Flags = 0>
-	struct DocumentGDMR : public DocumentDMR<_TW, _Flags>
+    template<TermWeight _tw, size_t _Flags = 0>
+	struct DocumentGDMR : public DocumentDMR<_tw, _Flags>
 	{
-		using BaseDocument = DocumentDMR<_TW, _Flags>;
-		using DocumentDMR<_TW, _Flags>::DocumentDMR;
+		using BaseDocument = DocumentDMR<_tw, _Flags>;
+		using DocumentDMR<_tw, _Flags>::DocumentDMR;
 		std::vector<Float> metadataC;
 
 		DEFINE_SERIALIZER_AFTER_BASE_WITH_VERSION(BaseDocument, 0, metadataC);

diff --git a/src/TopicModel/GDMRModel.hpp b/src/TopicModel/GDMRModel.hpp
@@ -5,27 +5,27 @@
 
 namespace tomoto
 {
-	template<TermWeight _TW>
-	struct ModelStateGDMR : public ModelStateDMR<_TW>
+	template<TermWeight _tw>
+	struct ModelStateGDMR : public ModelStateDMR<_tw>
 	{
 		/*Eigen::Matrix<Float, -1, 1> alphas;
 		Eigen::Matrix<Float, -1, 1> terms;
 		std::vector<std::vector<Float>> slpCache;
 		std::vector<size_t> ndimCnt;*/
 	};
 
-	template<TermWeight _TW, size_t _Flags = flags::partitioned_multisampling,
+	template<TermWeight _tw, size_t _Flags = flags::partitioned_multisampling,
 		typename _Interface = IGDMRModel,
 		typename _Derived = void,
-		typename _DocType = DocumentGDMR<_TW, _Flags>,
-		typename _ModelState = ModelStateGDMR<_TW>>
-	class GDMRModel : public DMRModel<_TW, _Flags, _Interface,
-		typename std::conditional<std::is_same<_Derived, void>::value, GDMRModel<_TW>, _Derived>::type,
+		typename _DocType = DocumentGDMR<_tw, _Flags>,
+		typename _ModelState = ModelStateGDMR<_tw>>
+	class GDMRModel : public DMRModel<_tw, _Flags, _Interface,
+		typename std::conditional<std::is_same<_Derived, void>::value, GDMRModel<_tw>, _Derived>::type,
 		_DocType, _ModelState>
 	{
 	protected:
-		using DerivedClass = typename std::conditional<std::is_same<_Derived, void>::value, GDMRModel<_TW>, _Derived>::type;
-		using BaseClass = DMRModel<_TW, _Flags, _Interface, DerivedClass, _DocType, _ModelState>;
+		using DerivedClass = typename std::conditional<std::is_same<_Derived, void>::value, GDMRModel<_tw>, _Derived>::type;
+		using BaseClass = DMRModel<_tw, _Flags, _Interface, DerivedClass, _DocType, _ModelState>;
 		friend BaseClass;
 		friend typename BaseClass::BaseClass;
 		friend typename BaseClass::BaseClass::BaseClass;

diff --git a/src/TopicModel/HDP.h b/src/TopicModel/HDP.h
@@ -3,16 +3,16 @@
 
 namespace tomoto
 {
-    template<TermWeight _TW>
-	struct DocumentHDP : public DocumentLDA<_TW>
+    template<TermWeight _tw>
+	struct DocumentHDP : public DocumentLDA<_tw>
 	{
 		/* 
 		For DocumentHDP, the topic in numByTopic, Zs indicates 'table id', not 'topic id'.
 		To get real 'topic id', check the topic field of numTopicByTable.
 		*/
-		using BaseDocument = DocumentLDA<_TW>;
-		using DocumentLDA<_TW>::DocumentLDA;
-		using WeightType = typename DocumentLDA<_TW>::WeightType;
+		using BaseDocument = DocumentLDA<_tw>;
+		using DocumentLDA<_tw>::DocumentLDA;
+		using WeightType = typename DocumentLDA<_tw>::WeightType;
 		struct TableTopicInfo
 		{
 			WeightType num;