Minor fixes in documentation (#813)

* Fix documentation typo * Fix title underlines in documentation to remove warnings during documentation building
bigartm · Jun 10, 2017 · 14d0e2b · 14d0e2b
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diff --git a/docs/api_references/c_interface.txt b/docs/api_references/c_interface.txt
@@ -1,6 +1,6 @@
-==================
+===========
 C Interface
-==================
+===========
 
 This document explains all public methods of the low level BigARTM interface, written in plain C language.
 

diff --git a/docs/api_references/index.txt b/docs/api_references/index.txt
@@ -6,7 +6,7 @@
 .. _tutorial:
 
 API References
-=========
+==============
 
 .. toctree::
    :maxdepth: 2

diff --git a/docs/api_references/python_interface.txt b/docs/api_references/python_interface.txt
@@ -1,5 +1,5 @@
 Python Interface
-====================
+================
 
 This document describes all classes and functions
 in python interface of BigARTM library.

diff --git a/docs/api_references/python_interface/artm_model.txt b/docs/api_references/python_interface/artm_model.txt
@@ -1,5 +1,5 @@
 ARTM model
-================
+==========
 
 This page describes ARTM class.
 

diff --git a/docs/api_references/python_interface/batches_utils.txt b/docs/api_references/python_interface/batches_utils.txt
@@ -1,5 +1,5 @@
 Batches Utils
-================
+=============
 
 This page describes BatchVectorizer class.
 

diff --git a/docs/api_references/python_interface/dictionary.txt b/docs/api_references/python_interface/dictionary.txt
@@ -1,5 +1,5 @@
 Dictionary
-================
+==========
 
 This page describes Dictionary class.
 

diff --git a/docs/api_references/python_interface/lda_model.txt b/docs/api_references/python_interface/lda_model.txt
@@ -1,5 +1,5 @@
 LDA model
-================
+=========
 
 This page describes LDA class.
 

diff --git a/docs/api_references/python_interface/regularizers.txt b/docs/api_references/python_interface/regularizers.txt
@@ -1,5 +1,5 @@
 Regularizers
-================
+============
 
 This page describes *KlFunctionInfo* and *Regularizer* classes.
 

diff --git a/docs/api_references/python_interface/score_tracker.txt b/docs/api_references/python_interface/score_tracker.txt
@@ -1,5 +1,5 @@
 Score Tracker
-================
+=============
 
 This page describes *ScoreTracker classes.
 

diff --git a/docs/api_references/python_interface/scores.txt b/docs/api_references/python_interface/scores.txt
@@ -1,5 +1,5 @@
 Scores
-================
+======
 
 This page describes *Scores classes.
 

diff --git a/docs/devguide/code_style.txt b/docs/devguide/code_style.txt
@@ -1,5 +1,5 @@
 Code style
-=========================
+==========
 
 .. sidebar:: Configure Visual Studio
 

diff --git a/docs/devguide/create_regularizer.txt b/docs/devguide/create_regularizer.txt
@@ -1,5 +1,5 @@
 Creating New Regularizer
-=========================
+========================
 
 This manual describes all necessary steps you need to proceed to create your own regularizer in the core of BigARTM library. We assume you are now in the root directory of BigARTM. The Google Protocol Buffers technology will be used, so we also assume you familiar with it. The instructions will be forwarded with corresponding examples of two regularizers, one per matrix (New Regulrizer Phi and New regularizer Theta).
 
@@ -183,7 +183,7 @@ Also take into consideration the notation of parameters naming (for example, cla
 for the changes to take effect.
 
 Phi regularizer C++ code
--------------
+------------------------
 
 All you need is to implement the method
 
@@ -196,7 +196,7 @@ All you need is to implement the method
 Here you use p_wt, n_wt and all information you have got as parameters through the config to count r_wt and put it in the ``result`` variable. The multiplication on ``tau`` and usage of coefficients of relative regularzation will be processed in further computations automaticaly and shouldn't worry you.
 
 Theta regularizer C++ code
--------------
+--------------------------
 
 You need to create a class implementing the ``RegularizeThetaAgent`` interface (e.g., ``NewRegularizerThetaAgent``) and a class implementing ``RegularizerInterface`` interface (e.g., ``NewRegularizerTheta``).
 

diff --git a/docs/devguide/dev_build_linux.txt b/docs/devguide/dev_build_linux.txt
@@ -1,5 +1,5 @@
 Build C++ code on Linux
-=========================
+=======================
 
 Refer to :doc:`/installation/linux`.
 

diff --git a/docs/devguide/downloads.txt b/docs/devguide/downloads.txt
@@ -1,5 +1,5 @@
 Downloads (Windows)
-=========================
+===================
 
 Download and install the following tools:
 

diff --git a/docs/devguide/ipython_windows.txt b/docs/devguide/ipython_windows.txt
@@ -1,5 +1,5 @@
 Working with iPython notebooks remotely
-=========================
+=======================================
 
 It turned out to be common scenario to run BigARTM on a Linux server (for example on Amazon EC2), while connecting to it from Windows through ``putty``.
 Here is a convenient way to use ``ipython notebook`` in this scenario:

diff --git a/docs/devguide/proto_windows.txt b/docs/devguide/proto_windows.txt
@@ -1,5 +1,5 @@
 Compiling .proto files on Windows
-=========================
+=================================
 
 1. Open a new command prompt
 

diff --git a/docs/devguide/python_windows.txt b/docs/devguide/python_windows.txt
@@ -1,5 +1,5 @@
 Python code on Windows
-=========================
+======================
 
 * Install Python 2.7 (this step is already done if you are following the instructions above),
 

diff --git a/docs/devguide/source_code.txt b/docs/devguide/source_code.txt
@@ -1,5 +1,5 @@
 Source code
-=========================
+===========
 
 BigARTM is hosted in public GitHub repository:
 

diff --git a/docs/installation/linux.txt b/docs/installation/linux.txt
@@ -113,7 +113,7 @@ Currently openSUSE require to install Boost from sources:
    brew install git cmake boost
 
 Step 2. Python packages
-----------------------------------------------------------------
+-----------------------
 BigARTM require Python packages ``numpy``, ``pandas``, ``protobuf`` and ``tqdm``.
 We recommend to install them with recent versino of ``pip``.
 

diff --git a/docs/tutorials/datasets.txt b/docs/tutorials/datasets.txt
@@ -1,5 +1,5 @@
 Input Data Formats and Datasets
-=======
+===============================
 
 * **Formats**
 

diff --git a/docs/tutorials/index.txt b/docs/tutorials/index.txt
@@ -6,7 +6,7 @@
 .. _tutorial:
 
 User's Guide
-=========
+============
 
 .. toctree::
    :maxdepth: 2

diff --git a/docs/tutorials/python_tutorial.txt b/docs/tutorials/python_tutorial.txt
@@ -1,5 +1,5 @@
 Python Tutorial
-===============================
+===============
 
 For more detailes about ``artm.LDA``, ``artm.ARTM``, ``artm.BatchVectorizer`` and ``artm.Dictionary`` see :doc:`../api_references/python_interface/` and :doc:`python_userguide/index`.
 

diff --git a/docs/tutorials/python_userguide/attach_model.txt b/docs/tutorials/python_userguide/attach_model.txt
@@ -1,5 +1,5 @@
 7. Attach Model and Custom Phi Initialization
-=======
+=============================================
 
 Detailed description of all parameters and methods of BigARTM Python API classes can be found in :doc:`../../api_references/python_interface`.
 

diff --git a/docs/tutorials/python_userguide/base_plsa.txt b/docs/tutorials/python_userguide/base_plsa.txt
@@ -1,5 +1,5 @@
 2. Base PLSA Model with Perplexity Score
-=========
+========================================
 
 Detailed description of all parameters and methods of BigARTM Python API classes can be found in :doc:`../../api_references/python_interface`.
 

diff --git a/docs/tutorials/python_userguide/coherence.txt b/docs/tutorials/python_userguide/coherence.txt
@@ -1,5 +1,5 @@
 6. Tokens Co-occurrence and Coherence Computation
-==============================================
+=================================================
 
 * **Interpretability and Coherence of Topics**
 

diff --git a/docs/tutorials/python_userguide/different.txt b/docs/tutorials/python_userguide/different.txt
@@ -1,5 +1,5 @@
 Different Useful Techniques
-=======
+===========================
 
 * **Dictionary filtering**:
 

diff --git a/docs/tutorials/python_userguide/index.txt b/docs/tutorials/python_userguide/index.txt
@@ -6,7 +6,7 @@
 .. _python_userguide:
 
 Python Guide
-=========
+============
 
 .. toctree::
    :maxdepth: 2

diff --git a/docs/tutorials/python_userguide/loading_data.txt b/docs/tutorials/python_userguide/loading_data.txt
@@ -1,5 +1,5 @@
 1. Loading Data: BatchVectorizer and Dictionary
-=======
+===============================================
 
 Detailed description of all parameters and methods of BigARTM Python API classes can be found in :doc:`../../api_references/python_interface`.
 

diff --git a/docs/tutorials/python_userguide/m_artm.txt b/docs/tutorials/python_userguide/m_artm.txt
@@ -1,9 +1,9 @@
 4. Multimodal Topic Models
-=======
+==========================
 
 Detailed description of all parameters and methods of BigARTM Python API classes can be found in :doc:`../../api_references/python_interface`.
 
-Now let's move to more complex cases. In last section цу mentioned the term `modality`. It's something that corresponds to each token. We prefer to think about it as about the type of token, For instance, some tokens form the main text in the document, some form the title, some from names of the authors, some from tags etc.
+Now let's move to more complex cases. In last section we mentioned the term `modality`. It's something that corresponds to each token. We prefer to think about it as about the type of token, For instance, some tokens form the main text in the document, some form the title, some from names of the authors, some from tags etc.
 
 In BigARTM each unique token has a modality. It is denoted as ``class_id`` (don't confuse with the classes in the task of classification). You can specify the ``class_id`` of the token, or the library will set it to ``@default_class``. This class id denotes the type of usual tokens, the type be default.
 

diff --git a/docs/tutorials/python_userguide/phi_theta_extraction.txt b/docs/tutorials/python_userguide/phi_theta_extraction.txt
@@ -1,5 +1,5 @@
 5. Phi and Theta Extraction. Transform Method
-=======
+=============================================
 
 Detailed description of all parameters and methods of BigARTM Python API classes can be found in :doc:`../../api_references/python_interface`.
 

diff --git a/docs/tutorials/python_userguide/ptdw.txt b/docs/tutorials/python_userguide/ptdw.txt
@@ -1,2 +1,2 @@
 8. Deal with Ptdw Matrix
-=======
+========================
diff --git a/docs/tutorials/python_userguide/regularizers_and_scores.txt b/docs/tutorials/python_userguide/regularizers_and_scores.txt
@@ -1,5 +1,5 @@
 3. Regularizers and Scores Usage
-=========
+================================
 
 Detailed description of all parameters and methods of BigARTM Python API classes can be found in :doc:`../../api_references/python_interface`. Description of regularizers can be found in :doc:`../regularizers_descr`.
 

diff --git a/docs/tutorials/regularizers_descr.txt b/docs/tutorials/regularizers_descr.txt
@@ -1,5 +1,5 @@
 Regularizers Description
-=========
+========================
 
 This page describes the features and cases of usage of the regularizers, that have already been implemented in the core of BigARTM library. Detailed description of parameters of the regularizers in the Python API can be seen in :doc:`../api_references/python_interface/regularizers`.
 
@@ -8,7 +8,7 @@ Examples of the usage of the regularizers can be found in :doc:`python_tutorial`
 Note: The influence of any regularizer with ``tau`` parameter in it's M-step formula can be controlled via this parameter.
 
 Smooth/Sparse Phi
--------------
+-----------------
 
 * **M-step formula:**
 
@@ -41,7 +41,7 @@ Notes:
 
 
 Smooth/Sparse Theta
--------------
+-------------------
 
 * **M-step formula:**
 
@@ -75,7 +75,7 @@ Notes:
 
 
 Decorrelator Phi
--------------
+----------------
 
 * **M-step formula:**
 
@@ -101,39 +101,39 @@ Notes:
 
 
 Label Regularization Phi
--------------
+------------------------
 
 * **M-step formula:**
 
 ``p_wt`` :math:`\propto` ``n_wt`` + ``tau`` * ``dict[w]`` * (``p_wt`` * ``n_t``) / (:math:`\sum_{s \in T}` (``p_ws`` * ``n_s``))
 
 
 Specified sparse Phi
--------------
+--------------------
 
 * **Description:**
 
 It is not a usual regularizer, it's a tool to sparse as many elements in :math:`\Phi`, as you need. You can sparse by columns or by rows.
 
 
 Improve Coherence Phi
--------------
+---------------------
 
 * **M-step formula:**
 
 ``p_wt`` :math:`\propto` ``n_wt`` + ``tau`` * :math:`\sum_{v \in W}` ``cooc_dict[w][v]`` * ``n_vt``
 
 
 Smooth Ptdw
--------------
+-----------
 
 * **M-step formula:**
 
 `ToDo(anyap)`
 
 
 Topic Selection Theta
--------------
+---------------------
 
 * **M-step formula:**
 
@@ -142,20 +142,20 @@ Topic Selection Theta
 where ``topic_value[t]`` = ``n`` / (``n_t`` * ``|T|``)
 
 Biterms Phi
--------------
+-----------
 
 * **M-step formula:**
 
 ``p_wt`` :math:`\propto` (``n_wt`` + ``tau`` * :math:`\sum_{u \in W}` (``p_tuw``)), :math:`\qquad` where ``p_tuw`` = :math:`\mathrm{norm}_{t \in T}` (``n_t`` * ``p_wt`` * ``p_ut``)
 
 
 Hierarchy Sparsing Theta
--------------
+------------------------
 
 `ToDo(nadiinchi)`
 
 
 Topic Segmentation Ptdw
--------------
+-----------------------
 
 `ToDo(anastasiabayandina)`