Merge branch 'develop' into release-2.0

Author: yomichi

README.md

@@ -1,5 +1,11 @@
 # abICS
-ab-Initio Configuration Sampling tool kit (abICS) is a Python code (library and application) for Metropolice Monte Carlo.
+abICS is a software framework for training a machine learning model to
+reproduce first-principles energies and then using the model to perform
+configurational sampling in disordered systems.
+Specific emphasis is placed on multi-component solid state systems such as metal and oxide alloys.
+The current version of abics can use neural network models implemented in aenet to be used as 
+the machine learning model. As of this moment, abICS can also generate Quantum Espresso, VASP, 
+and OpenMX input files for obtaining the reference training data for the machine learning model.
 
 ## Requirement
 
@@ -38,8 +44,8 @@ $ pip3 install abics
 
 will install abICS and dependencies.
 
-If you want to change the directory where installed,
-add `--user` option or `--prefix=DIRECTORY` option into the above command as
+If you want to change the directory where abICS is installed,
+add `--user` option or `--prefix=DIRECTORY` option to the above command as
 
 ``` bash
 $ pip3 install --user abics

docs/sphinx/en/source/tutorial/aenet.rst

@@ -136,7 +136,7 @@ Preparation of the QE reference file
 Place the input file to be referenced in the QE scf calculation in ``baseinput_ref``.
 The following is a description of the ``scf.in`` file in the sample directory.
 
-.. code-block::
+::
 
     &CONTROL
     calculation = 'relax'
@@ -227,7 +227,7 @@ In the tutorial we will use ``Al.fingerprint.stp``, ``Mg.fingerprint.stp`` and s
 
 As an example, the content of ``Al.fingerprint.stp`` is shown below:
 
-.. code-block ::
+::
 
   DESCR
    N. Artrith and A. Urban, Comput. Mater. Sci. 114 (2016) 135-150.
@@ -249,7 +249,7 @@ Please refer to the aenet documentation for more information on descriptor setti
 
 Next, prepare a file named ``generate.in.head`` as follows
 
-.. code-block ::
+::
 
     OUTPUT aenet.train
 
@@ -278,7 +278,7 @@ which reads the training data generated by ``generate`` and trains,
 in the ``train`` directory.
 The file name should be ``train.in``.
 
-.. code-block ::
+::
 
     TRAININGSET aenet.train
     TESTPERCENT 10
@@ -309,7 +309,7 @@ predict
 Place the input file ``predict.in`` for ``predict.x`` in the ``predict`` directory
 to evaluate the energy for the input coordinates using the trained potential model.
 
-.. code-block ::
+::
 
     TYPES
     2

docs/sphinx/en/source/tutorial/index.rst

@@ -4,7 +4,7 @@ Tutorial
 
 In this tutorial, we demonstrate the calculation of the degree of inversion of Mg and Al atoms
 in an ionic crystal :math:`{\rm Mg}{\rm Al}_2 {\rm O}_4`. 
-Input files are provided in ``examples/spinel/`` .
+Input files are provided in ``examples/active_learning_qe/`` .
 
 .. toctree::
    :maxdepth: 2

docs/sphinx/ja/source/tutorial/index.rst

@@ -3,7 +3,7 @@
 ***************************
 
 このチュートリアルでは多元系イオン結晶 :math:`{\rm Mg}{\rm Al}_2 {\rm O}_4` の Mg, Al 原子の反転度計算を例に、abICSの利用方法について説明します。
-入力ファイルは ``examples/spinel/`` にあります。
+入力ファイルは ``examples/active_learning_qe/`` にあります。
 
 .. toctree::
    :maxdepth: 2