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Documentation (#17)
* Updated citation and moved .nojekyll to makefile * Added tutorial
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‎README.md

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# QML: A Python Toolkit for Quantum Machine Learning
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[![Build Status](https://travis-ci.org/qmlcode/qml.svg?branch=master)](https://travis-ci.org/qmlcode/qml)
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QML is a Python2/3-compatible toolkit for representation learning of properties of molecules and solids. QML is not a high-level framework where you can do `model.train()`, but supplies the building blocks to carry out efficient and accurate machine learning on chemical compounds. As such, the goal is to provide usable and efficient implementations of concepts such as representations and kernels, which can then be implemented in other machine learning codes.
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QML is a Python2/3-compatible toolkit for representation learning of properties of molecules and solids.
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#### Current list of contributors:
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* Anders S. Christensen (University of Basel)
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* Felix Faber (University of Basel)
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* Felix A. Faber (University of Basel)
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* Bing Huang (University of Basel)
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* Lars A. Bratholm (University of Copenhagen)
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* O. Anatole von Lilienfeld (University of Basel)
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AS Christensen, F Faber, B Huang, LA Bratholm, OA von Lilienfeld (2017) "QML: A Python Toolkit for Quantum Machine Learning" https://github.com/qmlcode/qml
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## 2) Installation
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Installing prerequisite modules (for most Linux systems):
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## 2) Get help:
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```bash
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sudo apt-get install python-pip gfortran libblas-dev liblapack-dev git
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Documentation and installation instruction is found at: https://qmlcode.github.io
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```
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These should already be installed on most systems. The Intel compilers and MKL math-libraries are supported as well (see section 1.3).
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### 2.1) Installing via `pip`:
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The easiest way to install the stable version from the Python Package Index (PyPI) is using the official, built-in Python package manager, `pip`:
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```bash
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pip install qml --user -U
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```
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To use the Intel compiler, together with the MKL math library:
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```bash
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pip install qml --user -U --global-option="build" --global-option="--compiler=intelem" --global-option="--fcompiler=intelem"
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```
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Alternatively, you can install the most recent stable development snapshot directly from GitHub:
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```bash
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pip install git+https://github.com/qmlcode/qml --user -U
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```
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Use `pip2 install ...` or `pip3 install ...` to get the Python2 or Python3 versions explicitly. QML supports both flavors.
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To uninstall simply use `pip` again.
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```bash
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pip uninstall qml
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```
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### 2.2) Installing via `setup.py` with Intel compiler:
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If you have Intel compilers installed (2016 and newer), you can compile QML with Ifort/MKL using the following options:
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```bash
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pip install git+https://github.com/qmlcode/qml.git --user --upgrade --global-option="build" --global-option="--compiler=intelem" --global-option="--fcompiler=intelem"
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```
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### 2.3) Note on Apple/Mac support:
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Installing QML requires a Fortran compiler. On Darwin you can install it using `brew`:
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```bash
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brew install gcc
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```
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Note the Clang Fortran compiler from brew unfortunately does not support OpenMP. Therefore parallelism via OpenMP is disabled as default for Darwin systems.
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## 3) Get help:
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Documentation in found in the file [`DOCUMENTATION.md`](../blob/master/DOCUMENTATION.md).
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## 4) License:
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## 3) License:
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QML is freely available under the terms of the MIT license.
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‎docs/Makefile

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# Catch-all target: route all unknown targets to Sphinx using the new
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# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
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%: Makefile
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@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
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@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
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touch build/html/.nojekyll

‎docs/build/html/.nojekyll

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‎docs/source/citation.rst

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Citing use of QML
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-----------------
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QML is freely available under the terms of the MIT open-source license.
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However, we ask that you properly cite the relevant, underlying work in your published work.
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For convenience we provide a list of citations here.
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Until the preprint is available from arXiv, please cite use of QML as:
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::
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AS Christensen, FA Faber, B Huang, LA Bratholm, A Tkatchenko, KR Müller, OA von Lilienfeld (2017) "QML: A Python Toolkit for Quantum Machine Learning" https://github.com/qmlcode/qml
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‎docs/source/conf.py

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# Add any paths that contain custom static files (such as style sheets) here,
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# relative to this directory. They are copied after the builtin static files,
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# so a file named "default.css" will overwrite the builtin "default.css".
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html_static_path = ['_static']
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# html_static_path = ['_static']
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# -- Options for HTMLHelp output ------------------------------------------

‎docs/source/index.rst

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- Klaus-Robert Müller (Technische Universität Berlin/Korea University)
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- O. Anatole von Lilienfeld (University of Basel)
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1) Citing QML:
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Citing QML:
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--------------
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Until the preprint is available from arXiv, please cite this GitHub
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repository as:
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Until the preprint is available from arXiv, please cite use of QML as:
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::
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AS Christensen, F Faber, B Huang, LA Bratholm, A Tkatchenko, KR Müller, OA von Lilienfeld (2017) "QML: A Python Toolkit for Quantum Machine Learning" https://github.com/qmlcode/qml
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2) Installation
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---------------
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Please go to the QML github repository at https://github.com/qmlcode/qml/
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AS Christensen, FA Faber, B Huang, LA Bratholm, A Tkatchenko, KR Müller, OA von Lilienfeld (2017) "QML: A Python Toolkit for Quantum Machine Learning" https://github.com/qmlcode/qml
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For citation of the individual procedures of QML, please see: `citation`
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.. toctree::
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:maxdepth: 2
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:caption: GETTING STARTED:
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:name: index
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installation
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citation
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tutorial
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examples
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qml
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3) License:
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License:
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-----------
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QML is freely available under the terms of the MIT license.

‎docs/source/installation.rst

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Installation
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Installing QML
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---------------
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Installing prerequisite modules (for most Linux systems):
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.. code:: bash
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sudo apt-get install python-pip gfortran libblas-dev liblapack-dev git
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These should already be installed on most systems. The Intel compilers
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and MKL math-libraries are supported as well (see section 1.3).
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Installing via ``pip``:
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The easiest way to install the stable version from the Python Package
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Index (PyPI) is using the official, built-in Python package manager,
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``pip``:
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pip install qml --user -U
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To use the Intel compiler, together with the MKL math library:
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.. code:: bash
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pip install qml --user -U --global-option="build" --global-option="--compiler=intelem" --global-option="--fcompiler=intelem"
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Alternatively, you can install the most recent stable development
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snapshot directly from GitHub:
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.. code:: bash
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pip install git+https://github.com/qmlcode/qml --user -U
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pip install git+https://github.com/qmlcode/qml@develop --user -U
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Use ``pip2 install ...`` or ``pip3 install ...`` to get the Python2 or
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Python3 versions explicitly. QML supports both flavors.
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To uninstall simply use ``pip`` again.
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.. code:: bash
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pip uninstall qml
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Installing via with Intel compilers:
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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If you have Intel compilers installed (2016 and newer), you can compile
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QML with Ifort/MKL using the following options:
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.. code:: bash
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pip install git+https://github.com/qmlcode/qml.git --user --upgrade --global-option="build" --global-option="--compiler=intelem" --global-option="--fcompiler=intelem"
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Note on Apple/Mac support:
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Installing QML requires a Fortran compiler. On MacOS you can install it
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using ``brew``:
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.. code:: bash
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# Update brew
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/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
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# Install GCC
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brew install gcc
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Note the Clang Fortran compiler from brew unfortunately does not support
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OpenMP.
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Therefore parallelism via OpenMP is disabled as default for MacOS systems.
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Additionally, we found that some users have multiple version of the ``as`` assembler - this might happen if you have GCC from e.g. brew and macports at the same time. Look for the following error:
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``FATAL:/opt/local/bin/../libexec/as/x86_64/as: I don't understand 'm' flag!``
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If you experience this problems the setting the following path might fix the problem:
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.. code:: bash
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export PATH=/usr/bin:$PATH
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For more installation help, please see the github repository: https://github.com/qmlcode/qml/

‎docs/source/qml.rst

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:undoc-members:
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qml\.compound module
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qml\.Compound class
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--------------------
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.. automodule:: qml.compound
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:undoc-members:
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.. Module contents
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.. ---------------
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