mirror of
https://github.com/triqs/dft_tools
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28140f14fb
Mainly on the python part. I had a quick browse through to check if the scripts were still working.
72 lines
2.7 KiB
ReStructuredText
72 lines
2.7 KiB
ReStructuredText
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.. highlight:: bash
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Getting started
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===============
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TRIQS provides a set of python libraries that allows to easily write scripts
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for the study of quantum interaction systems. The executable ``ipytriqs`` which
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is installed in the :file:`path_to_install_directory/bin` directory is a normal
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ipython interpreter (see below for details about ipython) which has access to
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the TRIQS modules. You can either start an interactive session with::
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$ ipytriqs
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or run scripts with::
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$ ipytriqs my_script.py
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There is also an executable which allows to start an ipython notebook
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in your browser, just type::
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$ ipytriqs_notebook
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Now you can try to run some scripts to get familiar with TRIQS. Why don't you
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:ref:`go to our python tour <tour>` and run some of the examples there?
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Learn more about python, ipython and the notebook
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-------------------------------------------------
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The ``ipytriqs`` executable calls an `ipython interpreter
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<http://ipython.org>`_. This is basically a more user-friendly version of the
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standard python interpreter with an enhanced interactive shell that makes it
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easy to visualize data. It also provides the ipython notebook, a browser-based
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notebook with support for text, mathematical expressions, inline plots and
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inline python scripts. We really think it is a very powerful tool and recommend
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that you spend some time learning ipython and the notebook. Here are some
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useful links to learn python, ipython, scipy.
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* To learn the Python language itself the recommended starting point is the
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standard `python tutorial <http://docs.python.org/tutorial>`_.
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* A good set of lectures is the `Scipy lecture notes
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<http://scipy-lectures.github.com/>`_.
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* A good starting point to learn about scientific computing with Python and
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related ideas is `Software carpentry <http://software-carpentry.org>`_, which
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provides nice video/slides `lectures on Python
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<http://software-carpentry.org/4_0/python>`_
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* Python has a large number of libraries, which can be used in combination with
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TRIQS. For example:
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* The Python `standard library <http://docs.python.org/library>`_ is already
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very rich.
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* `Numpy <http://docs.scipy.org/doc/numpy/user>`_ allows to manipulate
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multidimensionnal arrays (cf also the `tutorial
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<http://www.scipy.org/Tentative_NumPy_Tutorial>`_).
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* `Scipy <http://www.scipy.org>`_ includes many packages for scientific
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computing.
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* `Matplotlib <http://matplotlib.sourceforge.net>`_ offers very nice plotting
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possibilities.
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* `SymPy <http://sympy.org/>`_ provides some formal computing capabilities.
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* `Cython <http://cython.org/>`_ is a quick way to build simple `C` modules in
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computationally intense case.
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