Quick start
***********
This Quickstart guide will run you through installing TEMPy2 and scoring models
and fitting assemblies with SMOC and gamma-TEMPy.

Getting TEMPy
-------------

TEMPy can be installed using the `pip` package manager. In a shell run:

.. code-block:: bash

   $ pip install BioTEMPy==2.0

Scoring a structure with SMOC
-----------------------------

The TEMPy package comes with a number of useful for programs.  The `TEMPy.smoc` tool
generates residue level model/map correlation scores.

To generate SMOC scores for the model with ID 5fj8 from the RCSB database and its associated cryo-EM map (3178 from the EMDB), we can run:

.. code-block:: bash

   $ TEMPy.smoc -p rcsb:5fj8 \      # Use the 5fj8 model from RCSB
                -m emdb:3178 \      # Use the 3178 map from EMDB
		-r 3.9 \            # The resolution
		--output-format png # Generate png images

This will generate a series of plots in PNG format, one per chain such as the plot below.

.. figure:: _static/images/quickstart_smoc.png
   :scale: 100 %
   :alt: generated smoc plot

The `--plot-type` argument allows you to choose two different plot
types.  The default is the "residue" plot as shown above, where each
chains SMOC score is in a separate file.  The "violin" option shows the
distribution of each chains residue in a single file.

.. code-block:: bash

   $ TEMPy.smoc -p rcsb:5fj8 \              # Use the 5fj8 model from RCSB
                -m emdb:3178 \              # Use the 3178 map from EMDB
		-r 3.9 \                    # The resolution
		--output-format png         # Generate png images
		--plot-type residue violin  # Plot residue plots and a violin plot

.. figure:: _static/images/quickstart_smoc_violin.png
   :scale: 100 %
   :alt: generated smoc violin plot

It is possible to generate tabulated data in either TSV or CSV format or JSON formatted output.  If you'd like to learn how develop Python programs which use the SMOC scrore, checkout the :doc:`guides/scoring_functions` guide.

For more details on `TEMPy.smoc` and its supported options see :doc:`../executables` 

Scoring chains with LoQFit
------------------------
Another similar scoring function is LoQFit, which evaluates the model/map correlation in fourier space.

The `TEMPy.loqfit` script will compute the loqfit score for each residue in a protien.

.. code-block:: bash

   $ TEMPy.loqfit -p rcsb:5fj8 \      # Use the 5fj8 model from RCSB
                  -m emdb:3178 \      # Use the 3178 map from EMDB
                  -r 3.9 \            # The resolution
                  --output-format png # Generate csv file

This script will generate a plot of the LoQFit score for each chain, such as the plot below
for chain A.

.. figure:: _static/images/quickstart_loqfit.png
   :scale: 100 %
   :alt: generated loqfit plot

Like the SMOC plot, the distribution of resolutions for all chains can
be viewed in a single plot by setting the `--plot-type` to "violin".

.. code-block:: bash

   $ TEMPy.loqfit -p rcsb:5fj8 \              # Use the 5fj8 model from RCSB
                  -m emdb:3178 \              # Use the 3178 map from EMDB
                  -r 3.9 \                    # The resolution
                  --output-format png         # Generate csv file
                  --plot-type residues violin # Plot residue plots and a violin plot

.. figure:: _static/images/quickstart_loqfit_violin.png
   :scale: 100 %
   :alt: generated loqfit violin plot 


Scoring chains with SCCC
------------------------
The SCCC (Segmented Cross-Correlation Coefficient) computes the cross-correlation to on arbitrary segments of a protein.

The `TEMPy.SCCC` script will compute them on each chain.

.. code-block:: bash

   $ TEMPy.sccc -p rcsb:5fj8 \      # Use the 5fj8 model from RCSB
                -m emdb:3178 \      # Use the 3178 map from EMDB
		-r 3.9 \            # The resolution
		--output-format csv # Generate csv file


Fitting an assembly with gamma-TEMPY
------------------------------------

To develop your own python scripts checkout the :doc:`guides` and :doc:`reference`.