.. _frompython_section:

====================================
Programming with Larch from Python
====================================

This chapter describes the use of the `larch` module from Python.
There are plenty of good reasons to want to do this, and it is certainly
recommended over using the Larch mini-language for anything fairly
complicated. 

All the functionality described elsewhere in this documentation is
available from the `larch` Python module - the focus here is on how to work
with the larch functions from Python.

To start, you can import larch from Python with

    >>> import larch

The toplevel `larch` module does not do much, so you will probably want to
import some of the submodules like `xafs` or `io`. A simple Python session
might look like this::

    >>> from larch.xafs import autobk
    >>> from larch.io import read_xdi
    >>> from wxmplot.interactive import plot

    >>> dat = read_xdi('examples/xafsdata/fe3c_rt.xdi')
    >>> dat.mu = dat.mutrans
    >>> autobk(dat, rbkg=1.0, kweight=2)
    >>> plot(dat.k, dat.k*dat.chi, xlabel='k 1/A', ylabel='chi*k')

    >>> from larch.xray import xray_line
    >>> print(xray_line('Cu', 'Ka1'))
    >>> (8046.3, 0.577108, u'K', u'L3')


More elaborate examples and documentation on what the larch functions do
are given throughout this documentation.


creating and using a larch interpreter in Python
==========================================================

The example above shows the larch functionality being accessed directly
from Python.  In addition, from Python you can create an instance of an
interpreter of the `larch` mini-language and communicate with it the Larch
macro language with::

    >>> from larch import Interpreter
    >>> session = Interpreter()
    >>> session("""
    >>>   dat = read_xdi('examples/xafsdata/fe3c_rt.xdi')
    >>>   dat.mu = dat.mutrans
    >>>   autobk(dat, rbkg=1.0, kweight=2)
    >>> """)

and so forth (and note that the tolerance against whitespace in the larch macro
language might seem not so silly after all!). If you're running pre-defined
scripts or starting from the larch code generated by one of the GUIs, this can be
a useful way to use Larch from python - combine that with some string formatting
and you can readily have a program that wraps analysis procedures.  Indeed this
is how `XAS_Viewer` works. 

The larch `session` instance will have a `symtable` attribute that is the
top-level of the data namespace in the larch session - the `_main` group - that
you can access directly from Python.  For example, following the above session,
you could do::

    >>> dat = session.symtable.dat
    >>> print(dat.filename, dat.e0, len(dat.energy), len(dat.chi))
    fe3c_rt.xdi 7122.5 348 299


The Larch `Group`
==========================================================


As described throughout the rest of the documentation, Larch organizes data using
`Group` objects.  For example, the `dat` value extracted from the larch session
in the example above will be a `Group`.  Many of the container objects created
and used in Larch will be larch Groups.

For the Python user, these Groups are very similar to instances of an empty
class or `argparse.Namespace` objects::

    class GroupLite(object):
        pass

That is, it is a containrer object with data accessed using Python's
`thing.attribute` syntax.  A larch Group has no public attributes or methods, but
does have a few private ones.  The most important of these is `__name__`, which
you can assign at initialization with the `name` argument and will be shown in
the "representation" string::

    >>> from larch import Group
    >>> g = Group(name='my group', x=1, y=2)
    >>> g
    <Group my group>
    >>> g.x, g.y
    (1, 2)
    >>> g.name
    Traceback (most recent call last):
      File "<stdin>", line 1, in <module>
    AttributeError: 'Group' object has no attribute 'name'
    >>> g.__name__
    'foo'
    >>> g.name = 'Bob'
    >>> g.x, g.y, g.name
    (1, 2, 'Bob')
    

As you can see, you can create and use Groups from Python and set them into the
namespace of a larch session and then access that data from the session::

    >>> from larch import Group
    >>> import numpy as np
    >>> mygroup = Group(a = 1, message='hello', x=np.linspace(-10, 10, 201))
    >>> session.symtable.frompy  = mygroup
    >>> session("print(frompy.message, len(frompy.x))")
    hello 201

This can make it very easy to embed a larch session (or more than one) into a
Python program and use it as a calculation engine.

     
The optional `_larch` argument
==========================================================


In earlier versions of larch, many functions in the Python interface required or
strongly recommended making a larch interpreter and passing this around as a
"session instance" to many of the larch functions.  That is, you might see::

    >>> from larch import Interreter
    >>> from larch.io import read_xdi

    >>> _larch = Interpreter()
    >>> dat = read_xdi('examples/xafsdata/fe3c_rt.xdi', _larch=_larch)  # not needed!

With version 0.9.49, this is no longer needed.  For backward compatibility, many
functions still have an optional `_larch` argument.  You may see this usage in
some existing code, but at this point, this is no longer needed or recommended.
    
     
Converting "Larch code" into Python
==========================================================

As discussed in more detail in the next section, the Larch macro language is
essentially a dialect of Python so that converting code from the macro language
into Python is nearly trivial.  The main differences between Python and the larch
macro language are described here.  Briefly, the differences are:

  1. `Larch language` is missing several constructs: `class`, `lambda`,
     generators, any asynchronous programming constructs.
     
  2. `Larch language` doe not use indentation.  Leading whitespace is ignored and
     blocks must be terminated with a matching `#endif`, `#endfor`, `#enddef`,
     `#endwhile`, or `#endtry`.

  3. `import` statements are not required for all of the built-in larch
     functionality, including large parts of `numpy` and `scipy`.  As is
     appropropriate for a domain-specific language, many functions are readily
     available, though they are organized in a namespace with look-up rules.
     From a Larch session, you can import and use Python modules.


Other than these changes, code in the `Larch language` *is* Python code (it is
parsed and evaluated using Python's language tools) and all Larch objects are
really Python objects. That means that converting Larch code into Python code
can be very easy, with the main steps being

   a. check indentation and `#end*` block terminators.
   b. make sure the import statements are correctly provided.


Note that if the code is properly indented and also uses `#end*` block
terminators that code can be both valid Python and Larch.  The examples in
the current document use this convention and have import statements
commented out at the top so that they can be easily run in Python or from
the Larch interpreter.
  

Larch submodules
============================

.. _lmfit:     https://lmfit.github.io/lmfit-py/
.. _xraydb:    https://xraypy.github.io/XrayDB/
.. _pyepics:   https://pyepics.github.io/pyepics/
.. _wxmplot:   https://newville.github.io/wxmplot/


The `larch` module is broken up into a number of submodules, as described
in the table and sections below.  To be clear, this list is incomplete and
subject to change.  The rest of this document should be used for details of
the functionality of the various modules and functions.

.. _pymodules_table:

**Table of the Larch Python Modules** This is an incomplete list of all the
Python modules available from `larch`, but should cover those that are most
useful to Python programmers.

   
  +--------------------------------+-----------------------------------------------------------+
  | module name                    |   Description                                             |
  +================================+===========================================================+
  | `larch`                        | top-level module, with Interpreter and applications       |
  +--------------------------------+-----------------------------------------------------------+
  | `larch.io`                     | input/output routines                                     |
  +--------------------------------+-----------------------------------------------------------+
  | `larch.xafs`                   | XAFS analysis and data processingd                        |
  +--------------------------------+-----------------------------------------------------------+
  | `larch.xray`                   | X-ray properties (with `xraydb`_)                         |
  +--------------------------------+-----------------------------------------------------------+
  | `larch.xrf`                    | X-ray fluorescenece processing and analysis               |
  +--------------------------------+-----------------------------------------------------------+
  | `larch.xrd`                    | X-ray diffraction processing                              |
  +--------------------------------+-----------------------------------------------------------+
  | `larch.xrmmap`                 | working with XRF/XRD microprobe maps                      |
  +--------------------------------+-----------------------------------------------------------+
  | `larch.fitting`                | Data fitting (with `lmfit`_)                              |
  +--------------------------------+-----------------------------------------------------------+
  | `larch.math`                   | General-purpose mathematical functions                    |
  +--------------------------------+-----------------------------------------------------------+
  | `larch.utils`                  | General-purpose utility functions                         |
  +--------------------------------+-----------------------------------------------------------+
  | `larch.epics`                  | using with Epics control system (with `pyepics`_)         |
  +--------------------------------+-----------------------------------------------------------+
  | `larch.xmlrpc_server`          | running a Larch server for other processes                |
  +--------------------------------+-----------------------------------------------------------+
  | `larch.shell`                  | command-line shell                                        |
  +--------------------------------+-----------------------------------------------------------+
  | `larch.wxlib`                  | Wx-python utilities (including `wxmplot`_ plotting)       |
  +--------------------------------+-----------------------------------------------------------+


Note that several of these modules (`xray`, `fitting`, `epics`, the plotting
functionality in `wxlib`) are fairly thin wrappers around other python libraries
that are generally well-documented and do not need to be used only from with
larch.  If you find yourself using these submodules, it might be easier to just
use the more general-purpose library.


Top-level `larch`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The top-level `larch` module contains several modules and a few important
classes and methods.  An incomplete list, but the most important objects in
the top-level module are:

.. class:: Interpreter

   class to build a Larch Interpreter	 

.. class:: Group
	   
   class to build a Larch Group

.. attribute:: site_config
	       
   a container (module) of site configuration information.
   

.. attribute:: is_from_python
	       
   a boolean value indicating whether this larch module has been imported
   into Python (True) or into a Larch Interpreter (False)
   

`larch.io`                     
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The `io` module contains functions for reading and writing data with known
formats.


`larch.xafs`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The `xafs` module contains functions for XAFS analysis.


`larch.xray`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The `xray` module contains functions for X-ray properties, as imported from `xraydb`_.


`larch.xrf`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~


The `xrf` module contains functions for X-ray fluorescence data.



`larch.xrd`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~


`larch.xrmmap`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~


`larch.fitting`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The `fitting` module contains functions for fitting data, including to
known lineshapes.  Much of this is taken directly from `lmfit`_ or modified
slightly for Larch.  If you're writing programs for fitting data, we do
recommend using `lmfit`_ directly.


`larch.math`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~


`larch.utils`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~


`larch.epics`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~


`larch.xmlrpc_server`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~


`larch.shell`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~


`larch.wxlib`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~


    
