[Ifeffit] Larch python instructions

Matt Newville newville at cars.uchicago.edu
Mon Apr 16 21:48:22 CDT 2018


Hi Imad,


On Mon, Apr 16, 2018 at 7:53 PM, Imad Ahmed <imad.ahmed at earth.ox.ac.uk>
wrote:

> Dear Matt,
>
> Thank you so much for your feedback. I’ve tested both the python and Larch
> scripts and they work absolutely fine. Although, I am able to work with the
> python route, I do like the Larch way!
>


Great!



> By the way, for a Larch script, how would you create plots in different
> windows? display = get_display(win=i); i = 1..n, following plot(), does not
> seem to work?
>


To plot in a new or different window, just add "win=N" to any of the
plot_*() functions, like

     plot(group.energy, group.mu, win=1)

     plot(group.r, group.chir_mag, win=2)

The windows are numbered starting with 1.   For common XAFS plots, see
http://xraypy.github.io/xraylarch/xafs/utilities.html#
plotting-macros-for-xafs   The usage in your earlier example could become

    plot_chik(path1, kweight=2, label = r'$\sigma^2 = 0$',
title=r'$\chi(k)$ from %s' % fname)

The `get_display(win=1)` function returns the PlotDisplay or wxPython Frame
object.  The most useful attribute of that is `panel` and its `axes` which
allows you to drill down to the matplotlib components.  I've tried to put
*most* of the functionality you'd need from matplotlib available from the
plot frame (especially from "configure plot") or from larch / wxmplot
functionality, but matplotlib is pretty vast, and if you're writing python
and know matplotlib you can get at it.   See, for example
    https://github.com/xraypy/xraylarch/blob/master/examples/plotting/nobox_
histogram.lar

which uses `get_display().panel.axes` to be able to plot a histogram with
matplotlib's `hist()` method.  It's meant for "advanced usage by python
programmers", so you might be interested....



>
> Out of interest how would you create the different paths from a cif file?
> e.g., similar to *.dat files in  ../xraylarch/examples/Feff_Cu. This does
> not seem possible using Atoms?
>


Atoms can turn CIF files into feff.inp files.  And then you can run feff6l
or feff85l to turn that into the feffNNNN.dat files. If some part of this
didn't work for you, please ask as a separate question.

Larch does use the very nice PyCifRW library but does not have full
capability to convert CIF into XYZ coordinates for feff.inp.  I am not
aware of any python package that does this, but there may very well be.
That functionality would be nice to add to Larch, but Atoms exists and does
a fine job.

--Matt



> Best wishes,
> Imad
>
>
>
>
> From: Matt Newville <newville at cars.uchicago.edu>
> <newville at cars.uchicago.edu>
> Reply: XAFS Analysis using Ifeffit <ifeffit at millenia.cars.aps.anl.gov>
> <ifeffit at millenia.cars.aps.anl.gov>
> Date: 16 April 2018 at 03:57:27
> To: Imad Ahmed <imad.ahmed at earth.ox.ac.uk> <imad.ahmed at earth.ox.ac.uk>, XAFS
> Analysis using Ifeffit <ifeffit at millenia.cars.aps.anl.gov>
> <ifeffit at millenia.cars.aps.anl.gov>
> Subject:  Re: [Ifeffit] Larch python instructions
>
> Hi Imad,
>
>
> On Sun, Apr 15, 2018 at 7:15 PM, Imad Ahmed <imad.ahmed at earth.ox.ac.uk>
> wrote:
>
>> Dear Matt,
>>
>> I am looking for some proper instructions on how to use Larch from
>> python.
>> I have larch installed on Anaconda2 and trying to run the
>> /examples/feffit/doc_feffdat1.lar script from python.
>> I tried the python code below but still having issues to run it,
>> especially with Feffpath and some larch plugins. Could you please help?
>>
>> Best wishes, Imad
>>
>>
>> import sys, os
>> import numpy as np
>> from scipy.optimize import leastsq as scipy_leastsq
>> import larch
>> from larch import Group, Parameter
>> from larch_plugins.io import read_ascii
>> from larch_plugins.xafs import FeffPathGroup
>> from larch_plugins.xafs.feffit import (TransformGroup,
>> FeffitDataSet,feffit, feffit_report)
>>
>> fname = ‘~/xraylarch/examples/feffit/feff0001.dat'
>> path1 = FeffPathGroup(fname)
>> path2chi(path1)
>> show(path1)
>> newplot(path1.k, path1.chi*path1.k**2, xlabel=r' $ k \rm\, (\AA^{-1})$',
>> ylabel=r'$ k^2\chi(k)$', label = r'$\sigma^2 = 0$', show_legend=True,
>> title=r'$\chi(k)$ from %s' % fname)
>> path1.sigma2 = 0.002
>> path2chi(path1)
>> plot(path1.k, path1.chi*path1.k**2, label = r'$\sigma^2 = 0.002$')
>>
>>
>>
> Well, there are some differences between Larch and Python.
>
> With some small modifications, your scaript can become a valid Larch
> script like this:
>       # larch
> from os.path import join, expanduser
> fname = join(expanduser(‘~'), '/xraylarch/examples/feffit/feff0001.dat')
> path1 = feffpath(fname)
>
>  path2chi(path1)
> show(path1)
> newplot(path1.k, path1.chi*path1.k**2, xlabel=r' $ k \rm\, (\AA^{-1})$',
> ylabel=r'$ k^2\chi(k)$', label = r'$\sigma^2 = 0$', show_legend=True,
> title=r'$\chi(k)$ from %s' % fname)
> path1.sigma2 = 0.002
> path2chi(path1)
> plot(path1.k, path1.chi*path1.k**2, label = r'$\sigma^2 = 0.002$')
>
>
> To do that from Python is a bit more involved.
>
> Each of the functions "feffpath", "path2chi", "show", "newplot", and
> "plot"  need to be translated.  As you probably say, "feffpath" is
> effectively `FeffPathGroup'.   The others are less obvious, and many of the
> larch functions really want to be passed a "larch session" so that they can
> find other larch function or data sources.  For example, FeffPathGroup
> needs a larch session in order to be able to look up atomic information.
>
> So in pure python that would be approximately:
>
>     import os
>     import os.path
>     import matplotlib.pyplot as plt   # using pyplot instead of build in
> plot commmands
>
>     from larch import Interpreter
>     from larch_plugins.xafs.feffdat import FeffPathGroup, _path2chi
>
>    # need to create a Larch interpreter for each "session"
>    _larch = Interpreter()
>
>     fname = os.path.join(os.path.expanduser("~"),
> "Codes/xraylarch/examples/feffit/feff0001.dat")
>
>     # note that many of the Larch functions will want a `_larch` instance
> passed in.
>     path1 = FeffPathGroup(fname, _larch=_larch)
>
>    _path2chi(path1, _larch=_larch)
>
>     # show, approximately
>     for attr in dir(path1):
>         print(attr, getattr(path1, attr))
>
>     # plot, approximately
>     plt.plot(path1.k, path1.chi*path1.k**2, label= r'$\sigma^2 = 0$')
>
>     path1.sigma2 = 0.002
>    _path2chi(path1, _larch=_larch)
>
>     plt.plot(path1.k, path1.chi*path1.k**2, label = r'$\sigma^2 = 0.002$')
>
>     plt.xlabel(r' $ k \rm\, (\AA^{-1})$')
>     plt.ylabel(r'$ k^2\chi(k)$')
>     plt.title(r'$\chi(k)$ from %s' % fname)
>
>     plt.legend()
>     plt.show()
>
>
> But also, since you have to build a Larch Interpreter, you could simply
> use it to execute the previous Larch script:
>
>
>     from larch import Interpreter
>
>    text = '''
>       # larch
> from os.path import join, expanduser
> fname = join(expanduser(‘~'), '/xraylarch/examples/feffit/feff0001.dat')
> path1 = feffpath(fname)
>
>  path2chi(path1)
> show(path1)
> newplot(path1.k, path1.chi*path1.k**2, xlabel=r' $ k \rm\, (\AA^{-1})$',
> ylabel=r'$ k^2\chi(k)$', label = r'$\sigma^2 = 0$', show_legend=True,
> title=r'$\chi(k)$ from %s' % fname)
> path1.sigma2 = 0.002
> path2chi(path1)
> plot(path1.k, path1.chi*path1.k**2, label = r'$\sigma^2 = 0.002$')
> '''
>     _larch = Interpreter()
>     _larch.run(text)
>
> The latter approach is highly recommended.
>
> --Matt Newville
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