Welcome to fplore’s documentation!

Indices and tables

Introduction

This library is meant to help make data evaluation of FPLO runs easier by supplying easy ways to load FPLO data and by offering some convenience functionality.

You can take a look at some examples here.

There are various ways of accessing your FPLO run data within fplore.

  1. Load the data in the scope of an FPLO run

  2. Load the data directly

Usually, number one would be preferable, as it would for example allow you to apply the symmetry operations from the symmetry group stated in the =.in file automatically to other data.

Usage method 1

With this method we will specify the FPLO run directory.

For example, the following will automatically load band data from +band or +band_kp, whichever is available. It will also process all k-points, so they lie within the first Brillouin zone.

from fplore import FPLORun
run = FPLORun("/home/jdoe/fplo_run/")
band_data = run.band.data

You can also specify the filename directly.

band_data = run['+band_kp'].data

For example, you can access arbitrary configuration settings from your =.in like so:

In [3]: run["=.in"].sections
Out[3]: dict_keys(['header', 'structure_information', 'structure_dependend', 'mesh', 'brillouin', 'bandstructure_plot', 'iteration_control', 'forces', 'options', 'cpa', 'numerics', 'LSDA_U', 'OPC', 'Advanced_output'])

In [4]: run["=.in"].structure_information
Out[4]: {'structure_type': {'type': 1, 'description': 'Crystal'}, 'spacegroup': {'number': 139, 'symbol': 'I4/MMM'}, 'subgroupgenerators': [], 'lengthunit': {'type': 2, 'description': 'Angstroem'}, 'lattice_constants': [4.0345, 4.0345, 9.828], 'axis_angles': [90.0, 90.0, 90.0], 'max_L': 4, 'nsort': 3, 'wyckoff_positions': [{'element': 'Yb', 'tau': [0, 0, 0]}, {'element': 'Ir', 'tau': [Fraction(1, 2), 0, Fraction(-1, 4)]}, {'element': 'Si', 'tau': [0, 0, 0.3807989986]}]}

In [5]: run["=.in"].structure_information.lengthunit.description
Out[5]: 'Angstroem'

Usage method 2

If you just want to use fplore to load the raw data of some file and nothing more, you can manually load a file by running

from fplore.files import FPLOFile
band = FPLOFile.load("/home/jdoe/fplo_run/+band)
raw_band_data = band.data

Which will automatically pick the correct loader class based on the filename. If the files are renamed and this fails, you can manually specify the loader class. See fplore.files.base.FPLOFile.registry for the appropriate loader class. For example:

from fplore.files import Band
band = Band("/home/jdoe/fplo_run/+band_old")
raw_band_data = band.data

Some FPLORun properties (excerpt)

In [1]: run.spacegroup_number
Out[1]: 139
In [2]: run.spacegroup
Out[2]: <pymatgen.symmetry.groups.cached_class.<locals>._decorated object at 0x7ff1609ca668>
In [3]: run.lattice
Out[3]: Lattice
    abc : 4.0345 4.0345 9.828
 angles : 90.0 90.0 90.0
 volume : 159.97222577700003
      A : 4.0345 0.0 2.4704187555799985e-16
      B : 6.48797083012039e-16 4.0345 2.4704187555799985e-16
      C : 0.0 0.0 9.828
In [4]: run.structure
Out[4]: Structure Summary
Lattice
    abc : 4.0345 4.0345 9.828
 angles : 90.0 90.0 90.0
 volume : 159.97222577700003
      A : 4.0345 0.0 2.4704187555799985e-16
      B : 6.48797083012039e-16 4.0345 2.4704187555799985e-16
      C : 0.0 0.0 9.828
PeriodicSite: Yb (0.0000, 0.0000, 0.0000) [0.0000, 0.0000, 0.0000]
PeriodicSite: Yb (2.0173, 2.0173, 4.9140) [0.5000, 0.5000, 0.5000]
PeriodicSite: Ir (2.0173, 0.0000, 7.3710) [0.5000, 0.0000, 0.7500]
PeriodicSite: Ir (0.0000, 2.0173, 7.3710) [0.0000, 0.5000, 0.7500]
PeriodicSite: Ir (2.0173, 0.0000, 2.4570) [0.5000, 0.0000, 0.2500]
PeriodicSite: Ir (0.0000, 2.0173, 2.4570) [0.0000, 0.5000, 0.2500]
PeriodicSite: Si (0.0000, 0.0000, 3.7425) [0.0000, 0.0000, 0.3808]
PeriodicSite: Si (0.0000, 0.0000, 6.0855) [0.0000, 0.0000, 0.6192]
PeriodicSite: Si (2.0173, 2.0173, 8.6565) [0.5000, 0.5000, 0.8808]
PeriodicSite: Si (2.0173, 2.0173, 1.1715) [0.5000, 0.5000, 0.1192]

Running the examples

You can run the examples in the examples subdirectory by running them as a module, for example python -m examples.band_plot.