Skip to main content

pygidSIM

pygidSIM calculates GIWAXS patterns from CIF files or other crystal structure descriptions.

GIDSIM

Installation

Install from PyPi

pip install pygidsim

Install from source

First, clone the repository:

git clone https://github.com/mlgid-project/pygidSIM.git

Then, to install all required modules, navigate to the cloned directory and execute:

cd pygidSIM
pip install -e .

Development Installation

For development and testing, install with development dependencies:

pip install -e .[dev]

Testing

The project uses pytest for testing. To run the test suite:

# Run all tests
pytest

# Run tests with coverage report
pytest --cov=pygidsim --cov-report=html

# Run tests in parallel
pytest -n auto

Usage

From CIF

To calculate the peak positions and their intensities in 2D GIWAXS pattern (qxy, qz) from a CIF file with the default orientation hkl = [001] (vector normal to the substrate, i.e. {001} contact plane) run the following:

from pygidsim import ExpParameters, GIWAXSFromCif

params = ExpParameters(
    q_xy_range=(0, 2.7),
    q_z_range=(0, 2.7),
    en=18000
)  # experimental parameters
el = GIWAXSFromCif(path_to_cif, params)
q_2d, intensity = el.giwaxs.giwaxs_sim()  # q_2d is array with shape (2, peaks number)

To add a crystal rotation use the argument orientation with the value "random" or a list containing the corresponding Miller indices [hkl]:

q_2d, intensity = el.giwaxs.giwaxs_sim(orientation='random')

q_2d, intensity = el.giwaxs.giwaxs_sim(orientation=[2., 0., 1.])

To move the peaks from the missing wedge to the visible area use the argument move_fromMW:

q_2d, intensity = el.giwaxs.giwaxs_sim(orientation=[2., 0., 1.], move_fromMW=True)

For 3D powder diffraction simulation (non-oriented case) use orientation=None:

q_1d, intensity_1d = el.giwaxs.giwaxs_sim(orientation=None)

To return the Miller indices, you can use the argument return_mi = True:

q_2d, intensity, mi = el.giwaxs.giwaxs_sim(return_mi=True)

To restrict the maximum Miller index for simulation use the argument max_mi:

q_2d, intensity = el.giwaxs.giwaxs_sim(max_mi=3)

Crystal description

To calculate a GIWAXS pattern from your own description, use the following example:

from pygidsim import GIWAXS, Crystal

# space group number
spgr = 221  # alternatively, use e.g. '146:R'

# lattice parameters [a, b, c, α, β, γ]
lat_par = [6.3026, 6.3026, 6.3026, 90., 90., 90.]

# list of atoms
atoms = ['Pb', 'I', 'I', 'I', 'N']

# relative atom positions
atom_positions = [[0., 0., 0.],
                  [0.5, 0., 0.],
                  [0., 0.5, 0.],
                  [0., 0., 0.5],
                  [0.5, 0.5, 0.5]]

# occupancies of the corresponding sites
occupancy = [1., 1., 1., 1., 1.]

cr = Crystal(lat_par, spgr, atoms, atom_positions, occupancy)
el = GIWAXS(cr, params)
q_2d, intensity = el.giwaxs_sim(orientation='random')

The intensities are set to one in case the arguments atoms or/and atom_positions are not provided.

Visualization

One can visualize a GIWAXS pattern using matplotlib:

import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable

fig, ax = plt.subplots(figsize=(5, 5))
ax.set_aspect('equal')
scatter = ax.scatter(*q_2d, c=intensity, cmap='Reds')

ax.set_xlabel(r'$q_{xy}$ $(Å^{-1})$', fontsize=18)
ax.set_ylabel(r'$q_{z}$ $(Å^{-1})$', fontsize=18)

divider = make_axes_locatable(ax)

# Append a new axes for the color bar to the right of the current axes
cax = divider.append_axes("right", size="5%", pad=0.05)

# Create color bar in the new axes
colorbar = fig.colorbar(scatter, cax=cax)
colorbar.set_label('Intensity')

plt.show()

Citation

If you use this package in your research, please cite it as follows:

Romodin, M., Starostin, V., Lapkin, D., Hinderhofer, A., & Schreiber, F. (2025).
mlgid-project/pygidSIM: v0.1.1. Zenodo. https://doi.org/10.5281/zenodo.17609569

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pygidsim-0.1.7.tar.gz (38.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pygidsim-0.1.7-py3-none-any.whl (32.4 kB view details)

Uploaded Python 3

File details

Details for the file pygidsim-0.1.7.tar.gz.

File metadata

  • Download URL: pygidsim-0.1.7.tar.gz
  • Upload date:
  • Size: 38.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.9

File hashes

Hashes for pygidsim-0.1.7.tar.gz
Algorithm Hash digest
SHA256 d535c60d11b76dc88109334a45cef5b174765855d7cb67d2c46329c0cd5242d9
MD5 16f4fc897e33ec83ae0c1a37688745ba
BLAKE2b-256 0bcd34cefa89211c8e36fd9fb5e9af8a7e69f4ac8b5e41134a9609609a99d13c

See more details on using hashes here.

File details

Details for the file pygidsim-0.1.7-py3-none-any.whl.

File metadata

  • Download URL: pygidsim-0.1.7-py3-none-any.whl
  • Upload date:
  • Size: 32.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.9

File hashes

Hashes for pygidsim-0.1.7-py3-none-any.whl
Algorithm Hash digest
SHA256 86ab65956a4ea22fd05c94dccf3fbcdb187e793fcdf62df902905d7625ad1c21
MD5 12201d849098e185b488c9d6e9b9fee6
BLAKE2b-256 8c8f6f2ee8672bdfa56cc997ae24a21779c50c5a2767cc860fe023f92530fa24

See more details on using hashes here.

Release history Release notifications | RSS feed

This release

0.1.7 This release

2 files

0.1.6

2 files

0.1.5

2 files

0.1.4

2 files

0.1.3

2 files

0.1.2

2 files

0.1.1

2 files

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page