Skip to main content

SOVA (Structural Order Visualization and Analysis) with python

Project description

SOVApy (Structural Order Viaualization and Analysis with Python)

SOVA can be installed in Windows, MacOS and Linux.
(The package name to be imported is "sovapy".)

Install from PyPI

pip install sovapy

Build and Install sovapy

  1. Clone the SOVA repo
git clone https://github.com/MotokiShiga/sova-cui.git

And move to the downloaded directory

cd sova-cui
  1. To compile and to generate so or dll files, run
    for macos and linux
bash run_install_mac_linux.sh

For windows, use "x64 Native Tools Command Prompt for Visual Studio 2022" to run

install_win.bat
  1. To install SOVA, run
pip install .  

For the usage, see example codes in the directory 'examples'.

Environment

Major packages used for our development

Package Version
Python 3.11 - 3.13
ase 3.22.1
h5py 3.13.0
igraph 0.11.3
matplotlib 3.10.0
networkx 3.1
numpy 2.1.0
PyCifRW 5.0.0
scipy 1.15.2
spglib 2.0.2

The versions of other packages can be found in requirements.txt.

You can make the virtual environment for sova by

python -m venv sova-cui
source sova-cui/bin/activate
pip install --upgrade pip
pip install -r requirements.txt

Acknowledgements

SOVA reuses source codes of the following package:

Examples

0_all_analysis  : All analysis and saving results in a hdf5
1_pdf_xyz       : PDF analysis from xyz file (amorphous SiO2)
2_pdf_cif       : PDF analysis from xyz file (beta-cristobalite)
3_pdf_cfg       : PDF analysis from cfg file generated by RMC++ (amorphous SiO2)
4_coordination  : Coordination number analysis (amorphous SiO2)
5_bond_angle    : Bond angle analysis (amorphous SiO2)
6_tetra_order   : Tetrahedral order analysis (q-value) (amorphous SiO2)
7_ring          : Ring analysis  (beta-cristobalite)
8_cavity        : Cavity analysis (amorphous SiO2)
9_save_result   : Save and load calculated results

Citation

We are preaparing a manuscript for this package. Before the publication, you should cite this url and the following papers. If you have implemented ring analysis, please cite the original papers of ring definitions (Guttman, King, and Primitive) and our paper:
[1] M. Shiga, A. Hirata, Y. Onodera, H. Masai, Ring-originated anisotropy of local structural ordering in amorphous and crystalline silicon dioxide. Commun. Mater. 4, 91 (2023). https://doi.org/10.1038/s43246-023-00416-w

For cavity analysis, please cite
[2] I. Meyer, F. Rhiem, F. Beule, D. Knodt, J. Heinen, R. O. Jones, pyMolDyn: Identification, structure, and properties of cavities/vacancies in condensed matter, J. Comput. Chem., 38, 389–394 (2017). https://doi.org/10.1002/jcc.24697

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

sovapy-0.8.0-cp313-cp313-win_amd64.whl (299.6 kB view details)

Uploaded CPython 3.13Windows x86-64

sovapy-0.8.0-cp313-cp313-manylinux1_x86_64.whl (318.1 kB view details)

Uploaded CPython 3.13

sovapy-0.8.0-cp313-cp313-macosx_14_0_arm64.whl (282.3 kB view details)

Uploaded CPython 3.13macOS 14.0+ ARM64

sovapy-0.8.0-cp312-cp312-win_amd64.whl (299.6 kB view details)

Uploaded CPython 3.12Windows x86-64

sovapy-0.8.0-cp312-cp312-manylinux1_x86_64.whl (317.9 kB view details)

Uploaded CPython 3.12

sovapy-0.8.0-cp312-cp312-macosx_14_0_arm64.whl (282.3 kB view details)

Uploaded CPython 3.12macOS 14.0+ ARM64

sovapy-0.8.0-cp311-cp311-win_amd64.whl (299.5 kB view details)

Uploaded CPython 3.11Windows x86-64

sovapy-0.8.0-cp311-cp311-manylinux1_x86_64.whl (316.4 kB view details)

Uploaded CPython 3.11

sovapy-0.8.0-cp311-cp311-macosx_14_0_arm64.whl (282.3 kB view details)

Uploaded CPython 3.11macOS 14.0+ ARM64

File details

Details for the file sovapy-0.8.0-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: sovapy-0.8.0-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 299.6 kB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for sovapy-0.8.0-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 137ee34fe8cf1fca5935779ebe4f535d7882c25f1ea4b2134285afbb6e32f986
MD5 60201e3366dc111f60fe89fc58e10503
BLAKE2b-256 0085c84d9aaef17c0a8d42641cb1746d02eb27b9350abc7ffcf2850e0e668768

See more details on using hashes here.

File details

Details for the file sovapy-0.8.0-cp313-cp313-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for sovapy-0.8.0-cp313-cp313-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 d3adf3ebedf609954cd163280cc884fa5e279fa3045fa4bfae384ced856b7148
MD5 6390c847c10bea7481965c3ec50b7f66
BLAKE2b-256 a02fffa6d9aca2d20976d77154b6749668a8b9f901dd32d78050c1529b6a8475

See more details on using hashes here.

File details

Details for the file sovapy-0.8.0-cp313-cp313-macosx_14_0_arm64.whl.

File metadata

File hashes

Hashes for sovapy-0.8.0-cp313-cp313-macosx_14_0_arm64.whl
Algorithm Hash digest
SHA256 3f120134b0492d0d141d07674c66d135da9d3631e92459995c8a1c350fb0cc40
MD5 6540717fe292dbe1b434d0cdc815c527
BLAKE2b-256 4fa736cb035dc3eaf337cf7a7d266950172b575996244f3449e96a84e1710e8a

See more details on using hashes here.

File details

Details for the file sovapy-0.8.0-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: sovapy-0.8.0-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 299.6 kB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for sovapy-0.8.0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 fd6d051b7dd3b50908aeb34fe7ebb62e37316e943c040848016d2a34f98af812
MD5 1b01dc0210fa7afda8dba5d4eb8d027a
BLAKE2b-256 a9d6ce1076f7e5a481f048e836db5b4eb5ca3017494cd71ea156692e11ca2882

See more details on using hashes here.

File details

Details for the file sovapy-0.8.0-cp312-cp312-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for sovapy-0.8.0-cp312-cp312-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 ade01a19ca6c514c9c3e4ed5a843eb5a4b5ba14d57e5797ab5e3af92c4c9ad78
MD5 a7c0f1eeec34c47864599b513cf777d9
BLAKE2b-256 dd1ebd6a2f61eff62c4bbabed63add5c333d30fe87516d4522d12a417a03c0cd

See more details on using hashes here.

File details

Details for the file sovapy-0.8.0-cp312-cp312-macosx_14_0_arm64.whl.

File metadata

File hashes

Hashes for sovapy-0.8.0-cp312-cp312-macosx_14_0_arm64.whl
Algorithm Hash digest
SHA256 7c7b55c5f60b7c284c7a1e4ac72935d353de3cc39322d8d3e2bc91422bb1cd61
MD5 f4639d05e51f995bc2e186a5905aa707
BLAKE2b-256 eea2c97e2f9bf3272263145a62f6a2b1d6115b2c2b7fbf267e37dc1507657641

See more details on using hashes here.

File details

Details for the file sovapy-0.8.0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: sovapy-0.8.0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 299.5 kB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for sovapy-0.8.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 4c390f2bd79bb309a9f94199ed3f48818bbbe76bd0f8a893f9cbac5aa7a3f3bd
MD5 7cc09f1d7209c0e714e9fec2941453de
BLAKE2b-256 cbbc9570fab656d822e9eec4808204cb75a08c0e195f79a689cb0db4ef4206dd

See more details on using hashes here.

File details

Details for the file sovapy-0.8.0-cp311-cp311-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for sovapy-0.8.0-cp311-cp311-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 c3ae58683531d39e87794bcada2d5421d488732c527f081067088f6ad28a8beb
MD5 7b3fd4ee654fb12e6d5be261713cb584
BLAKE2b-256 3105d9561b040a05d63e19b5027172e124a143e4bd20079f44f546b56b8ea64c

See more details on using hashes here.

File details

Details for the file sovapy-0.8.0-cp311-cp311-macosx_14_0_arm64.whl.

File metadata

File hashes

Hashes for sovapy-0.8.0-cp311-cp311-macosx_14_0_arm64.whl
Algorithm Hash digest
SHA256 b177692b4fd1caf60d4d767dc2ea2f406c9cda2f7addad59c2b34eab6f63ded8
MD5 08b4acf9f601234ce842c5bd824ee675
BLAKE2b-256 661a4d8476f299737872370ea5e98f7beda3009781c4c15d59710ddef2c5e90a

See more details on using hashes here.

Supported by

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