Skip to main content

Irreducible Brillouin zone symmetry and interpolation.

Project description

brille

A C++ library for symmetry operations and linear interpolation within an irreducible part of the first Brillouin zone. Wrapped for use in python using pybind11.

irreducible polyhedron

When provided with the lattice parameters or basis vectors of a real space spacegroup and its Hall symbol or number as determined by, e.g., Spglib, brille can

  • construct the first Brillouin zone
  • determine its high symmetry points
  • find a irreducible polyhedron and verify that its conforms to the pointgroup symmetry of the spacegroup.

Constructing and irreducible Brillouin zone polyhedron for a face centered cubic lattice can be accomplished with, e.g.,

	import brille

	direct_lattice = brille.Direct((4.96, 4.96, 4.96), (90, 90, 90), 'Fd-3m')
	brillouin_zone = brille.BrillouinZone(direct_lattice.star)

interpolation

Interpolating eigenvalues and eigenvectors across a degenerate point could lead to misidentified equivalent modes. Since the eigenvectors are distinguishable at all points away from the high-symmetry directions, a hybrid orthogonal/triangulated grid defined in an irreducible part of the Brillouin zone can be used to avoid mode misidentification.

brille can construct

  • an orthogonal grid guaranteed to contain the first Brillouin zone
  • a triangulated set of points filling an irreducible polyhedron or the first Brillouin zone
  • or a hybrid orthogonal/triangulated grid where only the surface cells are triangulated to improve point location time while preserving polyhedral conformity.

Of these options the third is most appropriate for the interpolation of models used in the analysis of inelastic neutron scattering data is the hybrid grid.

Dependencies

TetGen

A modified version of TetGen is used to create refined tetrahedral meshes in the irreducible portion of the first Brillouin zone.

The modified version is included as part of this repository.

Installation

From the root folder of this repository use Python 3 to build and install this library.

python setup.py install

Alternatively, the python module, C++ library, and catch2 based tests can be built directly using cmake.

Project details


Download files

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

Source Distribution

brille-0.5.3.tar.gz (1.4 MB view details)

Uploaded Source

Built Distributions

brille-0.5.3-cp38-cp38-win_amd64.whl (889.5 kB view details)

Uploaded CPython 3.8 Windows x86-64

brille-0.5.3-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.12+ x86-64

brille-0.5.3-cp38-cp38-macosx_10_15_x86_64.whl (1.2 MB view details)

Uploaded CPython 3.8 macOS 10.15+ x86-64

brille-0.5.3-cp37-cp37m-win_amd64.whl (884.4 kB view details)

Uploaded CPython 3.7m Windows x86-64

brille-0.5.3-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.12+ x86-64

brille-0.5.3-cp37-cp37m-macosx_10_15_x86_64.whl (1.2 MB view details)

Uploaded CPython 3.7m macOS 10.15+ x86-64

brille-0.5.3-cp36-cp36m-win_amd64.whl (884.3 kB view details)

Uploaded CPython 3.6m Windows x86-64

brille-0.5.3-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.12+ x86-64

brille-0.5.3-cp36-cp36m-macosx_10_15_x86_64.whl (1.2 MB view details)

Uploaded CPython 3.6m macOS 10.15+ x86-64

File details

Details for the file brille-0.5.3.tar.gz.

File metadata

  • Download URL: brille-0.5.3.tar.gz
  • Upload date:
  • Size: 1.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.8.11

File hashes

Hashes for brille-0.5.3.tar.gz
Algorithm Hash digest
SHA256 df71b372f4cca1add73cee1e4e7d8f5fd74b3036ae940757545a6c943977c586
MD5 bf0ce0b118f77153efefadbaeefde2d2
BLAKE2b-256 2937ccdfebccaa145470e2f0956790d8ac05570bb84dc5921c69f2d2676bc6b7

See more details on using hashes here.

File details

Details for the file brille-0.5.3-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: brille-0.5.3-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 889.5 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.8.10

File hashes

Hashes for brille-0.5.3-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 62cd00032c13f3e6fd96910d2b07eb8a21bb0efa160f8a0e02c271ecf95b193f
MD5 abe48e80bec6774f573473d01c41d2e8
BLAKE2b-256 c87f56318ebda679fe4325dbc51417c40e6b87d189ed3e1f86d002e4b1110e94

See more details on using hashes here.

File details

Details for the file brille-0.5.3-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for brille-0.5.3-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 f3314e1926823886c5c214a858c6cadab605cff1833ff486ad4bdc6859186635
MD5 c044abbfd6b1b9ee59d9e94518d84d56
BLAKE2b-256 9aa7f9b24e09b6784a727f5468fdc0ea64dc2f61f9d7bd4dae6d44f385a3ecbc

See more details on using hashes here.

File details

Details for the file brille-0.5.3-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

  • Download URL: brille-0.5.3-cp38-cp38-macosx_10_15_x86_64.whl
  • Upload date:
  • Size: 1.2 MB
  • Tags: CPython 3.8, macOS 10.15+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.8.11

File hashes

Hashes for brille-0.5.3-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 18ae512f429832fcbaa892f6360995938c121fbf0928437dba7cacff9445be27
MD5 5adbaf589f9973e7f10fe12366cd7c96
BLAKE2b-256 cff70519b50b242517660286716a84e8528d358d7248611b45427667ef3b8516

See more details on using hashes here.

File details

Details for the file brille-0.5.3-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: brille-0.5.3-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 884.4 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.7.9

File hashes

Hashes for brille-0.5.3-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 0859cd41109af91165efa76786d7140cb652dea09bf0f4e6d2e35ecd3a6a182d
MD5 7fb3c369f3c55a82b9d06eaecacd6df8
BLAKE2b-256 052caa4220f5e2c41a81dfb0ddb355fcd30d22e8209575913914f25ae1c49fa3

See more details on using hashes here.

File details

Details for the file brille-0.5.3-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for brille-0.5.3-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 77515d1151e5ffa08e8b8eec9b6666cc79c786244ab600cbc3350bf4740daca7
MD5 a51b46ec9578fbff89686e7540d569e8
BLAKE2b-256 a23f6d762c6e4ff5604a81e5f4ce86ae4ac626e9e68781117d21142d60ea9725

See more details on using hashes here.

File details

Details for the file brille-0.5.3-cp37-cp37m-macosx_10_15_x86_64.whl.

File metadata

  • Download URL: brille-0.5.3-cp37-cp37m-macosx_10_15_x86_64.whl
  • Upload date:
  • Size: 1.2 MB
  • Tags: CPython 3.7m, macOS 10.15+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.7.11

File hashes

Hashes for brille-0.5.3-cp37-cp37m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 72f57299147d3b6db9052aa0780affb421044b3cd12b6672de18b2b49b255083
MD5 9cc80205a06df033ae1a86af4fe48e87
BLAKE2b-256 97db3c29d3cfb1b152fe49a3ae5e766cb2898a9d87ccb9c582bfa7b9dadd5f60

See more details on using hashes here.

File details

Details for the file brille-0.5.3-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: brille-0.5.3-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 884.3 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.6.8

File hashes

Hashes for brille-0.5.3-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 aa41999873ea3ea2ba57508c393ad30144afd4b672aa8e5fe76dc95bbc9f9364
MD5 fe944f59b12c2281b3739f554731d548
BLAKE2b-256 663387d0cc379e29eb72ab2fd58c3d2b14390ff1bad4cf1924dddcac8971e96c

See more details on using hashes here.

File details

Details for the file brille-0.5.3-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for brille-0.5.3-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 f9a4d18e79e4c8c1508f39796c5f3054c18ac9a6e1dc520ae3f89e4b9fea02d7
MD5 6eef7abd598ecf525528a7710759c2d0
BLAKE2b-256 e05c169bc174c6fa9acf05e701edd0f6d0cff776ca12d7b108402b6e6e3c7dfd

See more details on using hashes here.

File details

Details for the file brille-0.5.3-cp36-cp36m-macosx_10_15_x86_64.whl.

File metadata

  • Download URL: brille-0.5.3-cp36-cp36m-macosx_10_15_x86_64.whl
  • Upload date:
  • Size: 1.2 MB
  • Tags: CPython 3.6m, macOS 10.15+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.6.14

File hashes

Hashes for brille-0.5.3-cp36-cp36m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 a005cabd9b988b7918aec8f6515eae4dabb6559946a1d588b024ea2111c845a8
MD5 cfcbbae043183ecb74f987dfbef0f283
BLAKE2b-256 4b80fcd25b08d7ddc3d7ec7a36888aa58b16e90837098e4d01db7804856b4ae1

See more details on using hashes here.

Supported by

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