Skip to main content

"T-matrix scattering code for nanophotonic computations"

Project description

Version PyPI License build docs doctests tests coverage

treams

The package treams provides a framework to simplify computations of the electromagnetic scattering of waves at finite and at periodic arrangements of particles based on the T-matrix method.

Installation

Installation using pip

To install the package with pip, use

pip install treams

If you're using the system wide installed version of python, you might consider the --user option.

Documentation

The documentation can be found at https://tfp-photonics.github.io/treams.

Publications

When using this code please cite:

D. Beutel, I. Fernandez-Corbaton, and C. Rockstuhl, treams - A T-matrix scattering code for nanophotonic computations, arXiv (preprint), 2309.03182 (2023).

Other relevant publications are

Features

  • T-matrix calculations using a spherical or cylindrical wave basis set
  • Calculations in helicity and parity (TE/TM) basis
  • Scattering from clusters of particles
  • Scattering from particles and clusters arranged in 3d-, 2d-, and 1d-lattices
  • Calculation of light propagation in stratified media
  • Band calculation in crystal structures

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

treams-0.4.1.tar.gz (1.9 MB view details)

Uploaded Source

Built Distributions

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

treams-0.4.1-cp311-cp311-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.11Windows x86-64

treams-0.4.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (6.2 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64

treams-0.4.1-cp311-cp311-macosx_10_9_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.11macOS 10.9+ x86-64

treams-0.4.1-cp310-cp310-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.10Windows x86-64

treams-0.4.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.8 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

treams-0.4.1-cp310-cp310-macosx_10_9_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.10macOS 10.9+ x86-64

treams-0.4.1-cp39-cp39-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.9Windows x86-64

treams-0.4.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.8 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

treams-0.4.1-cp39-cp39-macosx_10_9_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

treams-0.4.1-cp38-cp38-win_amd64.whl (1.5 MB view details)

Uploaded CPython 3.8Windows x86-64

treams-0.4.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.9 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64

treams-0.4.1-cp38-cp38-macosx_10_9_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.8macOS 10.9+ x86-64

File details

Details for the file treams-0.4.1.tar.gz.

File metadata

  • Download URL: treams-0.4.1.tar.gz
  • Upload date:
  • Size: 1.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for treams-0.4.1.tar.gz
Algorithm Hash digest
SHA256 990283851bf83701589b5028042316e77052fe54f8500b61e10b39a1ff7bcd34
MD5 af53434e2817827524b8a7fd98dd95ad
BLAKE2b-256 53aa5d8e171f451f4026722a8ef476a016da595fe7d206f7555297d547114961

See more details on using hashes here.

File details

Details for the file treams-0.4.1-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: treams-0.4.1-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for treams-0.4.1-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 da06b8d29d3c729c5cf2483a492544344182f3f5fc0afffc90299d445f01d1b8
MD5 8720a3715a9983e3680923ac9d69f53b
BLAKE2b-256 bfd433bd6df811b575f46427fde967c5cfa0b1bf5c625e3321c183070c576ba3

See more details on using hashes here.

File details

Details for the file treams-0.4.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for treams-0.4.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6a4c3bef33f3adb433675ed3666b5da2c5e386930aa9be77d82144c237f07860
MD5 a26556a7d6c55d2658ab4572876ba75d
BLAKE2b-256 18d556acb95701db54503bc3307bc8c5d4e4b5a8d1926c94f3d1020f28241d18

See more details on using hashes here.

File details

Details for the file treams-0.4.1-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for treams-0.4.1-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 27ded9dbf5b2735184bd4e002b3c4eb1e77d083791473045a23856d8dd153795
MD5 fa0a85d3c3fa36e7d8c636e8558c9216
BLAKE2b-256 f3fbc7b102b8c2b77f52f1ec780813d324b0615e7a2f23b540d0293ad9057921

See more details on using hashes here.

File details

Details for the file treams-0.4.1-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: treams-0.4.1-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for treams-0.4.1-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 04e3e1331c14b74c271f5a82bc50bedf6c3cb3f40745e649be049cbd818fe4f0
MD5 056f8addff994e5e132a1f2d59288850
BLAKE2b-256 537cf1b750faab89dc42d271cc15ccc1ca67d0c265ff4ca5fc0fc1403702593b

See more details on using hashes here.

File details

Details for the file treams-0.4.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for treams-0.4.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c74d129b943c0b506bdcf7a80e191e89a1c8bebbde58d39d969d7cf277c64889
MD5 410a5ec5efbdf84fba7258c353f2e3f7
BLAKE2b-256 e5f9fc5e13810084e002b0ac1355301cb2ff8867489f7db2ad02f70eef1d0e9f

See more details on using hashes here.

File details

Details for the file treams-0.4.1-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for treams-0.4.1-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 871940b6eb8eb704710ad22304522ae56f3bc83b1c7521d0113f2ee18b5cf46a
MD5 762c1200981a904b314c4d352998de88
BLAKE2b-256 52cc948ae7fbe83ee7cf9fa36f7f6c84b8519a2a4f17a82318a104596f12f99a

See more details on using hashes here.

File details

Details for the file treams-0.4.1-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: treams-0.4.1-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for treams-0.4.1-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 64d527ae3355be1507cf6050de85d13b7a0e2f5174ca9066c9ab751e1c913c66
MD5 4ef61c9fa11992d916762406fcd5e9b1
BLAKE2b-256 58c8c180b2faeb94f9c61c0b96ac7124374d182decf89f5dcbf1d41ced6b7fe4

See more details on using hashes here.

File details

Details for the file treams-0.4.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for treams-0.4.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2e87be0b0ffae23b6fb49a3817d5bea50444dae01ceb7aa963f554056b112411
MD5 b587b09d25612562378b7ed6dceb6886
BLAKE2b-256 a8cee9b8f19a0a5a80abbaad3673f3bf2bc39ba2ea3658babcddc7a15d8d0833

See more details on using hashes here.

File details

Details for the file treams-0.4.1-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for treams-0.4.1-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 2babff2f95b05ccf8cc2993d3565c1a3af763c92c02737afbd5bfe305fbee907
MD5 63c0270917c21fad1f56cb397894d142
BLAKE2b-256 a2cec184b7b42db9f529d8cbdb3de246aa09e81fae62824ed984ccbb3d272f1a

See more details on using hashes here.

File details

Details for the file treams-0.4.1-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: treams-0.4.1-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 1.5 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for treams-0.4.1-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 efe545e5cfeacd200f5770b926daa5bde0fda3c256f4d10b594c91ea0ffb03ab
MD5 62b3cbf74a98b5f4f1cd5b633799af12
BLAKE2b-256 285964a8ce1e558ede11a7818d2e1af1f4ac78de6060e0442f2c2fc20456e16e

See more details on using hashes here.

File details

Details for the file treams-0.4.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for treams-0.4.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c5f865de7e33c01ca782f9842332470f508593d6c31cb1dcdb37d6166b135f34
MD5 60449840d27613121160780176cc48ff
BLAKE2b-256 704a2c6881bb6a18d95997c3713206080b1facbf45d464fd6f19772f753903a7

See more details on using hashes here.

File details

Details for the file treams-0.4.1-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for treams-0.4.1-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 14a772f456b9cb0b4e72c9784bcc7b5a7594cd9dfcb721563887b3d9f9fbdd47
MD5 d5f53ed2f73f9c5be5919009e127ee24
BLAKE2b-256 e7d4871da43b31f8f4cac2272d513df32156d09e3492422d0525e8de8b117c59

See more details on using hashes here.

Supported by

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