ITK filters to estimate a strain tensor field from a displacement field or a spatial transformation

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for dzenanz from gravatar.com dzenanz Avatar for itkrobot from gravatar.com itkrobot Avatar for thewtex from gravatar.com thewtex

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: Apache Software License (Apache)
  • Author: Matthew M. McCormick
  • Tags ITK, Strain, Tensor, Displacement, Field
Classifiers

Project description

itk-strain provides N-dimensional computational framework of strain tensor images in the Insight Toolkit. The filters provided can compute a strain tensor image from a displacement field image and a strain tensor image from a general spatial transform. In both cases, infinitesimal, Green-Lagrangian, or Eulerian-Almansi strain can be generated. Please refer to: M. McCormick, “N-Dimensional Computation of Strain Tensor Images in the Insight Toolkit.”, Insight Journal, January-December 2017, https://hdl.handle.net/10380/3573

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for dzenanz from gravatar.com dzenanz Avatar for itkrobot from gravatar.com itkrobot Avatar for thewtex from gravatar.com thewtex

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: Apache Software License (Apache)
  • Author: Matthew M. McCormick
  • Tags ITK, Strain, Tensor, Displacement, Field
Classifiers

Release history Release notifications | RSS feed

1.0.1

0.4.0

0.3.9

0.3.8

This version

0.3.7

0.3.6

0.3.5

0.3.4

0.3.3

0.3.2

0.3.1

0.3.0

0.2.0

0.1.0

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

itk_strain-0.3.7-cp310-cp310-win_amd64.whl (678.4 kB view details)

Uploaded CPython 3.10 Windows x86-64

itk_strain-0.3.7-cp310-cp310-manylinux_2_28_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.28+ x86-64

itk_strain-0.3.7-cp310-cp310-macosx_10_9_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

itk_strain-0.3.7-cp39-cp39-win_amd64.whl (678.8 kB view details)

Uploaded CPython 3.9 Windows x86-64

itk_strain-0.3.7-cp39-cp39-manylinux_2_28_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.28+ x86-64

itk_strain-0.3.7-cp39-cp39-macosx_10_9_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

itk_strain-0.3.7-cp38-cp38-win_amd64.whl (678.9 kB view details)

Uploaded CPython 3.8 Windows x86-64

itk_strain-0.3.7-cp38-cp38-manylinux_2_28_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.28+ x86-64

itk_strain-0.3.7-cp38-cp38-macosx_10_9_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

itk_strain-0.3.7-cp37-cp37m-win_amd64.whl (698.2 kB view details)

Uploaded CPython 3.7m Windows x86-64

itk_strain-0.3.7-cp37-cp37m-manylinux_2_28_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.28+ x86-64

itk_strain-0.3.7-cp37-cp37m-macosx_10_9_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

File details

Details for the file itk_strain-0.3.7-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for itk_strain-0.3.7-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 a172e263d7e2b9aa42bea40126b9173e97600c62832cf08d4027a33897fd4279
MD5 eb6bc202692a686d0c77fd711c1b2d32
BLAKE2b-256 d54228f948ee8a088daabcfb970edad75f88d5a60267e9000d008a9335654896

See more details on using hashes here.

File details

Details for the file itk_strain-0.3.7-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_strain-0.3.7-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 9ab321a6bf57ea45caa5badd835ddaabdb6badbd7e93445778869591f49fe356
MD5 29641fab9b938139089d3d87d3d551ee
BLAKE2b-256 2fe748e7286bf1c1bd5fc0b79639dd289af92c8df0595244d400161208b61083

See more details on using hashes here.

File details

Details for the file itk_strain-0.3.7-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_strain-0.3.7-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 d8eb6589a84486b5b5d7aef604f6e33543386de900010025b00a7a84606f0c2f
MD5 098a081bd851911826422e26d6dc7138
BLAKE2b-256 f47815b8623188213f469215d465e99e60f8a1283117c6f00f380f104e128107

See more details on using hashes here.

File details

Details for the file itk_strain-0.3.7-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: itk_strain-0.3.7-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 678.8 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.13

File hashes

Hashes for itk_strain-0.3.7-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 0280efecfb7f358a38108e060382f36618aa038f6ad0051fd789ba886f941b5d
MD5 a0324abe6fc68971256a5fbc3d325a11
BLAKE2b-256 9b587351d53fb3004c74612588bf00c9a3ae88dbeccbe4d324bfe71048391410

See more details on using hashes here.

File details

Details for the file itk_strain-0.3.7-cp39-cp39-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_strain-0.3.7-cp39-cp39-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 481dbf493a2a47a567eac69ac72adb9069e596d43bfa7eef6236910fed794a38
MD5 b8f30515dca7b4fcabb64179323fe125
BLAKE2b-256 1751df87f0b998ba678ea2b618eac90c93b798093035153c6e2ebce5710e97b9

See more details on using hashes here.

File details

Details for the file itk_strain-0.3.7-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_strain-0.3.7-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 f71b72c045a0fe1e8454f2c63708470242fd77c4eb51490cff991944245ae207
MD5 b16cac368b78c12a58a076fb0edee20c
BLAKE2b-256 153a78f34408a9fcc450a6d040f983a5a7ec81641616b345975d0db96e5eb869

See more details on using hashes here.

File details

Details for the file itk_strain-0.3.7-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: itk_strain-0.3.7-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 678.9 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.13

File hashes

Hashes for itk_strain-0.3.7-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 ba0a5185976665bcff5a3243bd483a7ad68f735c6ed48c753140384447989d3e
MD5 2e2a06cf9ed260de4be96aaf0bccfe13
BLAKE2b-256 333c4076af66daf643dec46eb1df4f52c6e60870a133f78bcadc4261093389b4

See more details on using hashes here.

File details

Details for the file itk_strain-0.3.7-cp38-cp38-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_strain-0.3.7-cp38-cp38-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 5554141cbd6b1d1a0a4569681db249d557b0a9fe68497cf751ac0f95f707ea4d
MD5 d4b8c503d0d0f85308d58aa53982ef82
BLAKE2b-256 fc1d14521da7d80af870c6a5bef5fdb5636b571921bc370a757f243433aa5c3e

See more details on using hashes here.

File details

Details for the file itk_strain-0.3.7-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_strain-0.3.7-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 ef84d02f79f42001076e0f5aaedc637a5c850e2e4decaedd31af955b1e95787c
MD5 ff8bf9f5c74281933ac75f069453323f
BLAKE2b-256 f7cd302c5086bd017782b16fcfbbf3cd43941ae9b9a612055e9f2f34b8ec0e23

See more details on using hashes here.

File details

Details for the file itk_strain-0.3.7-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for itk_strain-0.3.7-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 b462596a43ee4d45e16dac20929c597dcadc66c2ece1c24b2b43c8cf366f5347
MD5 090fc05f20bcf554a22a76240a75d53e
BLAKE2b-256 cda5185b73a1c3e5ee39e55058f4e84c740c338a3c6dc66db16bb61db1fef611

See more details on using hashes here.

File details

Details for the file itk_strain-0.3.7-cp37-cp37m-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_strain-0.3.7-cp37-cp37m-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 4e06058d394f412ebcd4d3b1669b1bae445d7e3d469c5c596476eccae57b09fc
MD5 791cb2922276b54e19a446fb46cf9789
BLAKE2b-256 5e7ef9caa8bd608886d490b2123a3b49b9560d334c63ccfa8ac797071a213bb6

See more details on using hashes here.

File details

Details for the file itk_strain-0.3.7-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_strain-0.3.7-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 815868e9145c7d19b42acf6402954d05376d0cb33ece7e94e754617796488593
MD5 9894390840f9e2ca52dcbc922b234a60
BLAKE2b-256 2bc2ce4b79a117d848fe906d1d52f93e052fb1a8709187fad4881230a2484956

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