Skip to main content

Software for the practical analysis of materials

Project description

spam -- The Software for Practical Analysis of Materials
=========================================================

.. image:: https://gricad-gitlab.univ-grenoble-alpes.fr/ttk/spam/badges/master/build.svg
:target: https://gricad-gitlab.univ-grenoble-alpes.fr/ttk/spam/commits/master

.. image:: https://gricad-gitlab.univ-grenoble-alpes.fr/ttk/spam/badges/master/coverage.svg
:target: https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/coverage/

.. [![build status](https://gricad-gitlab.univ-grenoble-alpes.fr/ttk/spam/badges/master/build.svg)](https://gricad-gitlab.univ-grenoble-alpes.fr/ttk/spam/commits/master)
.. [![coverage report](https://gricad-gitlab.univ-grenoble-alpes.fr/ttk/spam/badges/master/coverage.svg)](https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/coverage/)

Spam is a piece of Python software built upon NumPy and SciPy
for the analysis and manipulation of 3D and 2D data sets in
material science, be they from x-ray tomography, random fields
or any other source.

A number of common functions are provided that are
either lacking or slow in Numpy and Scipy, which are expected
to be used by users within new python scripts.
These functions are in the tools/ directory, and include tools
to work with random fields, morphological operations, digital
image correlation, and labelled images.
Some of spam's functions transparently call C/C++ functions
for speed.

Some user-callable scipts are also provided -- they are more
complex pieces of code that combine a number of functions and
which have a command-line interface.
For the moment the clients are 3 different image correlation
techniques.

Please have a look at our online documentation for:

* `Installation instructions`_
* `General introduction`_
* `Examples`_
* And a number of detailed tutorials

If you find bugs, need help, or want to talk to the developers, we use a `riot`_/`matrix.org`_ **chat room** for organisation, please join it `here`_ and come and talk to us -- it is easy, there is a chat client that can run in your web broswer.
All you need to do is choose a user name!


.. _Installation instructions: https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/installation.html
.. _General introduction: https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/intro.html
.. _Examples: https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/spam_examples/index.html

.. _riot: https://about.riot.im/
.. _matrix.org: https://matrix.org/
.. _here: https://riot.im/app/#/room/#spam:matrix.org

Changelog
----------

.. include:: ChangeLog.txt


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

spam-0.3.2-cp36-cp36m-manylinux1_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.6m

spam-0.3.2-cp35-cp35m-manylinux1_x86_64.whl (9.3 MB view details)

Uploaded CPython 3.5m

spam-0.3.2-cp27-cp27mu-manylinux1_x86_64.whl (9.3 MB view details)

Uploaded CPython 2.7mu

spam-0.3.2-cp27-cp27m-manylinux1_x86_64.whl (9.3 MB view details)

Uploaded CPython 2.7m

File details

Details for the file spam-0.3.2-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

  • Download URL: spam-0.3.2-cp36-cp36m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 9.3 MB
  • Tags: CPython 3.6m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.15

File hashes

Hashes for spam-0.3.2-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 bc2c612328ec7d93b81c3e6dd3f5bf613749b4ad431f019d4a0635986bf477ab
MD5 e1ebadccce354a684d4f606a1421f9d9
BLAKE2b-256 7523966d3dd5a92fc166c3f0201df3e2995a68e681b602a45b9f47ec4733250e

See more details on using hashes here.

File details

Details for the file spam-0.3.2-cp35-cp35m-manylinux1_x86_64.whl.

File metadata

  • Download URL: spam-0.3.2-cp35-cp35m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 9.3 MB
  • Tags: CPython 3.5m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.15

File hashes

Hashes for spam-0.3.2-cp35-cp35m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 c79f32d8fb9c52408b693bd05cb0eb0ef2246872ce51c9d467942d714dc24beb
MD5 20b3a3c99bccea47635820e27b3222aa
BLAKE2b-256 edab4361bcd868cb1e94b3420115b8bf2960ba1afb5273f0e775503d7e700b9f

See more details on using hashes here.

File details

Details for the file spam-0.3.2-cp27-cp27mu-manylinux1_x86_64.whl.

File metadata

  • Download URL: spam-0.3.2-cp27-cp27mu-manylinux1_x86_64.whl
  • Upload date:
  • Size: 9.3 MB
  • Tags: CPython 2.7mu
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.15

File hashes

Hashes for spam-0.3.2-cp27-cp27mu-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 230218f76b1f557eb8bd7fb203ef0edafc1af0ca70a514c229455e70c63875e4
MD5 ff4883fb96e77f800ac96043b987d987
BLAKE2b-256 2761d2a89e768ce339e1c269ea885c23331ab5509318bb7b2177d1121703463a

See more details on using hashes here.

File details

Details for the file spam-0.3.2-cp27-cp27m-manylinux1_x86_64.whl.

File metadata

  • Download URL: spam-0.3.2-cp27-cp27m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 9.3 MB
  • Tags: CPython 2.7m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.15

File hashes

Hashes for spam-0.3.2-cp27-cp27m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 2d77bedae921598723598384a8e2bb445ac764ff1f80567d38dc2deb716fc6fb
MD5 9f2f3f7c43e6563fce29d3d1f0d775af
BLAKE2b-256 cb5b66d57ab9d1fa87f9a4a8be86625ed33ca2b467f5d258dc51e509846f16d8

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