# Iris - Ultrafast Electron Scattering Data Exploration
[](http://iris-ued.readthedocs.io/) [](https://pypi.python.org/pypi/iris-ued) [](https://anaconda.org/conda-forge/iris-ued) [](https://doi.org/10.1186/s40679-018-0060-y)
Iris is both a library for interacting with ultrafast electron
diffraction data, as well as a GUI frontend for interactively exploring
this data.
Iris also includes a plug-in manager so that you can explore your data.
## Contents:
- [Installation](#installation)
- [Usage](#usage)
- [Test Data](#test-data)
- [Documentation](#documentation)
- [Citations](#citations)
- [Support / Report Issues](#support--report-issues)
- [License](#license)
## Installation
To interact with `iris` datasets from a Python environment, the `iris` package must be installed. `iris` is available on PyPI; it can be installed with [pip](https://pip.pypa.io).:
python -m pip install iris-ued
`iris` is also available on the conda-forge channel:
conda config --add channels conda-forge
conda install iris-ued
To install the latest development version from
[Github](https://github.com/LaurentRDC/iris-ued):
python -m pip install git+git://github.com/LaurentRDC/iris-ued.git
Each version is tested against Python 3.8+. If you are using a different
version, tests can be run using the `pytest` package.
### Windows Installers
For Windows, installers are available on the [Releases](https://github.com/LaurentRDC/iris-ued/releases) page. You will still need to install `iris` via `pip` or `conda` to use the scripting functionality.
## Usage
Once installed, the package can be imported as `iris`.
The GUI component can be launched from a command line interpreter as
`python -m iris` or `pythonw -m iris` (no console window). See the documentation
for a visual guide.
## Documentation
The [Documentation on readthedocs.io](https://iris-ued.readthedocs.io)
provides API-level documentation, as well as tutorials.
## Citations
If you find this software useful, please consider citing the following
publication:
> L. P. René de Cotret, M. R. Otto, M. J. Stern. and B. J. Siwick, *An open-source software ecosystem for the interactive exploration of ultrafast electron scattering data*, Advanced Structural and Chemical Imaging 4:11 (2018) [DOI: 10.1186/s40679-018-0060-y.](https://ascimaging.springeropen.com/articles/10.1186/s40679-018-0060-y)
If you are using the baseline-removal functionality of iris-ued,
please consider citing the following publication:
> L. P. René de Cotret and B. J. Siwick, *A general method for baseline-removal in ultrafast electron powder diffraction data using the dual-tree complex wavelet transform*, Struct. Dyn. 4 (2017) [DOI: 10.1063/1.4972518](https://doi.org/10.1063/1.4972518).
## Support / Report Issues
All support requests and issue reports should be [filed on Github as an
issue](https://github.com/LaurentRDC/iris-ued/issues).
## License
iris is made available under the GPLv3 License. For more details, see
[LICENSE.txt](https://github.com/LaurentRDC/iris-ued/blob/master/LICENSE.txt).
Raw data
{
"_id": null,
"home_page": "http://iris-ued.readthedocs.io",
"name": "iris-ued",
"maintainer": "Laurent P. Ren\u00e9 de Cotret",
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": "laurent.renedecotret@mail.mcgill.ca",
"keywords": "ultrafast electron diffraction visualization pyqtgraph",
"author": "Laurent P. Ren\u00e9 de Cotret",
"author_email": "laurent.renedecotret@mail.mcgill.ca",
"download_url": "https://files.pythonhosted.org/packages/2f/6c/7214f15ded73cc953a09b701ffb6517992be69378dfec2f265243b6741b3/iris-ued-5.4.0.tar.gz",
"platform": null,
"description": "# Iris - Ultrafast Electron Scattering Data Exploration\n\n[](http://iris-ued.readthedocs.io/) [](https://pypi.python.org/pypi/iris-ued) [](https://anaconda.org/conda-forge/iris-ued) [](https://doi.org/10.1186/s40679-018-0060-y)\n\n\nIris is both a library for interacting with ultrafast electron\ndiffraction data, as well as a GUI frontend for interactively exploring\nthis data.\n\nIris also includes a plug-in manager so that you can explore your data.\n\n\n\n## Contents:\n - [Installation](#installation)\n - [Usage](#usage)\n - [Test Data](#test-data)\n - [Documentation](#documentation)\n - [Citations](#citations)\n - [Support / Report Issues](#support--report-issues)\n - [License](#license)\n\n## Installation\n\nTo interact with `iris` datasets from a Python environment, the `iris` package must be installed. `iris` is available on PyPI; it can be installed with [pip](https://pip.pypa.io).:\n\n python -m pip install iris-ued\n\n`iris` is also available on the conda-forge channel:\n\n conda config --add channels conda-forge\n conda install iris-ued\n\nTo install the latest development version from\n[Github](https://github.com/LaurentRDC/iris-ued):\n\n python -m pip install git+git://github.com/LaurentRDC/iris-ued.git\n\nEach version is tested against Python 3.8+. If you are using a different\nversion, tests can be run using the `pytest` package.\n\n### Windows Installers\n\nFor Windows, installers are available on the [Releases](https://github.com/LaurentRDC/iris-ued/releases) page. You will still need to install `iris` via `pip` or `conda` to use the scripting functionality.\n\n## Usage\n\nOnce installed, the package can be imported as `iris`.\n\nThe GUI component can be launched from a command line interpreter as\n`python -m iris` or `pythonw -m iris` (no console window). See the documentation\nfor a visual guide.\n\n## Documentation\n\nThe [Documentation on readthedocs.io](https://iris-ued.readthedocs.io)\nprovides API-level documentation, as well as tutorials.\n\n## Citations\n\nIf you find this software useful, please consider citing the following\npublication:\n\n> L. P. Ren\u00e9 de Cotret, M. R. Otto, M. J. Stern. and B. J. Siwick, *An open-source software ecosystem for the interactive exploration of ultrafast electron scattering data*, Advanced Structural and Chemical Imaging 4:11 (2018) [DOI: 10.1186/s40679-018-0060-y.](https://ascimaging.springeropen.com/articles/10.1186/s40679-018-0060-y)\n\nIf you are using the baseline-removal functionality of iris-ued,\nplease consider citing the following publication:\n\n> L. P. Ren\u00e9 de Cotret and B. J. Siwick, *A general method for baseline-removal in ultrafast electron powder diffraction data using the dual-tree complex wavelet transform*, Struct. Dyn. 4 (2017) [DOI: 10.1063/1.4972518](https://doi.org/10.1063/1.4972518).\n\n## Support / Report Issues\n\nAll support requests and issue reports should be [filed on Github as an\nissue](https://github.com/LaurentRDC/iris-ued/issues).\n\n## License\n\niris is made available under the GPLv3 License. For more details, see\n[LICENSE.txt](https://github.com/LaurentRDC/iris-ued/blob/master/LICENSE.txt).\n",
"bugtrack_url": null,
"license": "GPLv3",
"summary": "Ultrafast electron diffraction data exploration",
"version": "5.4.0",
"project_urls": {
"Documentation": "http://iris-ued.readthedocs.io/en/master/",
"Download": "http://github.com/LaurentRDC/iris-ued",
"Home": "http://www.physics.mcgill.ca/siwicklab/software.html",
"Homepage": "http://iris-ued.readthedocs.io",
"Source": "https://github.com/LaurentRDC/iris-ued",
"Tracker": "https://github.com/LaurentRDC/iris-ued/issues"
},
"split_keywords": [
"ultrafast",
"electron",
"diffraction",
"visualization",
"pyqtgraph"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "2f6c7214f15ded73cc953a09b701ffb6517992be69378dfec2f265243b6741b3",
"md5": "2dfe99f88764a1fe0bc88ff97149e173",
"sha256": "bbded7659456c0e9c651192efc420109407363489740d9fced5e163cf3ba6956"
},
"downloads": -1,
"filename": "iris-ued-5.4.0.tar.gz",
"has_sig": false,
"md5_digest": "2dfe99f88764a1fe0bc88ff97149e173",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 413851,
"upload_time": "2024-10-23T19:41:06",
"upload_time_iso_8601": "2024-10-23T19:41:06.962320Z",
"url": "https://files.pythonhosted.org/packages/2f/6c/7214f15ded73cc953a09b701ffb6517992be69378dfec2f265243b6741b3/iris-ued-5.4.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-10-23 19:41:06",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "LaurentRDC",
"github_project": "iris-ued",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [],
"lcname": "iris-ued"
}
JSON
