irispy-lmsal


Nameirispy-lmsal JSON
Version 0.5.0 PyPI version JSON
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home_pageNone
SummaryProvides tools to read and analyze data from the IRIS solar-observing satellite.
upload_time2025-10-06 23:53:20
maintainerNone
docs_urlNone
authorIRIS Instrument Team @ LMSAL
requires_python>=3.11
licenseCopyright (c) 2020-2025, IRIS Instrument Team @ LMSAL All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the IRIS Instrument Team @ LMSAL nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
keywords solar physics solar science nasa iris spectra lmsal
VCS
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requirements No requirements were recorded.
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            **********
``irispy``
**********

.. image:: ./iris_full.jpg
  :width: 400
  :alt: Image of the IRIS spacecraft

``irispy`` is a library that provides the tools to read in and analyze data from Interface Region Imaging Spectrograph (IRIS).

IRIS is a NASA-funded Small Explorer which uses a high-frame-rate ultraviolet imaging spectrometer to make observations of the Sun.
For more information see the instrument paper which is available `online for free <https://www.lmsal.com/iris_science/doc?cmd=dcur&proj_num=IS0196&file_type=pdf>`__.

`The data is publicly available <https://iris.lmsal.com/data.html>`__.

`Documentation is hosted on Read the Docs <https://irispy.readthedocs.io/en/stable/>`__

.. warning::

    Please be aware that the package name on pypi and conda-forge is ``irispy-lmsal`` to avoid name clashes with other packages.
    However, the package is imported as ``irispy`` and is referred to as ``irispy`` in the documentation.

Usage of Generative AI
----------------------

We expect authentic engagement in our community.
Be wary of posting output from Large Language Models or similar generative AI as comments on GitHub or any other platform, as such comments tend to be formulaic and low quality content.
If you use generative AI tools as an aid in developing code or documentation changes, ensure that you fully understand the proposed changes and can explain why they are the correct approach and an improvement to the current state.

License
-------

This project is Copyright (c) IRIS Instrument Team and licensed under the terms of the BSD 3-Clause license.
This package is based upon the `Openastronomy packaging guide <https://github.com/OpenAstronomy/packaging-guide>`_ which is licensed under the BSD 3-clause licence.
See the licenses folder for more information.

Contributing
------------

We love contributions! irispy is open source, built on open source, and we'd love to have you hang out in our community.

**Imposter syndrome disclaimer**: We want your help. No, really.

There may be a little voice inside your head that is telling you that you're not ready to be an open source contributor; that your skills aren't nearly good enough to contribute.
What could you possibly offer a project like this one?

We assure you - the little voice in your head is wrong.
If you can write code at all, you can contribute code to open source.
Contributing to open source projects is a fantastic way to advance one's coding skills.
Writing perfect code isn't the measure of a good developer (that would disqualify all of us!); it's trying to create something, making mistakes, and learning from those mistakes.
That's how we all improve, and we are happy to help others learn.

Being an open source contributor doesn't just mean writing code, either.
You can help out by writing documentation, tests, or even giving feedback about the project (and yes - that includes giving feedback about the contribution process).
Some of these contributions may be the most valuable to the project as a whole, because you're coming to the project with fresh eyes, so you can see the errors and assumptions that seasoned contributors have glossed over.

Note: This disclaimer was originally written by `Adrienne Lowe <https://github.com/adriennefriend>`_ for a `PyCon talk <https://www.youtube.com/watch?v=6Uj746j9Heo>`_, and was adapted by irispy based on its use in the README file for the `MetPy project <https://github.com/Unidata/MetPy>`_.

            

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