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‎.buildinfo‎

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# Sphinx build info version 1
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# This file records the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: bfb6e4b85e582bc952cd5a3e0c55c897
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tags: 645f666f9bcd5a90fca523b33c5a78b7

‎.nojekyll‎

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‎_images/cmi_problem_types.png‎

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‎_images/diffpycmi_screenshot.png‎

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‎_images/makerecipe_flow.png‎

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‎_images/pdfprimer.png‎

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‎_sources/api/diffpy.cmi.rst.txt‎

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:tocdepth: -1
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|title|
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=======
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.. |title| replace:: diffpy.cmi Contents
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``diffpy.cmi`` includes Python and C++ libraries developed by the DiffPy team as well as external libraries necessary for functionality.
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Libraries developed by the DiffPy team
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--------------------------------------
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.. include:: ../snippets/diffpy_libraries.rst
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External Libraries
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------------------
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.. include:: ../snippets/external_libraries.rst

‎_sources/getting-started.rst.txt‎

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:tocdepth: -1
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.. index:: getting-started
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.. _getting-started:
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================
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Getting started
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================
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.. image:: ./img/pdfprimer.png
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:alt: codecov-in-pr-comment
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:width: 150px
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:align: right
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For detailed instructions and in-depth examples of modeling with ``diffpy.cmi``, we highly recommend the book,
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*Atomic Pair Distribution Function Analysis: A Primer* by Simon J. L. Billinge and Kirsten M. Ø. Jensen (Oxford University Press, 2023).
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To purchase this book, please visit `this link <https://www.amazon.com/Atomic-Pair-Distribution-Function-Analysis/dp/0198885806>`_.
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Installation
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------------
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To install ``diffpy.cmi``, create a new conda environment or activate an existing environment and install the package from the conda-forge channel.
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.. code-block:: bash
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conda create -n diffpy.cmi-env
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conda install -c conda-forge diffpy.cmi
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conda activate diffpy.cmi-env
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To confirm that the installation was successful, type
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.. code-block:: bash
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python -c "import diffpy.cmi; print(diffpy.cmi.__version__)"
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The output should print the latest version.
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If the above does not work, you can use ``pip`` to download and install the latest release from
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`Python Package Index <https://pypi.python.org>`_.
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To install using ``pip`` into your ``diffpy.cmi_env`` environment, type
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.. code-block:: bash
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pip install diffpy.cmi
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Pack and Profile Installation
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-----------------------------
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Use the `cmi` command-line interface to install and manage modular optional dependencies, known as `packs`,
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and to configure or execute user-defined workflows that combine multiple packs with optional post-installation steps,
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known as `profiles`. To use `cmi`, you can run the following example commands:
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Show available commands and options with,
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.. code-block:: bash
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cmi -h
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List installed and available packs and profiles,
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.. code-block:: bash
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cmi pack list
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cmi profile list
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Show details of a specific pack or profile,
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.. code-block:: bash
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cmi pack show <pack_name>
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cmi profile show <profile_name>
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Install a pack or profile (by name or path),
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.. code-block:: bash
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cmi install <pack_name>
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cmi install <profile_name>
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cmi install </absolute/path/to/profile>
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List and get installed examples,
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.. code-block:: bash
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cmi example list
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cmi example (copy) <example_name>
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Data and Examples
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-----------------
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Worked examples and experimental data from the book are freely available at our
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`GitHub repository <https://github.com/Billingegroup/pdfttp_data>`_.

‎_sources/index.rst.txt‎

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#######
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|title|
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#######
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.. |title| replace:: diffpy.cmi documentation
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| Software version |release|
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| Last updated |today|.
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``diffpy.cmi`` - Complex modeling infrastructure: a modular framework for multi-modal modeling of scientific data.
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diffpy.cmi is designed as an extensible complex modeling infrastructure. Users and developers can readily integrate novel data types and constraints into custom workflows. While widely used for advanced analysis of structural data, the framework is general and can be applied to any problem where model parameters are refined to fit calculated quantities to data.
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diffpy.cmi is a community-driven project that supports Unix, Linux, macOS, and Windows platforms. It is designed to be used in Python scripts enabling flexible scripting and automation for advanced and reproducible workflows. Users are encouraged to leverage the software for their modeling needs and to contribute feedback, use cases, and extensions through the project community.
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.. image:: ./img/diffpycmi_screenshot.png
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:alt: codecov-in-pr-comment
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:width: 400px
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:align: center
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=======================================
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Community Use and Extensible Modeling
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=======================================
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One of the key strengths of ``diffpy.cmi`` is its modular design, which allows the integration and fitting of *any* data type, not just PDFs.
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While its current core functionality is in PDF modeling and multi-dataset fitting, **we actively encourage and support community-developed modules and workflows for any data types you see fit!**
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.. image:: ./img/cmi_problem_types.png
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:alt: codecov-in-pr-comment
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:width: 500px
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:align: center
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Have you built a new workflow you'd like to implement into ``diffpy.cmi``?
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We would love to **highlight your extension or application!**
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1. **Share your work:** Please `open an issue or a pull request <https://github.com/diffpy/diffpy.cmi>`_ to share your work and help us expand the platform.
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2. **Be recognized:** Community contributions and new use cases will be showcased and credited here.
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===============
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Getting started
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===============
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To get started, please visit the :ref:`Getting started <getting-started>` page.
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=======
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Authors
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=======
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``diffpy.cmi`` is developed by Simon Billinge and members of the Billinge Group. The maintainer for this project is Simon Billinge. For a detailed list of contributors see
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https://github.com/diffpy/diffpy.cmi/graphs/contributors.
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============
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Installation
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============
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See the `README <https://github.com/diffpy/diffpy.cmi#installation>`_
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file included with the distribution.
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================
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Acknowledgements
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================
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``diffpy.cmi`` is built and maintained with `scikit-package <https://scikit-package.github.io/scikit-package/>`_.
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========
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Citation
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========
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If you use ``diffpy.cmi`` in a scientific publication, we would like you to cite this package as
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Juhás, P.; Farrow, C. L.; Yang, X.; Knox, K. R.; Billinge, S. J. L.
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Complex Modeling: A Strategy and Software Program for Combining Multiple Information Sources to Solve Ill Posed Structure and Nanostructure Inverse Problems.
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*Acta Crystallogr A Found Adv* **2015**, *71* (6), 562–568.
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`https://doi.org/10.1107/S2053273315014473 <https://doi.org/10.1107/S2053273315014473>`_
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=================
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Table of contents
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=================
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.. toctree::
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:maxdepth: 2
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getting-started
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Tutorials <tutorials/index>
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Package API <api/diffpy.cmi>
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release
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license
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=======
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Indices
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=======
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* :ref:`genindex`
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* :ref:`search`

‎_sources/license.rst.txt‎

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:tocdepth: -1
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.. index:: license
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License
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#######
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OPEN SOURCE LICENSE AGREEMENT
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=============================
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BSD 3-Clause License
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Copyright (c) 2025, The Trustees of Columbia University in the City of New York.
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All Rights Reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are met:
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1. Redistributions of source code must retain the above copyright notice, this
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list of conditions and the following disclaimer.
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2. Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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3. Neither the name of the copyright holder nor the names of its
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contributors may be used to endorse or promote products derived from
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this software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

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