Skip to main content

Complex modeling infrastructure: a modular framework for multi-modal modeling of scientific data.

Project description

PyPI Forge PythonVersion PR

CI Codecov Black Tracking

Complex modeling infrastructure: a modular framework for multi-modal modeling of scientific data.

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.

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.

For more information about the diffpy.cmi library, please consult our online documentation.

Citation

If you use diffpy.cmi in a scientific publication, we would like you to cite this package as

Juhás, P.; Farrow, C. L.; Yang, X.; Knox, K. R.; Billinge, S. J. L. Complex Modeling: A Strategy and Software Program for Combining Multiple Information Sources to Solve Ill Posed Structure and Nanostructure Inverse Problems. Acta Crystallogr A Found Adv 2015, 71 (6), 562–568. https://doi.org/10.1107/S2053273315014473.

Installation

The preferred method is to use Miniconda Python and install from the “conda-forge” channel of Conda packages.

To add “conda-forge” to the conda channels, run the following in a terminal.

conda config --add channels conda-forge

We want to install our packages in a suitable conda environment. The following creates and activates a new environment named diffpy.cmi_env

conda create -n diffpy.cmi_env diffpy.cmi
conda activate diffpy.cmi_env

To confirm that the installation was successful, type

python -c "import diffpy.cmi; print(diffpy.cmi.__version__)"

The output should print the latest version displayed on the badges above.

If the above does not work, you can use pip to download and install the latest release from Python Package Index. To install using pip into your diffpy.cmi_env environment, type

pip install diffpy.cmi

If you prefer to install from sources, after installing the dependencies, obtain the source archive from GitHub. Once installed, cd into your diffpy.cmi directory and run the following

pip install .

Getting Started

Use the cmi command-line interface to install and manage modular optional dependencies, known as packs, and to configure or execute user-defined workflows that combine multiple packs with optional post-installation steps, known as profiles. To use cmi, you can run the following example commands:

Show available commands and options,

cmi -h

List installed and available packs and profiles,

cmi pack list
cmi profile list

Show details of a specific pack or profile,

cmi pack show <pack_name>
cmi profile show <profile_name>

Install a pack or profile (by name or path),

cmi install <pack_name|profile_name|/absolute/path/to/profile>

List and get installed examples,

cmi example list
cmi example (copy) <example_name>

You may consult our online documentation for more information, tutorials, and API references.

Support and Contribute

If you see a bug or want to request a feature, please report it as an issue and/or submit a fix as a PR.

Feel free to fork the project and contribute. To install diffpy.cmi in a development mode, with its sources being directly used by Python rather than copied to a package directory, use the following in the root directory

pip install -e .

To ensure code quality and to prevent accidental commits into the default branch, please set up the use of our pre-commit hooks.

  1. Install pre-commit in your working environment by running conda install pre-commit.

  2. Initialize pre-commit (one time only) pre-commit install.

Thereafter your code will be linted by black and isort and checked against flake8 before you can commit. If it fails by black or isort, just rerun and it should pass (black and isort will modify the files so should pass after they are modified). If the flake8 test fails please see the error messages and fix them manually before trying to commit again.

Improvements and fixes are always appreciated.

Before contributing, please read our Code of Conduct.

Contact

For more information on diffpy.cmi please visit the project web-page or email Simon Billinge at sb2896@columbia.edu.

Acknowledgements

diffpy.cmi is built and maintained with scikit-package.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

diffpy_cmi-3.1.2rc0.tar.gz (2.1 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

diffpy_cmi-3.1.2rc0-py3-none-any.whl (2.1 MB view details)

Uploaded Python 3

File details

Details for the file diffpy_cmi-3.1.2rc0.tar.gz.

File metadata

  • Download URL: diffpy_cmi-3.1.2rc0.tar.gz
  • Upload date:
  • Size: 2.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.11

File hashes

Hashes for diffpy_cmi-3.1.2rc0.tar.gz
Algorithm Hash digest
SHA256 17e403ef230f3df58be7e1eedf6a898832ac01e84f41b7538cd1ab421b28f8e3
MD5 3eb57d6b0e956f4bda612d9ddce00543
BLAKE2b-256 57f9ee766281a6f9ac95e0aaff17ac49a6a7c885e00c257d3fb76923e6cd1488

See more details on using hashes here.

File details

Details for the file diffpy_cmi-3.1.2rc0-py3-none-any.whl.

File metadata

  • Download URL: diffpy_cmi-3.1.2rc0-py3-none-any.whl
  • Upload date:
  • Size: 2.1 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.11

File hashes

Hashes for diffpy_cmi-3.1.2rc0-py3-none-any.whl
Algorithm Hash digest
SHA256 09198f7b683c62da9375149f1def487155009ef7b6576b00c4671684a18f0b79
MD5 f61cb7459d360f59fa731896c45deac9
BLAKE2b-256 0b910857f1a32ac380c67215eebfb08996358ba2fb816f8c62d0ce9da29ccdb1

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page