CIMS

The Python implementation of the CIMS economic climate model.
https://github.com/emrg-sfu/cims

Category: Climate Change
Sub Category: Earth and Climate Modeling

Last synced: about 20 hours ago
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README.md

CIMS

CIMS is a Python package providing the Python implementation of the CIMS
economic climate model.

βš™οΈ Installation

CIMS is not currently available on PyPi or other package indexes. Follow the installation guide to get CIMS running on your machine.

πŸ§‘β€πŸ’» Usage

Once you've installed CIMS you can call its functions and classes from within your own Python script, notebook, or program. Follow the quickstart guide to familiarize yourself with CIMS's key functionality.

import CIMS
model_file = 'path/to/model.xlsb'
my_reader = CIMS.ModelReader(infile=model_file)
my_model = CIMS.Model(my_reader)
my_model.run()

πŸ“ Contributing

Contributions to CIMS are welcome, in many different forms:

  • Issues β€” If you identify a bug, error in the documentation, or a potential improvement to CIMS, consider putting this information into an issue. First, search the list of existing issues to see if there is an ongoing discussion to join. If a relevant issue doesn't already exist, please create a new issue.
  • Code β€” If you are comfortable writing code feel free to make a Pull Request (PR) with your changes. If you've tackled a large feature request or bug, please also create a new issue, or mention an existing issue within your PR.
  • Documentation β€” If you notice typos, out-of-date information, or opportunities for improvements in the documentation (and are comfortable writing Markdown), please consider making a PR with changes.

Any kind of contribution, whether its fixing a small typo, refactoring existing code, or the implementation of a brand new module helps improve this project.

πŸ“– Citation

πŸ™ Acknowledgements

Bradford Griffin and Jillian Anderson are the project's lead researcher and lead technical developer, respectively.

In addition, contributions to the codebase have been made by members of Simon Fraser University's Big Data Hub and Research Computing Group:

Finally, thank you to the numerous EMRG graduate students who have attended meetings, submitted features requests, and flagged bugs:

  • Thomas Budd
  • Aaron Pardy
  • Emma Starke
  • Kaitlin Thompson
  • Heather Chambers
  • Ryan Safton

βš–οΈ License

The CIMS Python library is licensed under the MIT License. For more information about this license, checkout this overview.

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: CIMS energy-economy model
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Brad
    family-names: Griffin
    email: bradford_griffin@sfu.ca
    affiliation: Simon Fraser University
  - given-names: Jillian
    family-names: Anderson
    email: jillian_anderson@sfu.ca
    affiliation: Simon Fraser University
    orcid: 'https://orcid.org/0000-0002-2528-2580'
  - given-names: Matthew
    family-names: Sniatynski
    email: matt@exmath.org
    affiliation: The Laboratory for Experimental Mathematics Inc.
  - given-names: Thomas
    family-names: Budd
    email: tbudd@sfu.ca
    affiliation: Simon Fraser University
  - given-names: Emma
    family-names: Starke
    email: emma_starke@sfu.ca
    affiliation: Simon Fraser University
repository-code: 'https://github.com/EMRG-SFU/cims'
repository: 'https://github.com/EMRG-SFU/cims-models'
abstract: >-
  CIMS is an integrated energy-economy model designed to
  provide information to policy makers on the likely
  response of firms and households to policies that
  influence their technology acquisition and use decisions.
  As a technology simulation model, it reflects how people
  actually behave rather than how they ought to behave (as
  in cost minimization modelling). CIMS is able to provide
  policy makers with information on: (1) the ability of
  policies to achieve specific objectives (like greenhouse
  gas emissions reductions), (2) the likely costs of
  achieving these objectives, and (3) the uncertainties
  associated with the model’s simulations. 

  CIMS is maintained and operated by the Energy and
  Materials Research Group at the School of Resource and
  Environmental Management at Simon Fraser University in
  Burnaby, B.C., Canada.

  Funding for the development of the initial version of this
  project was provided by the Pacific Institute for Climate
  Solutions Opportunity Projects Program, Natural Resources
  Canada, and Environment and Climate Change Canada.
keywords:
  - energy
  - emissions
  - policy
  - simulation
  - jupyter-notebook
  - networkx
  - polars
  - ipwidgets
  - plotly
license: MIT
version: '0.1'
date-released: '2025-03-03'

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GitHub Events

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Last Year

Committers metadata

Last synced: about 1 month ago

Total Commits: 558
Total Committers: 25
Avg Commits per committer: 22.32
Development Distribution Score (DDS): 0.47

Commits in past year: 67
Committers in past year: 4
Avg Commits per committer in past year: 16.75
Development Distribution Score (DDS) in past year: 0.418

Name Email Commits
Jillian Anderson 1****8 296
Brad Griffin b****n@s****a 153
Kacy Wu K****2@g****m 20
mlachain m****n@s****a 18
rbarket b****d@h****m 16
β€œyya188” β€œ****8@s****” 12
Matt m****t@M****P 8
Maude Lachaine m****e@S****l 6
Steven Bergner g****b 4
Maude Lachaine m****e@d****a 4
rbarket 5****t@u****a 4
Daisy Yu 1****8@u****a 2
Maude Lachaine m****e@S****e 2
yya188 y****8@s****a 2
Kacy Wu 5****8@u****a 1
Maude Lachaine m****e@M****e 1
Maude Lachaine m****e@d****a 1
Maude Lachaine m****e@d****a 1
Maude Lachaine m****e@d****a 1
Maude Lachaine m****e@d****a 1
Maude Lachaine m****e@d****a 1
Maude Lachaine m****e@d****a 1
adrienaw 5****w@u****a 1
matt-exmath 1****h 1
EvanDungate e****e@g****m 1

Committer domains:


Issue and Pull Request metadata

Last synced: 7 days ago

Total issues: 72
Total pull requests: 28
Average time to close issues: about 2 months
Average time to close pull requests: 14 days
Total issue authors: 6
Total pull request authors: 3
Average comments per issue: 1.31
Average comments per pull request: 0.39
Merged pull request: 26
Bot issues: 0
Bot pull requests: 0

Past year issues: 69
Past year pull requests: 27
Past year average time to close issues: about 2 months
Past year average time to close pull requests: 11 days
Past year issue authors: 6
Past year pull request authors: 3
Past year average comments per issue: 1.35
Past year average comments per pull request: 0.3
Past year merged pull request: 25
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/emrg-sfu/cims

Top Issue Authors

  • brad-griffin (35)
  • jillianderson8 (28)
  • matt-exmath (4)
  • tcbudd (3)
  • ees88 (1)
  • gabi-diner-cer (1)

Top Pull Request Authors

  • jillianderson8 (21)
  • brad-griffin (5)
  • matt-exmath (4)

Top Issue Labels

  • bug (15)
  • enhancement (9)
  • refactoring (5)
  • low priority (1)
  • on hold (1)

Top Pull Request Labels

  • bug (6)
  • enhancement (3)
  • refactoring (2)
  • documentation (1)

Dependencies

environment.yml conda
  • jupyter
  • matplotlib
  • networkx
  • numpy
  • pandas >=2
  • pip
  • polars
  • pyarrow
  • python >=3.11
  • scipy
  • seaborn >=0.13.2
  • setuptools
  • xlrd
pyproject.toml pypi
  • matplotlib *
  • networkx *
  • numpy *
  • packaging *
  • pandas >=1.2
  • polars *
  • pyarrow *
  • pyxlsb *
  • requests *
  • scipy *
  • seaborn >=0.13.2
  • tqdm *
  • wasabi *
  • xlrd *

Score: 7.575584651557792