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Add function
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‎.calkit/env-locks/matlab-jupyter/osx-arm64.txt‎

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aiohappyeyeballs==2.6.1
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aiohttp==3.13.3
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aiohttp-session==2.12.1
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aiosignal==1.4.0
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anyio==4.12.1
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appnope==0.1.4
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argon2-cffi==25.1.0
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argon2-cffi-bindings==25.1.0
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arrow==1.4.0
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asttokens==3.0.1
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attrs==25.4.0
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beautifulsoup4==4.14.3
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bleach==6.3.0
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certifi==2026.1.4
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cffi==2.0.0
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charset-normalizer==3.4.4
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comm==0.2.3
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cryptography==46.0.5
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debugpy==1.8.20
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decorator==5.2.1
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defusedxml==0.7.1
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executing==2.2.1
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fastjsonschema==2.21.2
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fqdn==1.5.1
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frozenlist==1.8.0
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idna==3.11
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ipykernel==7.2.0
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ipython==9.10.0
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ipython-pygments-lexers==1.1.1
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isoduration==20.11.0
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jedi==0.19.2
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jinja2==3.1.6
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jsonpointer==3.0.0
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jsonschema==4.26.0
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jsonschema-specifications==2025.9.1
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jupyter-client==8.8.0
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jupyter-core==5.9.1
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jupyter-events==0.12.0
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jupyter-matlab-proxy==0.18.0
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jupyter-server==2.17.0
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jupyter-server-proxy==4.4.0
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jupyter-server-terminals==0.5.4
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jupyterlab-pygments==0.3.0
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lark==1.3.1
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markdown-it-py==4.0.0
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markupsafe==3.0.3
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matlab-proxy==0.30.1
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matplotlib-inline==0.2.1
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mdurl==0.1.2
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mistune==3.2.0
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multidict==6.7.1
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nbclient==0.10.4
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nbconvert==7.17.0
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nbformat==5.10.4
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nest-asyncio==1.6.0
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packaging==26.0
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pandocfilters==1.5.1
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parso==0.8.6
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pexpect==4.9.0
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platformdirs==4.7.0
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prometheus-client==0.24.1
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prompt-toolkit==3.0.52
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propcache==0.4.1
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psutil==7.2.2
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ptyprocess==0.7.0
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pure-eval==0.2.3
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pycparser==3.0
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pygments==2.19.2
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python-dateutil==2.9.0.post0
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python-json-logger==4.0.0
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pyyaml==6.0.3
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pyzmq==27.1.0
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referencing==0.37.0
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requests==2.32.5
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rfc3339-validator==0.1.4
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rfc3986-validator==0.1.1
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rfc3987-syntax==1.1.0
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rich==14.3.2
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rpds-py==0.30.0
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send2trash==2.1.0
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simpervisor==1.0.0
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six==1.17.0
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soupsieve==2.8.3
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stack-data==0.6.3
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terminado==0.18.1
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tinycss2==1.4.0
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tornado==6.5.4
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traitlets==5.14.3
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typing-extensions==4.15.0
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tzdata==2025.3
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uri-template==1.3.0
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urllib3==2.6.3
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watchdog==6.0.0
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wcwidth==0.6.0
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webcolors==25.10.0
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webencodings==0.5.1
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websocket-client==1.9.0
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yarl==1.22.0

‎.github/workflows/calkit-run.yml‎

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name: Run Calkit pipeline
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on:
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push:
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branches:
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- main
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pull_request:
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permissions:
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contents: write
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# Make sure we only ever run one per branch so we don't have issues pushing
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# after running the pipeline
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concurrency:
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group: calkit-run-${{ github.ref }}
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cancel-in-progress: true
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jobs:
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main:
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name: Run
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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with:
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# For PRs, checkout the head ref to avoid detached HEAD
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ref: ${{ github.head_ref || github.ref_name }}
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token: ${{ secrets.GITHUB_TOKEN }}
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submodules: true
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- name: Configure Git credentials
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run: |
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git config user.name github-actions[bot]
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git config user.email 41898282+github-actions[bot]@users.noreply.github.com
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- name: Setup uv
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uses: astral-sh/setup-uv@v5
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- name: Install Calkit
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run: uv tool install calkit-python
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- name: Setup matlab
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uses: matlab-actions/setup-matlab@v2
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with:
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cache: true
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release: R2024b
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products: >
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Parallel_Computing_Toolbox
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Global_Optimization_Toolbox
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Optimization_Toolbox
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Statistics_and_Machine_Learning_Toolbox
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MATLAB_Report_Generator
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Simulink
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Simscape
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Simscape_Multibody
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- name: Run Calkit
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uses: calkit/run-action@378d217f814687b57b1b71fd710c43e8c75dfdef
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with:
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dvc_token: ${{ secrets.CALKIT_DVC_TOKEN }}
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matlab: true

‎.gitignore‎

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scratch.m
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.DS_Store
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.env

‎calkit.yaml‎

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description: >
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This project shows how to incorporate MATLAB into a reproducible
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research project.
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environments:
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matlab:
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kind: matlab
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version: R2024b
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products:
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- Statistics_and_Machine_Learning_Toolbox
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- Parallel_Computing_Toolbox
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# environments:
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# matlab:
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# kind: matlab
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# version: R2024b
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# products:
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# - Statistics_and_Machine_Learning_Toolbox
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# - Parallel_Computing_Toolbox
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pipeline:
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stages:
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collect-data:
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kind: matlab-script
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environment: matlab
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script_path: scripts/collect_data.m
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environment: _system
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inputs:
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- src/myfunction.m
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outputs:
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- data/raw/data.parquet
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- path: data/raw/data.parquet
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storage: dvc
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plot-data:
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kind: matlab-script
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environment: matlab
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script_path: scripts/plot_data.m
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outputs:
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- figures/plot.png
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environment: _system
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inputs:
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- data/raw/data.parquet
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outputs:
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- path: figures/plot.png
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storage: dvc
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datasets:
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- path: data/raw/data.parquet
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title: Raw data
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description: The raw data from the experiment.
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stage: collect-data
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figures:
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- path: figures/plot.png
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title: The plot

‎dvc.lock‎

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md5: 0b2be6aa89192942ea0e1263f9f7e55c
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size: 384
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plot-data:
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cmd: calkit xenv -n matlab --no-check -- "run('scripts/plot_data.m');"
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cmd: matlab -batch "restoredefaultpath; run('scripts/plot_data.m');"
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deps:
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- path: .calkit/env-locks/matlab.json
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hash: md5
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md5: 074a6771582255a621b5fda8cb2cc2d3
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size: 5082
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- path: data/raw/data.parquet
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hash: md5
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md5: 7d4fadae29fbf5fdf9eedc81a9f0cc9e
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md5: 69f8e2d950d29dc34ce8b1ce944c637c
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size: 9853
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- path: scripts/plot_data.m
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hash: md5
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md5: dd5ffb54107b06b64d0f3fb5be4429f9
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size: 144
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md5: ba7e2fcc376bc1f4b17fca546082cf7b
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size: 148
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outs:
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- path: figures/plot.png
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hash: md5
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md5: 0459648a57a7fd45c8264e4902a15494
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size: 79715
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md5: beee9043fe29cb7f49f6c4343e06a615
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size: 58503
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collect-data:
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cmd: calkit xenv -n matlab --no-check -- "run('scripts/collect_data.m');"
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cmd: matlab -batch "restoredefaultpath; run('scripts/collect_data.m');"
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deps:
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- path: .calkit/env-locks/matlab.json
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hash: md5
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md5: 074a6771582255a621b5fda8cb2cc2d3
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size: 5082
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- path: scripts/collect_data.m
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hash: md5
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md5: e9f0c4b4277e253b9034dbc7e5495058
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size: 142
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md5: 698569e0ca9128c52f0dec553a9badd1
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size: 210
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- path: src/myfunction.m
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hash: md5
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md5: 84a5dc7525d6297428329a1a79c8ac87
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size: 53
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outs:
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- path: data/raw/data.parquet
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hash: md5
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md5: 7d4fadae29fbf5fdf9eedc81a9f0cc9e
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md5: 69f8e2d950d29dc34ce8b1ce944c637c
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size: 9853
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_check_env_matlab:
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cmd: calkit check matlab-env --name matlab --output .calkit/env-locks/matlab.json

‎dvc.yaml‎

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stages:
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_check-env-matlab:
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cmd: calkit check matlab-env --name matlab --output .calkit/env-locks/matlab.json
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deps: []
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outs:
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- .calkit/env-locks/matlab.json:
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cache: false
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persist: true
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always_changed: true
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collect-data:
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cmd: calkit xenv -n matlab --no-check -- "run('scripts/collect_data.m');"
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cmd: matlab -batch "restoredefaultpath; run('scripts/collect_data.m');"
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deps:
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- scripts/collect_data.m
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- .calkit/env-locks/matlab.json
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- src/myfunction.m
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outs:
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- data/raw/data.parquet
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- data/raw/data.parquet:
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cache: true
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persist: false
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desc: Automatically generated from the 'collect-data' stage in calkit.yaml.
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Changes made here will be overwritten.
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plot-data:
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cmd: calkit xenv -n matlab --no-check -- "run('scripts/plot_data.m');"
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cmd: matlab -batch "restoredefaultpath; run('scripts/plot_data.m');"
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deps:
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- scripts/plot_data.m
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- data/raw/data.parquet
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- .calkit/env-locks/matlab.json
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outs:
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- figures/plot.png
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- figures/plot.png:
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cache: true
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persist: false
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desc: Automatically generated from the 'plot-data' stage in calkit.yaml.
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Changes made here will be overwritten.

‎requirements.txt‎

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jupyter-matlab-proxy

‎scripts/collect_data.m‎

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disp("Processing data");
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addpath("../src");
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myfunction();
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% Set random seed
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rng(432);
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voltage = rand(1000, 1);
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data = table(voltage);
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mkdir("../data/raw");
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parquetwrite("../data/raw/data.parquet", data);
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parquetwrite("../data/raw/data.parquet", data);

‎scripts/plot_data.m‎

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disp("Plotting");
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data = parquetread("../data/raw/data.parquet");
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plot(data, "voltage");
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mkdir("../figures");
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saveas(gcf, "../figures/plot.png")
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saveas(gcf, "../figures/plot.png")

‎src/myfunction.m‎

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function myfunction()
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disp('Hello, World!');
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end

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