MLDynamicMetabolicControl/dvc.lock at main · Toepfer-Lab/MLDynamicMetabolicControl · GitHub

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schema: '2.0'
stages:
  generate_data:
    cmd: "python scripts/generate_fba_data.py --model-path model/iML1515.xml --vman
      ACKr --condition anaerobic --n-samples 1000\n"
    deps:
    - path: scripts/generate_fba_data.py
      hash: md5
      md5: 785548a1a8109b0de912fdc9f998e94e
      size: 3439
    - path: src/
      hash: md5
      md5: f6c83e7b769865a83d79d6258359a2dc.dir
      size: 36118
      nfiles: 13
    params:
      params.yaml:
        data.condition: anaerobic
        data.n_samples: 1000
        data.vman: ACKr
    outs:
    - path: data/fba_data_ACKr_anaerobic.npz
      hash: md5
      md5: e3c93baf815dc7bd37dfa0deb58869ef
      size: 20030
  train_surrogate:
    cmd: "python scripts/train_surrogate.py --vman ACKr --condition anaerobic --hidden-dim
      4 --epochs 500 --patience 50 --lr 0.001 --model-name ACKr_trained_model_input-1_output-4_hidden-4\n"
    deps:
    - path: data/fba_data_ACKr_anaerobic.npz
      hash: md5
      md5: e3c93baf815dc7bd37dfa0deb58869ef
      size: 20030
    - path: scripts/train_surrogate.py
      hash: md5
      md5: 2ed2d008fa851e5b497dc4ccdcecf5eb
      size: 4573
    - path: src/
      hash: md5
      md5: f6c83e7b769865a83d79d6258359a2dc.dir
      size: 36118
      nfiles: 13
    params:
      params.yaml:
        training.epochs: 500
        training.hidden_dim: 4
        training.lr: 0.001
        training.patience: 50
    outs:
    - path: trained_models/ACKr_trained_model_input-1_output-4_hidden-4.pt
      hash: md5
      md5: 9e3b14e55777580b0ecb8b3ccc3e601f
      size: 4431
  optimize:
    cmd: "python scripts/optimize_vman.py --checkpoint trained_models/ACKr_trained_model_input-1_output-4_hidden-4.pt
      --t-start 0.0 --t-end 12 --num-intervals 40 --n-eval 1000 --bounds-lower -32.0
      --bounds-upper 12.0 --initial-state 10.0 0.0 0.01 --output-path results/optimize_vman_ACKr_hidden-4_tend-12_N-40.npz
      --logs-path results/optimize_vman_ACKr_hidden-4_tend-12_N-40_logs.npz\n"
    deps:
    - path: scripts/optimize_vman.py
      hash: md5
      md5: a141db1ae91ea2ed015a494ff00fd561
      size: 5546
    - path: src/
      hash: md5
      md5: 3e7730d724273291199d4873358ff43d.dir
      size: 36118
      nfiles: 13
    - path: trained_models/ACKr_trained_model_input-1_output-4_hidden-4.pt
      hash: md5
      md5: 9e3b14e55777580b0ecb8b3ccc3e601f
      size: 4431
    params:
      params.yaml:
        optimize:
          t_start: 0.0
          t_end: 12
          num_intervals: 40
          n_eval: 1000
          bounds_lower: -32.0
          bounds_upper: 12.0
          initial_state: 10.0 0.0 0.01
    outs:
    - path: results/optimize_vman_ACKr_hidden-4_tend-12_N-40.npz
      hash: md5
      md5: 2e9a614c483fec7b385cea3377716928
      size: 13242
    - path: results/optimize_vman_ACKr_hidden-4_tend-12_N-40_logs.npz
      hash: md5
      md5: 8e35e422433ac5a25f6ed76ca9e0e2d3
      size: 2866668
  plot:
    cmd: "python scripts/plot_optimize_vman.py --results results/optimize_vman_ACKr_hidden-4_tend-12_N-40.npz
      --logs results/optimize_vman_ACKr_hidden-4_tend-12_N-40_logs.npz --outdir plots/tend-12_N-40\n"
    deps:
    - path: results/optimize_vman_ACKr_hidden-4_tend-12_N-40.npz
      hash: md5
      md5: 2e9a614c483fec7b385cea3377716928
      size: 13242
    - path: results/optimize_vman_ACKr_hidden-4_tend-12_N-40_logs.npz
      hash: md5
      md5: 8e35e422433ac5a25f6ed76ca9e0e2d3
      size: 2866668
    - path: scripts/plot_optimize_vman.py
      hash: md5
      md5: 9d23b41558f5a005acbb088b189fa710
      size: 6868
    outs:
    - path: plots/tend-12_N-40/
      hash: md5
      md5: 2408d9c6ac3f44bac48954cd519d2d95.dir
      size: 795518
      nfiles: 2