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Merge pull request #4 from codegithubka/kimon
Kimon
2 parents f33cbab + 254bfd6 commit 047e457

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docs/HPC_GUIDE.md

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### Snellius Usage Breakdown
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```
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ssh <your_username>@snellius.surf.nl
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# On a separate terminal run the following
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# Upload the entire project directory (including your models/ folder)
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scp -r ~/Documents/CSS_Project <your_username>@snellius.surf.nl:~/
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# On the Snellius terminal
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module load 2023 Python/3.11.3-GCCcore-12.3.0
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python3 -m venv ~/css_env
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source ~/css_env/bin/activate
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pip install numpy scipy matplotlib joblib
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# To do a dry run for testing the entire environment
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python3 pp_analysis.py --mode full --dry-run
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# For async run
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python3 pp_analysis.py --mode full --output results_${SLURM_JOB_ID} --cores $SLURM_CPUS_PER_TASK --async
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# To submit a job
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sbatch run_analysis.sh
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# Check Queue Status
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squeue -u $USER
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# Cancel a job
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scancel <JOBID>
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# Monitoring live progress
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tail -f logs_<JOBID>.err
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# Fetching the results once the job is done
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scp -r <your_username>@snellius.surf.nl:~/results_18514601 ~/Downloads/
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```
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The jobscript template can be found in ```run_analysis.sh``` (default rome paritition).
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Snellius Partitions Page: https://servicedesk.surf.nl/wiki/spaces/WIKI/pages/30660209/Snellius+partitions+and+accounting

docs/prompts.md

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### output
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Made large changes to multiple functions. See git commit for details.
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---
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### Mean Field class
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7. Create a bifuracation diagram to confirm the monotonic relationship for a varying prey death rate vs. equilibrium density.
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###
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---
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### Testing CA class
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1. Create a comprehensive testing suite for the CA and PP classes. Test initialization, async update changes, synchronous update changes, prey growth in isolation behavior, predator starvation, parameter evolution and long run dynamics. Also make sur ethe test_viz mehtod works as desired
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### Parameter Sweep and PP Class Analysis
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2. Create a skeletal version of a .py script that will be subimtted into Snellius for parameter analysis. The purpose of this script should be to identify power law distribution with the consideration of finite size scaling, the hydra effect, and suitable parameter configurtaions for time series analysis for model evolution. Compare the non-evo to the evo model.
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3. Create a config class adjustable depending on the CPU budget. We want to run a prey_birth vs. predator_death parameter sweep (2D), quantify the hydra effect using the derivative, search for the critical point (power law relartionship paramameter), quantify evolution sensitivity and analyze finite grid size scaling. Include script options for cost optimal runs as well. Make sure to have a summary of collected data stored for reference and future usage.
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4. Add configuration option to run the asynchronous version of the CA class. The synchronous functionality should also be preserved. Provide me with a small smoke test to see if the updated file runs as expected.
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5. Create a minimal bash script for Snellius. Use the rome configiuration.
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