Quick Reference: Parallel HOMFLY Processing

TL;DR - Getting Started

# 1. Create a new virtual environment in the .venv folder:  
python3 -m venv .venv 

# 2. Activate this environment:
source .venv/bin/activate

# 3. Install dependencies
pip install -r requirements.txt

# 4. Put pdb files into "data" folder (or adjust the path in run_all_knots.py)

# 5. Run with defaults (8 workers, save every 500 structures)
python run_all_knots.py

# 6. Check results in homfly_results/ folder
ls -la homfly_results/

Command Line Usage

Default (Recommended)

python run_all_knots.py

Output Files Structure

homfly_results/
├── homfly_results_20260707_150530_checkpoint_100.csv
├── homfly_results_20260707_150530_checkpoint_100.xlsx
├── homfly_results_20260707_150530_checkpoint_200.csv
├── homfly_results_20260707_150530_checkpoint_200.xlsx
├── ...
├── homfly_results_20260707_150530_final.csv
└── homfly_results_20260707_150530_final.xlsx

Monitoring Progress

During execution, you'll see:

Total files to process: 1900
Processed: 1/1900
Processed: 2/1900
...
Processed: 100/1900
Saved checkpoint at 100 structures
Saved CSV: homfly_results/homfly_results_20260707_150530_checkpoint_100.csv
Saved Excel: homfly_results/homfly_results_20260707_150530_checkpoint_100.xlsx
...
Final results saved! Total: 1900 structures processed

CSV/Excel Column Reference

Column	Description	Example
ID	File path	data_batch/pept_seq_last_refine_100_1.pdb
Knot_Type	Detected knot type	4_1
Probability	Max probability (filtered)	0.85
Unknot_Probability	Unknot (0_1) probability	0.05
Details	Full polynomial data (JSON)	{"4_1": 0.85, "5_1": 0.10}

Example Output Preview

CSV (excerpt)

ID,Knot_Type,Probability,Unknot_Probability,Details
data/pept_seq_last_refine_100_1.pdb,4_1,0.85,0.05,"{""4_1"": 0.85, ""5_1"": 0.10}"
data/pept_seq_last_refine_100_2.pdb,3_1,0.72,0.12,"{""3_1"": 0.72, ""4_1"": 0.16}"