Condition_learning/evaluation-scripts/run_diversity_experiments.sh at main · MolecularAI/Condition_learning · GitHub

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uv run src/condition_learning/evaluation/diversity.py \
    --hte_dataset_path data/datasets/val_data_pfizer1_no_additive.h5 \
    --reaction_type amide_coupling \
    --method morgan \
    --max_batch_size 32 \
    --num_repeats 2048 \
    --kernel_type gaussian \
    --kernel_metric jaccard \
    --kernel_length_scale 1 0.5 0.25 0.125 0.0625 0.030125 \
    --output_path data/condition_diversity/morgan/param_screen/jaccard_distance.csv

uv run src/condition_learning/evaluation/diversity.py \
    --hte_dataset_path data/datasets/val_data_pfizer1_no_additive.h5 \
    --reaction_type amide_coupling \
    --method mordred \
    --max_batch_size 32 \
    --num_repeats 2048 \
    --kernel_type gaussian \
    --kernel_metric cityblock \
    --kernel_length_scale 8 16 32 64 128 256 \
    --output_path data/condition_diversity/mordred/param_screen/manhattan_distance.csv

uv run src/condition_learning/evaluation/diversity.py \
    --hte_dataset_path data/datasets/val_data_pfizer1_no_additive.h5 \
    --precomputed_embeddings_path embeddings/evaluation/diversity.h5 \
    --reaction_type amide_coupling \
    --method learnt \
    --max_batch_size 32 \
    --num_repeats 2048 \
    --kernel_type gaussian \
    --kernel_metric eucldiean \
    --kernel_length_scale 2 4 8 16 32 64 128 \
    --output_path data/condition_diversity/mordred/param_screen/eucldiean_distance.csv