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95 lines
1.9 KiB
Groovy
95 lines
1.9 KiB
Groovy
import cz.siret.prank.features.weight.WeightFun
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import cz.siret.prank.program.params.Params
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(params as Params).with {
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/**
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* Number of computing threads
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*/
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threads = Runtime.getRuntime().availableProcessors() + 1
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/**
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* define this if you want dataset program parameters to be evaluated relative to this directory
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* (set absolute path or path relative to install dir, null defaults to working dir)
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*/
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dataset_base_dir = "./test_data"
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/**
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* all output of the prorgam will be stored in subdirectores of this directory
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* (set absolute path or path relative to install dir, null defaults to working dir)
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*/
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output_base_dir = "./test_output"
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/**
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* default model
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* (set path relative to install_dir/models/)
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*/
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model = "p2rank_a.model"
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/**
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* produce pymol visualisations
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*/
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visualizations = true
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/**
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* copy all protein pdb files to visualization folder (making visualizations portable)
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*/
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vis_copy_proteins = true
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/**
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* stop processing a datsaset on the first unrecoverable error with a dataset item
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*/
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fail_fast = false
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delete_models = true
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delete_vectors = true
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cache_datasets = false
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predictions = true
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out_prefix_date = false
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log_cases = false
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max_train_instances = 0
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classifier="FastRandomForest"
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rf_trees = 100
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seed = 42
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loop = 10
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use_volsite_features = true
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atom_table_features = ["apRawValids","apRawInvalids","atomicHydrophobicity"]
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extra_features = ["protrusion","bfactor"]
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residue_table_features = []
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protrusion_radius = 10
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weight_function = WeightFun.Option.INV
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// optimized values
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pred_point_threshold = 0.35
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pred_clustering_dist = 3
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neighbourhood_radius = 6
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positive_point_ligand_distance = 2.6
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train_pockets = 9
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surface_additional_cutoff = 2.5
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}
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