Commenting out defunct scripts

from deepchem.scripts.dock_dude import *

from ipyparallel import Client

rc = Client()

dview = rc[:]

prepare_ligands_and_dock_ligands_to_receptors("/home/enf/datasets/all", "/home/enf/deep-docking/shallow/dude_docked", dview)

#from deepchem.scripts.dock_dude import *

#from ipyparallel import Client

#rc = Client()

#dview = rc[:]

#prepare_ligands_and_dock_ligands_to_receptors("/home/enf/datasets/all", "/home/enf/deep-docking/shallow/dude_docked", dview)

#

import os

from deepchem.utils.save import load_from_disk, save_to_disk

from deepchem.featurizers.fingerprints import CircularFingerprint

from deepchem.featurizers.basic import RDKitDescriptors

from deepchem.featurizers.nnscore import NNScoreComplexFeaturizer

from deepchem.featurizers.grid_featurizer import GridFeaturizer

from deepchem.featurizers.featurize import DataLoader

dataset_file = "../../../datasets/pdbbind_full_df.pkl.gz"

print("About to load dataset form disk.")

dataset = load_from_disk(dataset_file)

print("Loaded dataset.")

grid_featurizer = GridFeaturizer(

    voxel_width=16.0, feature_types="voxel_combined",

    voxel_feature_types=["ecfp", "splif", "hbond", "pi_stack", "cation_pi",

    "salt_bridge"], ecfp_power=9, splif_power=9,

    parallel=True, flatten=True)

featurizers = [CircularFingerprint(size=1024)]

featurizers += [grid_featurizer, NNScoreComplexFeaturizer()]

#Make a directory in which to store the featurized complexes.

base_dir = "../../../grid_nnscore_circular_features"

if not os.path.exists(base_dir):

    os.makedirs(base_dir)

data_dir = os.path.join(base_dir, "data")

if not os.path.exists(data_dir):

    os.makedirs(data_dir)

featurized_samples_file = os.path.join(data_dir, "featurized_samples.joblib")

feature_dir = os.path.join(base_dir, "features")

if not os.path.exists(feature_dir):

    os.makedirs(feature_dir)

samples_dir = os.path.join(base_dir, "samples")

if not os.path.exists(samples_dir):

    os.makedirs(samples_dir)

featurizers = compound_featurizers + complex_featurizers

featurizer = DataLoader(tasks=["label"],

                        smiles_field="smiles",

                        protein_pdb_field="protein_pdb",

                        ligand_pdb_field="ligand_pdb",

                        compound_featurizers=compound_featurizers,

                        complex_featurizers=complex_featurizers,

                        id_field="complex_id",

                        verbose=False)

from ipyparallel import Client

c = Client()

print("c.ids")

print(c.ids)

dview = c[:]

featurized_samples = featurizer.featurize(dataset_file, feature_dir, samples_dir,

                                          worker_pool=dview, shard_size=1024)

save_to_disk(featurized_samples, featurized_samples_file)

#import os

#from deepchem.utils.save import load_from_disk, save_to_disk

#from deepchem.featurizers.fingerprints import CircularFingerprint

#from deepchem.featurizers.basic import RDKitDescriptors

#from deepchem.featurizers.nnscore import NNScoreComplexFeaturizer

#from deepchem.featurizers.grid_featurizer import GridFeaturizer

#from deepchem.featurizers.featurize import DataLoader

#

#dataset_file = "../../../datasets/pdbbind_full_df.pkl.gz"

#print("About to load dataset form disk.")

#dataset = load_from_disk(dataset_file)

#print("Loaded dataset.")

#

#grid_featurizer = GridFeaturizer(

#    voxel_width=16.0, feature_types="voxel_combined",

#    voxel_feature_types=["ecfp", "splif", "hbond", "pi_stack", "cation_pi",

#    "salt_bridge"], ecfp_power=9, splif_power=9,

#    parallel=True, flatten=True)

#featurizers = [CircularFingerprint(size=1024)]

#featurizers += [grid_featurizer, NNScoreComplexFeaturizer()]

#

##Make a directory in which to store the featurized complexes.

#base_dir = "../../../grid_nnscore_circular_features"

#if not os.path.exists(base_dir):

#    os.makedirs(base_dir)

#data_dir = os.path.join(base_dir, "data")

#if not os.path.exists(data_dir):

#    os.makedirs(data_dir)

#    

#featurized_samples_file = os.path.join(data_dir, "featurized_samples.joblib")

#

#feature_dir = os.path.join(base_dir, "features")

#if not os.path.exists(feature_dir):

#    os.makedirs(feature_dir)

#

#samples_dir = os.path.join(base_dir, "samples")

#if not os.path.exists(samples_dir):

#    os.makedirs(samples_dir)

#

#

#

#featurizers = compound_featurizers + complex_featurizers

#featurizer = DataLoader(tasks=["label"],

#                        smiles_field="smiles",

#                        protein_pdb_field="protein_pdb",

#                        ligand_pdb_field="ligand_pdb",

#                        compound_featurizers=compound_featurizers,

#                        complex_featurizers=complex_featurizers,

#                        id_field="complex_id",

#                        verbose=False)

#from ipyparallel import Client

#c = Client()

#print("c.ids")

#print(c.ids)

#dview = c[:]

#featurized_samples = featurizer.featurize(dataset_file, feature_dir, samples_dir,

#                                          worker_pool=dview, shard_size=1024)

#

#save_to_disk(featurized_samples, featurized_samples_file)