Merge pull request #29 from ECRL/dev

Bug fixes, database creation improvements

ecnet/__init__.py

@@ -1,2 +1,2 @@
 from ecnet.server import Server
-__version__ = '3.0.0'
+__version__ = '3.0.1'

ecnet/models/mlp.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 #
 # ecnet/models/mlp.py
-# v.3.0.0
+# v.3.0.1
 # Developed in 2019 by Travis Kessler <[email protected]>
 #
 # Contains the "MultilayerPerceptron" (feed-forward neural network) class

ecnet/server.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 #
 # ecnet/server.py
-# v.3.0.0
+# v.3.0.1
 # Developed in 2019 by Travis Kessler <[email protected]>
 #
 # Contains the "Server" class, which handles ECNet project creation, neural
@@ -23,9 +23,9 @@
     save_config, save_df, train_model, use_model
 
 # Stdlib imports
-from os import listdir, makedirs, path, walk
+from os import listdir, makedirs, name, path, walk
 from operator import itemgetter
-from multiprocessing import Pool
+from multiprocessing import Pool, set_start_method
 from shutil import rmtree
 from zipfile import ZipFile, ZIP_DEFLATED
 
@@ -53,6 +53,9 @@ def __init__(self, model_config='config.yml', prj_file=None,
 
         self._num_processes = num_processes
 
+        if name != 'nt':
+            set_start_method('spawn', force=True)
+
         if prj_file is not None:
             self._open_project(prj_file)
             return

ecnet/tasks/limit_inputs.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 #
 # ecnet/tasks/limit_inputs.py
-# v.3.0.0
+# v.3.0.1
 # Developed in 2019 by Travis Kessler <[email protected]>
 #
 # Contains functions for selecting influential input parameters
@@ -37,6 +37,7 @@ def limit_rforest(df, limit_num, num_estimators=1000, num_processes=1):
     if logger.file_level != 'disable':
         ditto_logger.log_dir = logger.log_dir
         ditto_logger.file_level = logger.file_level
+    ditto_logger.default_call_loc('LIMIT')
     item_collection = ItemCollection(df._filename)
     for inp_name in df.input_names:
         item_collection.add_attribute(Attribute(inp_name))

ecnet/tasks/remove_outliers.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 #
 # ecnet/tasks/remove_outliers.py
-# v.3.0.0
+# v.3.0.1
 # Developed in 2019 by Travis Kessler <[email protected]>
 #
 # Contains function for removing outliers from ECNet DataFrame
@@ -38,6 +38,7 @@ def remove_outliers(df, leaf_size=40, num_processes=1):
     if logger.file_level != 'disable':
         ditto_logger.log_dir = logger.log_dir
         ditto_logger.file_level = logger.file_level
+    ditto_logger.default_call_loc('OUTLIERS')
     item_collection = ItemCollection(df._filename)
     for inp_name in df.input_names:
         item_collection.add_attribute(Attribute(inp_name))

ecnet/tasks/tuning.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 #
 # ecnet/tasks/tuning.py
-# v.3.0.0
+# v.3.0.1
 # Developed in 2019 by Travis Kessler <[email protected]>
 #
 # Contains functions/fitness functions for tuning hyperparameters
@@ -73,6 +73,7 @@ def tune_hyperparameters(df, vars, num_employers, num_iterations,
     if logger.file_level != 'disable':
         abc._logger.log_dir = logger.log_dir
         abc._logger.file_level = logger.file_level
+    abc._logger.default_call_loc('TUNE')
     abc.create_employers()
     for i in range(num_iterations):
         logger.log('info', 'Iteration {}'.format(i + 1), call_loc='TUNE')
@@ -92,7 +93,7 @@ def tune_hyperparameters(df, vars, num_employers, num_iterations,
     vars['beta_2'] = params[1]
     vars['decay'] = params[2]
     vars['epsilon'] = params[3]
-    vars['learning_date'] = params[4]
+    vars['learning_rate'] = params[4]
     for l_idx in range(len(vars['hidden_layers'])):
         vars['hidden_layers'][l_idx][0] = params[5 + l_idx]
     return vars

ecnet/tools/conversions.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 #
 # ecnet/tools/conversions.py
-# v.3.0.0
+# v.3.0.1
 # Developed in 2019 by Travis Kessler <[email protected]>
 #
 # Contains functions for converting various chemical file formats
@@ -39,7 +39,7 @@ def get_smiles(name):
 
     smiles = [m.isomeric_smiles for m in get_compounds(name, 'name')]
     if len(smiles) == 0:
-        raise IndexError('PubChem entry not found for {}'.format(name))
+        return ''
     else:
         return smiles[0]
 
@@ -84,13 +84,15 @@ def smiles_to_mdl(smiles_file, mdl_file):
                 continue
 
 
-def mdl_to_descriptors(mdl_file, descriptors_csv):
+def mdl_to_descriptors(mdl_file, descriptors_csv, fingerprints=False):
     '''Generates QSPR descriptors from supplied MDL file using
     PaDEL-Descriptor
 
     Args:
         mdl_file (str): path to source MDL file
         descriptors_csv (str): path to resulting CSV file w/ descriptors
+        fingerprints (bool): if True, generates molecular fingerprints instead
+            of QSPR descriptors
 
     Returns:
         list: list of dicts, where each dict is a molecule populated with
@@ -105,20 +107,35 @@ def mdl_to_descriptors(mdl_file, descriptors_csv):
     dn = open(devnull, 'w')
     for attempt in range(3):
         try:
-            call([
-                'java',
-                '-jar',
-                _PADEL_PATH,
-                '-2d',
-                '-3d',
-                '-retainorder',
-                '-retain3d',
-                '-dir',
-                mdl_file,
-                '-file',
-                descriptors_csv
-            ], stdout=dn, stderr=dn, timeout=3600)
-            break
+            if fingerprints:
+                call([
+                    'java',
+                    '-jar',
+                    _PADEL_PATH,
+                    '-fingerprints',
+                    '-retainorder',
+                    '-retain3d',
+                    '-dir',
+                    mdl_file,
+                    '-file',
+                    descriptors_csv
+                ], stdout=dn, stderr=dn, timeout=600)
+                break
+            else:
+                call([
+                    'java',
+                    '-jar',
+                    _PADEL_PATH,
+                    '-2d',
+                    '-3d',
+                    '-retainorder',
+                    '-retain3d',
+                    '-dir',
+                    mdl_file,
+                    '-file',
+                    descriptors_csv
+                ], stdout=dn, stderr=dn, timeout=600)
+                break
         except Exception as e:
             if attempt == 2:
                 raise e

ecnet/tools/database.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 #
 # ecnet/tools/database.py
-# v.3.0.0
+# v.3.0.1
 # Developed in 2019 by Travis Kessler <[email protected]>
 #
 # Contains functions for creating ECNet-formatted databases
@@ -20,7 +20,7 @@
 
 def create_db(input_txt, output_name, id_prefix='', targets=None, form='name',
               smiles_file='mols.smi', mdl_file='mols.mdl',
-              desc_file='descriptors.csv', clean_up=True):
+              desc_file='descriptors.csv', clean_up=True, fingerprints=False):
     '''Create an ECNet-formatted database from either molecule names or SMILES
     strings
 
@@ -37,6 +37,8 @@ def create_db(input_txt, output_name, id_prefix='', targets=None, form='name',
         desc_file (str): name of descriptors file generated by PaDEL-Descriptor
         clean_up (bool): if True, cleans up all files generated during
             processing except for the input text files and output database
+        fingerprints (bool): if True, generates molecular fingerprints instead
+            of QSPR descriptors
     '''
 
     input_data = _read_txt(input_txt)
@@ -67,7 +69,7 @@ def create_db(input_txt, output_name, id_prefix='', targets=None, form='name',
         target_data = [0 for _ in range(len(input_data))]
 
     smiles_to_mdl(smiles_file, mdl_file)
-    desc = mdl_to_descriptors(mdl_file, desc_file)
+    desc = mdl_to_descriptors(mdl_file, desc_file, fingerprints)
     desc_keys = list(desc[0].keys())
     try:
         desc_keys.remove('Name')

ecnet/tools/project.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 #
 # ecnet/tools/project.py
-# v.3.0.0
+# v.3.0.1
 # Developed in 2019 by Travis Kessler <[email protected]>
 #
 # Contains functions for predicting data using pre-existing .prj files

ecnet/utils/data_utils.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 #
 # ecnet/utils/data_utils.py
-# v.3.0.0
+# v.3.0.1
 # Developed in 2019 by Travis Kessler <[email protected]>
 #
 # Contains functions/classes for loading data, saving data, saving results

ecnet/utils/error_utils.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 #
 # ecnet/utils/error_utils.py
-# v.3.0.0
+# v.3.0.1
 # Developed in 2019 by Travis Kessler <[email protected]>
 #
 # Contains functions for error calculations

ecnet/utils/logging.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 #
 # ecnet/utils/logging.py
-# v.3.0.0
+# v.3.0.1
 # Developed in 2019 by Travis Kessler <[email protected]>
 #
 # Contains logger used by ECNet

ecnet/utils/server_utils.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 #
 # ecnet/utils/server_utils.py
-# v.3.0.0
+# v.3.0.1
 # Developed in 2019 by Travis Kessler <[email protected]>
 #
 # Contains functions used by ecnet.Server

setup.py

@@ -2,7 +2,7 @@
 
 setup(
     name='ecnet',
-    version='3.0.0',
+    version='3.0.1',
     description='UMass Lowell Energy and Combustion Research Laboratory Neural'
                 ' Network Software',
     url='http://github.com/tjkessler/ecnet',

tests/test_create_db.py

@@ -22,7 +22,20 @@ def from_smiles():
     )
 
 
+def fingerprints():
+
+    print('Creating database with fingerprints...')
+    create_db(
+        'mols_smiles.txt',
+        'db_with_fingerprints.csv',
+        targets='mols_targets.txt',
+        form='smiles',
+        fingerprints=True
+    )
+
+
 if __name__ == '__main__':
 
     from_names()
     from_smiles()
+    fingerprints()