Add qm9db

1 files changed, 62 insertions, 0 deletions

diff --git a/ml_exp/qm9db.py b/ml_exp/qm9db.py
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+++ b/ml_exp/qm9db.py
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+"""MIT License
+
+Copyright (c) 2019 David Luevano Alvarado
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+"""
+from ml_exp.compound import Compound
+import numpy as np
+try:
+    import tensorflow as tf
+    TF_AV = True
+except ImportError:
+    print('Tensorflow couldn\'t be imported. Maybe it is not installed.')
+    TF_AV = False
+import random
+
+
+def qm9db(db_path='data',
+          is_shuffled=True,
+          r_seed=111,
+          use_tf=True):
+    """
+    Creates a list of compounds with the qm9 database.
+    db_path: path to the database directory.
+    is_shuffled: if the resulting list of compounds should be shuffled.
+    r_seed: random seed to use for the shuffling.
+    use_tf: if tensorflow should be used.
+    """
+    # If tf is to be used but couldn't be imported, don't try to use it.
+    if use_tf and not TF_AV:
+        use_tf = False
+
+    fname = f'{db_path}/xyz_qm9.txt'
+    with open(fname, 'r') as f:
+        lines = f.readlines()
+
+    compounds = []
+    for i, line in enumerate(lines):
+        line = line.strip()
+        compounds.append(Compound(f'{db_path}/{line}', db='qm9'))
+
+    if is_shuffled:
+        random.seed(r_seed)
+        random.shuffle(compounds)
+
+    return compounds