1 files changed, 0 insertions, 62 deletions
diff --git a/ml_exp/qm9db.py b/ml_exp/qm9db.py
deleted file mode 100644
index 8354075bc..000000000
--- a/ml_exp/qm9db.py
+++ /dev/null
@@ -1,62 +0,0 @@
-"""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