Merge pull request #110 from usnistgov/develop

Develop

README.md

@@ -230,6 +230,8 @@ run_alignn_ff.py -h
 Performances
 -------------------------
 
+Please refer to [JARVIS-Leaderboard](https://pages.nist.gov/jarvis_leaderboard/) to check the performance of ALIGNN models on several databases.
+
 ### 1) On JARVIS-DFT 2021 dataset (classification)
 
 |     Model                               |     Threshold         |     ALIGNN    |
@@ -283,7 +285,7 @@ Performances
 
 ### 3) On Materials project 2018 dataset
 
-The results from models other than ALIGNN are reported as given in corresponding papers, not necessarily reproduced by us. You can also refer to [MatBench](https://matbench.materialsproject.org/) project to check the performance of ALIGNN model on the Materials project and other databases.
+The results from models other than ALIGNN are reported as given in corresponding papers, not necessarily reproduced by us. 
 
 |     Prop    |     Unit      |     MAD     |     CFID     |     CGCNN    |     MEGNet    |     SchNet    |     ALIGNN    |     MAD:MAE    |
 |-------------|---------------|-------------|--------------|--------------|---------------|---------------|---------------|----------------|

alignn/__init__.py

@@ -1,2 +1,2 @@
 """Version number."""
-__version__ = "2023.05.30"
+__version__ = "2023.05.31"

alignn/train_folder_ff.py

@@ -323,7 +323,7 @@ def train_for_folder(
     train_for_folder(
         root_dir=args.root_dir,
         config_name=args.config_name,
-        keep_data_order=args.keep_data_order,
+        # keep_data_order=args.keep_data_order,
         classification_threshold=args.classification_threshold,
         output_dir=args.output_dir,
         batch_size=(args.batch_size),

setup.py

@@ -10,7 +10,7 @@
 
 setuptools.setup(
     name="alignn",
-    version="2023.05.30",
+    version="2023.05.31",
     author="Kamal Choudhary, Brian DeCost",
     author_email="[email protected]",
     description="alignn",