Release v0.6 (#246)

* update

* run test

* update

.github/workflows/mac.yml

@@ -46,7 +46,7 @@ jobs:
       fail-fast: false
       max-parallel: 6
       matrix:
-        python-version: [3.6, 3.7, 3.8]
+        python-version: [3.7, 3.8, 3.9]
         os: ["macos-11.0", "macos-10.15"]
 
     steps:

.github/workflows/ubuntu.yml

@@ -46,7 +46,7 @@ jobs:
       fail-fast: false
       max-parallel: 6
       matrix:
-        python-version: [3.6, 3.7, 3.8]
+        python-version: [3.7, 3.8, 3.9]
         os: ["ubuntu-18.04", "ubuntu-latest"]
 
     steps:

.github/workflows/win.yml

@@ -46,7 +46,7 @@ jobs:
       fail-fast: false
       max-parallel: 3
       matrix:
-        python-version: [3.6, 3.7, 3.8]
+        python-version: [3.7, 3.8, 3.9]
         os: ["windows-latest"]
 
     steps:

README.md

@@ -35,7 +35,10 @@ See our documents for details: http://xenonpy.readthedocs.io
 
 1. Yamada, H. et al. Predicting Materials Properties with Little Data Using Shotgun Transfer Learning. ACS Cent. Sci. acscentsci.9b00804 (2019). doi:10.1021/acscentsci.9b00804
 
-## XenonPy images
+## XenonPy images (deprecated)
+
+> Docker has introduced a new [Subscription Service Agreement](https://www.docker.com/legal/docker-subscription-service-agreement) which requires organizations with more than 250 employees or more than $10 million in revenue to buy a paid subscription.
+> Since the fact that Docker company has been changed their policy to business first mode, we decided to drop the prebuilt Docker images service.
 
 [XenonPy base images](https://hub.docker.com/repository/docker/yoshidalab/base) packed a lot of useful packages for materials informatics using.
 The following table list some core packages in XenonPy images.

docs/source/changes.rst

@@ -5,6 +5,24 @@
 Changes
 =======
 
+v0.6.0
+======
+
+**Bug fix**
+
+* Fix a bug in the ``Scaler`` class. ( `#243`_ )
+
+**New features**
+
+* Add ``average`` option to the ``classification_metrics`` function. Now users can decide how to calculate scores for multilabel tasks. ( `#240`_ )
+* Add ``only_best_states`` option to the ``Persist`` class. If ``True``, ``Persist`` will only save the best state to reduce the storage space. ( `#233`_ )
+* Add ``warming_up`` option to the ``Validator`` class. ( `#238`_ )
+
+.. _#243: https://github.com/yoshida-lab/XenonPy/pull/243
+.. _#240: https://github.com/yoshida-lab/XenonPy/pull/240
+.. _#233: https://github.com/yoshida-lab/XenonPy/pull/233
+.. _#238: https://github.com/yoshida-lab/XenonPy/pull/238
+
 v0.5.2
 ======
 

xenonpy/model/training/base.py

@@ -15,6 +15,7 @@
 __all__ = ['BaseRunner', 'BaseLRScheduler', 'BaseOptimizer', 'BaseExtension']
 
 
+
 class BaseExtension(object):
 
     def before_proc(self, trainer: 'BaseRunner' = None, is_training: bool = True, *_dependence: 'BaseExtension') -> None: