Merge branch 'master' into 'develop'

Master2Dev

See merge request toar/mlair!172

CHANGELOG.md

 # Changelog
 All notable changes to this project will be documented in this file.
 
+## v1.0.0 -  2020-10-08  - official release of new version 1.0.0
+
+### general:
+- This is the first official release of MLAir ready for use
+- updated license, installation instruction
+
+### technical:
+- restructured order of packages in requirements
 
 ## v0.12.2 -  2020-10-01  - HDFML support
 

README.md

@@ -29,7 +29,7 @@ HPC systems, see [here](#special-instructions-for-installation-on-jülich-hpc-sy
 * Installation of **MLAir**:
     * Either clone MLAir from the [gitlab repository](https://gitlab.version.fz-juelich.de/toar/mlair.git) 
       and use it without installation (beside the requirements) 
-    * or download the distribution file ([current version](https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/dist/mlair-0.12.2-py3-none-any.whl)) 
+    * or download the distribution file ([current version](https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/dist/mlair-1.0.0-py3-none-any.whl)) 
       and install it via `pip install <dist_file>.whl`. In this case, you can simply import MLAir in any python script 
       inside your virtual environment using `import mlair`.
 * (tf) Currently, TensorFlow-1.13 is mentioned in the requirements. We already tested the TensorFlow-1.15 version and couldn't

docs/_source/get-started.rst

@@ -31,7 +31,7 @@ Installation of MLAir
 * Install all requirements from `requirements.txt <https://gitlab.version.fz-juelich.de/toar/machinelearningtools/-/blob/master/requirements.txt>`_
   preferably in a virtual environment
 * Either clone MLAir from the `gitlab repository <https://gitlab.version.fz-juelich.de/toar/machinelearningtools.git>`_
-* or download the distribution file (`current version <https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/dist/mlair-0.12.2-py3-none-any.whl>`_)
+* or download the distribution file (`current version <https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/dist/mlair-1.0.0-py3-none-any.whl>`_)
   and install it via :py:`pip install <dist_file>.whl`. In this case, you can simply
   import MLAir in any python script inside your virtual environment using :py:`import mlair`.
 * (tf) Currently, TensorFlow-1.13 is mentioned in the requirements. We already tested the TensorFlow-1.15 version and couldn't

mlair/__init__.py

 __version_info__ = {
-    'major': 0,
-    'minor': 12,
-    'micro': 2,
+    'major': 1,
+    'minor': 0,
+    'micro': 0,
 }
 
 from mlair.run_modules import RunEnvironment, ExperimentSetup, PreProcessing, ModelSetup, Training, PostProcessing
@@ -13,7 +13,7 @@ from mlair.model_modules import AbstractModelClass
 def get_version():
     assert set(__version_info__.keys()) >= {"major", "minor"}
     vers = [f"{__version_info__['major']}.{__version_info__['minor']}"]
-    if __version_info__["micro"]:
+    if "micro" in __version_info__:
         vers.append(f".{__version_info__['micro']}")
     return "".join(vers)