changelog, version, and readme is up-to-date, include distribution file

CHANGELOG.md

@@ -2,6 +2,19 @@
 All notable changes to this project will be documented in this file.
 
 
+## v0.12.1 -  2020-09-28  - examples in notebook
+
+### general:
+- introduced a notebook documentation for easy starting, #174
+- updated special installation instructions for the Juelich HPC systems, #172
+
+### new features:
+- names of input and output shape are renamed consistently to: input_shape, and output_shape, #175
+
+### technical:
+- it is possible to assign a custom name to a run module (e.g. used in logging), #173
+
+
 ## v0.12.0 -  2020-09-21  - Documentation and Bugfixes
 
 ### general:

README.md

@@ -17,17 +17,18 @@ install the geo packages. For special instructions to install MLAir on the Jueli
 
 * (geo) Install **proj** on your machine using the console. E.g. for opensuse / leap `zypper install proj`
 * (geo) A c++ compiler is required for the installation of the program **cartopy**
-* Install all requirements from [`requirements.txt`](https://gitlab.version.fz-juelich.de/toar/machinelearningtools/-/blob/master/requirements.txt)
+* Install all requirements from [`requirements.txt`](https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/requirements.txt)
   preferably in a virtual environment
 * (tf) Currently, TensorFlow-1.13 is mentioned in the requirements. We already tested the TensorFlow-1.15 version and couldn't
   find any compatibility errors. Please note, that tf-1.13 and 1.15 have two distinct branches each, the default branch 
   for CPU support, and the "-gpu" branch for GPU support. If the GPU version is installed, MLAir will make use of the GPU
   device.
 * Installation of **MLAir**:
-    * Either clone MLAir from the [gitlab repository](https://gitlab.version.fz-juelich.de/toar/machinelearningtools.git) 
+    * 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 (?? .whl) and install it via `pip install <??>`. In this case, you can simply
-      import MLAir in any python script inside your virtual environment using `import mlair`.
+    * or download the distribution file ([current version](https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/dist/mlair-0.12.1-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`.
       
 
 # How to start with MLAir

mlair/__init__.py

 __version_info__ = {
     'major': 0,
     'minor': 12,
-    'micro': 0,
+    'micro': 1,
 }
 
 from mlair.run_modules import RunEnvironment, ExperimentSetup, PreProcessing, ModelSetup, Training, PostProcessing