Added explaination of how to compile to the manylinux standard. (#15)

* updated version and installation notes

* a little more install info, fixed package

* added manylinux distribution information.

MANYLINUX.md

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+[Install docker](https://docs.docker.com/get-docker/).
+
+Get the [manylinux docker environment](https://github.com/pypa/manylinux). 
+At the time of this writing, `manylinux1` is compatible; however, I used `manylinx2014`. 
+There is a tool which will label the manylinux binary with the oldest compatible standard. 
+
+```bash
+docker pull quay.io/pypa/manylinux2014_x86_64
+```
+
+Run an interactive bash shell in the manylinux docker environment.
+
+```bash
+docker run -it quay.io/pypa/manylinux2014_x86_64 /bin/bash
+```
+
+Inside the interactive bash shell for the docker environment, download lie_learn and change to the source directory.
+
+```bash
+git clone https://github.com/AMLab-Amsterdam/lie_learn.git
+cd lie_learn
+```
+
+Create wheels. You have to determine which versions of python are appropriate.
+
+```bash
+/opt/python/cp35-cp35m/bin/python setup.py bdist_wheel
+/opt/python/cp36-cp36m/bin/python setup.py bdist_wheel
+/opt/python/cp37-cp37m/bin/python setup.py bdist_wheel
+/opt/python/cp38-cp38/bin/python setup.py bdist_wheel
+```
+
+Use auditwheel to check for success and modify the binaries to be labeled with the oldest compatible standard (lowest
+ priority).
+
+```bash
+auditwheel repair ./dist/lie_learn-0.0.1.post1-cp35-cp35m-linux_x86_64.whl -w ./manylinux
+auditwheel repair ./dist/lie_learn-0.0.1.post1-cp36-cp36m-linux_x86_64.whl -w ./manylinux
+auditwheel repair ./dist/lie_learn-0.0.1.post1-cp37-cp37m-linux_x86_64.whl -w ./manylinux
+auditwheel repair ./dist/lie_learn-0.0.1.post1-cp38-cp38-linux_x86_64.whl -w ./manylinux
+``` 
+
+Open a new terminal window (host environment) and get the running docker `CONTAINER ID`.
+
+```bash
+docker ps
+```
+
+yields
+
+```
+CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
+8e2b2c3baa8e quay.io/pypa/manylinux2014_x86_64 "/bin/bash" 30 minutes ago Up 30 minutes charming_shannon
+```
+
+In my case, the `CONTAINER ID` is `8e2b2c3baa8e`. 
+In the new terminal window, copy the manylinux wheels from the running container to a folder you'll remember.
+
+```bash
+mkdir ~/manylinux
+docker cp 8e2b2c3baa8e:/lie_learn/manylinux/lie_learn-0.0.1.post1-cp35-cp35m-manylinux1_x86_64.whl ~/manylinux/
+docker cp 8e2b2c3baa8e:/lie_learn/manylinux/lie_learn-0.0.1.post1-cp36-cp36m-manylinux1_x86_64.whl ~/manylinux/
+docker cp 8e2b2c3baa8e:/lie_learn/manylinux/lie_learn-0.0.1.post1-cp37-cp37m-manylinux1_x86_64.whl ~/manylinux/
+docker cp 8e2b2c3baa8e:/lie_learn/manylinux/lie_learn-0.0.1.post1-cp38-cp38-manylinux1_x86_64.whl ~/manylinux/
+```
+
+First do a test by uploading to test pypi. 
+
+```bash
+twine upload --repository-url https://test.pypi.org/legacy/ ~/manylinux/*
+```
+
+Try downloading and testing `lie_learn` from there before proceeding. 
+This is easier said than done. You will need to download all of the dependencies manually then download from test 
+pypi without any dependencies using 
+`pip install --no-cache-dir --index-url https://test.pypi.org/simple/ --no-deps lie_learn`.
+
+Once you know it's working, upload the wheels to pypi with twine.
+
+```bash
+twine upload ~/manylinux/*
+```
+
+For a bit more info, another useful resource is https://opensource.com/article/19/2/manylinux-python-wheels.