electrificationplanner: Document pip freeze from modelrunner.io

[ingenieroariel]

As new packages get released conda may install different versions to what is already tested and running. I think it would be good to document complete known configurations (for example from what is on modelrunner.io) for posterity.

In my case, I set up an instance on Ubuntu 18.04 but had to go back and forth between conda and pip to be able to get to a working system, I am quite sure the version of Pandas and GDAL I ended up using were different to what was originally used (but it works).

For electrificationplanner this is the complete list of dependencies that worked for me:

archiveIO==0.4.4
attrs==18.1.0
backports-abc==0.5
backports.functools-lru-cache==1.5
certifi==2018.4.16
click==6.7
click-plugins==1.0.3
cligj==0.4.0
configparser==3.5.0
cycler==0.10.0
Cython==0.28.4
decorator==4.3.0
enum34==1.1.6
Fiona==1.7.12
funcsigs==1.0.2
functools32==3.2.3.post2
futures==3.2.0
GDAL==2.3.0
geographiclib==1.49
geometryIO==0.9.7.6
geopy==1.14.0
-e git+https://github.com/SEL-columbia/infrastructure-planning@112328b917366b297c408aa42594b5b048e40b38#egg=infrastructure_planning
invisibleroads-macros==0.9.4.4
jsonschema==2.6.0
kiwisolver==1.0.1
llvmlite==0.23.2
matplotlib==2.2.2
mkl-fft==1.0.2
mkl-random==1.0.1
munch==2.3.2
-e git+https://github.com/sel-columbia/networker@d9aee4f1d4f0ed530e4f5986c353af55f1a85207#egg=networker
networkx==1.11
nose==1.3.7
numba==0.38.0+0.g2a2b772fc.dirty
numexpr==2.6.4
numpy==1.14.5
pandas==0.23.3
pathlib==1.0.1
pyparsing==2.2.0
pyproj==1.9.5.1
python-dateutil==2.7.3
pytz==2018.5
Rtree==0.8.3
scikit-learn==0.19.1
scipy==1.1.0
-e git+https://github.com/piensa/sequencer@b68117bd623f33d5de722f7fd8c139960a0be51b#egg=Sequencer
Shapely==1.6.4.post1
simplejson==3.16.0
singledispatch==3.4.0.3
six==1.11.0
subprocess32==3.5.2
tornado==5.1