docstrings added to percolations.py
changed simulation output file format and content

simulations export the following files:
a binary list of infecteds for each set of parameters
OR dictionary: dict[T] = [epiOR1, epiOR2, etc.]
diagnostics, OR_episize for epid only, data exp

diagnostic plots added:
epidemic size by T
number of epidemics by T

output plot added:
OR by epidemic size scatter for epidemics only

changed data outputs similar to vaxcov and vaxeff scripts
parameters for Ts near epi threshold - exploration

ran 2000 simulations for these Ts
there appears to be a slight decreasing pattern at T
values near the threshold of 0.0562
converted x-axis from coverage to efficacy

age_perc_vaxcov.py edits:
After running simulations, the ORs appear similar across
different vax efficacies even though the x-axis is the
only thing that should have changed. When plotted with coverage
in the x-axis, it appears that there is a slight increase in OR as
coverage (ie. efficacy) increases. Epidemic sizes don't vary
as much as expected.

Need to create a branch where we look at coverage in x-axis again
to see if the results are comparable.
time-based percolations - first commit

age_perc_T_time.py runs time-based percolations and outputs
added time-based percolation functions and OR calculations by
time to percolations.py
added OR by time printer to pretty_print.py
removed inefficient percolation functions

There were three commented out functions that were
deleted. Two were percolation functions that used
only list searches and only dictionaries. These were
moved to bad_percolations.py for reference. The
flawed function that calculated incidence for the
general percolation scenarios was also removed
because it did not return a value. If needed, it can
be written to a cleaner form.
moved write dict to file to end of script

age_perc_T_time.py
reorganization only
perc_gen includes OR function, found vaxcov error

percolations.py
- perc_age_gen percolation function incorporates OR
calculation
- changed variable name in calc_OR_from_list to be
more general because this function is now used in
perc_age_gen function to calculate OR for non time-
based simulations

age_perc_vaxcov.py
- removed incidence and OR calculations and changed
percolation results to accommodate OR value
- graph on which simulations were run was incorrectly
assigned to the non-vax graph (G) instead of the
random vax graph (VG); error was in place for results
produced between Aug 14, 2013 and Aug 22, 2013
added explanatory comments for dicts

age_perc_vaxeff.py
- no real changes
- retiring this script for now because the
vaxcov implementation of vax efficacy is
preferred by SB at this point
param change, T set to 40% AR in naive pop

age_perc_vaxcov.py
changed parameters to run simulations where T = 0.077
time-based epidemic S to I probability fixed

percolations.py
- In previous iterations, probability of s getting infected
at each time step was 1 - e^(-beta * number_infected_neighbors)
multiplied by the number of infected neighbors because the
simulation iterated through each susceptible neighbor of an
infected node. However, a susceptible could have multiple
infected neighbors, so the probability 1 - e^ was multiplied
by the number of infected neighbors. Now, the simulation
iterates through susceptibles for the S to I transition so
each susceptible has only one times 1 - e^ chance of getting
infected. For the I to R transition, the probability is equal
to gamma.
- Each simulation and OR calculation takes 0 to 15 seconds -
could try to improve this

age_perc_T_time.py
- changed parameters for simulation
perc fxn, fixed OR by episize, plt colors, cleaned

age_perc_T.py
- changed code to calculate OR using new perc_age_gen
function in percolations.py
- OR by episizes charts were updated to include all
results and epidemics only with careful sorting of
dict keys
- plot colors for each T value in OR by episize are
now a rainbow using colormap
- added additional comments and organized code to
improve readability
dict value sorting, rm some extra dicts

age_perc_vaxcov.py
- for dicts where lists are the values, and keys
were tuples, double checked that keys were sorted
prior to adding new values to the dictionary
(particularly with diagnostic plots)
- removed extraneous dicts that listed standard dev
renamed time-based sim fxn

percolations.py
- renamed function to be more explanatory
- minor formatting changes
prepared to write code for incid, preval, avgOR

age_perc_T_time.py
- added some new sections that have yet to be written
that examine: incidence over time, prevalence over time,
and calculate average OR at time = t
- consider using the profile python method to see why
the time-based simulations are so slow