NEW MODULED: filter_phot() in mywrangle.py

- filter_phot takes in a data np struct array with columns of
  mags, magerrs, ra, dec, etc (observed or mock data), and
  depending on the filter, it makes cuts to the dataset. Right
  now those cuts are those provided by MG in the case of the
  Herc data set.

- main.py: within if sim == 1:, removed mass_min to the call to
  simulate_cmd.py. Ideally, don't want to simulate a CMD with
  mass cuts due to the possiblity of Malmquist biases when
  converting to magnitude space. Have not revised sim == 0
  case. Still get bad fit to alpha with input alpha=2.35 and
  output ~ 1.96

- Next update will be to instead create a small module to
  guesstimate how many stars should be selected from the
  entire CMD *if* we want Nstars in a given range of masses.
  This will slow down computation a bit but is the cleanest
  way to create an unbiased CMD. The alternative is to give
  instead a tolerance value for how much lower should one go
  in the mass function so that all or most observed stars within
  the photometric cuts are reproduced (even those that are up-
  scattered from lower-masses due to photometric errors).