BF/UT: adapt to new values of getstart
BF/UT: adapt to new values of getstart

We adapt to new numerical values of getstart here. The deviance value is only
slightly smaller (< 0.01), so this seems reasonable enough.

from pypsignifit import *
import swignifit.swignifit_raw as sfr
import swignifit.interface_methods as sfi
import swignifit.utility as sfu
x = [0., 2., 4., 6., 8., 10.]
k = [24, 32, 40, 48, 50, 48]
n = [50]*6
priors = [None, None, 'Uniform(0., 0.1)']
data, pmf, nparam = sfu.make_dataset_and_pmf(zip(x, k, n), 2, 'logistic', 'abCore', priors)
start = sfr.getstart(pmf,data, 7, 3, 3)
print start
p2 =(3.29584, 0.988751, 0.0185185)
print 'deviance param new:', sfi.diagnostics(zip(x,k,n), start, nafc=2)[2]
print 'deviance param old:', sfi.diagnostics(zip(x,k,n), p2, nafc=2)[2]

(3.3333333333333339, 0.88888888888888884, 0.020370370370370358)
deviance param new: 4.04819160657
deviance param old: 3.99714191303

esc/Psignifit-3.x,esc/Psignifit-3.x,esc/Psignifit-3.x,esc/Psignifit-3.x,esc/Psignifit-3.x,esc/Psignifit-3.x