added validate_ktransit function

[skgrunblatt]

import ktransit

def validate_ktransit(self, ticid=None, lc=None, rprs=0.02): from ktransit import FitTransit fitT = FitTransit()

    if ticid is not None:
        lc = self.from_eleanor(ticid)[1]
        lc = self._clean_data(lc)
    elif lc is None:
        lc = self.lc

    lc.flux = lc.flux / np.mean(lc.flux)
    model = BoxLeastSquares(lc.time, lc.flux)
    results = model.autopower(0.16)
    #periods = np.linspace(3,15,400)
    #results = model.power(periods, 0.16)
    period = results.period[np.argmax(results.power)]
    t0 = results.transit_time[np.argmax(results.power)]
    if rprs is None:
        depth = results.depth[np.argmax(results.power)]
        rprs = depth ** 2

    fitT.add_guess_star(rho=0.022, zpt=0, ld1=0.6505,ld2=0.1041) #come up with better way to estimate this using AS
    fitT.add_guess_planet(T0=t0, period=period, impact=0.5, rprs=rprs)

    ferr=np.ones_like(lc.time) * 0.00001
    fitT.add_data(time=lc.time,flux=lc.flux,ferr=ferr)#*1e-3)

    vary_star = ['zpt']      # free stellar parameters
    vary_planet = (['period', 'impact',       # free planetary parameters
        'T0', #'esinw', 'ecosw',
        'rprs']) #'impact',               # free planet parameters are the same for every planet you model

    fitT.free_parameters(vary_star, vary_planet)
    fitT.do_fit()                   # run the fitting

    fitT.print_results()            # print some results
    res=fitT.fitresultplanets
    res2=fitT.fitresultstellar

    fig = ktransit.plot_results(lc.time,lc.flux,fitT.transitmodel)

    fig.show()