3/19/2023 0 Comments Emcee tutorial![]() ![]() figure () # Get the posterior median orbital parameters p = np. Now we can also look at the corner plot of some of that parameters of interest:įor n, letter in enumerate ( "bc" ): plt. That looks pretty good! Fitting this without exoplanet would have taken a lot more patience. Normal ( "obs", mu = light_curve, sd = yerr, observed = y ) # Fit for the maximum a posteriori parameters given the simuated # dataset map_soln = xo. eval_in_model ( light_curve ) y += yerr * np. sum ( light_curves, axis =- 1 ) + mean # Here we track the value of the model light curve for plotting # purposes pm. ![]() get_light_curve ( orbit = orbit, r = r, t = t ) light_curve = pm. KeplerianOrbit ( period = period, t0 = t0, b = b ) # Compute the model light curve using starry light_curves = xo. rand ( 2 ) ) # Set up a Keplerian orbit for the planets orbit = xo. ImpactParameter ( "b", ror = r, shape = 2, testval = np. Uniform ( "r", lower = 0.01, upper = 0.1, shape = 2, testval = np. exp ( logP )) # The Kipping (2013) parameterization for quadratic limb darkening paramters u = xo. log ( periods ), sd = 0.1, shape = 2 ) period = pm. ![]() Normal ( "t0", mu = t0s, sd = 1.0, shape = 2 ) # The log period also tracking the period itself logP = pm. Normal ( "mean", mu = 0.0, sd = 1.0 ) # The time of a reference transit for each planet t0 = pm. Model () as model : # The baseline flux mean = pm. ![]()
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