def main(Ndim = 10, n = 200, max_iter=5000): """ Run the sampling """ mod = MultiGaussModel(Ndim) guess = [ mod.fromPrior() for k in xrange(n) ] xx = np.array([ (rk.pos[0], rk.pos[1], rk.logL) for rk in guess]) sampler = NestedSampler(mod) sampler.run_nested(guess, max_iter) sampler.process_results() return xx, sampler, mod
def lighthouse_main(n = 100, max_iter=2000): """ Run the sampling """ #n=100 # number of objects #max_iter = 2000 # number of iterations mod = LightHouseModel() guess = [ mod.fromPrior() for k in xrange(n) ] xx = np.array([ (rk.pos[0], rk.pos[1], rk.logL) for rk in guess]) sampler = NestedSampler(mod) sampler.run_nested(guess, max_iter) sampler.process_results() return xx, sampler, mod
def lighthouse_main(n=100, max_iter=2000):
""" Run the sampling """
#n=100 # number of objects
#max_iter = 2000 # number of iterations
mod = LightHouseModel()
guess = [mod.fromPrior() for k in xrange(n)]
xx = np.array([(rk.pos[0], rk.pos[1], rk.logL) for rk in guess])
sampler = NestedSampler(mod)
sampler.run_nested(guess, max_iter)
sampler.process_results()
return xx, sampler, mod