def it_difference(params, comp_tmatrix): """Return the distance between implied timescales.""" gold_its, n_timescales, lag_time = params comp_its = analysis.get_implied_timescales(comp_tmatrix, n_timescales, lag_time) diff = gold_its - comp_its return np.sqrt(np.dot(diff, diff))
def calculate_implied_timescales(self, lag_times, n_timescales): implied_timescales = list() for lag_time in lag_times: t_matrix = self.gold.build_msm(lag_time) it = analysis.get_implied_timescales(t_matrix, n_timescales, lag_time) implied_timescales.append((lag_time, it)) print "Calculated lag time at time {}".format(lag_time) self.implied_timescales = implied_timescales
def it_difference_setup(gold_tmatrix, n_timescales=3, lag_time=20): """Save gold implied timescales.""" gold_its = analysis.get_implied_timescales(gold_tmatrix, n_timescales=n_timescales, lag_time=20) return (gold_its, n_timescales, lag_time)
def anal_func(t_matrix, *params): return analysis.get_implied_timescales(t_matrix, n_timescales=self.n_its, lag_time=params[2] * self.stride)
def calculate_analytic_its(self): """Calculate analytic results.""" analytic_its = analysis.get_implied_timescales(self.t_matrix, n_timescales=self.n_its, lag_time=1) self.vd.analytic_its = analytic_its