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 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(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 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
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
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 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)