def test_dtram_api(self): """testing the dTRAM API""" tramdata = TRAMData(self.inp, b_K_i=self.b_K_i, verbose=True) dtram_obj = dtram(tramdata, lag=1, maxiter=1, ftol=1.0E-14, verbose=True) dtram_obj = dtram(tramdata, lag=1, maxiter=100000, ftol=1.0E-14, verbose=True) maxerr = 1.0E-1 assert_allclose(dtram_obj.f_K, self.f_K, atol=maxerr) assert_allclose(dtram_obj.f_i, self.f_i, atol=maxerr) assert_allclose(dtram_obj.pi_i, self.pi_i, atol=maxerr) assert_allclose(dtram_obj.f_K_i, self.f_K_i, atol=maxerr) assert_allclose(dtram_obj.pi_K_i, self.pi_K_i, atol=maxerr) assert_allclose(dtram_obj.estimate_transition_matrices(), self.tmat, atol=maxerr)
plt.plot(gridpoints, p) #%% ################################ # OLD code continues... ################################ dtramdata = TRAMData( sim_data.trajs, b_K_i=sim_data.gen_harmonic_bias_mtx(gridpoints=sim_data.gridpoints)) try: dtram_obj = dtram(dtramdata, lag=opts.lag_time, maxiter=1, ftol=opts.f_toler_dtram, verbose=False) except pytram.ExpressionError: raise pytram.ExpressionError, "Input was faulty, ending..." except pytram.NotConvergedWarning: pass #%% converged = False nruns = 0 while not converged: try: print "Running another 1k steps ..."
T = sim_data.get_reweighted_TransMtx() p = sim_data.get_reweighted_distribution(T) plt.plot(gridpoints, p) #%% ################################ # OLD code continues... ################################ dtramdata = TRAMData( sim_data.trajs, b_K_i=sim_data.gen_harmonic_bias_mtx(gridpoints=sim_data.gridpoints) ) try: dtram_obj = dtram(dtramdata, lag=opts.lag_time, maxiter=1, ftol=opts.f_toler_dtram, verbose=False ) except pytram.ExpressionError: raise pytram.ExpressionError, "Input was faulty, ending..." except pytram.NotConvergedWarning: pass #%% converged = False nruns=0 while not converged: try: print "Running another 1k steps ..." nruns+=1