markovmodel / pyemma_ipython Goto Github PK

CellExecutionError: An error occurred while executing the following cell:
------------------
lags = tica_itss[0].lags
colors = ['blue', 'green', 'red']
kinvars = [[(M.eigenvalues()**2).sum() for M in its_obj.models] for its_obj in tica_itss]
for i, kinvar in enumerate(kinvars):
    plot(0.01*lags, kinvar, linewidth=2, label='TICA '+labels[i], color=colors[i])
kinvars = [[(M.eigenvalues()**2).sum() for M in its_obj.models] for its_obj in pca_itss]
for i, kinvar in enumerate(kinvars):
    plot(0.01*lags, kinvar, linewidth=2, label='PCA '+labels[i], color=colors[i], linestyle='dashed')
text(0.2, 40, 'MSM ', fontweight='bold')
xlabel('lag time / $\mu$s')
ylim(0, 45); ylabel('total kinetic variance')
legend(fontsize=14)
savefig('./figs/total_kinetic_variance.png', bbox_inches='tight')
------------------

ValueError: x and y must have same first dimension

CellExecutionError: An error occurred while executing the following cell:
------------------
tpt = msm.tpt(bhmm, [i_meta_unbound], [i_meta_bound])
------------------

ValueError: Sets A and B have to be disjoint

------------------
N_dtraj = np.array([5, 10, 20, 50, 100])
effort_nrev = N_dtraj*10000*dt_long  # N_C + N_pi in ns
data_nrev = generate_stats_nrev(dtrajs_long, N_dtraj, n_samples*n_bs)
------------------

ValueError: Sparsity patterns of C and X are different.