### Simulations done over all peptides from run_mc import * nb_cycles = 1 beta = 1.0 nb_runs = 1000 test_peptide = PDZ_Data.peptides[11] calc_energy_ground() run_mc(nb_runs, test_peptide, beta, nb_cycles=nb_cycles, plot=True, verbose=False) plot_freq_matrix(test_peptide) print compute_entropy_sequence(test_peptide) mi = compute_mutual_information(test_peptide) plt.imshow(mi, interpolation="nearest", cmap=plt.cm.Blues, aspect="auto") plt.colorbar() plt.show()
### Testing whether code functions well or not
from all_data import *
from run_mc import *
bn = 7.0
PDZ_Data.divide_peps()
calc_energy_ground()
test_peptide = PDZ_Data.peptide_dist[bn][0]
print test_peptide.name
print test_peptide.sequence_bis
print test_peptide.energy_ground
for peptide in PDZ_Data.peptide_dist[bn]:
print "{} {}".format(peptide.name, peptide.sequence_bis)
run_mc(100, test_peptide, beta = 1.01, nb_cycles = 5, plot = True)
print compute_entropy_sequence(test_peptide)