Python convert_sequences_to_pdbの例、utilities.convert_sequences_to_pdb Pythonの例

コード例 #1

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ファイルを表示

ファイル: rep_1_respawning.py プロジェクト: shenglan0407/TryMSMbuilder

#check for mismatch
for this_assign, that_assign in zip(micro_assign, geo_assign):
    for this_item, that_item in zip(this_assign, that_assign):
        if this_item == raw_to_micro_mapping[that_item]:
            pass
        else:
            print('mismatch %d, %d' % (this_item, that_item))

micro_assign_path = '/home/shenglan/TryMSMbuilder/output/ten_ligands/KC_microassign_c' + str(
    N_MICRO) + '_s' + str(LOAD_STRIDE) + '.out'
pickle.dump(micro_assign, open(micro_assign_path, 'wb'))

save_micro_pdb_path = '/home/shenglan/TryMSMbuilder/output/ten_ligands/KC_microassign_c' + str(
    N_MICRO) + '_s' + str(LOAD_STRIDE) + '.pdb'
util.convert_sequences_to_pdb(seq_path, micro_assign_path, save_micro_pdb_path)

# dictionary; key: microstate id;
# item: list of distances to binding pocket for points in microstate
clusters_dist = {}

for ii in range(len(distances)):
    if len(distances) == len(micro_assign) and len(distances[ii]) == len(
            micro_assign[ii]):
        for nn in range(len(distances[ii])):
            if micro_assign[ii][nn] in clusters_dist.keys():
                clusters_dist[micro_assign[ii][nn]].append(distances[ii][nn])
            else:
                clusters_dist.update(
                    {micro_assign[ii][nn]: [distances[ii][nn]]})

コード例 #2

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ファイルを表示

np.savetxt(countsmat_path, countsmat, fmt='%8.4g')

transmat_path = '/home/shenglan/TryMSMbuilder/output/C/ergodic/KC_transmat_c' + str(
    N_CLUSTER) + '_s' + str(LOAD_STRIDE) + '.out'
np.savetxt(transmat_path, transmat, fmt='%10.4g')

centers_path = '/home/shenglan/TryMSMbuilder/output/C/ergodic/KC_centers_c' + str(
    N_CLUSTER) + '_s' + str(LOAD_STRIDE) + '.out'
np.savetxt(centers_path, centers, fmt='%10.4g')

#----------------------------------------------------------------------------------
# Convert to pdb
#----------------------------------------------------------------------------------
pdb_path = '/home/shenglan/TryMSMbuilder/output/C/ergodic/KC_c' + str(
    N_CLUSTER) + '_s' + str(LOAD_STRIDE) + '.pdb'
util.convert_sequences_to_pdb(seq_path, assign_path, pdb_path)

#----------------------------------------------------------------------------------
# Visualization of data
#----------------------------------------------------------------------------------
# fig5 = plt.figure(figsize=(14,3))
#
# plt.plot(assignments[0],'r.',alpha = 0.5)
# plt.plot(assignments[1],'b.',alpha = 0.5)
# plt.plot(assignments[2],'g.',alpha = 0.5)
# plt.xlabel('Frame')
# plt.ylabel('Cluster number')
# plt.title('cluster numbers, condition B')
# plt.savefig('/home/shenglan/TryMSMbuilder/output/fig5.png')
# plt.close(fig5)
#

コード例 #3

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ファイルを表示

ファイル: lumping_ergodic_C.py プロジェクト: shenglan0407/TryMSMbuilder

    
# assignments to macro states
macro_assign = []

for this_assign in geo_assign:
    this_list = np.zeros(len(this_assign),dtype = int)
    macro_assign.append(this_list)

for nn in range(len(macro_assign)):
    for ii in range(len(macro_assign[nn])):
        macro_assign[nn][ii] = micro_to_macro_mapping[micro_assign[nn][ii]]

macro_assign_path = '/home/shenglan/TryMSMbuilder/output/C/ergodic/KC_macroassign_c'+str(N_MACRO)+'_s'+str(LOAD_STRIDE)+'.out'
pickle.dump(macro_assign,open(macro_assign_path,'wb'))

micro_assign_path = '/home/shenglan/TryMSMbuilder/output/C/ergodic/KC_microassign_c'+str(N_MICRO)+'_s'+str(LOAD_STRIDE)+'.out'
pickle.dump(micro_assign,open(micro_assign_path,'wb'))

seq_path = '/home/shenglan/TryMSMbuilder/output/C/ergodic/sequences_s'+str(LOAD_STRIDE)+'.out'

save_macro_pdb_path = '/home/shenglan/TryMSMbuilder/output/C/ergodic/KC_macroassign_c'+str(N_MACRO)+'_s'+str(LOAD_STRIDE)+'.pdb'
save_micro_pdb_path = '/home/shenglan/TryMSMbuilder/output/C/ergodic/KC_microassign_c'+str(N_MICRO)+'_s'+str(LOAD_STRIDE)+'.pdb'

util.convert_sequences_to_pdb(seq_path,macro_assign_path,save_macro_pdb_path)
util.convert_sequences_to_pdb(seq_path,micro_assign_path,save_micro_pdb_path)


# macro_assign = pcca.fit(partial_micro_assign)
# 
# print macro_assign

コード例 #4

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ファイルを表示

ファイル: cluster_compare.py プロジェクト: shenglan0407/TryMSMbuilder

KC_assignments = KC_clustering.fit_predict(sequences_all)
KC_centers = KC_clustering.cluster_centers_

KM_clustering = KCenters(n_clusters = N_CLUSTER)
KM_assignments = KM_clustering.fit_predict(sequences_all)
KM_centers = KM_clustering.cluster_centers_

KC_output_file = '/home/shenglan/TryMSMbuilder/output/KC_centers_c'+str(N_CLUSTER)+'_s'+str(LOAD_STRIDE)+'.out'
KM_output_file = '/home/shenglan/TryMSMbuilder/output/KM_centers_c'+str(N_CLUSTER)+'_s'+str(LOAD_STRIDE)+'.out'
np.savetxt(KC_output_file,KC_centers,fmt = '%10.4g')
np.savetxt(KM_output_file,KM_centers,fmt = '%10.4g')

KC_assign_file = '/home/shenglan/TryMSMbuilder/output/KC_assign_'+str(N_CLUSTER)+'_s'+str(LOAD_STRIDE)+'.out'
KM_assign_file = '/home/shenglan/TryMSMbuilder/output/KM_assign_'+str(N_CLUSTER)+'_s'+str(LOAD_STRIDE)+'.out'
pickle.dump(KC_assignments,open(KC_assign_file,'wb'))
pickle.dump(KM_assignments,open(KM_assign_file,'wb'))

KC_pdb_path = KC_output_file.split('.')[0]+'.pdb' 
KM_pdb_path = KM_output_file.split('.')[0]+'.pdb' 

util.convert_to_pdb(KC_output_file,KC_pdb_path)
util.convert_to_pdb(KM_output_file,KM_pdb_path)


KC_pdb_file = '/home/shenglan/TryMSMbuilder/output/KC_c'+str(N_CLUSTER)+'.pdb'
util.convert_sequences_to_pdb(seqfile,KC_assign_file,KC_pdb_file)

KM_pdb_file = '/home/shenglan/TryMSMbuilder/output/KM_c'+str(N_CLUSTER)+'.pdb'
util.convert_sequences_to_pdb(seqfile,KM_assign_file,KM_pdb_file)

コード例 #5

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ファイルを表示

ファイル: build_MSM_C.py プロジェクト: shenglan0407/TryMSMbuilder

pickle.dump(assignments,open(assign_path,'wb'))

countsmat_path = '/home/shenglan/TryMSMbuilder/output/C/all_clusters/KC_countsmat_c'+str(N_CLUSTER)+'_s'+str(LOAD_STRIDE)+'.out'
np.savetxt(countsmat_path,countsmat,fmt = '%8.4g')

transmat_path = '/home/shenglan/TryMSMbuilder/output/C/all_clusters/KC_transmat_c'+str(N_CLUSTER)+'_s'+str(LOAD_STRIDE)+'.out'
np.savetxt(transmat_path,transmat,fmt = '%10.4g')

centers_path = '/home/shenglan/TryMSMbuilder/output/C/all_clusters/KC_centers_c'+str(N_CLUSTER)+'_s'+str(LOAD_STRIDE)+'.out'
np.savetxt(centers_path,centers,fmt = '%10.4g')

#----------------------------------------------------------------------------------
# Convert to pdb
#----------------------------------------------------------------------------------
pdb_path = '/home/shenglan/TryMSMbuilder/output/C/all_clusters/KC_c'+str(N_CLUSTER)+'_s'+str(LOAD_STRIDE)+'.pdb'
util.convert_sequences_to_pdb(seq_path,assign_path,pdb_path)

#----------------------------------------------------------------------------------
# Visualization of data
#----------------------------------------------------------------------------------
# fig5 = plt.figure(figsize=(14,3))
# 
# plt.plot(assignments[0],'r.',alpha = 0.5)
# plt.plot(assignments[1],'b.',alpha = 0.5)
# plt.plot(assignments[2],'g.',alpha = 0.5)
# plt.xlabel('Frame')
# plt.ylabel('Cluster number')
# plt.title('cluster numbers, condition B')
# plt.savefig('/home/shenglan/TryMSMbuilder/output/fig5.png')
# plt.close(fig5)
#

コード例 #6

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ファイルを表示

ファイル: convert_output.py プロジェクト: shenglan0407/TryMSMbuilder

import utilities as util
import numpy as np
import pickle

# crd_file = '/home/shenglan/TryMSMbuilder/output/cluster_centers.out'
# pdb_path = '/home/shenglan/TryMSMbuilder/output/cluster_centers.pdb'
# 
# util.convert_to_pdb(crd_file,pdb_path)
# 
# crd_file = '/home/shenglan/TryMSMbuilder/output/KM_centers_50.out'
# pdb_path = '/home/shenglan/TryMSMbuilder/output/KM_centers_50.pdb'
# 
# util.convert_to_pdb(crd_file,pdb_path)
# 
# crd_file = '/home/shenglan/TryMSMbuilder/output/KC_centers_50.out'
# pdb_path = '/home/shenglan/TryMSMbuilder/output/KC_centers_50.pdb'
# 
# util.convert_to_pdb(crd_file,pdb_path)


seqfile = '/home/shenglan/TryMSMbuilder/output/sequences.out'
assignfile = '/home/shenglan/TryMSMbuilder/output/KC_assign_5.out'
savefile = '/home/shenglan/TryMSMbuilder/output/KC_rec_crds.pdb'
util.convert_sequences_to_pdb(seqfile,assignfile,savefile)

コード例 #7

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ファイルを表示

import utilities as util
import numpy as np
import pickle

# crd_file = '/home/shenglan/TryMSMbuilder/output/cluster_centers.out'
# pdb_path = '/home/shenglan/TryMSMbuilder/output/cluster_centers.pdb'
#
# util.convert_to_pdb(crd_file,pdb_path)
#
# crd_file = '/home/shenglan/TryMSMbuilder/output/KM_centers_50.out'
# pdb_path = '/home/shenglan/TryMSMbuilder/output/KM_centers_50.pdb'
#
# util.convert_to_pdb(crd_file,pdb_path)
#
# crd_file = '/home/shenglan/TryMSMbuilder/output/KC_centers_50.out'
# pdb_path = '/home/shenglan/TryMSMbuilder/output/KC_centers_50.pdb'
#
# util.convert_to_pdb(crd_file,pdb_path)

seqfile = '/home/shenglan/TryMSMbuilder/output/sequences.out'
assignfile = '/home/shenglan/TryMSMbuilder/output/KC_assign_5.out'
savefile = '/home/shenglan/TryMSMbuilder/output/KC_rec_crds.pdb'
util.convert_sequences_to_pdb(seqfile, assignfile, savefile)

コード例 #8

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ファイルを表示

ファイル: cluster_compare.py プロジェクト: shenglan0407/TryMSMbuilder

KM_assignments = KM_clustering.fit_predict(sequences_all)
KM_centers = KM_clustering.cluster_centers_

KC_output_file = '/home/shenglan/TryMSMbuilder/output/KC_centers_c' + str(
    N_CLUSTER) + '_s' + str(LOAD_STRIDE) + '.out'
KM_output_file = '/home/shenglan/TryMSMbuilder/output/KM_centers_c' + str(
    N_CLUSTER) + '_s' + str(LOAD_STRIDE) + '.out'
np.savetxt(KC_output_file, KC_centers, fmt='%10.4g')
np.savetxt(KM_output_file, KM_centers, fmt='%10.4g')

KC_assign_file = '/home/shenglan/TryMSMbuilder/output/KC_assign_' + str(
    N_CLUSTER) + '_s' + str(LOAD_STRIDE) + '.out'
KM_assign_file = '/home/shenglan/TryMSMbuilder/output/KM_assign_' + str(
    N_CLUSTER) + '_s' + str(LOAD_STRIDE) + '.out'
pickle.dump(KC_assignments, open(KC_assign_file, 'wb'))
pickle.dump(KM_assignments, open(KM_assign_file, 'wb'))

KC_pdb_path = KC_output_file.split('.')[0] + '.pdb'
KM_pdb_path = KM_output_file.split('.')[0] + '.pdb'

util.convert_to_pdb(KC_output_file, KC_pdb_path)
util.convert_to_pdb(KM_output_file, KM_pdb_path)

KC_pdb_file = '/home/shenglan/TryMSMbuilder/output/KC_c' + str(
    N_CLUSTER) + '.pdb'
util.convert_sequences_to_pdb(seqfile, KC_assign_file, KC_pdb_file)

KM_pdb_file = '/home/shenglan/TryMSMbuilder/output/KM_c' + str(
    N_CLUSTER) + '.pdb'
util.convert_sequences_to_pdb(seqfile, KM_assign_file, KM_pdb_file)