from lazysignup.decorators import allow_lazy_user
from lazysignup.utils import is_lazy_user
import random
+import logging
+
+logging.basicConfig()
+logger = logging.getLogger(__name__)
res_codes = [
# 20 canonical amino acids
task = get_object_or_404(Task, id=task_id)
if request.method == 'POST':
if '_example' in request.POST:
- data= {'name':task.name,'pdbid':'1L2Y','md_pdbref':True,'md_seed':-39912345}
+ data= {'name':task.name,'pdbid':'2HPL:A','md_seq':'DDLYG','dock_peptide':True,'md_seed':-39912345,'md_nstep':600000}
form = TaskForm_dock_a(initial=data)
+ task.example='dock_peptide'
+ task.save()
else:
form = TaskForm_dock_a(request.POST,request.FILES)
if form.is_valid():
if pdbid2:
task.myfile2=load_pdbid(pdbid2,task.jobdirname,'plik2.pdb')
task.pdbcode2=pdbid2
+ seq2,ssbond2=from_pdb(task.myfile2)
else:
task.myfile2=form.cleaned_data["file2"]
if not task.myfile2:
task.md_ntwx=task.remd_nstex
task.md_start="pdbstart"
- task.md_pdbref=True
+ if task.md_seq2 =='':
+ task.md_pdbref=True
task.md_respa=False
task.ssbond=""
task.dock_peptide=form.cleaned_data["dock_peptide"]
task.md_ntwe=form.cleaned_data["md_ntwe"]
task.remd_cluter_temp=form.cleaned_data["remd_cluter_temp"]
+ task.remd_cluster_n=form.cleaned_data["remd_cluster_n"]
task.unres_ff=form.cleaned_data["unres_ff"]
if any(c.islower() for c in seq):
'temperatures':
'["270", "280", "290", "300", "310", "320", "330", "340"]'
}
+ elif task.example == 'dock_peptide':
+ data= {'name':task.name,'nrep':task.remd_nrep,'multiplexing':
+ '["4", "8", "4", "4", "4", "4", "4", "4"]',
+ 'temperatures':
+ '["270", "280", "290", "300", "310", "320", "330", "345"]'
+ }
elif task.unres_ff == 'FF2':
data= {'name':task.name,'nrep':task.remd_nrep,'multiplexing':
'["1", "1", "1", "1", "1", "1", "1", "1"]',
@login_required
def details(request,task_id):
task = get_object_or_404(Task, id=task_id)
- return render(request, "details.html",{'task':task})
+ try:
+ remd_models=json.loads(task.remd_models)
+ except:
+ remd_models=[]
+ remd_models.append(task.remd_model1)
+ remd_models.append(task.remd_model2)
+ remd_models.append(task.remd_model3)
+ remd_models.append(task.remd_model4)
+ remd_models.append(task.remd_model5)
+ return render(request, "details.html",{'task':task,'remd_models':remd_models,'range':range(1,task.remd_cluster_n+1)})
def details1(request,user_id,task_id):
task = get_object_or_404(Task, id=task_id)
- return render(request, "details1.html",{'task':task})
+ try:
+ remd_models=json.loads(task.remd_models)
+ except:
+ remd_models=[]
+ remd_models.append(task.remd_model1)
+ remd_models.append(task.remd_model2)
+ remd_models.append(task.remd_model3)
+ remd_models.append(task.remd_model4)
+ remd_models.append(task.remd_model5)
+ return render(request, "details1.html",{'task':task,'remd_models':remd_models,'range':range(1,task.remd_cluster_n+1)})
@login_required
add_restart_inp()
ret_code = subprocess.Popen(' /opt/torque/bin/qsub pbs.csh', shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
os.chdir('..')
- elif task.type == 'remd':
+ elif task.type == 'remd' or task.type == 'dock':
os.chdir(task.jobdirname)
add_restart_inp()
tmp1=json.loads(task.remd_multi_m)
f2.write(line)
os.remove('file_wham.inp')
os.rename('file_wham.tmp','file_wham.inp')
+ if task.type == 'dock':
+ with open('pbs8.csh','r') as f1, open ('pbs8.tmp','w') as f2:
+ for line in f1:
+ if 'generator_v13' in line:
+ f2.write('#'+line)
+ else:
+ f2.write(line)
+ os.remove('pbs8.csh')
+ os.rename('pbs8.tmp','pbs8.csh')
ret_code = subprocess.Popen(' /opt/torque/bin/qsub pbs8.csh', shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
os.chdir('..')
return
task.results_text=text
+ remd_models=[]
if task.md_pdbref and task.type=='remd' or task.type=='dock' and task.md_seq2 == '':
- for i in range(1,6):
+ for i in range(1,task.remd_cluster_n+1):
try:
with open(task.jobdirname+'/file_wham_T'+str(int(task.remd_cluter_temp))+'K_000'+str(i)+'.pdb', 'r') as f:
line=f.readline()
- if i==1:
- task.remd_model1='Cluster1 '+' '.join(line.split()[-3:])
- elif i==2:
- task.remd_model2='Cluster2 '+' '.join(line.split()[-3:])
- elif i==3:
- task.remd_model3='Cluster3 '+' '.join(line.split()[-3:])
- elif i==4:
- task.remd_model4='Cluster4 '+' '.join(line.split()[-3:])
- elif i==5:
- task.remd_model5='Cluster5 '+' '.join(line.split()[-3:])
+ remd_models.append('Cluster'+str(i)+' '+' '.join(line.split()[-3:]))
except EnvironmentError:
print 'file_wham_T*pdb open error'
- for i in range(1,6):
+ for i in range(1,task.remd_cluster_n+1):
with open(task.jobdirname+'/tmscore'+str(i)+'.out', 'r') as f:
text=''
for line in f:
if 'GDT-TS-score=' in line:
text=text+' GDT_TS='+line.split()[1]
- if i==1:
- task.remd_model1=task.remd_model1+text
- elif i==2:
- task.remd_model2=task.remd_model2+text
- elif i==3:
- task.remd_model3=task.remd_model3+text
- elif i==4:
- task.remd_model4=task.remd_model4+text
- elif i==5:
- task.remd_model5=task.remd_model5+text
+ remd_models[i-1]=remd_models[i-1]+text
if task.type=='dock':
- for i in range(1,6):
+ for i in range(1,task.remd_cluster_n+1):
with open(task.jobdirname+'/dockq_'+str(i)+'.out', 'r') as f:
text=''
for line in f:
if 'DockQ ' in line:
text=text+' DockQ='+line.split()[1]
- if i==1:
- task.remd_model1=task.remd_model1+text
- elif i==2:
- task.remd_model2=task.remd_model2+text
- elif i==3:
- task.remd_model3=task.remd_model3+text
- elif i==4:
- task.remd_model4=task.remd_model4+text
- elif i==5:
- task.remd_model5=task.remd_model5+text
-
+ remd_models[i-1]=remd_models[i-1]+text
+# logger.warning("models %d %s" % (i,remd_models))
if task.type=='remd' or task.type=='dock':
with open(task.jobdirname+'/file_cluster_clust.out_000', 'r') as f:
i=0
for line1 in f:
i+=1
- if i>6:
+ if i>task.remd_cluster_n:
break
- if i==1:
- task.remd_model1=task.remd_model1+' Cluster1 probability= '+line1.split()[-2]
- elif i==2:
- task.remd_model2=task.remd_model2+' Cluster2 probability= '+line1.split()[-2]
- elif i==3:
- task.remd_model3=task.remd_model3+' Cluster3 probability= '+line1.split()[-2]
- elif i==4:
- task.remd_model4=task.remd_model4+' Cluster4 probability= '+line1.split()[-2]
- elif i==5:
- task.remd_model5=task.remd_model5+' Cluster5 probability= '+line1.split()[-2]
+ try:
+ remd_models[i-1]=remd_models[i-1]+' Cluster'+str(i)+' probability= '+line1.split()[-2]
+ except:
+ if len(line1.split())==4:
+ remd_models.append(' Cluster'+str(i)+' probability= '+line1.split()[-2])
-
-
+ task.remd_models=json.dumps(remd_models)
+# logger.warning("models%s" % task.remd_models)
task.save()
elif os.path.isfile(task.jobdirname+'/file_GB000.stat') and not task.done:
if (task.type=='min'):