help_text='box z dimension')
+ wsaxs = forms.FloatField(label='SAXS weight',initial=100.0,
+ help_text='weight for SAXS restraint term')
+ scal_rad = forms.FloatField(label='Scal_rad (SAXS)',initial=1.0,
+ help_text='downscaling factor of residue radii used in SAXS restraints')
+ saxs_data = forms.CharField(label='P(r) SAXS data',
+ help_text='distance distribution from SAXS, two columns: r and P(r)',
+ required=False,
+ widget=forms.Textarea(attrs={'cols': 25, 'rows': 20}))
+
+
def clean(self):
cleaned_data = super(TaskForm_remd_a, self).clean()
WSCLOC=0.10554 WTOR=1.34316 WTORD=1.26571 WCORRH=0.19212 WCORR5=0.00000 &
WCORR6=0.00000 WEL_LOC=0.37357 WTURN3=1.40323 WTURN4=0.64673 WTURN6=0.00000 &
WVDWPP=0.23173 WHPB=1.00000 WSCCOR=0.25 &
-CUTOFF=7.00000 WCORR4=0.00000
-"""
+CUTOFF=7.00000 WCORR4=0.00000"""
else:
w="""WSC=0.82686 WSCP=0.96947 WELEC=0.79373 WBOND=1.00000 WANG=0.46542 &
WSCLOC=0.07969 WTOR=0.81684 WTORD=0.67806 WCORRH=0.00000 WCORR5=0.00000 &
WCORR6=0.00000 WEL_LOC=0.71100 WTURN3=2.30298 WTURN4=0.86517 WTURN6=0.00000 &
WSCCOR=0.14577 WVDWPP=0.17781 WHPB=1.00000 WSCP14=0.00000 &
-CUTOFF=7.00000 WCORR4=0.00000
-"""
+CUTOFF=7.00000 WCORR4=0.00000"""
with open(instance.jobdirname+'/file.inp','w') as f:
if instance.md_pdbref:
control_line = control_line+'pdbref '
-
+
+ cntrl_saxs=''
+ if instance.saxs_data != '':
+ lines=instance.saxs_data.split('\n')
+ nsaxs=0
+ for line in lines:
+ if len(line.split())==2:
+ nsaxs+=1
+ cntrl_saxs=' nsaxs='+str(nsaxs)+' scal_rad='+str(instance.scal_rad)
+ control_line += cntrl_saxs
type_line = 'reset_vel='+ str(instance.remd_nstex)\
+' nstep='+str(instance.md_nstep)\
for element in word_list[:-1]:
f.write('{:79}'.format(element)+'&\n')
f.write(word_list[-1]+'\n')
-
- f.write(w)
+
+ if instance.saxs_data != '':
+ w+=' wsaxs='+str(instance.wsaxs)
+ f.write(w+'\n')
if instance.type == 'min' or instance.md_start == 'pdbstart':
f.write(seq[i:i+80]+'\n')
f.write('0\n0\n')
-
+ if instance.saxs_data != '':
+ lines=instance.saxs_data.split('\n')
+ for line in lines:
+ tmp=line.split()
+ if len(tmp)==2:
+ f.write(tmp[0]+' '+tmp[1]+'\n')
if instance.type == 'min':
f.write('{:79}'.format('SEED='+str(instance.md_seed)+' isampl='+str(isampl)+
' einicheck=1 rescale=2 delta=0.02 cxfile classify')+'&\n')
f.write('BOXX='+str(instance.boxx)+' BOXY='+str(instance.boxy)+
- ' BOXZ='+str(instance.boxz) +'\n')
+ ' BOXZ='+str(instance.boxz)+cntrl_saxs +'\n')
else:
f.write('{:79}'.format('SEED='+str(instance.md_seed)+' isampl='+str(isampl)+
' einicheck=1 rescale=2 delta=0.02 cxfile')+'&\n')
f.write('BOXX='+str(instance.boxx)+' BOXY='+str(instance.boxy)+
- ' BOXZ='+str(instance.boxz) +'\n')
+ ' BOXZ='+str(instance.boxz)+cntrl_saxs +'\n')
f.write('nres='+str(len(seq))+' one_letter\n')
for i in range(0,len(seq),80):
f.write(seq[i:i+80]+'\n')
f.write(write_ssbond(instance.ssbond))
-
- f.write(w)
+ if instance.saxs_data != '':
+ fsaxs = open(instance.jobdirname+'/saxs.data', 'w')
+ lines=instance.saxs_data.split('\n')
+ for line in lines:
+ tmp=line.split()
+ if len(tmp)==2:
+ f.write(tmp[0]+' '+tmp[1]+'\n')
+ fsaxs.write(tmp[0]+' '+tmp[1]+'\n')
+ fsaxs.close()
+
+ f.write(w+'\n')
f.write('\n')
f.write('nt='+str(instance.remd_nrep)+' replica read_iset\n')
tmp1=json.loads(instance.remd_multi_t)
+' one_letter rescale=2 PRINT_CART PDBOUT=1 iopt=1'
+' temper='+str(instance.remd_cluter_temp))+'&\n')
f.write('BOXX='+str(instance.boxx)+' BOXY='+str(instance.boxy)+
- ' BOXZ='+str(instance.boxz) +'\n')
- f.write(w)
+ ' BOXZ='+str(instance.boxz)+cntrl_saxs +'\n')
+ f.write(w+'\n')
for i in range(0,len(seq),80):
f.write(seq[i:i+80]+'\n')
f.write(write_ssbond(instance.ssbond))
+ if instance.saxs_data != '':
+ lines=instance.saxs_data.split('\n')
+ for line in lines:
+ tmp=line.split()
+ if len(tmp)==2:
+ f.write(tmp[0]+' '+tmp[1]+'\n')
os.chdir(instance.jobdirname)
ret_code = subprocess.Popen(' /opt/torque/bin/qsub pbs8.csh', shell=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
remd_model3 = models.TextField(default='')
remd_model4 = models.TextField(default='')
remd_model5 = models.TextField(default='')
+
+#saxs
+ scal_rad = models.FloatField(default=1.0)
+ wsaxs = models.FloatField(default=100.0)
+ saxs_data = models.TextField(max_length=10000,default='')
+
# system
ready = models.BooleanField(default=False)
<div class="col-xs-10"> temperature for clustering</div>
<div class="col-xs-10">{{ task.remd_cluter_temp}}</div>
</li>
-
+ {% if task.saxs_data != "" %}
+ <li class="list-group-item task-item">
+ <div class="col-xs-10"> wsaxs </div>
+ <div class="col-xs-10">{{ task.wsaxs }}</div>
+ </li>
+ <li class="list-group-item task-item">
+ <div class="col-xs-10"> scal_rad (saxs) </div>
+ <div class="col-xs-10">{{ task.scal_rad }}</div>
+ </li>
+ <li class="list-group-item task-item">
+ <div class="col-xs-10"> saxs distribution </div>
+ <div class="col-xs-10"><pre> {{ task.saxs_data }}</pre></div>
+ </li>
+ {% endif %}
{% endif %}
width="500"> </div>
</li>
+ {% if task.saxs_data != "" %}
+ <li class="list-group-item task-item">
+ <div class="col-xs-10"> P(r) of input SAXS data and
+ calculated for 5 models </div>
+ <div class="col-xs-10"> <img
+ src="/myfiles/download-file/{{task.jobdirname}}/saxs.png"
+ width="500"> </div>
+ </li>
+ {% endif %}
+
<li class="list-group-item task-item">
<div class="col-xs-10">
<button onclick="plusDivs(-1)">❮</button>
<div class="col-xs-10"> temperature for clustering</div>
<div class="col-xs-10">{{ task.remd_cluter_temp}}</div>
</li>
-
+
+ {% if task.saxs_data != "" %}
+ <li class="list-group-item task-item">
+ <div class="col-xs-10"> wsaxs </div>
+ <div class="col-xs-10">{{ task.wsaxs }}</div>
+ </li>
+ <li class="list-group-item task-item">
+ <div class="col-xs-10"> scal_rad (saxs) </div>
+ <div class="col-xs-10">{{ task.scal_rad }}</div>
+ </li>
+ <li class="list-group-item task-item">
+ <div class="col-xs-10"> saxs distribution </div>
+ <div class="col-xs-10"><pre> {{ task.saxs_data }}</pre></div>
+ </li>
+ {% endif %}
{% endif %}
src="/myfiles/download-file/{{task.jobdirname}}/remd_ex.png"
width="500"> </div>
</li>
+ {% if task.saxs_data != "" %}
+ <li class="list-group-item task-item">
+ <div class="col-xs-10"> P(r) of input SAXS data and
+ calculated for 5 models </div>
+ <div class="col-xs-10"> <img
+ src="/myfiles/download-file/{{task.jobdirname}}/saxs.png"
+ width="500"> </div>
+ </li>
+ {% endif %}
+
<li class="list-group-item task-item">
<div class="col-xs-10">
</table>
<button type="submit" class="save btn btn-default">Save & submit</button>
<button type="submit" value="example" name="_example" class="save btn btn-default">Load example data</button>
+ {% if p_type == "replica exchange molecular dynamics - advanced options" %}
+ <button type="submit" value="example_saxs"
+ name="_example_saxs" class="save btn btn-default">Load example SAXS data</button>
+ {% endif %}
</form>
@login_required
def add_remd_a(request,task_id):
+ from django.core.files.uploadedfile import UploadedFile
task = get_object_or_404(Task, id=task_id)
if request.method == 'POST':
if '_example' in request.POST:
'md_nstep':500000,'md_lang':'berendsen','unres_ff':'opt-wtfsa-2',
'remd_cluter_temp':280}
form = TaskForm_remd_a(initial=data)
+ elif '_example_saxs' in request.POST:
+ data= {'name':task.name,'pdbid':'5UJQ','md_pdbref':True,
+ 'md_nstep':200000,'md_lang':'langevin','unres_ff':'E0LL2Y',
+ 'remd_cluter_temp':270,
+ 'scal_rad':4.0,'wsaxs':100.0,'saxs_data':
+""" 0.5 1.33868e-02
+ 1.5 1.95880e-02
+ 2.5 2.68896e-02
+ 3.5 3.43737e-02
+ 4.5 4.07099e-02
+ 5.5 4.47875e-02
+ 6.5 4.63486e-02
+ 7.5 4.60514e-02
+ 8.5 4.49130e-02
+ 9.5 4.36744e-02
+10.5 4.26085e-02
+11.5 4.17464e-02
+12.5 4.11217e-02
+13.5 4.07835e-02
+14.5 4.06776e-02
+15.5 4.06060e-02
+16.5 4.03241e-02
+17.5 3.96655e-02
+18.5 3.85756e-02
+19.5 3.70537e-02
+20.5 3.50982e-02
+21.5 3.27236e-02
+22.5 3.00046e-02
+23.5 2.70643e-02
+24.5 2.40044e-02
+25.5 2.08595e-02
+26.5 1.76342e-02
+27.5 1.43802e-02
+28.5 1.12281e-02
+29.5 8.34574e-03
+30.5 5.87354e-03
+31.5 3.88732e-03
+32.5 2.39755e-03
+33.5 1.36323e-03
+34.5 7.06686e-04
+35.5 3.30592e-04
+36.5 1.38359e-04"""}
+ form = TaskForm_remd_a(initial=data)
else:
form = TaskForm_remd_a(request.POST,request.FILES)
if form.is_valid():
task.remd_cluter_temp=form.cleaned_data["remd_cluter_temp"]
task.unres_ff=form.cleaned_data["unres_ff"]
+ task.scal_rad = form.cleaned_data["scal_rad"]
+ task.saxs_data = form.cleaned_data["saxs_data"]
+ task.wsaxs = form.cleaned_data["wsaxs"]
+
task.save()
return redirect('addmlist',task_id=task.id)
else:
/users2/local/bin/tmscore MODEL5.pdb plik1.pdb > tmscore5.out
rm plik1.pdb
+if (-e saxs.data) then
+awk -f ../files/saxs_dist.awk MODEL1.pdb > MODEL1_saxs.data
+awk -f ../files/saxs_dist.awk MODEL2.pdb > MODEL2_saxs.data
+awk -f ../files/saxs_dist.awk MODEL3.pdb > MODEL3_saxs.data
+awk -f ../files/saxs_dist.awk MODEL4.pdb > MODEL4_saxs.data
+awk -f ../files/saxs_dist.awk MODEL5.pdb > MODEL5_saxs.data
+../files/plot_saxs.py
+endif
+
#END
touch finished
/users2/local/bin/tmscore MODEL5.pdb plik1.pdb > tmscore5.out
rm plik1.pdb
+if (-e saxs.data) then
+awk -f ../files/saxs_dist.awk MODEL1.pdb > MODEL1_saxs.data
+awk -f ../files/saxs_dist.awk MODEL2.pdb > MODEL2_saxs.data
+awk -f ../files/saxs_dist.awk MODEL3.pdb > MODEL3_saxs.data
+awk -f ../files/saxs_dist.awk MODEL4.pdb > MODEL4_saxs.data
+awk -f ../files/saxs_dist.awk MODEL5.pdb > MODEL5_saxs.data
+../files/plot_saxs.py
+endif
+
+
#END
touch finished
--- /dev/null
+#! /usr/bin/env python
+
+import matplotlib
+#matplotlib.use('GTK')
+matplotlib.use('Agg')
+import matplotlib.pyplot as plt
+import matplotlib.cm as cm
+import numpy as np
+import sys
+
+x,y= np.loadtxt('saxs.data',usecols=(0,1),unpack=True)
+x1,y1= np.loadtxt('MODEL1_saxs.data',usecols=(0,2),unpack=True)
+x2,y2= np.loadtxt('MODEL2_saxs.data',usecols=(0,2),unpack=True)
+x3,y3= np.loadtxt('MODEL3_saxs.data',usecols=(0,2),unpack=True)
+x4,y4= np.loadtxt('MODEL4_saxs.data',usecols=(0,2),unpack=True)
+x5,y5= np.loadtxt('MODEL5_saxs.data',usecols=(0,2),unpack=True)
+
+
+plt.clf()
+plt.xlabel('r')
+plt.ylabel('P(r)')
+plt.xlim(x[0], x[-1])
+plt.plot(x,y,'-',color='black')
+plt.plot(x1,y1,'-',color='red')
+plt.plot(x2,y2,'-',color='lime')
+plt.plot(x3,y3,'-',color='blue')
+plt.plot(x4,y4,'-',color='magenta')
+plt.plot(x5,y5,'-',color='cyan')
+plt.legend(['reference','MODEL1','MODEL2','MODEL3','MODEL4','MODEL5'])
+plt.savefig('saxs.png')
--- /dev/null
+{
+ if ($1 == "ATOM" && $3 == "CA") {
+ nres = nres + 1
+ x[nres] = substr($0,31,8)
+ y[nres] = substr($0,39,8)
+ z[nres] = substr($0,47,8)
+
+# print "nres",nres," x",x[nres],y[nres],z[nres]
+ }
+}END{
+# print "nres",nres
+ sigma = 2.50
+ for (i=1;i<=nres;i++) {
+ for (j=1;j<i;j++) {
+ dij = sqrt ((x[i]-x[j])^2+(y[i]-y[j])^2+(z[i]-z[j])^2)
+# print i,j,dij
+ ibin = int(dij)
+ h[ibin] = h[ibin] + 1
+ for (k=0;k<=100;k++) {
+ dd = k+0.5
+# print k,dd,dij,dd-dij,(dd-dij)^2/(2*sigma^2)
+ if ((dd-dij)^2/(2*sigma^2)<100) hh[k] = hh[k] + exp(-(dd-dij)^2/(2*sigma^2))
+ }
+ }
+ }
+ norm = 0;
+ nnorm = 0;
+ for (k=0;k<=100;k++) {
+ norm = norm + h[k];
+ nnorm = nnorm + hh[k];
+ }
+ for (k=0;k<=100;k++) printf("%10.5f%15.5e%15.5e\n",k+0.5,h[k]/norm,hh[k]/nnorm)
+}
projects / django_unres.git / commitdiff