def convertEkinprjs(local=None, server=None, project=None, username=None):
"""convert old ekin prjs in a db to new"""
if local != None:
DB = PDatabase(local=local)
elif server != None:
DB = PDatabase(server=server,
username='******',
port=8080,
password='******',
project=project)
for f in DB['userfields']:
if DB['userfields'][f]['field_type'] in ekintypes:
print f
for r in DB.getRecs():
rec = DB[r]
if rec.has_key(f):
E = rec[f]
E.checkDatasets()
for d in E.datasets:
ek = E.getDataset(d)
#ek.prettyPrint()
rec[f] = E
print DB.getChanged()
DB.commit('converted ekin data')
return
def createdb(local=None,
server=None,
project=None,
username=None,
norecs=1000):
"""Create and add some test data"""
if local != None:
if os.path.exists(local):
for i in ['.lock', '.index', '']:
try:
os.remove(local + i)
except:
pass
DB = PDatabase(local=local)
elif server != None:
DB = PDatabase(server=server,
username=username,
password='******',
project=project)
import string
import DNAtool.mutation as mutation
choices = ['a', 'b', 'c', 'd']
DB.addField('choice', 'text')
DB.addField('stab', 'text')
DB.addField('activity', 'text')
#DB.addField('ekin', 'General')
E = EkinProject()
data = E.readDataset('Ekin/test.Ekindat')
E.insertDataset(data['data'], 'test', fit=data['fit'])
print 'creating dummy data..'
j = 0
count = 0
for i in range(norecs):
if j > 3: j = 0
c = ''
for k in range(10):
c += random.choice(string.letters)
DB.add(c)
DB.data[c].choice = choices[j]
DB.data[c].DNASeq = simulate_sequence(300)
AAseqs3, AAseqs1 = mutation.translate(DB.data[c].DNASeq)
DB.addProtseq(c, AAseqs3[1][5:80], 1)
DB.data[c].stab = str(round(random.normalvariate(1, 2), 3))
DB.data[c].activity = str(round(random.normalvariate(30, 4), 3))
#DB.data[c].ekin = E
j += 1
count += 1
if count > 3000:
print 'saving..'
DB.commit()
DB.db.cacheMinimize()
count = 0
DB.commit()
return DB
def loadDB(prj=None, remote=False, settings={}):
"""Load a local or remote db, settings are the remote db arguments
such as server, username, password and project name"""
if settings.has_key('port'):
settings['port'] = int(settings['port'])
if remote == True:
DB = PDatabase(project=prj, **settings)
else:
DB = PDatabase(local=prj)
return DB
def saveDBCopy(DB, filename, callback=None):
"""Save local copy of a remote or another local DB"""
import copy
total = len(DB.getRecs())
if filename == '' or filename == None:
return False
if os.path.exists(filename):
for i in ['.lock','.index','']:
os.remove(filename+i)
newDB = PDatabase(local=filename)
newDB = copyDB(DB, newDB)
newDB.commit()
newDB.close()
return newDB
def PEATSAJobs(prjs, resubmit=False):
"""Submit PEATSA runs for all projects or merge results if done"""
for name in prjs:
print name
DB = PDatabase(local=os.path.join(savepath,name))
pdb = DB['wt'].Structure
PS = PEATSAPlugin()
PS.main(DB=DB)
if hasattr(DB.meta,'peatsa_jobs') and resubmit == False:
if 'mycalc' in DB.meta.peatsa_jobs:
print 'job is present'
#try to merge results
S = PEATTableModel(DB)
job,n = PS.getJob('mycalc')
PS.mergeResults(job, 'prediction', S)
DB.commit()
print 'merged results'
else:
mutlist = []
for p in DB.getRecs():
mutlist.append(DB.get(p).Mutations)
#print mutlist
pdbfile = PS.writetempPDB()
#we add source project data so exp data can be read from summary
prjdata = {'server':'enzyme.ucd.ie','username':'******',
'project':name,'password':'******','port':'8080'}
PS.submitJob(name='mycalc', pdbname=DB.meta.refprotein, pdbfile=pdbfile,
mutations=mutlist, calcs=['stability'],
meta={'protein':name,'expcol':'Exp','project':prjdata})
#required to end process
PS.jobManager.stopLogging()
DB.close()
return
def showResults(self, name=None, showtable=True, ax=None, stats=True):
"""Show results with correlation plot from selected job"""
job, name = self.getJob(name)
if job == None:
print 'job not in DB'
return
if job.state() != 'Finished':
print 'job not finished'
return
self.matrices = job.data.allMatrices()
#print self.matrices['ModellingResults'].csvRepresentation()
jobmeta = job.metadata()
cols = self.DB.getSimpleFields()
expcol = None
expdata = None
#print jobmeta
if jobmeta.has_key('expcol'):
expcol = jobmeta['expcol']
if expcol not in cols and jobmeta.has_key('project'):
#we may have stored the exp data in another project
prjdata = jobmeta['project']
print 'trying to loading exp data from external project(s)'
from PEATDB.Base import PDatabase
from PEATTables import PEATTableModel
tmpdb = PDatabase(**prjdata)
print tmpdb
S = PEATTableModel(tmpdb)
expdata = S.simpleCopy(include=['Mutations'])
print expdata
#if exp column not known then ask user
if expcol == '' or expcol == None:
mpDlg = MultipleValDialog(title='Select Experimental Data',
initialvalues=[cols],
labels=['exp data column:'],
types=['list'],
parent=self.mainwin)
if mpDlg.result == True:
expcol = mpDlg.results[0]
else:
return
for m in self.matrices:
matrix = self.matrices[m]
if matrix == None or not 'Total' in matrix.columnHeaders():
continue
ax, mh, x, y = self.plotMerged(matrix, expcol, expdata, m,
showtable, ax, name, stats)
#need to add this for mousehandler to work.. hack
'''from Correlation import MouseHandler
mh = MouseHandler(ax, labels=expcol, key='Mutations')
mh.connect()'''
return ax, mh, x, y
def loadDB():
from PEATDB.Base import PDatabase
DB = PDatabase(server='peat.ucd.ie',
username='******',
password='******',
project='titration_db',
port=8080)
return DB
def convertClass():
"""Convert records to proper module name"""
project='test'
DB=PDatabase(server='localhost',port=8080,
username='******',password='******',
project=project)
for k in DB.getRecs():
r=PEATRecord(k)
rec = DB.data[k]
print rec.__class__
for f in rec.getFields():
r[f] = rec[f]
DB.data[k] = r
print DB.data[k].__class__
DB.commit(note='convert')
return
def testBlob():
"""write a file as binary data to blob and read back"""
from ZODB.PersistentMapping import PersistentMapping
import mimetypes
from PILView import PILViewer
DB = PDatabase(server='localhost',port=8090,
username='******',
password='******')
def addfile(fname):
myblob = Blob()
b=myblob.open('w')
o=open(fname)
data = o.read()
b.write(data)
print b.name
b.close()
return myblob
dirlist=os.listdir(os.getcwd())
for f in dirlist:
m = mimetypes.guess_type(f)[0]
if m != None and 'image' in m:
print f
b=addfile(f)
DB.add(f)
DB.data[f]['testfile']=FileRecord(name=f,blob=b)
DB.commit()
for k in DB.data:
if not DB.data[k].has_key('testfile'):
continue
rec = DB.data[k]['testfile']
myblob = rec.blob
f = myblob.open("r")
print f.name
#app = PILViewer(imgfile=f.name)
#app.mainloop()
DB.close()
return
def testBlob():
"""write a file as binary data to blob and read back"""
from ZODB.PersistentMapping import PersistentMapping
import mimetypes
from PILView import PILViewer
DB = PDatabase(server='localhost',
port=8090,
username='******',
password='******')
def addfile(fname):
myblob = Blob()
b = myblob.open('w')
o = open(fname)
data = o.read()
b.write(data)
print b.name
b.close()
return myblob
dirlist = os.listdir(os.getcwd())
for f in dirlist:
m = mimetypes.guess_type(f)[0]
if m != None and 'image' in m:
print f
b = addfile(f)
DB.add(f)
DB.data[f]['testfile'] = FileRecord(name=f, blob=b)
DB.commit()
for k in DB.data:
if not DB.data[k].has_key('testfile'):
continue
rec = DB.data[k]['testfile']
myblob = rec.blob
f = myblob.open("r")
print f.name
#app = PILViewer(imgfile=f.name)
#app.mainloop()
DB.close()
return
def setDisplayFields(local=None, server=None, project=None, username=None):
"""Update display attributes for every cell"""
if local != None:
DB = PDatabase(local=local)
elif server != None:
DB = PDatabase(server=server,
username=username,
port=8080,
password='******',
project=project)
for r in DB.getRecs():
rec = DB[r]
for f in rec:
x = rec.setDisplayAttribute(f, rec[f])
rec._display[f] = x
print f, rec.getDisplayAttribute(f)
#DB.commit('displ attrs')
return
def convertClass():
"""Convert records to proper module name"""
project = 'test'
DB = PDatabase(server='localhost',
port=8080,
username='******',
password='******',
project=project)
for k in DB.getRecs():
r = PEATRecord(k)
rec = DB.data[k]
print rec.__class__
for f in rec.getFields():
r[f] = rec[f]
DB.data[k] = r
print DB.data[k].__class__
DB.commit(note='convert')
return
def speedTest1():
"""benchmark read and write"""
DB = PDatabase(server='localhost', port=8090)
#DB = PDatabase(local='./Data.fs')
for i in range(100, 300):
DB.add(i)
for i in range(100, 290):
DB.delete(i)
DB.commit()
print DB
DB.close()
return
def checkdb(server=None, project=None, local=None):
"""test basic ops for the db"""
if server != None:
DB = PDatabase(server=server,
port=8080,
username='******',
password='******',
project=project)
else:
DB = PDatabase(local=local)
print DB
#DB.listRecs()
'''first = DB.data.keys()[0]
rec = DB.data[first]
for k in rec.keys():
print type(rec[k])'''
print DB['userfields']
print DB.meta
DB.close()
return
def main():
import os
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-f", "--file", dest="file", help="Open a local db")
opts, remainder = parser.parse_args()
#test
if opts.file != None and os.path.exists(opts.file):
path = os.path.abspath(opts.file)
from PEATDB.Base import PDatabase
DB = PDatabase(local=path)
P = PEATSAPlugin()
P.main(DB=DB)
P.test()
def send2Server(projects):
"""Send all projects to remote versions"""
settings={'server':'enzyme.ucd.ie','username':'******',
'password':'******','port':8080}
adminsettings={'host':'enzyme.ucd.ie','user':'******',
'passwd':'nielsen','port':8080}
'''for p in projects:
print p
DB = PDatabase(local=os.path.join(savepath,p))
Utils.createDBonServer(prj=p,settings=adminsettings,
access='guest')
Utils.copyDBtoServer(DB,p,settings)'''
DB = PDatabase(local='summary.fs')
Utils.copyDBtoServer(DB,'PotapovDataset',settings)
return
def connect(self):
"""Connect to the peat db"""
saveout = sys.stdout
logpath = os.path.abspath('out.log')
fsock = open(logpath, 'w')
sys.stdout = fsock
sys.stdout.flush()
print self.server
DB = PDatabase(server=self.server, port=self.port,
username=self.user,
password=self.password,
project=self.project)
sys.stdout.flush()
sys.stdout = saveout
fsock.close()
return DB
def saveDBCopy(DB, filename, callback=None):
"""Save local copy of a remote or another local DB"""
import copy
total = len(DB.getRecs())
if filename == '' or filename == None:
return False
if os.path.exists(filename):
for i in ['.lock', '.index', '']:
os.remove(filename + i)
newDB = PDatabase(local=filename)
newDB = copyDB(DB, newDB)
newDB.commit()
newDB.close()
return newDB
def testMemory():
"""test memory behaviour of DB, how can cache be managed"""
DB = PDatabase(server='localhost',
username='******',
password='******',
project='novo')
#DB = PDatabase(local='large.fs')
print DB
db = DB.db
print db.cacheSize()
for k in DB.getRecs()[:50]:
#print k
r = DB[k]
r.name
if db.cacheSize() > 500:
db.cacheMinimize()
print db.cacheSize()
return
def info(projects):
"""Just return info in current projects"""
total=0
summDB = PDatabase(local='summary.fs')
for p in projects:
DB = PDatabase(local=os.path.join(savepath,p))
l = DB.length()
total += l
print '%s has %s records' %(p,l)
if p not in summDB.getRecs():
print 'not present in summary project'
print '-----------------------'
print 'info on %s projects' %len(projects)
print 'with total of %s records' %total
print '%s mutants' %(total-len(projects))
return
def remodel():
#DB=PDatabase(local='hewlsample.fs')
DB = PDatabase(server='localhost',
port=8080,
username='******',
password='******',
project='novo')
print DB, 'curr ref:', DB.meta.refprotein
'''rec= DB['wt+D52N']
print rec.getDisplayAttribute('Structure')
rec['Structure'] = rec.Structure'''
r = '6 c9'
rec = DB[r]
DBActions.checkModels(DB=DB, selected=[r])
print rec.Structure
#print rec.aaseq
'''for r in DB.getRecs():
print r, type(DB.get(r).Structure)
print DB.get(r).getDisplayAttribute('Structure')'''
#DB.commit(note='modelling')
return
def testLoading():
"""Test loading times for large DB"""
from PEATDB.PEATTables import PEATTableModel
t1 = time()
DB = PDatabase(local='large.fs')
#DB = PDatabase(server='localhost', port=8080, username='******',
# password='******', project='large')
t2 = time()
print round(t2 - t1, 2)
print DB.getRecs()
t3 = time()
print round(t3 - t2, 2)
print DB.meta
t4 = time()
print t4 - t3
M = PEATTableModel(DB)
print M
t5 = time()
print t5 - t4
return
def importOldProj(datadir,local=None, server=None,
project=None, username=None):
"""Import old peat projects"""
import PEAT_DB.Database as peatDB
from PEAT_DB.PEAT_dict import PEAT_dict, sub_dict
import copy
if local != None:
newDB = PDatabase(local=local)
elif server != None:
newDB = PDatabase(server=server, username=username, port=8080,
password='******', project=project)
print newDB
PT = peatDB.Database(datadir, Tk=False)
oldDB = PT.DB
print 'got old peat_db with %s proteins' %len(PT.proteins)
print PT.DB.keys()
#import meta stuff like userfields, table
for p in newDB.meta.special:
if not p in PT.DB.keys():
continue
print 'adding',p
for k in PT.DB[p]:
newDB.meta[p][k] = copy.deepcopy(PT.DB[p][k])
newDB.meta._p_changed = 1
for p in PT.proteins:
if p in newDB.meta.special:
continue
name = oldDB[p]['Name']
rec = PEATRecord(name=name)
for col in oldDB[p].keys():
cdata = oldDB[p][col]
recdata = {}
if col == 'name':
cdata = oldDB[p]['Name']
if oldDB['userfields'].has_key(col) and oldDB['userfields'][col]['field_type'] in ekintypes:
E=EkinProject(data=cdata)
E.length = len(E.datasets)
if len(E.datasets)==0:
continue
cdata = E
if type(cdata) == sub_dict:
for k in cdata.keys():
recdata[k] = copy.deepcopy(cdata[k])
else:
recdata = cdata
if cdata != '' and cdata != None:
rec.addField(col, data=recdata)
newDB.add(p,rec)
print newDB.meta.userfields
#remove any file cols, too hard to import
for m in newDB.meta.userfields.keys()[:]:
if newDB.meta.userfields[m]['field_type'] == 'File':
newDB.deleteField(m)
newDB.commit(user='******', note='import')
newDB.close()
print 'import done'
return
def loadDB(self, local=None):
from PEATDB.Base import PDatabase
if local != None:
self.DB = PDatabase(local=local)
return
def mergeDBs(DB1, DB2):
"""Combine two databases"""
newDB = PDatabase()
return newDB
def summarise(projects):
summDB = PDatabase(local='summary.fs')
C = CorrelationAnalyser()
figs = []
for f in range(4):
figs.append(plt.figure())
gs = gridspec.GridSpec(5, 5, wspace=0.3, hspace=0.5)
i=0
data=[]
print 'processing %s projects' %len(projects)
for p in projects:
print 'structure:',p
DB = PDatabase(local=os.path.join(savepath,p))
S = PEATTableModel(DB)
try:
exp,pre = S.getColumns(['Exp','prediction'],allowempty=False)
errs = [j[0]-j[1] for j in zip(exp,pre)]
except:
print 'no results'
continue
#DB.close()
#add link to proj
summDB.add(p)
summDB.addField('project',fieldtype='Project')
summDB[p]['project'] = {'server':'enzyme.ucd.ie','username':'******',
'project':p,'password':'******','port':'8080'}
print summDB.isChanged()
#stats
cc,rmse,meanerr = C.getStats(pre,exp)
#ttest for mean errs 0
ttp = round(stats.ttest_1samp(errs, 0)[1],2)
#normality of errs
w,swp = C.ShapiroWilk(errs)
x={'name':p,'mutants':len(pre),'rmse':rmse,'corrcoef':cc,'meanerr':meanerr,
'ttest':ttp,'shapirowilk':swp}
'''ax = figs[0].add_subplot(gs[0, i])
C.plotCorrelation(pre,exp,title=p,ms=2,axeslabels=False,ax=ax)
ax = figs[1].add_subplot(gs[0, i])
C.showHistogram([pre,exp],title=p,labels=['pre','exp'],ax=ax)
ax = figs[2].add_subplot(gs[0, i])
C.plotNorm(errs,title=p,lw=1,ax=ax)
#qqplot
ax = figs[3].add_subplot(gs[0, i])
C.QQplot(errs,title=p,ax=ax)'''
#get PDB info
parser = PDBParser()
descr = parser.getDescription(p)
x.update(descr)
data.append(x)
i+=1
summDB.importDict(data)
print summDB.isChanged()
summDB.commit()
#add all peatsa jobs to summary proj also
'''print 'adding peatsa job info'
PS = PEATSAPlugin()
PS.main(DB=summDB)
#summDB.meta.peatsa_jobs = None
#from ZODB.PersistentMapping import PersistentMapping
#summDB.meta.peatsa_jobs = PersistentMapping()
PS.checkJobsDict()
PS.jobManager.stopLogging()
for p in projects:
#print summDB.meta
DB = PDatabase(local=os.path.join(savepath,p))
job = DB.meta.peatsa_jobs['mycalc']
summDB.meta.peatsa_jobs[p] = job
print job
#DB.close()
print summDB.isChanged()
print summDB.meta.peatsa_jobs
summDB.commit()'''
#for i in range(len(figs)):
# figs[i].savefig('fig%s.png' %i)
#plt.show()
return
def main():
"""Run some analysis"""
from optparse import OptionParser
parser = OptionParser()
app = NMRTitration()
DB=None; E=None
parser.add_option("-f", "--file", dest="file",
help="Open a local db")
parser.add_option("-e", "--ekinprj", dest="ekinprj",
help="Open an ekin project")
parser.add_option("-s", "--server", dest="server", help="field")
parser.add_option("-t", "--analysis", dest="analysis", action='store_true',
help="titr db analysis", default=False)
parser.add_option("-r", "--refit", dest="refit", action='store_true',
help="refit specific ekin data", default=False)
parser.add_option("-u", "--getexperrs", dest="getexperrs", action='store_true',
help="get exp uncertainties", default=False)
parser.add_option("-m", "--addmeta", dest="addmeta", action='store_true',
help="add meta data for NMR", default=False)
parser.add_option("-p", "--protein", dest="protein", help="protein")
parser.add_option("-c", "--col", dest="col", help="field")
parser.add_option("-a", "--atom", dest="atom", help="atom")
parser.add_option("-x", "--export", dest="export", action='store_true',
help="export db", default=False)
parser.add_option("-b", "--benchmark", dest="benchmark", action='store_true',
help="benchmark some stuff", default=False)
parser.add_option("-g", "--gui", dest="gui", action='store_true',
help="start gui app", default=False)
opts, remainder = parser.parse_args()
if opts.file != None and os.path.exists(opts.file):
app.loadDB(opts.file)
elif opts.server != None:
DB = PDatabase(server='localhost', username='******',
password='******', project='titration_db',
port=8080)
if opts.gui == True:
app.main()
app.mainwin.mainloop()
return
yuncerts = {'H':0.03,'N':0.1,'C':0.2}
try:
yuncert=yuncerts[opts.atom]
except:
yuncert=None
if opts.ekinprj != None:
E = EkinProject()
E.openProject(opts.ekinprj)
#some tit db analysis
if opts.analysis == True and opts.server != None:
complete = ['HEWL', 'Bovine Beta-Lactoglobulin',
'Plastocyanin (Anabaena variabilis)',
'Plastocyanin (Phormidium)',
'Glutaredoxin',
'Protein G B1','Xylanase (Bacillus subtilus)']
if opts.col == None:
print 'provide a column'
else:
app.analyseTitDB(DB, opts.col)#, complete)
#app.addpKaTables(DB, complete)
elif opts.benchmark == True:
app.benchmarkExpErr(DB)
elif opts.col != None or E != None:
app.titDBUtils(DB, opts.col, opts.protein, a=opts.atom, E=E,
refit=opts.refit, addmeta=opts.addmeta,
getexperrs=opts.getexperrs, yuncert=yuncert)
elif opts.export == True:
app.exportAll(DB, col=opts.col)
def loadDB(self):
"""Load a DB"""
from PEATDB.Base import PDatabase
if local != None:
self.DB = PDatabase(local=local)
return
def importTest():
DB = PDatabase(local='import.fs')
DB.importCSV(filename='testdata.csv')
return
def summarystats(projects):
"""summary stats"""
for p in projects:
DB = PDatabase(local=os.path.join(savepath,p))
def createProjects(files):
"""Create multiple projects at once from csv files"""
for filename in files:
print filename
name = os.path.splitext(filename)[0]
#create/open db
DB = PDatabase(local=os.path.join(savepath,name))
DB.add('wt')
#add wt pdb
stream = DBActions.fetchPDB(name)
DBActions.addPDBFile(DB, 'wt', pdbdata=stream, pdbname=name, gui=False)
DB.meta.refprotein = 'wt'
DB.meta.info['protein'] = name
#import data from csv
DB.importCSV(os.path.join(cpath,filename), namefield='Mutations')
print 'imported ok'
DB.deleteField('PDB')
DB.commit()
DB.close()
print 'done'
return
def importOldProj(datadir,
local=None,
server=None,
project=None,
username=None):
"""Import old peat projects"""
import PEAT_DB.Database as peatDB
from PEAT_DB.PEAT_dict import PEAT_dict, sub_dict
import copy
if local != None:
newDB = PDatabase(local=local)
elif server != None:
newDB = PDatabase(server=server,
username=username,
port=8080,
password='******',
project=project)
print newDB
PT = peatDB.Database(datadir, Tk=False)
oldDB = PT.DB
print 'got old peat_db with %s proteins' % len(PT.proteins)
print PT.DB.keys()
#import meta stuff like userfields, table
for p in newDB.meta.special:
if not p in PT.DB.keys():
continue
print 'adding', p
for k in PT.DB[p]:
newDB.meta[p][k] = copy.deepcopy(PT.DB[p][k])
newDB.meta._p_changed = 1
for p in PT.proteins:
if p in newDB.meta.special:
continue
name = oldDB[p]['Name']
rec = PEATRecord(name=name)
for col in oldDB[p].keys():
cdata = oldDB[p][col]
recdata = {}
if col == 'name':
cdata = oldDB[p]['Name']
if oldDB['userfields'].has_key(col) and oldDB['userfields'][col][
'field_type'] in ekintypes:
E = EkinProject(data=cdata)
E.length = len(E.datasets)
if len(E.datasets) == 0:
continue
cdata = E
if type(cdata) == sub_dict:
for k in cdata.keys():
recdata[k] = copy.deepcopy(cdata[k])
else:
recdata = cdata
if cdata != '' and cdata != None:
rec.addField(col, data=recdata)
newDB.add(p, rec)
print newDB.meta.userfields
#remove any file cols, too hard to import
for m in newDB.meta.userfields.keys()[:]:
if newDB.meta.userfields[m]['field_type'] == 'File':
newDB.deleteField(m)
newDB.commit(user='******', note='import')
newDB.close()
print 'import done'
return
from PEATDB.Ekin.Base import EkinProject
from PEATDB.DictEdit import DictEditor
import os
import pickle
cols = ['15N NMR', '1H NMR']
nuclnames = {'1H NMR': 'H', '15N NMR': 'N'}
complete = [
'HEWL', 'Bovine Beta-Lactoglobulin', 'Plastocyanin (Anabaena variabilis)',
'Plastocyanin (Phormidium)', 'Glutaredoxin', 'CexCD (Apo)', 'Protein G B1',
'Xylanase (Bacillus subtilus)'
]
col = cols[0]
nucl = nuclnames[col]
t = TitrationAnalyser()
#ghost mapping..
DB = PDatabase(server='peat.ucd.ie',
username='******',
password='******',
project='titration_db',
port=8080)
p = t.extractpKas(DB,
col,
names=['HEWL'],
titratable=False,
reliable=False,
minspan=0.06)
t.mappKas(DB, col, p, names=['HEWL'], nucleus=nucl, calculatespans=False)