def loadTemporal(fname):
global tempSamples, popNames
f = open(fname)
l = f.readline()
i = 0
tempSamples = []
while l != '':
if i > len(popNames):
break
try:
tempSamples.append(int(l.rstrip()))
except:
error(frame, "Temporal file syntax error, please check")
return False
i += 1
l = f.readline()
f.close()
if i != len(popNames):
error(
frame,
"Number of temporal samples (%d) is less than the number of time points specified (%d)"
% (i, len(popNames)))
return False
else:
info(frame, "Temporal points set at: %s" % str(tempSamples))
return True
def checkAlleles(file):
df = FileParser.read(file)
countAlleles = []
for locus in df.loci_list:
countAlleles.append(set())
indiv = df.get_individual()
while indiv:
if type(indiv) == tuple:
name, loci = indiv
for l in range(len(loci)):
for a in loci[l]:
if a:
countAlleles[l].add(a)
indiv = df.get_individual()
probLoci = []
for l in range(len(countAlleles)):
if len(countAlleles[l]) > 2:
probLoci.append(df.loci_list[l])
if probLoci != []:
if len(probLoci) > 5:
error(frame,
"Many (%d) loci have more than 2 alleles" % (len(probLoci)))
else:
error(frame,
"Some loci have more than 2 alleles: %s" % (str(probLoci)))
def propertyChange(self, evt):
if self.ignoreChanges: return
change = False
if not self.isTemporal:
if evt.getSource() == self.fst and evt.getPropertyName() == 'value':
new = float(evt.getNewValue())
old = float(evt.getOldValue())
if new > 0.99:
evt.getSource().setValue(old)
if new < -0.2:
evt.getSource().setValue(old)
elif new< 0.0:
self.systemPanel.force.setSelected(False)
self.systemPanel.force.setEnabled(False)
else:
self.systemPanel.force.setEnabled(True)
else:
if evt.getSource() == self.ne and evt.getPropertyName() == 'value':
new = int(evt.getNewValue())
old = int(evt.getOldValue())
if new < 0:
evt.getSource().setValue(old)
if self.isDominant and evt.getSource() in [self.theta, self.beta1,
self.beta2, self.crit] and evt.getPropertyName() == 'value':
new = float(evt.getNewValue())
old = float(evt.getOldValue())
if new > 0.99 or new < -0.2:
evt.getSource().setValue(old)
if evt.getSource() == self.sampleSize and evt.getPropertyName() == 'value':
change = True
new = int(evt.getNewValue())
old = int(evt.getOldValue())
if new > 50 and old > 4:
warn(self, 'A sample size bigger than 50 is not expected to produce better results, while it slows the computation')
if new < 5 and (new!=0 and not self.isDominant):
evt.getSource().setValue(old)
if evt.getSource() == self.pops and evt.getPropertyName() == 'value':
change = True
new = int(evt.getNewValue())
old = int(evt.getOldValue())
if new > 100:
error(self, 'Maximum value for total populations is 100')
evt.getSource().setValue(100)
if new < self.knownPops:
error(self,
'Expected total populations has to be at least the same as the number of populations under study.'
)
evt.getSource().setValue(self.knownPops)
if not self.isTemporal:
if evt.getSource() == self.mut:
change = True
if not change: return
if self.menuHandles['item5000'].isEnabled():
self.menuHandles['item5000'].setEnabled(False)
warn(self, "Changed parameter will require restarting simulations")
def loadGenePop(file):
global rec2, popNames, remPops, remLoci #,rec
#rec = GenePop.read(open(str(file)))
try:
rec2 = FileParser.read(file)
if isDominant:
checkAlleles(file)
remPops = []
remLoci = []
#popNames = ['pop' + str(i+1) for i in range(len(rec.populations))]
popNames = ['pop' + str(i+1) for i in range(countPops(rec2))]
except:
error(frame, "Not a genepop file!")
def loadTemporal(fname):
global tempSamples, popNames
f = open(fname)
l = f.readline()
i = 0
tempSamples = []
while l<>'':
if i>len(popNames):
break
tempSamples.append(int(l.rstrip()))
i += 1
l = f.readline()
f.close()
if i!=len(popNames):
error(frame, "Number of temporal samples is less than the number of time points specified")
else:
info(frame, "Temporal points set at: %s" % str(tempSamples))
def _changeList(dialog, orig_list, orig_model, dest_model, requiresTwo = True):
#sel = orig_list.getSelectedIndex()
#if sel == -1:
# return
#value = orig_model.get(sel)
#orig_model.remove(sel)
#dest_model.addElement(value)
sels = orig_list.getSelectedIndices()
if requiresTwo:
if len(sels) > orig_model.getSize() - 2:
error(dialog, 'At least 2 elements have to remain')
return
selsA = []
for sel in sels:
selsA.append(sel)
selsA.sort(lambda x, y : cmp(y,x))
for sel in selsA:
value = orig_model.get(sel)
orig_model.remove(sel)
dest_model.addElement(value)
def _changeList(dialog, orig_list, orig_model, dest_model, requiresTwo=True):
#sel = orig_list.getSelectedIndex()
#if sel == -1:
# return
#value = orig_model.get(sel)
#orig_model.remove(sel)
#dest_model.addElement(value)
sels = orig_list.getSelectedIndices()
if requiresTwo:
if len(sels) > orig_model.getSize() - 2:
error(dialog, 'At least 2 elements have to remain')
return
selsA = []
for sel in sels:
selsA.append(sel)
selsA.sort(lambda x, y: cmp(y, x))
for sel in selsA:
value = orig_model.get(sel)
orig_model.remove(sel)
dest_model.addElement(value)
def checkAlleles(file):
df = FileParser.read(file)
countAlleles = []
for locus in df.loci_list:
countAlleles.append(set())
indiv = df.get_individual()
while indiv:
if type(indiv) == tuple:
name, loci = indiv
for l in range(len(loci)):
for a in loci[l]:
if a: countAlleles[l].add(a)
indiv = df.get_individual()
probLoci = []
for l in range(len(countAlleles)):
if len(countAlleles[l])>2:
probLoci.append(df.loci_list[l])
if probLoci != []:
if len(probLoci)>5:
error(frame, "Many (%d) loci have more than 2 alleles" % (len(probLoci)))
else:
error(frame, "Some loci have more than 2 alleles: %s" % (str(probLoci)))
def loadTemporal(fname):
global tempSamples, popNames
f = open(fname)
l = f.readline()
i = 0
tempSamples = []
while l != '':
if i > len(popNames):
break
try:
tempSamples.append(int(l.rstrip()))
except:
error(frame, "Temporal file syntax error, please check")
return False
i += 1
l = f.readline()
f.close()
if i != len(popNames):
error(frame, "Number of temporal samples (%d) is less than the number of time points specified (%d)" % (i, len(popNames)))
return False
else:
info(frame, "Temporal points set at: %s" % str(tempSamples))
return True
def runFDist(more=False):
global numAttempts
global selRec2, frame, fdRequest, runState
global empiricalPanel, systemPanel, statusPanel, chartPanel
global isDominant, isTemporal
chartPanel.resetData(True)
try:
if not more:
os.remove(lpath + os.sep + 'out.dat') # careful, not for 5000 case
except OSError:
pass # Its ok if it doesn't exist
disableAllMenus()
disablePanel(empiricalPanel)
disablePanel(systemPanel)
npops = empiricalPanel.getTotalPops()
nsamples = countPops(selRec2)
if nsamples > npops:
error(frame, "Expected total populations lower then selected populations")
return
if isTemporal:
ne = empiricalPanel.getNe()
else:
fst = empiricalPanel.getFst()
if not isTemporal and not isDominant:
mutStr = empiricalPanel.mut.getSelectedItem()
mut = getMut(mutStr)
if isDominant:
theta = empiricalPanel.getTheta()
beta = empiricalPanel.getBeta()
crit = empiricalPanel.getCrit()
mut = None
else:
theta = beta = crit = None
if more:
statusPanel.setStatus('Running an extra 5000 simulations', Color.YELLOW)
numSims = 5000
else:
numSims = systemPanel.getNumSims()
numCores = systemPanel.getNumCores()
sampSize = empiricalPanel.getSampleSize()
if not more:
if not isTemporal:
force = systemPanel.getForce()
else:
force = False
neutral = systemPanel.getNeutral()
if neutral and force:
statusPanel.setStatus('Forcing correct mean Fst for first pass', Color.RED)
fdRequest = 'NeuFor'
runState = 'ForceBeforeNeutral'
numAttempts = 0
numSims = 50000
elif neutral:
statusPanel.setStatus('First simulation pass to determine initial neutral set', Color.CYAN)
fdRequest = 'Neutral'
runState = 'Neutral'
elif force:
statusPanel.setStatus('Forcing correct mean Fst for final simulation', Color.RED)
fdRequest = 'Force'
runState = 'Force'
numAttempts = 0
numSims = 50000
else:
statusPanel.setStatus('Running simulation', Color.YELLOW)
fdRequest = ''
runState = 'Final'
else:
fdRequest = ''
runState = 'Final'
if isTemporal:
runFtempPart(more, selRec2, numSims, npops, nsamples, ne,
sampSize, numCores)
else:
runFDistPart(more, selRec2, mut, numSims, npops, nsamples, fst,
sampSize, theta, beta, crit, numCores)
def propertyChange(self, evt):
if self.ignoreChanges:
return
change = False
if not self.isTemporal:
if evt.getSource() == self.fst and evt.getPropertyName(
) == 'value':
new = float(evt.getNewValue())
old = float(evt.getOldValue())
if new > 0.99:
evt.getSource().setValue(old)
if new < -0.2:
evt.getSource().setValue(old)
elif new < 0.0:
self.systemPanel.force.setSelected(False)
self.systemPanel.force.setEnabled(False)
else:
self.systemPanel.force.setEnabled(True)
else:
if evt.getSource() == self.ne and evt.getPropertyName() == 'value':
new = int(evt.getNewValue())
old = int(evt.getOldValue())
if new < 0:
evt.getSource().setValue(old)
if self.isDominant and \
evt.getSource() in [self.theta, self.beta1, self.beta2, self.crit] and \
evt.getPropertyName() == 'value':
new = float(evt.getNewValue())
old = float(evt.getOldValue())
if new > 0.99 or new < -0.2:
evt.getSource().setValue(old)
# Subsample size
if evt.getSource() == self.sampleSize and evt.getPropertyName(
) == 'value':
change = True
new = int(evt.getNewValue())
old = int(evt.getOldValue())
if new > 50 and old > 4:
warn(
self,
'A sample size bigger than 50 is not expected to produce better results, '
+ 'while it slows the computation')
if new < 5 and (new != 0 and not self.isDominant):
evt.getSource().setValue(old)
if evt.getSource() == self.pops and evt.getPropertyName() == 'value':
change = True
new = int(evt.getNewValue())
old = int(evt.getOldValue())
if new > 100:
error(self, 'Maximum value for total populations is 100')
evt.getSource().setValue(100)
if new < self.knownPops:
error(
self,
'Expected total populations has to be at least the same as the number of populations under study.'
)
evt.getSource().setValue(self.knownPops)
if not self.isTemporal:
if evt.getSource() == self.mut:
change = True
if not change:
return
if self.menuHandles['item5000'].isEnabled():
self.menuHandles['item5000'].setEnabled(False)
warn(self, "Changed parameter will require restarting simulations")
