def main():
assert (len(argv) == 2), "need the sampleID and nothing else"
sampleId = argv[1]
explainFailure = True
path = "kmer_histograms"
print sampleId
# perform haploid fit to the sample (ignoring thge diploid component)
hFitter = HaploidFitter(path+"/"+sampleId+".mixed.kmer_dist")
hParamNames = hFitter.paramNames
hFitParams = hFitter.fit()
if (hFitParams == None):
print >>stderr, "haploid: failure or non-convergence"
print "(haploid: failure or non-convergence)"
if (explainFailure):
print "... return code ..."
print hFitter.retCode
print "... stdout ..."
print hFitter.stdout
print "... stderr ..."
print hFitter.stderr
else:
print params_to_text(hParamNames,hFitParams,prefix="cvrg.haploid:")
# ask for default values for the hap-hap enrichment model
hhFitter = EnrichedHapHapFitter(path+"/"+sampleId+".mixed.kmer_dist")
hhParamNames = hhFitter.paramNames
hhDefaultParams = hhFitter.default_params()
if (hhDefaultParams == None):
print >>stderr, "hap-hap: failed to get default params"
print "(hap-hap: failed to get default params)"
if (explainFailure):
print "... return code ..."
print hhFitter.retCode
print "... stdout ..."
print hhFitter.stdout
print "... stderr ..."
print hhFitter.stderr
else:
print params_to_text(hhParamNames,hhDefaultParams,prefix="dflt.haphap:")
assert (hFitParams != None) and (hhDefaultParams != None), \
"(no point in trying to fit the hap-hap model)"
# create an initial vector for the enrichment model, borrowing some
# elements from the haploid model fit
hhInitParams = dict(hhDefaultParams)
hhInitParams["zp.copy.y"] = hFitParams["zp.copy"]
hhInitParams["p.e" ] = hFitParams["p.e"]
hhInitParams["shape.e" ] = hFitParams["shape.e"]
hhInitParams["scale.e" ] = hFitParams["scale.e"]
hhInitParams["u.y" ] = hFitParams["u.v"]
hhInitParams["sd.y" ] = hFitParams["sd.v"]
hhInitParams["shape.y" ] = hFitParams["shape.v"]
pAuto = 1 - float(hhInitParams["p.y"])
hhInitParams["u.auto" ] = pAuto * float(hhInitParams["u.y"])
hhInitParams["sd.auto" ] = sdHom = pAuto * float(hhInitParams["sd.y"])
# perform hap-hap fit to the mixed components
hhFitParams = hhFitter.fit(hhInitParams)
if (hhFitParams == None):
print >>stderr, "hap-hap: failure or non-convergence"
print "(hap-hap: failure or non-convergence)"
print params_to_text(hhParamNames,hhInitParams,prefix="smart.haphap:")
if (explainFailure):
print "... return code ..."
print hhFitter.retCode
print "... stdout ..."
print hhFitter.stdout
print "... stderr ..."
print hhFitter.stderr
else:
print params_to_text(hhParamNames,hhInitParams,hhFitParams,
prefix="smart.haphap:",prefix2="cvrg.haphap:")
assert (hhFitParams != None), \
"(no point in trying to fit the hap-dip model)"
# ask for default values for the hap-dip enrichment model
hdFitter = EnrichedHapDipFitter(path+"/"+sampleId+".mixed.kmer_dist")
hdParamNames = hdFitter.paramNames
hdDefaultParams = hdFitter.default_params()
if (hdDefaultParams == None):
print >>stderr, "hap-dip: failed to get default params"
print "(hap-dip: failed to get default params)"
if (explainFailure):
print "... return code ..."
print hdFitter.retCode
print "... stdout ..."
print hdFitter.stdout
print "... stderr ..."
print hdFitter.stderr
else:
print params_to_text(hdParamNames,hdDefaultParams,prefix="dflt.hapdip:")
assert (hdDefaultParams != None), \
"(no point in trying to fit the hap-dip model)"
# read the sample's "cheat" parameters for comparison (usually produced by
# explore3_hap_dip)
fitFilename = path+"/"+sampleId+".mixed.fit"
f = file(fitFilename,"rt")
hdCheatParams = params_from_text([line for line in f])
f.close()
for name in hdDefaultParams:
assert (name in hdCheatParams), \
"parameter \"%s\" missing from %s" % (name,fitFilename)
for name in hdCheatParams:
assert (name in hdDefaultParams), \
"extra parameter \"%s\" in %s" % (name,fitFilename)
# create an initial vector for the hap-dip enrichment model, borrowing some
# elements from the hap-hap model fit
hdInitParams = dict(hdDefaultParams)
hdInitParams["zp.copy.y"] = hhFitParams["zp.copy.y"]
hdInitParams["p.e" ] = hhFitParams["p.e"]
hdInitParams["shape.e" ] = hhFitParams["shape.e"]
hdInitParams["scale.e" ] = hhFitParams["scale.e"]
hdInitParams["p.y" ] = hhFitParams["p.y"]
hdInitParams["u.y" ] = hhFitParams["u.y"]
hdInitParams["sd.y" ] = hhFitParams["sd.y"]
hdInitParams["shape.y" ] = hhFitParams["shape.y"]
pAuto = 1 - float(hdInitParams["p.y"])
pHom = float(hdInitParams["p.hom"])
hdInitParams["u.hom" ] = pAuto * pHom * float(hdInitParams["u.y"])
hdInitParams["sd.hom" ] = sdHom = pAuto * pHom * float(hdInitParams["sd.y"])
hdInitParams["var.het" ] = sdHom * sdHom
# perform hap-dip fit to the mixed components
hdFitParams = hdFitter.fit(hdInitParams)
if (hdFitParams == None):
print >>stderr, "hap-dip: failure or non-convergence"
print "(hap-dip: failure or non-convergence)"
print params_to_text(hdParamNames,hdInitParams,hdCheatParams,
prefix="smart.hapdip:",prefix2="cheat.hapdip:")
if (explainFailure):
print "... return code ..."
print hdFitter.retCode
print "... stdout ..."
print hdFitter.stdout
print "... stderr ..."
print hdFitter.stderr
else:
print params_to_text(hdParamNames,hdInitParams,hdFitParams,
prefix="smart.hapdip:",prefix2="cvrg.hapdip:")
print params_to_text(hdParamNames,hdCheatParams,prefix="cheat.hapdip:")
# if convergence failed, try moving the initial parameters toward the
# cheat parameters in small steps until we get convergence
# $$$ a binary search would be "better"
numSteps = 100
step = 0
while (hdFitParams == None):
step += 1
if (step == numSteps): break
print >>stderr, "step %d" % step
hdStepParams = {}
for name in hdInitParams:
if (name in ["u.hom","sd.hom","var.het"]): continue
param = float(hdInitParams[name])
param += (step * (float(hdCheatParams[name]) - param)) / numSteps
hdStepParams[name] = param
pAuto = 1 - float(hdStepParams["p.y"])
pHom = float(hdStepParams["p.hom"])
hdStepParams["u.hom" ] = pAuto * pHom * float(hdStepParams["u.y"])
hdStepParams["sd.hom" ] = sdHom = pAuto * pHom * float(hdStepParams["sd.y"])
hdStepParams["var.het" ] = sdHom * sdHom
hdFitParams = hdFitter.fit(hdStepParams)
if (hdFitParams == None):
print params_to_text(hdParamNames,hdStepParams,
prefix="step[%d].hapdip:" % step)
#if (explainFailure):
# print "... return code ..."
# print hdFitter.retCode
# print "... stdout ..."
# print hdFitter.stdout
# print "... stderr ..."
# print hdFitter.stderr
else:
print params_to_text(hdParamNames,hdStepParams,hdFitParams,
prefix="step[%d].hapdip:" % step,prefix2="cvrg.hapdip:")
def main(): assert (len(argv) == 2), "need the sampleID and nothing else" sampleId = argv[1] explainFailure = True path = "kmer_histograms" print sampleId # perform haploid fit to the sample (ignoring thge diploid component) hFitter = HaploidFitter(path+"/"+sampleId+".mixed.kmer_dist") hParamNames = hFitter.paramNames hFitParams = hFitter.fit() if (hFitParams == None): print >>stderr, "haploid: failure or non-convergence" print "(haploid: failure or non-convergence)" if (explainFailure): print "... return code ..." print hFitter.retCode print "... stdout ..." print hFitter.stdout print "... stderr ..." print hFitter.stderr else: print params_to_text(hParamNames,hFitParams,prefix="cvrg.haploid:") # ask for default values for the enrichment model hhFitter = EnrichedHapHapFitter(path+"/"+sampleId+".mixed.kmer_dist") hhParamNames = hhFitter.paramNames hhDefaultParams = hhFitter.default_params() if (hhDefaultParams == None): print >>stderr, "hap-hap: failed to get default params" print "(hap-hap: failed to get default params)" if (explainFailure): print "... return code ..." print hhFitter.retCode print "... stdout ..." print hhFitter.stdout print "... stderr ..." print hhFitter.stderr else: print params_to_text(hhParamNames,hhDefaultParams,prefix="dflt.haphap:") assert (hFitParams != None) and (hhDefaultParams != None), \ "(no point in trying to fit the hap-hap model)" # create an initial vector for the enrichment model, borrowing some # elements from the haploid model fit hhInitParams = dict(hhDefaultParams) hhInitParams["zp.copy.y"] = hFitParams["zp.copy"] hhInitParams["p.e" ] = hFitParams["p.e"] hhInitParams["shape.e" ] = hFitParams["shape.e"] hhInitParams["scale.e" ] = hFitParams["scale.e"] hhInitParams["u.y" ] = hFitParams["u.v"] hhInitParams["sd.y" ] = hFitParams["sd.v"] hhInitParams["shape.y" ] = hFitParams["shape.v"] pAuto = 1 - float(hhInitParams["p.y"]) hhInitParams["u.auto" ] = pAuto * float(hhInitParams["u.y"]) hhInitParams["sd.auto" ] = sdHom = pAuto * float(hhInitParams["sd.y"]) # perform hap-hap fit to the mixed components hhFitParams = hhFitter.fit(hhInitParams) if (hhFitParams == None): print >>stderr, "hap-hap: failure or non-convergence" print "(hap-hap: failure or non-convergence)" print params_to_text(hhParamNames,hhInitParams,prefix="smart.haphap:") if (explainFailure): print "... return code ..." print hhFitter.retCode print "... stdout ..." print hhFitter.stdout print "... stderr ..." print hhFitter.stderr else: print params_to_text(hhParamNames,hhInitParams,hhFitParams, prefix="smart.haphap:",prefix2="cvrg.haphap:")
