/
explore5_hap_hap.py
executable file
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/
explore5_hap_hap.py
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#!/usr/bin/env python
"""
Without cheating, use estimates from a haploid fit to the mixed data to
contribute to the initial vector for the hap-hap fit.
"""
from sys import argv,stderr
from kmervature import HaploidFitter,DiploidFitter,EnrichedHapHapFitter, \
params_to_text,params_from_text
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:")
if __name__ == "__main__": main()