def getKL(self, usage):
"""return Kullback-Leibler Divergence (relative entropy) of sequences with
respect to reference codon usage.
"""
e = 0
freqs = Genomics.CalculateCodonFrequenciesFromCounts(
self.mCodonCounts, self.mPseudoCounts)
for codon, count in self.mCodonCounts.items():
e += usage[codon] * math.log(usage[codon] / freqs[codon])
return e
def getEntropy(self, usage=None):
"""return entropy of a source in terms of a reference usage.
Also called conditional entropy or encoding cost.
Note that here I compute the sum over 20 entropies, one for each amino acid.
If not given, calculate entropy.
"""
e = 0
freqs = Genomics.CalculateCodonFrequenciesFromCounts(
self.mCodonCounts, self.mPseudoCounts)
if usage == None: usage = freqs
for codon, count in self.mCodonCounts.items():
e -= freqs[codon] * math.log(usage[codon])
return e
def updateProperties(self):
SequencePropertiesCodons.updateProperties(self)
self.mCodonFrequencies = Genomics.CalculateCodonFrequenciesFromCounts(
self.mCodonCounts)
