def consolidate(usages):
"""Sums frequencies of a list of usages into one usage."""
result = CodonUsage()
for u in usages:
result += u
result.normalize()
return result
def adapt_pr2_bias(codon_usages, block="GC", bin_lowbound=0.0, bin_upbound=1.0, binwidth=0.1):
"""Returns the bin midpoint and the PR2 biases for each bin of GC3."""
result = []
for i, bin in enumerate(bin_by_p3(codon_usages, bin_lowbound, bin_upbound, binwidth)):
if not bin:
continue
try:
tot_usage = CodonUsage()
for c in bin:
tot_usage += c
curr_pr2 = tot_usage.pr2bias(block)
midbin = bin_lowbound + (i + 0.5) * binwidth
result.append([midbin] + list(curr_pr2))
except (ZeroDivisionError, FloatingPointError):
pass
return array(result)
def adapt_pr2_bias(codon_usages, block='GC', bin_lowbound=0.0, bin_upbound=1.0,\
binwidth=0.1):
"""Returns the bin midpoint and the PR2 biases for each bin of GC3."""
result = []
for i, bin in enumerate(bin_by_p3(codon_usages, bin_lowbound, bin_upbound, \
binwidth)):
if not bin:
continue
try:
tot_usage = CodonUsage()
for c in bin:
tot_usage += c
curr_pr2 = tot_usage.pr2bias(block)
midbin = bin_lowbound + (i+0.5)*binwidth
result.append([midbin]+list(curr_pr2))
except (ZeroDivisionError, FloatingPointError):
pass
return array(result)
def adapt_fingerprint(codon_usages, which_blocks="quartets", include_mean=True, normalize=True):
"""takes a sequence of CodonUsage objects
and returns an array for a fingerprint plot with:
x: the g3/(g3+c3)
y: the a3/(a3+u3)
frequency: total of the base/total of all
in the order:
alanine, arginine4, glycine, leucine4,
proline, serine4, threonine, valine (if quartets_only is True).
codon_usages: list of CodonUsage objects
quartets_only: return only the quartets that all code for the same aa(True)
quartets_only set to false yeilds a 16 fingerprint
include_mean: include a point for the mean in the result (True)
normalize: ensure the frequencies returned sum to 1 (True)
"""
tot_codon_usage = CodonUsage()
for idx, c in enumerate(codon_usages):
tot_codon_usage += c
return tot_codon_usage.fingerprint(which_blocks=which_blocks, include_mean=include_mean, normalize=normalize)
def adapt_fingerprint(codon_usages, which_blocks='quartets', \
include_mean=True, normalize=True):
"""takes a sequence of CodonUsage objects
and returns an array for a fingerprint plot with:
x: the g3/(g3+c3)
y: the a3/(a3+u3)
frequency: total of the base/total of all
in the order:
alanine, arginine4, glycine, leucine4,
proline, serine4, threonine, valine (if quartets_only is True).
codon_usages: list of CodonUsage objects
quartets_only: return only the quartets that all code for the same aa(True)
quartets_only set to false yeilds a 16 fingerprint
include_mean: include a point for the mean in the result (True)
normalize: ensure the frequencies returned sum to 1 (True)
"""
tot_codon_usage = CodonUsage()
for idx, c in enumerate(codon_usages):
tot_codon_usage += c
return tot_codon_usage.fingerprint(which_blocks=which_blocks, \
include_mean=include_mean, normalize=normalize)
