def read_mute_freqs(self, mute_freq_dir):
# NOTE these are mute freqs, not branch lengths, but it's ok for now
for mtype in ['all',] + utils.regions:
infname = mute_freq_dir + '/' + mtype + '-mean-mute-freqs.csv'
self.branch_lengths[mtype] = {}
self.branch_lengths[mtype]['lengths'], self.branch_lengths[mtype]['probs'] = [], []
mutehist = Hist(fname=infname)
self.branch_lengths[mtype]['mean'] = mutehist.get_mean()
# if mutehist.GetBinContent(0) > 0.0 or mutehist.GetBinContent(mutehist.GetNbinsX()+1) > 0.0:
# print 'WARNING nonzero under/overflow bins read from %s' % infname
mutehist.normalize(include_overflows=False, overflow_eps_to_ignore=1e-2) # if it was written with overflows included, it'll need to be renormalized
check_sum = 0.0
for ibin in range(1, mutehist.n_bins + 1): # ignore under/overflow bins
freq = mutehist.get_bin_centers()[ibin]
branch_length = self.convert_observed_changes_to_branch_length(float(freq))
prob = mutehist.bin_contents[ibin]
self.branch_lengths[mtype]['lengths'].append(branch_length)
self.branch_lengths[mtype]['probs'].append(prob)
check_sum += self.branch_lengths[mtype]['probs'][-1]
if not utils.is_normed(check_sum):
raise Exception('not normalized %f' % check_sum)
if self.args.debug:
print ' mean branch lengths'
for mtype in ['all',] + utils.regions:
print ' %4s %7.3f (ratio %7.3f)' % (mtype, self.branch_lengths[mtype]['mean'], self.branch_lengths[mtype]['mean'] / self.branch_lengths['all']['mean'])
