def _get_annotation(c, loci):
"""get annotation of transcriptional units"""
data_ann_temp = {}
data_ann = []
counts = Counter()
for lid in c.loci2seq:
# original Py 2.7 code
#for dbi in loci[lid].db_ann.keys():
# data_ann_temp[dbi] = {dbi: map(lambda (x): loci[lid].db_ann[dbi].ann[x].name, loci[lid].db_ann[dbi].ann.keys())}
# suggestion by 2to3
for dbi in list(loci[lid].db_ann.keys()):
data_ann_temp[dbi] = {
dbi: [
loci[lid].db_ann[dbi].ann[x].name
for x in list(loci[lid].db_ann[dbi].ann.keys())
]
}
logger.debug("_json_: data_ann_temp %s %s" %
(dbi, data_ann_temp[dbi]))
counts[dbi] += 1
# original Py 2.7 code
#data_ann = data_ann + map(lambda (x): data_ann_temp[x], data_ann_temp.keys())
# suggestion by 2to3
data_ann = data_ann + [
data_ann_temp[x] for x in list(data_ann_temp.keys())
]
logger.debug("_json_: data_ann %s" % data_ann)
counts = {k: v for k, v in iter(counts.items())}
total_loci = sum([counts[db] for db in counts])
valid_ann = [
k for k, v in iter(counts.items()) if up_threshold(v, total_loci, 0.7)
]
return data_ann, valid_ann
def _common(s1, s2, i1, i2):
"""calculate the common % percentage of sequences"""
c = len(set(s1).intersection(s2))
t = min(len(s1), len(s2))
pct = 1.0 * c / t * t
is_gt = up_threshold(pct, t * 1.0, parameters.similar)
logger.debug("_common: pct %s of clusters:%s %s = %s" % (1.0 * c / t, i1, i2, is_gt))
if pct < parameters.similar and is_gt and pct > 0:
pct = parameters.similar
return pct / t
def _common(s1, s2, i1, i2):
"""calculate the common % percentage of sequences"""
c = len(set(s1).intersection(s2))
t = min(len(s1), len(s2))
pct = 1.0 * c / t * t
is_gt = up_threshold(pct, t * 1.0, parameters.similar)
logger.debug("_common: pct %s of clusters:%s %s = %s" %
(1.0 * c / t, i1, i2, is_gt))
if pct < parameters.similar and is_gt and pct > 0:
pct = parameters.similar
return pct / t
def _get_annotation(c, loci):
"""get annotation of transcriptional units"""
data_ann_temp = {}
data_ann = []
counts = Counter()
for lid in c.loci2seq:
# original Py 2.7 code
#for dbi in loci[lid].db_ann.keys():
# data_ann_temp[dbi] = {dbi: map(lambda (x): loci[lid].db_ann[dbi].ann[x].name, loci[lid].db_ann[dbi].ann.keys())}
# suggestion by 2to3
for dbi in list(loci[lid].db_ann.keys()):
data_ann_temp[dbi] = {dbi: [loci[lid].db_ann[dbi].ann[x].name for x in list(loci[lid].db_ann[dbi].ann.keys())]}
logger.debug("_json_: data_ann_temp %s %s" % (dbi, data_ann_temp[dbi]))
counts[dbi] += 1
# original Py 2.7 code
#data_ann = data_ann + map(lambda (x): data_ann_temp[x], data_ann_temp.keys())
# suggestion by 2to3
data_ann = data_ann + [data_ann_temp[x] for x in list(data_ann_temp.keys())]
logger.debug("_json_: data_ann %s" % data_ann)
counts = {k: v for k, v in iter(counts.items())}
total_loci = sum([counts[db] for db in counts])
valid_ann = [k for k, v in iter(counts.items()) if up_threshold(v, total_loci, 0.7)]
return data_ann, valid_ann