def is_positioned_compatibly(self, other):
""" Are these InwardsPointingCodingBlockGraph positioned compatibly? """
mutualorgs = self.mutual_organisms(other)
analyses = []
for (pacbpkey, nodeQ, nodeS), pacbporf in self.pacbps.iteritems():
orgQ = self.organism_by_node(nodeQ)
orgS = self.organism_by_node(nodeS)
if not orgQ in mutualorgs or not orgS in mutualorgs: continue
for (_pacbpkey, _nodeQ,
_nodeS), _pacbporf in other.pacbps.iteritems():
_orgQ = other.organism_by_node(_nodeQ)
_orgS = other.organism_by_node(_nodeS)
if _orgQ != orgQ or _orgS != orgS: continue
pos = pacbporf.relatively_positioned_towards(_pacbporf)
(q1, s1) = relpos2binaryrelpos(pos['Q1'], pos['S1'])
(q2, s2) = relpos2binaryrelpos(pos['Q2'], pos['S2'])
# check positioning
if q1 != s1: analyses.append([False, None])
elif q2 != s2: analyses.append([False, None])
else: analyses.append([True, q1[0] == 1])
# Have closer look on the (True,...) tuples.
# The orientation self->other or other->self is stored in the 2th value
# These orientations must therefor be identical
cnt_false = [a for a, b in analyses].count(False)
cnt_ab = [b for a, b in analyses].count(True)
cnt_ba = [b for a, b in analyses].count(False)
return_list = []
for pos in range(0, cnt_false):
return_list.append(False)
if cnt_ab > cnt_ba:
for pos in range(0, cnt_ba):
return_list.append(False)
for pos in range(0, cnt_ab):
return_list.append(True)
elif cnt_ab < cnt_ba:
for pos in range(0, cnt_ab):
return_list.append(False)
for pos in range(0, cnt_ba):
return_list.append(True)
else:
# identical in size
for pos in range(0, cnt_ab):
return_list.append(False)
for pos in range(0, cnt_ba):
return_list.append(True)
# return the return_list outcome
return return_list
def relatively_positioned_towards(cbg1, cbg2):
"""
"""
# get union of organisms between two CBGs
allorgs = cbg1.organism_set().union(cbg2.organism_set())
posRel = []
posBin = []
orfIdent = []
# get overall minimal spanning range data structures for comparison
omsrCbg1 = cbg1.overall_minimal_spanning_range()
omsrCbg2 = cbg2.overall_minimal_spanning_range()
for org in allorgs:
if org in cbg1.organism_set() and org in cbg2.organism_set():
nodeCbg1 = cbg1.node_by_organism(org)
nodeCbg2 = cbg2.node_by_organism(org)
if len(omsrCbg1[nodeCbg1]) == 0 or len(omsrCbg2[nodeCbg2]) == 0:
continue
# get relative positioning of the OMSRs
(a1, a2, a3), (b1, b2, b3) = rel_pos_sets(
omsrCbg1[nodeCbg1],
omsrCbg2[nodeCbg2],
)
# get binary relative positioning of the OMSRs
(Ba1, Ba2, Ba3), (Bb1, Bb2, Bb3) = relpos2binaryrelpos(
(a1, a2, a3), (b1, b2, b3))
posRel.append(((a1, a2, a3), (b1, b2, b3)))
posBin.append(((Ba1, Ba2, Ba3), (Bb1, Bb2, Bb3)))
# check if the orfs are identical
orfCbg1 = cbg1.get_orfs_of_graph(organism=org)[0]
orfCbg2 = cbg2.get_orfs_of_graph(organism=org)[0]
orfIdent.append(orfCbg1.id == orfCbg2.id)
# make summed binary tuples
summedPosBin = ([0, 0, 0], [0, 0, 0])
for i in range(0, 2):
for j in range(0, 3):
summedPosBin[i][j] = sum([item[i][j] for item in posBin])
# and make binary tuples of this one
(binPosCbg1,
binPosCbg2) = relpos2binaryrelpos(summedPosBin[0],
summedPosBin[1],
overlap_offset=0,
percentual_overlap_offset=0.0)
# return summed tuples, binary tuples and orfIdent for cbg1 and cbg2
return summedPosBin[0], summedPosBin[
1], binPosCbg1, binPosCbg2, orfIdent, posRel, posBin
def relatively_positioned_towards(cbg1,cbg2):
"""
"""
# get union of organisms between two CBGs
allorgs = cbg1.organism_set().union( cbg2.organism_set() )
posRel = []
posBin = []
orfIdent= []
# get overall minimal spanning range data structures for comparison
omsrCbg1 = cbg1.overall_minimal_spanning_range()
omsrCbg2 = cbg2.overall_minimal_spanning_range()
for org in allorgs:
if org in cbg1.organism_set() and org in cbg2.organism_set():
nodeCbg1 = cbg1.node_by_organism(org)
nodeCbg2 = cbg2.node_by_organism(org)
if len(omsrCbg1[nodeCbg1]) == 0 or len(omsrCbg2[nodeCbg2]) == 0:
continue
# get relative positioning of the OMSRs
(a1,a2,a3), (b1,b2,b3) = rel_pos_sets(
omsrCbg1[nodeCbg1],
omsrCbg2[nodeCbg2],
)
# get binary relative positioning of the OMSRs
(Ba1,Ba2,Ba3), (Bb1,Bb2,Bb3) = relpos2binaryrelpos( (a1,a2,a3), (b1,b2,b3) )
posRel.append( ( (a1,a2,a3), (b1,b2,b3) ) )
posBin.append( ( (Ba1,Ba2,Ba3), (Bb1,Bb2,Bb3) ) )
# check if the orfs are identical
orfCbg1 = cbg1.get_orfs_of_graph(organism=org)[0]
orfCbg2 = cbg2.get_orfs_of_graph(organism=org)[0]
orfIdent.append( orfCbg1.id == orfCbg2.id )
# make summed binary tuples
summedPosBin = ( [0,0,0], [0,0,0] )
for i in range(0,2):
for j in range(0,3):
summedPosBin[i][j] = sum([ item[i][j] for item in posBin ] )
# and make binary tuples of this one
( binPosCbg1, binPosCbg2 ) = relpos2binaryrelpos(
summedPosBin[0],
summedPosBin[1],
overlap_offset = 0,
percentual_overlap_offset = 0.0
)
# return summed tuples, binary tuples and orfIdent for cbg1 and cbg2
return summedPosBin[0], summedPosBin[1], binPosCbg1, binPosCbg2, orfIdent, posRel, posBin
def is_positioned_compatibly(self,other):
""" Are these InwardsPointingCodingBlockGraph positioned compatibly? """
mutualorgs = self.mutual_organisms(other)
analyses = []
for (pacbpkey,nodeQ,nodeS),pacbporf in self.pacbps.iteritems():
orgQ = self.organism_by_node(nodeQ)
orgS = self.organism_by_node(nodeS)
if not orgQ in mutualorgs or not orgS in mutualorgs: continue
for (_pacbpkey,_nodeQ,_nodeS),_pacbporf in other.pacbps.iteritems():
_orgQ = other.organism_by_node(_nodeQ)
_orgS = other.organism_by_node(_nodeS)
if _orgQ != orgQ or _orgS != orgS: continue
pos = pacbporf.relatively_positioned_towards(_pacbporf)
(q1,s1) = relpos2binaryrelpos(pos['Q1'],pos['S1'])
(q2,s2) = relpos2binaryrelpos(pos['Q2'],pos['S2'])
# check positioning
if q1 != s1: analyses.append( [ False, None ] )
elif q2 != s2: analyses.append( [ False, None ] )
else: analyses.append( [ True, q1[0]==1 ] )
# Have closer look on the (True,...) tuples.
# The orientation self->other or other->self is stored in the 2th value
# These orientations must therefor be identical
cnt_false = [ a for a,b in analyses ].count(False)
cnt_ab = [ b for a,b in analyses ].count(True)
cnt_ba = [ b for a,b in analyses ].count(False)
return_list = []
for pos in range(0,cnt_false): return_list.append(False)
if cnt_ab > cnt_ba:
for pos in range(0,cnt_ba): return_list.append(False)
for pos in range(0,cnt_ab): return_list.append(True)
elif cnt_ab < cnt_ba:
for pos in range(0,cnt_ab): return_list.append(False)
for pos in range(0,cnt_ba): return_list.append(True)
else:
# identical in size
for pos in range(0,cnt_ab): return_list.append(False)
for pos in range(0,cnt_ba): return_list.append(True)
# return the return_list outcome
return return_list
