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#!/usr/bin/python3
# encoding: utf-8
from __future__ import (absolute_import, division,
print_function, unicode_literals)
import os, sys, re
import logging
import TGraph
import TNode
import Node_alignment
import Compact_graph_whole
from Topological_sort import Topological_sort
import TGLOBALS
logger = logging.getLogger(__name__)
class Compact_graph_partial(Compact_graph_whole.Compact_graph_whole):
def __init__(self):
pass
def compact_graph(self, tgraph):
compacted_flag = True
round = 0
while compacted_flag:
round += 1
logger.debug("\n\t### Partial graph compaction, Round: {}".format(round))
tgraph.clear_touch_settings() # start fresh
compacted_flag = False # reset for this round
sorted_nodes = Topological_sort.topologically_sort(tgraph.get_all_nodes())
if TGLOBALS.DEBUG:
dot_filename = "ladeda.BEGIN.compacted_partial.round_{}.dot".format(round)
tgraph.draw_graph(dot_filename)
logger.debug("-wrote dot: {}".format(dot_filename))
for node in sorted_nodes:
if node.get_touched_val() > 0:
continue
logger.debug("\n\n/////////// R[{}] Exploring compaction from node: {}\n\n".format(round, node.toString()))
# try compact upward
prev_nodes = node.get_prev_nodes()
if len(prev_nodes) > 1 and self.untouched(prev_nodes) and self.all_have_lower_topological_orderings(node, prev_nodes):
if self.compact_upward(prev_nodes):
compacted_flag = True
next_nodes = node.get_next_nodes()
if len(next_nodes) > 1 and self.untouched(next_nodes) and self.all_have_higher_topological_orderings(node, next_nodes):
if self.compact_downward(next_nodes):
compacted_flag = True
if compacted_flag:
if TGLOBALS.DEBUG:
dot_filename = "ladeda.END.compacted_partial.round_{}.dot".format(round)
tgraph.draw_graph(dot_filename)
logger.debug("-wrote dot: {}".format(dot_filename))
self.compact_unbranched(tgraph)
####################
## Upward Compaction
def compact_upward(self, prev_nodes):
logger.debug("compact_upward: Partial {}".format(prev_nodes))
prev_nodes = list(prev_nodes)
for i in range(0, len(prev_nodes)-1):
for j in range(i+1, len(prev_nodes)):
if self.compact_upward_node_pair(prev_nodes[i], prev_nodes[j]):
return True
return False
def compact_upward_node_pair(self, node_A, node_B):
logger.debug("compact_upward_node_pair:\nnode_A: {}\nnode_B: {}".format(node_A.toString(), node_B.toString()))
# ensure they're on parallel paths in the graph.
if (node_A.is_ancestral(node_B) or node_B.is_ancestral(node_A)):
logger.debug("-not parallel paths. excluding compaction of {} and {}".format(node_A, node_B))
return False
# switch A,B so A is the shorter sequence node
if len(node_B.get_seq()) < len(node_A.get_seq()):
(node_A, node_B) = (node_B, node_A)
seqA = node_A.get_seq()
seqB = node_B.get_seq()
shorter_len = len(seqA)
# reverse the strings and check number of mismatches
seqA_rev = seqA[::-1]
seqB_rev = seqB[::-1]
num_matches = 0
for i in range(0, shorter_len):
if seqA_rev[i] == seqB_rev[i]:
num_matches += 1
else:
break
if num_matches == 0:
logger.debug("no matching suffix between {} and {}".format(node_A, node_B))
return False
# go ahead and merge the two in their region of common overlap
tgraph = node_A.get_graph()
shared_seq = seqA[-1*num_matches:]
uniqA_seq = seqA[0:(len(seqA)-num_matches)]
uniqB_seq = seqB[0:(len(seqB)-num_matches)]
logger.debug("Suffices:\nseqA:{}\nSeqB:{}\nShared:{}".format(seqA, seqB, shared_seq))
assert len(seqA) == len(shared_seq) + len(uniqA_seq)
assert len(seqB) == len(shared_seq) + len(uniqB_seq)
##### operations needed:
#
# A A
# \ \
# X --> C --X
# / /
# B B
#
# - create C and set to partial shared sequence
# - add B and A transcripts to C
# - A and B link to C only
# - C recapitulates all outgoing edges from A and B
logger.debug("node_A before mods: {}".format(node_A.toString()))
logger.debug("node_B before mods: {}".format(node_B.toString()))
combined_transcripts = node_A.get_transcripts().union(node_B.get_transcripts())
combined_loc_id = "Upart:" + node_A.get_loc_id() + "," + node_B.get_loc_id()
node_C = tgraph.get_node(combined_transcripts, combined_loc_id, shared_seq)
node_A.set_seq(uniqA_seq)
node_B.set_seq(uniqB_seq)
# reset next nodes from A,B to C
all_next_nodes = node_A.get_next_nodes().union(node_B.get_next_nodes())
tgraph.prune_edges([node_A], node_A.get_next_nodes())
tgraph.prune_edges([node_B], node_B.get_next_nodes())
tgraph.add_edges([node_C], all_next_nodes)
node_C.touch()
if len(uniqA_seq) == 0:
# no longer need this now
tgraph.add_edges(node_A.get_prev_nodes(), [node_C])
tgraph.prune_node(node_A)
else:
tgraph.add_edges([node_A], [node_C])
node_A.touch()
if len(uniqB_seq) == 0:
# no longer need it
tgraph.add_edges(node_B.get_prev_nodes(), [node_C])
tgraph.prune_node(node_B)
else:
tgraph.add_edges([node_B], [node_C])
node_B.touch()
logger.debug("node_A after mods: {}".format(node_A.toString()))
logger.debug("node_B after mods: {}".format(node_B.toString()))
logger.debug("node_C after mods: {}".format(node_C.toString()))
logger.debug("\n\n\t*** partially UP-compacted nodes: {} and {} + {} ***".format(node_A, node_B, node_C))
return True
######################
## Downward compaction
def compact_downward(self, next_nodes):
logger.debug("compact_downward: Partial {}".format(next_nodes))
next_nodes = list(next_nodes)
for i in range(0, len(next_nodes)-1):
for j in range(i+1, len(next_nodes)):
if self.compact_downward_node_pair(next_nodes[i], next_nodes[j]):
return True
return False
def compact_downward_node_pair(self, node_A, node_B):
logger.debug("compact_downward_node_pair:\nnode_A: {}\nnode_B: {}".format(node_A.toString(), node_B.toString()))
# ensure they're on parallel paths in the graph.
if (node_A.is_descendant(node_B) or node_B.is_descendant(node_A)):
logger.debug("-not parallel paths. excluding compaction of {} and {}".format(node_A, node_B))
return False
# switch A,B so A is the shorter sequence node
if len(node_B.get_seq()) < len(node_A.get_seq()):
(node_A, node_B) = (node_B, node_A)
seqA = node_A.get_seq()
seqB = node_B.get_seq()
shorter_len = len(seqA)
num_matches = 0
for i in range(0, shorter_len):
if seqA[i] == seqB[i]:
num_matches += 1
else:
break
if num_matches == 0:
logger.debug("-no matching prefix match between {} and {}".format(node_A, node_B))
return False
# go ahead and merge the two in their region of common overlap
tgraph = node_A.get_graph()
shared_seq = seqA[0:num_matches]
uniqA_seq = seqA[num_matches:]
uniqB_seq = seqB[num_matches:]
logger.debug("Prefixes:\nseqA:{}\nSeqB:{}\nShared:{}".format(seqA, seqB, shared_seq))
##### operations needed:
#
# A A
# / /
# -- X --> -- X -- C
# \ \
# B B
#
# - find shared prefix of A,B
# - create C for shared prefix, shorten A,B
# - link A,B down from C
# - C takes on all prev nodes from A,B
logger.debug("node_A before mods: {}".format(node_A.toString()))
logger.debug("node_B before mods: {}".format(node_B.toString()))
combined_transcripts = node_A.get_transcripts().union(node_B.get_transcripts())
combined_loc_id = "Dpart:" + node_A.get_loc_id() + "," + node_B.get_loc_id()
node_C = tgraph.get_node(combined_transcripts, combined_loc_id, shared_seq)
node_A.set_seq(uniqA_seq)
node_B.set_seq(uniqB_seq)
# reset prev nodes from A,B to C
all_prev_nodes = node_A.get_prev_nodes().union(node_B.get_prev_nodes())
tgraph.prune_edges(node_A.get_prev_nodes(), [node_A])
tgraph.prune_edges(node_B.get_prev_nodes(), [node_B])
tgraph.add_edges(all_prev_nodes, [node_C])
node_C.touch()
if len(uniqA_seq) == 0:
# no longer need this now
tgraph.add_edges([node_C], node_A.get_next_nodes())
tgraph.prune_node(node_A)
else:
tgraph.add_edges([node_C], [node_A])
node_A.touch()
if len(uniqB_seq) == 0:
# no longer need it
tgraph.add_edges([node_C], node_B.get_next_nodes())
tgraph.prune_node(node_B)
else:
tgraph.add_edges([node_C], [node_B])
node_B.touch()
logger.debug("node_A after mods: {}".format(node_A.toString()))
logger.debug("node_B after mods: {}".format(node_B.toString()))
logger.debug("node_C after mods: {}".format(node_C.toString()))
logger.debug("\n\n\t*** partially compacted nodes: {} and {} + {} ***".format(node_A, node_B, node_C))
return True
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