elif words[0] == "r":
RANDOM_TYPE = int(words[1])
elif words[0] == "ls":
TIME_FOR_SEARCH = float(words[1])
elif words[0] == "d":
MIN_TRANSFER_DIST = int(words[1])
elif words[0] == "rd":
RANDOM = int(words[1])
elif words[0] == "ts":
THRESHOLD_CONSTRAINTS = float(words[1])
else:
print
"unused parameter (bad format):", p
name_constraint_file = parameters[1]
tree = script_tree.readTree(open(parameters[0], "r").readline())
constraints = open(name_constraint_file, "r").readlines()
root = script_tree.getRoot(tree)
print
name_constraint_file
def maximum_spearman(n):
if n % 2 == 0:
m = n / 2
return 2 * m * m
else:
m = (n - 1) / 2
return 2 * m * m + 2 * m
mots = fichier_ensembl[l].split()
species = mots[1].split("_")[0].title() + "_" + mots[1].split(
"_")[1]
genes[mots[2]] = [
species, mots[3],
int(mots[4]),
int(mots[5]), mots[6]
]
l = l + 1
adjacence_file = open(analysisDir + "/deco_adjacences_" + name, "w")
gene_file = open(analysisDir + "/deco_genes_" + name, "w")
restricted_genes = []
for line in tree_file:
tree = script_tree.readTree(line)
leaves = script_tree.getLeavesNames(tree)
for l in leaves:
restricted_genes.append(l)
print len(tree_file), len(restricted_genes)
#print restricted_genes
def compare(x, y):
#print x,y
if genes[x][0] != genes[y][0]:
return cmp(genes[x][0], genes[y][0])
elif genes[x][1] != genes[y][1]:
return cmp(genes[x][1], genes[y][1])
import sys, script_tree, random, time, math, string
MINIMUM_SUPPORT_WITHIN_A_FAMILY = 0.05
MINIMUM_FAMILY_SIZE = 5
#MAXIMUM_DIFFERENCE_WITH_PROFILE = 6000
OUTPUT_FILE_REC = "constraints_from_recs"
OUTPUT_FILE_TRF = "constraints_from_transfers"
parameters = sys.argv[1:]
species_tree = script_tree.readTree(open(parameters[0], "r").readline())
extant_species = script_tree.getLeavesNames(species_tree)
gene_tree_file = parameters[1]
gene_trees = []
for gt in open(gene_tree_file, "r").readlines():
gene_trees.append(gt.strip())
nodes = script_tree.getNodes(species_tree)
for n in nodes:
script_tree.setLength(species_tree, n, 1.0)
def distance_from(x, y):
nodes = script_tree.getNodes(species_tree)
for n in nodes:
if script_tree.isLeaf(species_tree, n):
name = script_tree.getName(species_tree, n)
else:
name = script_tree.getBootstrap(species_tree, n)
if name == x:
A = n
if name == y:
import sys,script_tree,random,time,math,string
MINIMUM_SUPPORT_WITHIN_A_FAMILY = 0.05
MINIMUM_FAMILY_SIZE = 5
#MAXIMUM_DIFFERENCE_WITH_PROFILE = 6000
OUTPUT_FILE_REC = "constraints_from_recs"
OUTPUT_FILE_TRF = "constraints_from_transfers"
parameters = sys.argv[1:]
species_tree = script_tree.readTree(open(parameters[0],"r").readline())
extant_species = script_tree.getLeavesNames(species_tree)
gene_tree_file = parameters[1]
gene_trees = []
for gt in open(gene_tree_file,"r").readlines():
gene_trees.append(gt.strip())
nodes = script_tree.getNodes(species_tree)
for n in nodes:
script_tree.setLength(species_tree,n,1.0)
def distance_from(x,y):
nodes = script_tree.getNodes(species_tree)
for n in nodes:
if script_tree.isLeaf(species_tree,n):
name = script_tree.getName(species_tree,n)
else:
name = script_tree.getBootstrap(species_tree,n)
if name == x:
A = n
genes = {}
l = 0
while l < len(fichier_ensembl):
if fichier_ensembl[l][:3] == "SEQ":
mots = fichier_ensembl[l].split()
species = mots[1].split("_")[0].title()+"_"+mots[1].split("_")[1]
genes[mots[2]] = [species,mots[3],int(mots[4]),int(mots[5]),mots[6]]
l = l + 1
adjacence_file = open(analysisDir+"/deco_adjacences_"+name,"w")
gene_file = open(analysisDir+"/deco_genes_"+name,"w")
restricted_genes = []
for line in tree_file:
tree = script_tree.readTree(line)
leaves = script_tree.getLeavesNames(tree)
for l in leaves:
restricted_genes.append(l)
print len(tree_file),len(restricted_genes)
#print restricted_genes
def compare(x,y):
#print x,y
if genes[x][0] != genes[y][0]:
return cmp(genes[x][0],genes[y][0])
elif genes[x][1] != genes[y][1]:
return cmp(genes[x][1],genes[y][1])
else:
return cmp(genes[x][2],genes[y][2])
nodes = script_tree.getNodes(tree)
root = script_tree.getRoot(tree)
for n in nodes:
if not script_tree.isLeaf(tree, n):
order.append(n)
# print order
order.sort(lambda x, y: cmp(script_tree.distanceFrom(tree, x, root),
script_tree.distanceFrom(tree, y, root)))
for i in range(len(order)):
order[i] = script_tree.getBootstrap(tree, order[i])
return order
with open((parameters[0])) as f1:
for line_number, mt in enumerate(f1):
tree = script_tree.readTree(mt.strip())
root = script_tree.getRoot(tree)
# useful variables
nodes = script_tree.getNodes(tree)
leaves = script_tree.getLeavesNames(tree)
root = script_tree.getRoot(tree)
internal_nodes = []
order_tree = order_from_tree(tree)
with open(parameters[1]) as f2:
all_orders = f2.readlines()
morders = random.sample(all_orders, 100)
for morder in morders:
order_input = morder.strip().split(",")
while len(pile) > 0 and (not (b in marques)):
sommet = pile[-1]
del pile[-1]
voisins = g[sommet]
for v in voisins:
if not v in marques:
marques.append(v)
pile.append(v)
if b in marques:
return True
else:
return False
tree = script_tree.readTree(open(parameters[0],"r").readline())
constraints = open(parameters[1],"r").readlines()
root = script_tree.getRoot(tree)
def value(order):
index = {}
for i in range(len(order)):
index[order[i]] = i
result = 0
for e in edge_keys:
sommets = e.split(",")
if index.has_key(sommets[0]) and index.has_key(sommets[1]) and index[sommets[0]] > index[sommets[1]]:
result = result + edge[e]
return result
def optimisation_locale(order,duration):