def test():
import chemconvert
G1 = chemconvert.hash2graph("CH@1,CH@1,CH@2,CH2,CH@2,O,OH,OH,OH,O,PO3-2~0110101000000100010000100000100000000000200000000010000")
G2 = chemconvert.hash2graph("CH@2,CH@1,CH@2,CH2,CH@1,O,OH,OH,OH,O,PO3-2~0110101000000100010000100000100000000000200000000010000")
G3 = chemconvert.hash2graph("CH@1,CH@2,CH@1,CH2,CH@2,O,OH,OH,OH,O,PO3-2~0110101000000100010000100000100000000000200000000010000")
print G1.hash()
print G2.hash()
print G3.hash()
def test():
import chemconvert
G1 = chemconvert.hash2graph(
"CH@1,CH@1,CH@2,CH2,CH@2,O,OH,OH,OH,O,PO3-2~0110101000000100010000100000100000000000200000000010000"
)
G2 = chemconvert.hash2graph(
"CH@2,CH@1,CH@2,CH2,CH@1,O,OH,OH,OH,O,PO3-2~0110101000000100010000100000100000000000200000000010000"
)
G3 = chemconvert.hash2graph(
"CH@1,CH@2,CH@1,CH2,CH@2,O,OH,OH,OH,O,PO3-2~0110101000000100010000100000100000000000200000000010000"
)
print G1.hash()
print G2.hash()
print G3.hash()
def generate_all_graphs(motif_hist, size):
"""Generates hash strings for all the likely connected graphs with 'size' nodes
"""
if (size <= 1):
raise Exception("size must be greater than 1 for using generate_all_graphs")
# start by adding all the existing graph of size atoms
hash_set = set(motif_hist[size])
# expand by seeding with all graphs of (size-1) atoms that appear in the database
# and adding another atom to them
graph_seeds = [chemconvert.hash2graph(h) for h in motif_hist[size-1]]
# connect the new atom by all possible bond configurations (all possible values for the new row in the matrix)
bonds_list = [[]]
for i in range(size-1):
bonds_list = [(l + [b]) for l in bonds_list for b in bond_types]
n = size-1 # the index for the new added atom
for G in graph_seeds: # for all motifs with size-1 atoms
G.add_node("")
for atom in atom_types: # add each of the atoms in atom_types
G.set_node(n, atom)
for bonds in bonds_list: # connect with all possible bond combinations
for m in range(n):
G.set_bond(n, m, bonds[m])
if (get_likelihood(G, motif_hist, size-1) > log_zero and G.is_connected() and G.is_legal_valence()): # check connectivity and valence
h = G.hash()
if (not h in hash_set):
hash_set.add(h)
return list(hash_set)
def generate_all_graphs(motif_hist, size):
"""Generates hash strings for all the likely connected graphs with 'size' nodes
"""
if (size <= 1):
raise Exception(
"size must be greater than 1 for using generate_all_graphs")
# start by adding all the existing graph of size atoms
hash_set = set(motif_hist[size])
# expand by seeding with all graphs of (size-1) atoms that appear in the database
# and adding another atom to them
graph_seeds = [chemconvert.hash2graph(h) for h in motif_hist[size - 1]]
# connect the new atom by all possible bond configurations (all possible values for the new row in the matrix)
bonds_list = [[]]
for i in range(size - 1):
bonds_list = [(l + [b]) for l in bonds_list for b in bond_types]
n = size - 1 # the index for the new added atom
for G in graph_seeds: # for all motifs with size-1 atoms
G.add_node("")
for atom in atom_types: # add each of the atoms in atom_types
G.set_node(n, atom)
for bonds in bonds_list: # connect with all possible bond combinations
for m in range(n):
G.set_bond(n, m, bonds[m])
if (get_likelihood(G, motif_hist, size - 1) > log_zero
and G.is_connected() and G.is_legal_valence()
): # check connectivity and valence
h = G.hash()
if (not h in hash_set):
hash_set.add(h)
return list(hash_set)
def read_hash():
try:
hash = input_stringvar.get()
graph = hash2graph(hash)
graph.initialize_pos()
error_stringvar.set("Ready.\nHASH = %s" % hash)
graph_list.append(graph)
except ChemException, strerror:
error_stringvar.set("ERROR :" + str(strerror))
root.update()
graph = None
def read_hash():
try:
hash = input_stringvar.get()
graph = hash2graph(hash)
graph.initialize_pos()
error_stringvar.set("Ready.\nHASH = %s" % hash)
graph_list.append(graph)
except ChemException, strerror:
error_stringvar.set("ERROR :" + str(strerror))
root.update()
graph = None
def convert_compounds_hash(compound_dat_filename):
compound2hash = util.parse_dat(compound_dat_filename, "UNIQUE-ID", "HASH")
util._mkdir("../mol")
for (key, smiles) in compound2hash.iteritems():
mol_filename = "../mol/" + key + ".mol"
if (not os.path.exists(mol_filename)):
print "Writing a MOL file to: " + mol_filename
if (len(smiles) > 0):
mol = chemconvert.hash2graph(smiles[0]).to_mol()
mol_file = open(mol_filename, "w")
mol_file.write(mol)
mol_file.close()
else:
print "Found the MOL file: " + mol_filename
return
def convert_compounds_hash(compound_dat_filename):
compound2hash = util.parse_dat(compound_dat_filename, "UNIQUE-ID", "HASH")
util._mkdir("../mol")
for (key, smiles) in compound2hash.iteritems():
mol_filename = "../mol/" + key + ".mol"
if (not os.path.exists(mol_filename)):
print "Writing a MOL file to: " + mol_filename
if (len(smiles) > 0):
mol = chemconvert.hash2graph(smiles[0]).to_mol()
mol_file = open(mol_filename, "w")
mol_file.write(mol)
mol_file.close()
else:
print "Found the MOL file: " + mol_filename
return
def __init__(self, carbon_only=True, ignore_chirality=True, use_antimotifs=True, reaction_database_fname="../rec/reaction_templates.dat"):
def deduce_reaction_list(dict):
G_subs = dict['G_SUBS']
G_prod = dict['G_PROD']
import_indices = dict['IMPORT']
export_indices = dict['EXPORT']
reaction_list = []
N = G_subs.get_num_nodes()
# add the new imported atoms to the graph
if (import_indices != []):
import_atoms = [G_subs.get_node(n) for n in import_indices]
reaction_list.append(Reaction("import", import_indices, None, import_atoms, external=True))
# add the bonds that the imported atoms come with 'built-in'
for n in import_indices:
for m in import_indices:
if (n > m and G_subs.get_bond(n, m) != 0):
reaction_list.append(Reaction("bond", [n, m], 0, G_subs.get_bond(n, m), external=True))
reaction_list.append(Reaction("update_position", import_indices, None, None, external=True))
# change the attributes of all the atoms in the graph from 'subs' to 'prod'
for n in range(N):
if (G_prod.chirality[n] != G_subs.chirality[n]):
reaction_list.append(Reaction("chirality", [n], G_subs.chirality[n], G_prod.chirality[n]))
if (G_prod.charges[n] != G_subs.charges[n]):
reaction_list.append(Reaction("charge", [n], G_subs.charges[n], G_prod.charges[n]))
if (G_prod.hydrogens[n] != G_subs.hydrogens[n]):
reaction_list.append(Reaction("hydrogen", [n], G_subs.hydrogens[n], G_prod.hydrogens[n]))
# change the values of all the bonds from 'subs' to 'prod'
for n in range(N):
for m in range(n):
if (G_prod.get_bond(n, m) != G_subs.get_bond(n, m)):
reaction_list.append(Reaction("bond", [n, m], G_subs.get_bond(n, m), G_prod.get_bond(n, m)))
# break all the bonds in the exported atoms
for n in export_indices:
for m in export_indices:
if (n > m and G_prod.get_bond(n, m) != 0):
reaction_list.append(Reaction("bond", [n, m], G_prod.get_bond(n, m), 0, external=True))
# remove the exported atoms from the graph
if (export_indices != []):
reaction_list.append(Reaction("export", export_indices, None, None, external=True))
return reaction_list
# read the template file and store the information in a dictionary
self.forward_reaction_list = []
self.backward_reaction_list = []
self.reaction_templates = {}
self.antimotif_counter = {}
self.ignore_chirality = ignore_chirality
self.use_antimotifs = use_antimotifs
self.carbon_only = carbon_only
print >> sys.stderr, "Parsing reaction database file: " + reaction_database_fname
file = open(reaction_database_fname, 'r')
while (True):
dict = util.read_next_dat_section(file)
if (dict == None):
break
elif ('SUBSTRATE' in dict and 'PRODUCT' in dict):
unique_id = dict['UNIQUE_ID']
#if (not unique_id in ['ec2.2.1a', 'ec2.2.1b']): # transketolase and transaldolase
# continue
# if the reaction is not tagged as "CARBON", and we are working only on carbon, skip.
if (self.carbon_only and dict.get('CARBON', 'FALSE') == 'FALSE'):
continue
# if the reaction has to do with chirality, and we choose to ignore it, skip.
if (self.ignore_chirality and dict.get('CHIRAL', 'FALSE') == 'TRUE'):
continue
forward_id = unique_id + "_forward"
backward_id = unique_id + "_backward"
try:
forward_dict = {}
forward_dict['EC'] = dict['EC']
forward_dict['REMARK'] = dict.get('REMARK', "")
forward_dict['NAME'] = dict['NAME']
forward_dict['DESCRIPTION'] = dict.get('DESCRIPTION', '')
forward_dict['DIRECTION'] = 'forward'
forward_dict['SUBSTRATE'] = dict['SUBSTRATE']
forward_dict['PRODUCT'] = dict['PRODUCT']
forward_dict['IMPORT'] = util.str2intvector(dict.get('IMPORTED_ATOMS', ''))
forward_dict['EXPORT'] = util.str2intvector(dict.get('EXPORTED_ATOMS', ''))
forward_dict['G_SUBS'] = hash2graph(dict['SUBSTRATE'])
forward_dict['G_PROD'] = hash2graph(dict['PRODUCT'])
forward_dict['REACTION'] = deduce_reaction_list(forward_dict)
forward_dict['UNIQUE_ID'] = forward_id
forward_dict['REVERSE_ID'] = backward_id
self.reaction_templates[forward_id] = forward_dict
except KeyError, msg:
raise ReactionException(str(msg) + " in " + forward_id)
try:
backward_dict = {}
backward_dict['EC'] = dict['EC']
backward_dict['REMARK'] = dict.get('REMARK', "")
backward_dict['NAME'] = dict.get('REV_NAME', dict['NAME'] + " [r]")
backward_dict['DESCRIPTION'] = dict.get('DESCRIPTION', '')
backward_dict['DIRECTION'] = 'backward'
backward_dict['SUBSTRATE'] = dict['PRODUCT']
backward_dict['PRODUCT'] = dict['SUBSTRATE']
backward_dict['IMPORT'] = util.str2intvector(dict.get('EXPORTED_ATOMS', ''))
backward_dict['EXPORT'] = util.str2intvector(dict.get('IMPORTED_ATOMS', ''))
backward_dict['G_SUBS'] = hash2graph(dict['PRODUCT'])
backward_dict['G_PROD'] = hash2graph(dict['SUBSTRATE'])
backward_dict['REACTION'] = deduce_reaction_list(backward_dict)
backward_dict['UNIQUE_ID'] = backward_id
backward_dict['REVERSE_ID'] = forward_id
self.reaction_templates[backward_id] = backward_dict
self.forward_reaction_list.append(forward_id)
self.backward_reaction_list.append(backward_id)
if (dict['REVERSIBLE'] == 'TRUE'):
self.forward_reaction_list.append(backward_id)
self.backward_reaction_list.append(forward_id)
except KeyError, msg:
raise ReactionException(msg + " in " + backward_id)
def __init__(
self,
carbon_only=True,
ignore_chirality=True,
use_antimotifs=True,
reaction_database_fname="../rec/reaction_templates.dat",
):
def deduce_reaction_list(dict):
G_subs = dict["G_SUBS"]
G_prod = dict["G_PROD"]
import_indices = dict["IMPORT"]
export_indices = dict["EXPORT"]
reaction_list = []
N = G_subs.get_num_nodes()
# add the new imported atoms to the graph
if import_indices != []:
import_atoms = [G_subs.get_node(n) for n in import_indices]
reaction_list.append(Reaction("import", import_indices, None, import_atoms, external=True))
# add the bonds that the imported atoms come with 'built-in'
for n in import_indices:
for m in import_indices:
if n > m and G_subs.get_bond(n, m) != 0:
reaction_list.append(Reaction("bond", [n, m], 0, G_subs.get_bond(n, m), external=True))
reaction_list.append(Reaction("update_position", import_indices, None, None, external=True))
# change the attributes of all the atoms in the graph from 'subs' to 'prod'
for n in range(N):
if G_prod.chirality[n] != G_subs.chirality[n]:
reaction_list.append(Reaction("chirality", [n], G_subs.chirality[n], G_prod.chirality[n]))
if G_prod.charges[n] != G_subs.charges[n]:
reaction_list.append(Reaction("charge", [n], G_subs.charges[n], G_prod.charges[n]))
if G_prod.hydrogens[n] != G_subs.hydrogens[n]:
reaction_list.append(Reaction("hydrogen", [n], G_subs.hydrogens[n], G_prod.hydrogens[n]))
# change the values of all the bonds from 'subs' to 'prod'
for n in range(N):
for m in range(n):
if G_prod.get_bond(n, m) != G_subs.get_bond(n, m):
reaction_list.append(Reaction("bond", [n, m], G_subs.get_bond(n, m), G_prod.get_bond(n, m)))
# break all the bonds in the exported atoms
for n in export_indices:
for m in export_indices:
if n > m and G_prod.get_bond(n, m) != 0:
reaction_list.append(Reaction("bond", [n, m], G_prod.get_bond(n, m), 0, external=True))
# remove the exported atoms from the graph
if export_indices != []:
reaction_list.append(Reaction("export", export_indices, None, None, external=True))
return reaction_list
# read the template file and store the information in a dictionary
self.forward_reaction_list = []
self.backward_reaction_list = []
self.reaction_templates = {}
self.antimotif_counter = {}
self.ignore_chirality = ignore_chirality
self.use_antimotifs = use_antimotifs
self.carbon_only = carbon_only
print >> sys.stderr, "Parsing reaction database file: " + reaction_database_fname
file = open(reaction_database_fname, "r")
while True:
dict = util.read_next_dat_section(file)
if dict == None:
break
elif "SUBSTRATE" in dict and "PRODUCT" in dict:
unique_id = dict["UNIQUE_ID"]
# if (not unique_id in ['ec2.2.1a', 'ec2.2.1b']): # transketolase and transaldolase
# continue
# if the reaction is not tagged as "CARBON", and we are working only on carbon, skip.
if self.carbon_only and dict.get("CARBON", "FALSE") == "FALSE":
continue
# if the reaction has to do with chirality, and we choose to ignore it, skip.
if self.ignore_chirality and dict.get("CHIRAL", "FALSE") == "TRUE":
continue
forward_id = unique_id + "_forward"
backward_id = unique_id + "_backward"
try:
forward_dict = {}
forward_dict["EC"] = dict["EC"]
forward_dict["REMARK"] = dict.get("REMARK", "")
forward_dict["NAME"] = dict["NAME"]
forward_dict["DESCRIPTION"] = dict.get("DESCRIPTION", "")
forward_dict["DIRECTION"] = "forward"
forward_dict["SUBSTRATE"] = dict["SUBSTRATE"]
forward_dict["PRODUCT"] = dict["PRODUCT"]
forward_dict["IMPORT"] = util.str2intvector(dict.get("IMPORTED_ATOMS", ""))
forward_dict["EXPORT"] = util.str2intvector(dict.get("EXPORTED_ATOMS", ""))
forward_dict["G_SUBS"] = hash2graph(dict["SUBSTRATE"])
forward_dict["G_PROD"] = hash2graph(dict["PRODUCT"])
forward_dict["REACTION"] = deduce_reaction_list(forward_dict)
forward_dict["UNIQUE_ID"] = forward_id
forward_dict["REVERSE_ID"] = backward_id
self.reaction_templates[forward_id] = forward_dict
except KeyError, msg:
raise ReactionException(str(msg) + " in " + forward_id)
try:
backward_dict = {}
backward_dict["EC"] = dict["EC"]
backward_dict["REMARK"] = dict.get("REMARK", "")
backward_dict["NAME"] = dict.get("REV_NAME", dict["NAME"] + " [r]")
backward_dict["DESCRIPTION"] = dict.get("DESCRIPTION", "")
backward_dict["DIRECTION"] = "backward"
backward_dict["SUBSTRATE"] = dict["PRODUCT"]
backward_dict["PRODUCT"] = dict["SUBSTRATE"]
backward_dict["IMPORT"] = util.str2intvector(dict.get("EXPORTED_ATOMS", ""))
backward_dict["EXPORT"] = util.str2intvector(dict.get("IMPORTED_ATOMS", ""))
backward_dict["G_SUBS"] = hash2graph(dict["PRODUCT"])
backward_dict["G_PROD"] = hash2graph(dict["SUBSTRATE"])
backward_dict["REACTION"] = deduce_reaction_list(backward_dict)
backward_dict["UNIQUE_ID"] = backward_id
backward_dict["REVERSE_ID"] = forward_id
self.reaction_templates[backward_id] = backward_dict
self.forward_reaction_list.append(forward_id)
self.backward_reaction_list.append(backward_id)
if dict["REVERSIBLE"] == "TRUE":
self.forward_reaction_list.append(backward_id)
self.backward_reaction_list.append(forward_id)
except KeyError, msg:
raise ReactionException(msg + " in " + backward_id)
#!/usr/bin/python
import sys
import os
import util
from chemconvert import hash2graph
from html_writer import HtmlWriter
from svg import Scene
html = HtmlWriter("../results/hash_list.html")
util._mkdir("../results/hash_list")
for line in util.parse_text_file(sys.argv[1]):
print line
graph = hash2graph(line)
graph.initialize_pos()
scene = graph.svg(Scene(200, 200, font_size=12))
html.write_svg(scene, "../results/hash_list/" + line)
html.display()
#!/usr/bin/python
import sys
import os
import util
from chemconvert import hash2graph
from html_writer import HtmlWriter
from svg import Scene
html = HtmlWriter("../results/hash_list.html")
util._mkdir("../results/hash_list")
for line in util.parse_text_file(sys.argv[1]):
print line
graph = hash2graph(line)
graph.initialize_pos()
scene = graph.svg(Scene(200, 200, font_size=12))
html.write_svg(scene, "../results/hash_list/" + line)
html.display()
def main():
init()
subdir = "motifs"
motif_fullpath = html_path + "/motifs"
util._mkdir(motif_fullpath)
main_html_file = open(html_path + "/motifs.html", "w")
anti_motif_list = []
for size in motif_sizes:
motifs = verify_file(size)
motifs_t = motifs_templates(motifs)
motif_hist = normalize_motifs(motifs)
motif_hist_t = normalize_motifs(motifs_t)
print "Generating all graphs of size %d ..." % size,
all_graphs = generate_all_graphs(motif_hist, size)
print "[DONE]"
results = {}
for h in all_graphs:
G = chemconvert.hash2graph(h)
template = G.template()
count = int(motifs.get(h, 0))
likelihoods = [0, 0]
for i in range(2, size+1):
likelihoods.append(get_likelihood(G, motif_hist, i))
delta_l = likelihoods[-2] - likelihoods[-1]
if (not results.has_key(template)):
results[template] = []
results[template].append((delta_l, likelihoods, count, h))
main_html_file.write("<p>")
size_html_file = util.embed_link(main_html_file, html_path, subdir + "/motifs%s" % size, "Motifs of size %s" % size)
main_html_file.write("</p>")
for (template, graph_list) in results.iteritems():
size_html_file.write("<p>")
template_svg = chemconvert.hash2svg(template, 200, 200, node_color=black, bond_color=grey)
template_svg.embed_in_html(size_html_file, motif_fullpath, template)
count_t = len(graph_list)
if (count_t > 0):
template_html_file = util.embed_link(size_html_file, motif_fullpath, template, "View all %d instances" % count_t)
for (delta_l, likelihoods, count, h) in sorted(graph_list):
if (likelihoods[-1] <= log_zero and likelihoods[-2] <= log_zero):
continue
elif (likelihoods[-1] <= log_zero):
bond_color = red
anti_motif_list.append(h)
else:
#bond_color = (0, 255 * math.exp(-delta_l), 255 * (1 - math.exp(-delta_l)))
bond_color = green
motif_svg = chemconvert.hash2svg(h, 150, 150, black, bond_color)
motif_svg.set_attribute("height", 200)
if (True): # add
#motif_svg.add(svg.Text((35, 25), h, 12, green))
l_string = ",".join(["%.1f" % l for l in likelihoods[2:]])
motif_svg.add(svg.Text((10, 160), "ΔL = %.1f" % delta_l, font_size=12))
motif_svg.add(svg.Text((10, 175), l_string, font_size=12))
if (count > 0):
#motif_svg.add(svg.Text((35, 75), "diff = %.1f" % (l1-l0), 12, black))
motif_svg.add(svg.Text((10, 190), "count = %d" % count, font_size=12))
motif_svg.embed_in_html(template_html_file, motif_fullpath, h)
else:
template_html_file.write("<p>")
motif_svg.embed_in_html(template_html_file, motif_fullpath, h)
template_html_file.write("<a href=\"" + h + ".svg\">" + h + "</a>")
template_html_file.write(", count = %d" % count)
for i in range(2, size+1):
template_html_file.write(", L(%d) = %.1f" % (i, likelihoods[i]))
template_html_file.write("</p>")
template_html_file.close()
else:
size_html_file.write("No instances")
size_html_file.write("</p>")
size_html_file.close()
main_html_file.close()
util.write_text_file(anti_motif_list, "../results/stat/anti_motifs.txt")
return
def main():
init()
subdir = "motifs"
motif_fullpath = html_path + "/motifs"
util._mkdir(motif_fullpath)
main_html_file = open(html_path + "/motifs.html", "w")
anti_motif_list = []
for size in motif_sizes:
motifs = verify_file(size)
motifs_t = motifs_templates(motifs)
motif_hist = normalize_motifs(motifs)
motif_hist_t = normalize_motifs(motifs_t)
print "Generating all graphs of size %d ..." % size,
all_graphs = generate_all_graphs(motif_hist, size)
print "[DONE]"
results = {}
for h in all_graphs:
G = chemconvert.hash2graph(h)
template = G.template()
count = int(motifs.get(h, 0))
likelihoods = [0, 0]
for i in range(2, size + 1):
likelihoods.append(get_likelihood(G, motif_hist, i))
delta_l = likelihoods[-2] - likelihoods[-1]
if (not results.has_key(template)):
results[template] = []
results[template].append((delta_l, likelihoods, count, h))
main_html_file.write("<p>")
size_html_file = util.embed_link(main_html_file, html_path,
subdir + "/motifs%s" % size,
"Motifs of size %s" % size)
main_html_file.write("</p>")
for (template, graph_list) in results.iteritems():
size_html_file.write("<p>")
template_svg = chemconvert.hash2svg(template,
200,
200,
node_color=black,
bond_color=grey)
template_svg.embed_in_html(size_html_file, motif_fullpath,
template)
count_t = len(graph_list)
if (count_t > 0):
template_html_file = util.embed_link(
size_html_file, motif_fullpath, template,
"View all %d instances" % count_t)
for (delta_l, likelihoods, count, h) in sorted(graph_list):
if (likelihoods[-1] <= log_zero
and likelihoods[-2] <= log_zero):
continue
elif (likelihoods[-1] <= log_zero):
bond_color = red
anti_motif_list.append(h)
else:
#bond_color = (0, 255 * math.exp(-delta_l), 255 * (1 - math.exp(-delta_l)))
bond_color = green
motif_svg = chemconvert.hash2svg(h, 150, 150, black,
bond_color)
motif_svg.set_attribute("height", 200)
if (True): # add
#motif_svg.add(svg.Text((35, 25), h, 12, green))
l_string = ",".join(
["%.1f" % l for l in likelihoods[2:]])
motif_svg.add(
svg.Text((10, 160),
"ΔL = %.1f" % delta_l,
font_size=12))
motif_svg.add(
svg.Text((10, 175), l_string, font_size=12))
if (count > 0):
#motif_svg.add(svg.Text((35, 75), "diff = %.1f" % (l1-l0), 12, black))
motif_svg.add(
svg.Text((10, 190),
"count = %d" % count,
font_size=12))
motif_svg.embed_in_html(template_html_file,
motif_fullpath, h)
else:
template_html_file.write("<p>")
motif_svg.embed_in_html(template_html_file,
motif_fullpath, h)
template_html_file.write("<a href=\"" + h + ".svg\">" +
h + "</a>")
template_html_file.write(", count = %d" % count)
for i in range(2, size + 1):
template_html_file.write(", L(%d) = %.1f" %
(i, likelihoods[i]))
template_html_file.write("</p>")
template_html_file.close()
else:
size_html_file.write("No instances")
size_html_file.write("</p>")
size_html_file.close()
main_html_file.close()
util.write_text_file(anti_motif_list, "../results/stat/anti_motifs.txt")
return
