def find_synthesis():
args = arg_parser.get_args()
makeit = MAKEIT(
args.TARGET, args.expansion_time, args.max_depth, args.max_branching,
args.max_trees, args.retro_mincount, args.retro_mincount_chiral,
args.synth_mincount, args.rank_threshold, args.prob_threshold,
args.max_contexts, args.template_count, args.max_ppg, args.output,
args.chiral, args.nproc, args.celery, args.context_recommender,
args.forward_scoring, args.tree_scoring, args.context_prioritization,
args.template_prioritization, args.precursor_prioritization,
args.parallel_tree, args.precursor_score_mode,
args.max_cum_template_prob, args.apply_fast_filter,
args.filter_threshold)
MyLogger.initialize_logFile(makeit.output_dir_root, makeit.case_dir)
tree_status, trees = makeit.construct_buyable_trees()
MyLogger.print_and_log(
'MAKEIT generated {} buyable tree(s) that meet(s) all constraints.'.
format(len(trees)), makeit_loc)
feasible_trees = makeit.evaluate_synthesis_trees(trees)
MyLogger.print_and_log(
'MAKEIT found {} tree(s) that are(is) likely to result in a successful synthesis.'
.format(len(feasible_trees)), makeit_loc)
def writefunc(string):
return MyLogger.print_and_log(string, makeit_loc)
for i, feasible_tree in enumerate(
sorted(feasible_trees, key=lambda x: x['score'], reverse=True)):
MyLogger.print_and_log('', makeit_loc)
MyLogger.print_and_log(
'Feasible tree {}, plausible = {}, overall score = {}'.format(
i + 1, feasible_tree['plausible'], feasible_tree['score']),
makeit_loc)
print_at_depth(feasible_tree['tree'], writefunc=writefunc)
with open(
os.path.join(makeit.output_dir_root,
'{}_trees.html'.format(makeit.case_dir)), 'w') as fid:
def writefunc(string):
return fid.write('{}<br>\n'.format(string))
fid.write('<html><title>Results for {}</title>\n'.format(args.TARGET))
fid.write('<body>\n')
fid.write('<h1>{}</h1><br>\n'.format(args.TARGET))
fid.write('<i><b>Settings: </b>{}</i><br>\n'.format(args.__dict__))
for i, feasible_tree in enumerate(
sorted(feasible_trees, key=lambda x: x['score'],
reverse=True)):
writefunc(
'<h3>Feasible tree {}, plausible = {}, overall score = {}</h3><br>'
.format(i + 1, feasible_tree['plausible'],
feasible_tree['score']))
print_at_depth(feasible_tree['tree'],
writefunc=writefunc,
delim=' ',
img=True)
fid.write('</body>\n')
if stop_if in product.smiles_list:
print(
'Found true product - skipping remaining templates to apply'
)
return True
else:
results.append(product)
# Were we trying to stop early?
if stop_if:
return False
return results
if __name__ == '__main__':
MyLogger.initialize_logFile()
ft = ForwardTransformer(mincount=10)
ft.load()
template_count = ft.template_count()
smiles = 'NC(=O)[C@H](CCC=O)N1C(=O)c2ccccc2C1=O'
for batch_size in range(100, 1000, 100):
print()
print(batch_size)
outcomes = []
i = 0
for start_at in range(0, template_count, batch_size):
i += 1
outcomes.append(
ft.get_outcomes(smiles,
100,
