def entry_point():
parser = build_args_parser(
prog='stats',
description='Statistics on SBML file(s)',
m_add_args=add_arguments
)
args = parser.parse_args()
from rptools.__main__ import init
logger = init(parser, args)
# Build the list of pathways to rank
pathways = [
rpPathway.from_rpSBML(
infile=pathway_filename,
logger=logger
) for pathway_filename in args.pathways
]
# Rank pathways
stats = counts(pathways)
print_stats(
pathways=pathways,
reactions=stats['reactions'],
species=stats['species'],
)
def entry_point():
parser = build_args_parser(
prog='rpscore',
description=
'Calculate global score by combining all scores (rules, FBA, Thermo)',
m_add_args=add_arguments)
args = parser.parse_args()
from rptools.__main__ import init
logger = init(parser, args)
# if len(args.pathways) == 1:
# if args.outfile is None or args.outfile == '':
# logger.error('Option --outfile has to be set in case of single input pathway, exiting...')
# exit(1)
# pathways = []
# for pathway in args.pathways:
# pathways.append(
# rpPathway.from_rpSBML(
# infile=pathway,
# logger=logger
# )
# )
pathway = rpPathway.from_rpSBML(infile=args.infile, logger=logger)
score = predict_score(
pathway=pathway,
# data_train_file=args.data_train_file,
# models_path=models_path,
no_of_rxns_thres=args.no_of_rxns_thres)
# if len(pathways) > 1:
# if not os_path.exists(args.outdir):
# makedirs(args.outdir)
# for i in range(len(pathways)):
# # Write results into the pathway
# pathways[i].set_global_score(
# scores[i]
# )
# # Write pathway into file
# pathways[i].to_rpSBML().write_to_file(
# os_path.join(
# args.outdir,
# os_path.basename(args.pathways[i])
# )
# )
# else:
# Write results into the pathway
pathway.set_global_score(score)
# Write pathway into file
pathway.to_rpSBML().write_to_file(args.outfile)
def entry_point():
def _make_dir(filename):
dirname = os_path.dirname(filename)
if dirname != '' and not os_path.exists(dirname):
try:
os_makedirs(dirname)
except OSError as exc: # Guard against race condition
if exc.errno != errno_EEXIST:
raise
# Args.
parser = build_args_parser(prog='rpfba',
description='Process to Flux Balance Analysis',
m_add_args=add_arguments)
args = parser.parse_args()
from rptools.__main__ import init
logger = init(parser, args)
pathway = rpPathway.from_rpSBML(infile=args.pathway_file, logger=logger)
# Load compounds.
df_medium_base, df_medium_user = load_compounds(medium_id=args.medium_id,
file_base=__MEDIUM_PATH,
file_user=args.medium_file,
logger=logger)
results = runFBA(pathway=pathway,
gem_sbml_path=args.model_file,
compartment_id=args.compartment_id,
biomass_rxn_id=args.biomass_rxn_id,
objective_rxn_id=args.objective_rxn_id,
sim_type=args.sim,
fraction_coeff=args.fraction_of,
merge=args.merge,
ignore_orphan_species=args.ignore_orphan_species,
medium_compartment_id=args.medium_compartment_id,
df_medium_base=df_medium_base,
df_medium_user=df_medium_user,
logger=logger)
if results is None:
logger.info('No results written. Exiting...')
else:
logger.info('Writing into file...')
_make_dir(args.outfile)
pathway.to_rpSBML().write_to_file(args.outfile)
logger.info(' |--> written in ' + args.outfile)
if args.minimal_medium_file:
minimal_medium = results.get('minimal_medium', pd.DataFrame())
_make_dir(args.minimal_medium_file)
minimal_medium.to_csv(args.minimal_medium_file)
logger.info(' |--> written in ' + args.minimal_medium_file)
def _cli():
parser = build_args_parser(
prog='rpcompletion',
description=
'Parse RP2 pathways to generate rpSBML collection of unique and complete (cofactors) pathways',
m_add_args=add_arguments)
args = parser.parse_args()
from rptools.__main__ import init
logger = init(parser, args)
check_args(args.max_subpaths_filter, args.outdir, logger)
cache = rrCache(attrs=[
'rr_reactions',
'template_reactions',
'cid_strc',
'deprecatedCompID_compid',
])
pathways = rp_completion(rp2_metnet=args.rp2_metnet,
sink=args.sink,
rp2paths_compounds=args.rp2paths_compounds,
rp2paths_pathways=args.rp2paths_pathways,
cache=cache,
upper_flux_bound=int(args.upper_flux_bound),
lower_flux_bound=int(args.lower_flux_bound),
max_subpaths_filter=args.max_subpaths_filter,
logger=logger)
# WRITE OUT
if not os_path.exists(args.outdir):
os_mkdir(args.outdir)
# Write out selected pathways
for pathway in pathways:
pathway.to_rpSBML().write_to_file(
os_path.join(args.outdir, 'rp_' + pathway.get_id()) + '.xml')
# for pathway_id, sub_pathways in pathways.items():
# for sub_pathway in sub_pathways[-args.max_subpaths_filter:]:
# sub_pathway.to_rpSBML().write_to_file(
# os_path.join(
# args.outdir,
# 'rp_'+sub_pathway.get_id()
# ) + '.xml'
# )
StreamHandler.terminator = ""
logger.info('{color}{typo}Results are stored in {rst}'.format(
color=fg('white'), typo=attr('bold'), rst=attr('reset')))
StreamHandler.terminator = "\n"
logger.info('{color}{outdir}\n'.format(color=fg('grey_70'),
outdir=args.outdir))
def _cli():
parser = build_args_parser(
prog = 'rpthermo',
description = 'Calculate score by processing thermodynamics',
m_add_args = add_arguments
)
args = parser.parse_args()
from rptools.__main__ import init
logger = init(parser, args)
msg = f'Parameters\n----------\n'
for param in ['pH', 'ionic_strength', 'pMg']:
value = getattr(args, param)
msg += f'- {param}: {value}\n'
logger.info(
'{color}{msg}{rst}'.format(
color=fg('light_cyan'),
msg=msg,
rst=attr('reset')
)
)
## READ PATHWAY FROM FILE
pathway = rpPathway.from_rpSBML(
infile=args.infile,
logger=logger
)
# RUN THERMO
results = runThermo(
pathway=pathway,
ph=args.pH,
ionic_strength=args.ionic_strength,
pMg=args.pMg,
logger=logger
)
# Print results
print_results(pathway, results, logger)
# Write pathway into file
pathway.to_rpSBML().write_to_file(args.outfile)
logger.info(
"{color}{typo}Written into file: {file}{rst}".format(
color=fg('white'),
typo=attr('bold'),
rst=attr('reset'),
file=args.outfile
)
)
def _cli():
parser = build_args_parser(
prog = 'rpextractsink',
description = 'Generate the sink from a model SBML by specifying the compartment',
m_add_args = add_arguments
)
args = parser.parse_args()
from rptools.__main__ import init
logger = init(parser, args)
cache = rrCache(['cid_strc'], logger=logger)
genSink(cache,
args.input_sbml,
args.output_sink,
args.remove_dead_end,
args.compartment_id,
logger=logger)
def entry_point():
parser = build_args_parser(
prog='rpreport',
description=
'generates HTML pages to explore the main characteristics (thermodynamics, fluxes, number of '
'metabolic steps, reaction rule score) of pathways predicted with RetroPath suite',
m_add_args=add_arguments)
args = parser.parse_args()
from rptools.__main__ import init
logger = init(parser, args)
run_report(
input_dir=args.input_dir,
source_path=args.source_path,
output_folder=args.output_folder,
dev=args.dev,
verbose=args.verbose,
standalone=args.standalone,
)
def entry_point():
parser = build_args_parser(prog='rprank',
description='Rank pathways',
m_add_args=add_arguments)
args = parser.parse_args()
from rptools.__main__ import init
logger = init(parser, args)
# Build the list of pathways to rank
pathways = [
rpPathway.from_rpSBML(infile=pathway_filename, logger=logger)
for pathway_filename in args.pathways
]
# Rank pathways
sorted_pathways = rank(pathways)
sorted_pathways_str = '\n'.join(
args.delimiter.join(item) for item in sorted_pathways.items())
print(f'#Name{args.delimiter}Score')
print(sorted_pathways_str)