def parseCTDCommandLine(argv, model, openms_param):
# Configure CTDOpt to use OpenMS style on the command line.
directives = parse_cl_directives(argv,
input_ctd='ini',
write_tool_ctd='write_ini',
prefix='-')
if directives[
"write_tool_ctd"] is not None: # triggered if -write_ini was provided on CML
# if called with -write_ini write CTD
model.write_ctd(directives["write_tool_ctd"])
exit(0)
elif directives["input_ctd"] is not None: # read ctd/ini file
model = CTDModel(from_file=directives["input_ctd"])
# print(model.get_defaults())
param = pms.Param()
fh = pms.ParamXMLFile()
fh.load(directives["input_ctd"], param)
openms_param.update(param, True)
return model.get_defaults(), openms_param
else: # only command line options provided
temp = tempfile.NamedTemporaryFile(
suffix='ini') # makes sure we get a writable file
tmp_name = temp.name
temp.close() # removes the file
model.write_ctd(tmp_name)
param = pms.Param()
fh = pms.ParamXMLFile()
fh.load(tmp_name, param)
openms_param.update(param)
os.remove(tmp_name)
return model.parse_cl_args(argv), openms_param
# Let's print out the name attributes of these parameters.
print('The following parameters were registered in the model:')
print([p.name for p in params])
print()
# In the above model, certain parameters were registered under parameter groups. We can access their 'lineage' and see
# their nesting levels. Let's display nesting levels separated by colons:
print('The same parameters with subgroup information, if they were registered under parameter groups:')
print([':'.join(p.get_lineage(name_only=True)) for p in params])
print()
# (Parameter.get_lineage() returns a list of ParameterGroups down to the leaf Parameter. `name_only` setting returns
# only the names of the objects, instead of the actual Parameter objects.
# Some of the parameters had default values in the model. We can get those:
print('A dictionary of parameters with default values, returned by CTDModel.get_defaults():')
defaults = model_2.get_defaults()
pretty_print(defaults)
print()
print ('As you can see, parameter values are usually stored in nested dictionaries. If you want a flat dictionary, you can'
'get that using CTDopts.flatten_dict(). Flat keys can be either tuples of tree node (subgroup) names down to the parameter...')
flat_defaults = flatten_dict(defaults)
pretty_print(flat_defaults)
print()
print('...or they can be strings where nesing levels are separated by colons:')
flat_defaults_colon = flatten_dict(defaults, as_string=True)
pretty_print(flat_defaults_colon)
print()
print ('We can create dictionaries of arguments on our own that we want to validate against the model.'
except ModelTypeError:
pass
try:
ini_model = Parameters(from_file=args.ini_file)
except ModelTypeError:
pass
assert ini_model is not None, "Could not parse %s, seems to be no CTD/PARAMS" % (
args.ini_file)
# get a dictionary of the ctd arguments where the values of the parameters
# given on the command line are overwritten
ini_values = ini_model.parse_cl_args(cl_args=cliargs, ignore_required=True)
if args.ctd_file:
ctd_model = CTDModel(from_file=args.ctd_file)
ctd_values = ctd_model.get_defaults()
for param in ini_model.get_parameters():
if not param.required and (param.default is None
or type(param.default) is _Null):
lineage = param.get_lineage(name_only=True)
try:
default = getFromDict(ctd_values, lineage)
except KeyError:
continue
setInDict(ini_values, lineage, default)
# write the ctd with the values taken from the dictionary
out = StringIO()
ctd_tree = ini_model.write_ctd(out, ini_values)
print(out.getvalue())
# In the above model, certain parameters were registered under parameter groups. We can access their 'lineage' and see
# their nesting levels. Let's display nesting levels separated by colons:
print(
'The same parameters with subgroup information, if they were registered under parameter groups:'
)
print([':'.join(p.get_lineage(name_only=True)) for p in params])
print()
# (Parameter.get_lineage() returns a list of ParameterGroups down to the leaf Parameter. `name_only` setting returns
# only the names of the objects, instead of the actual Parameter objects.
# Some of the parameters had default values in the model. We can get those:
print(
'A dictionary of parameters with default values, returned by CTDModel.get_defaults():'
)
defaults = model_2.get_defaults()
pretty_print(defaults)
print()
print(
'As you can see, parameter values are usually stored in nested dictionaries. If you want a flat dictionary, you can'
'get that using CTDopts.flatten_dict(). Flat keys can be either tuples of tree node (subgroup) names down to the parameter...'
)
flat_defaults = flatten_dict(defaults)
pretty_print(flat_defaults)
print()
print('...or they can be strings where nesing levels are separated by colons:')
flat_defaults_colon = flatten_dict(defaults, as_string=True)
pretty_print(flat_defaults_colon)
print()