def test_prior_inherit_differentgiven():
test_info = deepcopy(test_info_common)
test_info["prior"] = {"third": "lambda a1: 1"}
updated_info, _ = run(test_info)
likname = list(test_info_common["likelihood"])[0]
default_info = get_default_info(likname, "likelihood")
default_info["prior"].update(test_info["prior"])
assert updated_info["prior"] == default_info["prior"]
def test_prior_inherit_samegiven():
test_info = deepcopy(test_info_common)
likname = list(test_info_common["likelihood"])[0]
default_info = get_default_info(likname, "likelihood")
name, prior = deepcopy(default_info["prior"]).popitem()
test_info["prior"] = {name: prior}
updated_info, _ = run(test_info)
assert updated_info["prior"] == default_info["prior"]
def test_prior_inherit_differentgiven():
test_info = deepcopy(test_info_common)
test_info[_prior] = {"third": "lambda a1: 1"}
updated_info, products = run(test_info)
likname = list(test_info_common[_likelihood].keys())[0]
default_info = get_default_info(likname, _likelihood)
default_info[_prior].update(test_info[_prior])
assert updated_info[_prior] == default_info[_prior]
def test_prior_inherit_samegiven_differentdefinition():
test_info = deepcopy(test_info_common)
likname = list(test_info_common[_likelihood].keys())[0]
default_info = get_default_info(likname, _likelihood)
name, prior = deepcopy(default_info[_prior]).popitem()
test_info[_prior] = {name: "this is not a prior"}
with pytest.raises(HandledException):
updated_info, products = run(test_info)
def test_prior_inherit_samegiven():
test_info = deepcopy(test_info_common)
likname = list(test_info_common[_likelihood].keys())[0]
default_info = get_default_info(likname, _likelihood)
name, prior = deepcopy(default_info[_prior]).popitem()
test_info[_prior] = {name: prior}
updated_info, products = run(test_info)
assert updated_info[_prior] == default_info[_prior]
def test_prior_inherit_samegiven_differentdefinition():
test_info = deepcopy(test_info_common)
likname = list(test_info_common[kinds.likelihood])[0]
default_info = get_default_info(likname, kinds.likelihood)
name, prior = deepcopy(default_info[_prior]).popitem()
test_info[_prior] = {name: "this is not a prior"}
with pytest.raises(LoggedError):
updated_info, products = run(test_info)
def test_prior_inherit_samegiven_differentdefinition():
test_info = deepcopy(test_info_common)
likname = list(test_info_common["likelihood"])[0]
default_info = get_default_info(likname, "likelihood")
name, prior = deepcopy(default_info["prior"]).popitem()
test_info["prior"] = {name: "this is not a prior"}
with pytest.raises(LoggedError):
run(test_info)
def test_run_file(tmpdir):
input_file = os.path.join(tmpdir, 'pars.yaml')
root = os.path.join(tmpdir, 'test')
yaml_dump_file(input_file, dict(test_info_common, output=root))
run_script([input_file, '--force'])
likname = list(test_info_common["likelihood"])[0]
default_info = get_default_info(likname, "likelihood")
updated_info = yaml_load_file(root + '.updated.yaml')
assert updated_info["prior"] == default_info["prior"]
def test_inherit_label_and_bounds():
test_info = deepcopy(test_info_common)
likname = list(test_info_common[kinds.likelihood])[0]
default_info_params = get_default_info(likname, kinds.likelihood)[_params]
test_info[_params] = deepcopy(default_info_params)
test_info[_params]["a1"].pop(partag.latex, None)
# Remove limits, so they are inherited
test_info = deepcopy(test_info_common)
test_info[_params] = deepcopy(default_info_params)
test_info[_params]["b1"].pop("min")
test_info[_params]["b1"].pop("max")
updated_info, products = run(test_info)
assert updated_info[_params]["b1"]["min"] == default_info_params["b1"][
"min"]
assert updated_info[_params]["b1"]["max"] == default_info_params["b1"][
"max"]
def test_inherit_label_and_bounds():
test_info = deepcopy(test_info_common)
likname = list(test_info_common["likelihood"])[0]
default_info_params = get_default_info(likname, "likelihood")["params"]
test_info["params"] = deepcopy(default_info_params)
test_info["params"]["a1"].pop("latex", None)
# Remove limits, so they are inherited
test_info = deepcopy(test_info_common)
test_info["params"] = deepcopy(default_info_params)
test_info["params"]["b1"].pop("min")
test_info["params"]["b1"].pop("max")
updated_info, _ = run(test_info)
assert updated_info["params"]["b1"]["min"] == default_info_params["b1"][
"min"]
assert updated_info["params"]["b1"]["max"] == default_info_params["b1"][
"max"]
def __init__(self, kind, component, parent=None):
super().__init__()
self.clipboard = parent.clipboard
self.setWindowTitle("%s : %s" % (kind, component))
self.setGeometry(0, 0, 500, 500)
# noinspection PyArgumentList
self.move(QApplication.desktop().screenGeometry().center() -
self.rect().center())
self.show()
# Main layout
self.layout = QVBoxLayout()
self.setLayout(self.layout)
self.display_tabs = QTabWidget()
self.display = {}
for k in ["yaml", "python", "bibliography"]:
self.display[k] = QTextEdit()
self.display[k].setLineWrapMode(QTextEdit.NoWrap)
self.display[k].setFontFamily("mono")
self.display[k].setCursorWidth(0)
self.display[k].setReadOnly(True)
self.display_tabs.addTab(self.display[k], k)
self.layout.addWidget(self.display_tabs)
# Fill text
defaults_txt = get_default_info(component, kind, return_yaml=True)
_indent = " "
defaults_txt = (kind + ":\n" + _indent + component + ":\n" +
2 * _indent +
("\n" + 2 * _indent).join(defaults_txt.split("\n")))
from cobaya.yaml import yaml_load
self.display["python"].setText(pformat(yaml_load(defaults_txt)))
self.display["yaml"].setText(defaults_txt)
self.display["bibliography"].setText(get_bib_component(
component, kind))
# Buttons
self.buttons = QHBoxLayout()
self.close_button = QPushButton('Close', self)
self.copy_button = QPushButton('Copy to clipboard', self)
self.buttons.addWidget(self.close_button)
self.buttons.addWidget(self.copy_button)
self.close_button.released.connect(self.close)
self.copy_button.released.connect(self.copy_clipb)
self.layout.addLayout(self.buttons)
def __init__(self, kind, module, parent=None):
super(DefaultsDialog, self).__init__()
self.clipboard = parent.clipboard
self.setWindowTitle("%s : %s" % (kind, module))
self.setGeometry(0, 0, 500, 500)
self.move(
QApplication.desktop().screenGeometry().center() - self.rect().center())
self.show()
# Main layout
self.layout = QVBoxLayout()
self.setLayout(self.layout)
self.display_tabs = QTabWidget()
self.display = {}
for k in ["yaml", "python", "bibliography"]:
self.display[k] = QTextEdit()
self.display[k].setLineWrapMode(QTextEdit.NoWrap)
self.display[k].setFontFamily("mono")
self.display[k].setCursorWidth(0)
self.display[k].setReadOnly(True)
self.display_tabs.addTab(self.display[k], k)
self.layout.addWidget(self.display_tabs)
# Fill text
defaults_txt = get_default_info(
module, kind, return_yaml=True, fail_if_not_found=True)
from cobaya.yaml import yaml_load
self.display["python"].setText(
"from collections import OrderedDict\n\ninfo = " +
pformat(yaml_load(defaults_txt)))
self.display["yaml"].setText(defaults_txt)
self.display["bibliography"].setText(get_bib_module(module, kind))
# Buttons
self.buttons = QHBoxLayout()
self.close_button = QPushButton('Close', self)
self.copy_button = QPushButton('Copy to clipboard', self)
self.buttons.addWidget(self.close_button)
self.buttons.addWidget(self.copy_button)
self.close_button.released.connect(self.close)
self.copy_button.released.connect(self.copy_clipb)
self.layout.addLayout(self.buttons)
def test_inherit_label_and_bounds():
test_info = deepcopy(test_info_common)
likname = list(test_info_common[_likelihood].keys())[0]
default_info_params = get_default_info(likname, _likelihood)[_params]
test_info[_params] = deepcopy(default_info_params)
test_info[_params]["a1"].pop(_p_label, None)
# First, change one limit (so no inheritance at all)
test_info[_params]["b1"].pop("min")
new_max = 2
test_info[_params]["b1"]["max"] = new_max
updated_info, products = run(test_info)
assert updated_info[_params]["a1"] == default_info_params["a1"]
assert updated_info[_params]["b1"].get("min") is None
assert updated_info[_params]["b1"]["max"] == new_max
# Second, remove limits, so they are inherited
test_info = deepcopy(test_info_common)
test_info[_params] = deepcopy(default_info_params)
test_info[_params]["b1"].pop("min")
test_info[_params]["b1"].pop("max")
updated_info, products = run(test_info)
assert updated_info[_params]["b1"]["min"] == default_info_params["b1"]["min"]
assert updated_info[_params]["b1"]["max"] == default_info_params["b1"]["max"]
def get_product_id_and_clik_file(name):
"""Gets the PLA product info from the defaults file."""
defaults = get_default_info(name, _likelihood)[_likelihood][name]
return defaults.get("product_id"), defaults.get("clik_file")
def doc_script(args=None):
"""Command line script for the documentation."""
warn_deprecation()
logger_setup()
logger = get_logger("doc")
# Parse arguments
import argparse
parser = argparse.ArgumentParser(
prog="cobaya doc",
description="Prints defaults for Cobaya's components.")
parser.add_argument(
"component",
action="store",
nargs="?",
default="",
metavar="component_name",
help=("The component whose defaults are requested. "
"Pass a component kind (sampler, theory, likelihood) to "
"list all available (internal) ones, pass nothing to list "
"all available (internal) components of all kinds."))
parser.add_argument("-p",
"--python",
action="store_true",
default=False,
help="Request Python instead of YAML.")
expand_flag, expand_flag_ishort = "expand", 1
parser.add_argument("-" + expand_flag[expand_flag_ishort],
"--" + expand_flag,
action="store_true",
default=False,
help="Expand YAML defaults.")
arguments = parser.parse_args(args)
# Nothing passed: list all
if not arguments.component:
msg = "Available components: (some may need external code/data)"
print(msg + "\n" + "-" * len(msg))
for kind in kinds:
print("%s:" % kind)
print(_indent +
("\n" +
_indent).join(get_available_internal_class_names(kind)))
return
# A kind passed (plural or singular): list all of that kind
if arguments.component.lower() in subfolders.values():
arguments.component = next(k for k in subfolders
if arguments.component == subfolders[k])
if arguments.component.lower() in kinds:
print("%s:" % arguments.component.lower())
print(_indent + ("\n" + _indent).join(
get_available_internal_class_names(arguments.component.lower())))
return
# Otherwise, try to identify the component
try:
cls = get_component_class(arguments.component, logger=logger)
except ComponentNotFoundError:
suggestions = similar_internal_class_names(arguments.component)
logger.error(
f"Could not identify component '{arguments.component}'. "
f"Did you mean any of the following? {suggestions} (mind capitalization!)"
)
return 1
to_print = get_default_info(cls,
return_yaml=not arguments.python,
yaml_expand_defaults=arguments.expand)
if arguments.python:
print(pformat({cls.get_kind(): {arguments.component: to_print}}))
else:
print(cls.get_kind() + ":\n" + _indent + arguments.component + ":\n" +
2 * _indent + ("\n" + 2 * _indent).join(to_print.split("\n")))
if "!defaults" in to_print:
print("# This file contains defaults. "
"To populate them, use the flag --%s (or -%s)." %
(expand_flag, expand_flag[expand_flag_ishort]))
def doc_script():
from cobaya.mpi import am_single_or_primary_process
if not am_single_or_primary_process():
return
warn_deprecation()
# Parse arguments
import argparse
parser = argparse.ArgumentParser(
description="Prints defaults for Cobaya's internal modules.")
parser.add_argument("module",
action="store",
nargs="?",
default="",
metavar="module_name",
help="The module whose defaults are requested.")
kind_opt, kind_opt_ishort = "kind", 0
parser.add_argument(
"-" + kind_opt[kind_opt_ishort],
"--" + kind_opt,
action="store",
nargs=1,
default=None,
metavar="module_kind",
help=("Kind of module whose defaults are requested: " +
", ".join(['%s' % kind for kind in _kinds]) + ". " +
"Use only when module name is not unique (it would fail)."))
parser.add_argument("-p",
"--python",
action="store_true",
default=False,
help="Request Python instead of YAML.")
expand_flag, expand_flag_ishort = "expand", 1
parser.add_argument("-" + expand_flag[expand_flag_ishort],
"--" + expand_flag,
action="store_true",
default=False,
help="Expand YAML defaults.")
arguments = parser.parse_args()
# Remove plurals (= name of src subfolders), for user-friendliness
if arguments.module.lower() in subfolders.values():
arguments.module = next(k for k in subfolders
if arguments.module == subfolders[k])
# Kind given, list all
if not arguments.module:
msg = "Available modules: (some may need external code/data)"
print(msg + "\n" + "-" * len(msg))
for kind in _kinds:
print("%s:" % kind)
print(_indent + ("\n" + _indent).join(get_available_modules(kind)))
return
# Kind given: list all modules of that kind
if arguments.module.lower() in _kinds:
print("%s:" % arguments.module.lower())
print(_indent +
("\n" +
_indent).join(get_available_modules(arguments.module.lower())))
return
# Otherwise, check if it's a unique module name
try:
if arguments.kind:
arguments.kind = arguments.kind[0].lower()
to_print = get_default_info(arguments.module,
arguments.kind,
return_yaml=not arguments.python,
yaml_expand_defaults=arguments.expand,
fail_if_not_found=True)
if arguments.python:
print(import_odict + pformat(to_print))
else:
print(to_print)
if "!defaults" in to_print:
print("# This file contains defaults. "
"To populate them, use the flag --%s (or -%s)." %
(expand_flag, expand_flag[expand_flag_ishort]))
except:
if not arguments.kind:
print("Specify its kind with '--%s [module_kind]'." % kind_opt)
return 1
return
def doc_script():
from cobaya.mpi import is_main_process
if not is_main_process():
return
warn_deprecation()
# Parse arguments
import argparse
parser = argparse.ArgumentParser(
description="Prints defaults for Cobaya's components.")
parser.add_argument("component",
action="store",
nargs="?",
default="",
metavar="component_name",
help="The component whose defaults are requested.")
kind_opt, kind_opt_ishort = "kind", 0
parser.add_argument(
"-" + kind_opt[kind_opt_ishort],
"--" + kind_opt,
action="store",
nargs=1,
default=None,
metavar="component_kind",
help=("Kind of component whose defaults are requested: " +
", ".join(['%s' % kind for kind in kinds]) + ". " +
"Use only when component name is not unique (it would fail)."))
parser.add_argument("-p",
"--python",
action="store_true",
default=False,
help="Request Python instead of YAML.")
expand_flag, expand_flag_ishort = "expand", 1
parser.add_argument("-" + expand_flag[expand_flag_ishort],
"--" + expand_flag,
action="store_true",
default=False,
help="Expand YAML defaults.")
arguments = parser.parse_args()
# Remove plurals (= name of src subfolders), for user-friendliness
if arguments.component.lower() in subfolders.values():
arguments.component = next(k for k in subfolders
if arguments.component == subfolders[k])
# Kind given, list all
if not arguments.component:
msg = "Available components: (some may need external code/data)"
print(msg + "\n" + "-" * len(msg))
for kind in kinds:
print("%s:" % kind)
print(_indent +
("\n" +
_indent).join(get_available_internal_class_names(kind)))
return
# Kind given: list all components of that kind
if arguments.component.lower() in kinds:
print("%s:" % arguments.component.lower())
print(_indent + ("\n" + _indent).join(
get_available_internal_class_names(arguments.component.lower())))
return
# Otherwise, check if it's a unique component name
try:
if arguments.kind:
arguments.kind = arguments.kind[0].lower()
if arguments.kind not in kinds:
print("Kind %r not recognized. Try one of %r" %
(arguments.kind, tuple(kinds)))
raise ValueError
else:
arguments.kind = get_kind(arguments.component)
to_print = get_default_info(arguments.component,
arguments.kind,
return_yaml=not arguments.python,
yaml_expand_defaults=arguments.expand)
if arguments.python:
print(pformat({arguments.kind: {arguments.component: to_print}}))
else:
print(arguments.kind + ":\n" + _indent + arguments.component +
":\n" + 2 * _indent +
("\n" + 2 * _indent).join(to_print.split("\n")))
if "!defaults" in to_print:
print("# This file contains defaults. "
"To populate them, use the flag --%s (or -%s)." %
(expand_flag, expand_flag[expand_flag_ishort]))
except Exception:
if isinstance(Exception, LoggedError.__class__):
pass
else:
if not arguments.kind:
print("Specify its kind with '--%s [component_kind]'." %
kind_opt)
return 1
return
def body_of_test(modules,
best_fit,
info_likelihood,
info_theory,
ref_chi2,
best_fit_derived=None):
assert modules, "I need a modules folder!"
info = {
_path_install: modules,
_theory: info_theory,
_likelihood: info_likelihood,
_sampler: {
"evaluate": None
}
}
# Add best fit
info[_params] = merge_params_info(*([yaml_load(baseline_cosmology)] + [
get_default_info(lik, _likelihood).get(_params, {})
for lik in info[_likelihood]
]))
for p in best_fit:
try:
if _prior in info[_params].get(p, {}):
info[_params][p]["ref"] = best_fit[p]
except: # was fixed or derived
info[_params][p] = best_fit[p]
# We'll pop some derived parameters, so copy
derived = deepcopy(baseline_cosmology_derived)
best_fit_derived = deepcopy(best_fit_derived)
if list(info[_theory].keys())[0] == "classy":
# More stuff that CLASS needs for the Planck model
info[_params].update(baseline_cosmology_classy_extra)
# Remove "cosmomc_theta" in favour of "H0" (remove it from derived then!)
info[_params].pop("cosmomc_theta")
info[_params].pop("theta")
info[_params]["H0"] = {
_prior: {
"min": 0,
"max": 100
},
_p_ref: best_fit["H0"]
}
derived.pop("H0")
if best_fit_derived is not None:
best_fit_derived.pop("H0", None)
# Don't test those that have not been implemented yet
for p in [
"zstar",
"rstar",
"thetastar",
"DAstar",
"zdrag",
"kd",
"thetad",
"zeq",
"keq",
"thetaeq",
"thetarseq",
# BBN!!!
"DH",
"Y_p"
]:
derived.pop(p)
best_fit_derived.pop(p, None)
else:
info[_theory]["camb"] = info[_theory]["camb"] or {}
info[_theory]["camb"].update({"stop_at_error": True})
# Add derived
if best_fit_derived is not None:
info[_params].update(derived)
updated_info, products = run(info)
# Check value of likelihoods
for lik in info[_likelihood]:
chi2 = products["sample"][_chi2 + separator + lik][0]
assert abs(chi2 - ref_chi2[lik]) < ref_chi2["tolerance"], (
"Testing likelihood '%s': | %g - %g | = %g >= %g" %
(lik, chi2, ref_chi2[lik], abs(chi2 - ref_chi2[lik]),
ref_chi2["tolerance"]))
# Check value of derived parameters
not_tested = []
not_passed = []
for p in best_fit_derived or {}:
if best_fit_derived[p][0] is None or p not in best_fit_derived:
not_tested += [p]
continue
rel = (abs(products["sample"][_derived_pre + p][0] -
best_fit_derived[p][0]) / best_fit_derived[p][1])
if rel > tolerance_derived * (2 if p in ("YHe", "Y_p", "DH", "sigma8",
"s8omegamp5") else 1):
not_passed += [(p, rel)]
print("Derived parameters not tested because not implemented: %r" %
not_tested)
assert not not_passed, "Some derived parameters were off: %r" % not_passed
def create_input(**kwargs):
get_comments = kwargs.pop("get_comments", False)
preset = kwargs.pop("preset", None)
if preset:
fields = deepcopy(input_database.preset[preset])
fields.update(kwargs)
return create_input(get_comments=get_comments, **fields)
# Need to copy to select theory.
# Likelihoods always AT THE END!
# (to check that sampled parameters are not redefined as derived)
infos = odict()
kwargs_params = [
"primordial", "geometry", "hubble", "matter", "neutrinos",
"dark_energy", "bbn", "reionization"
]
kwargs_likes = ["like_cmb", "like_bao", "like_sn", "like_H0"]
for k in kwargs_params + kwargs_likes:
if k not in kwargs:
infos[k] = odict()
try:
infos[k] = deepcopy(
getattr(input_database, k)[kwargs.get(k,
input_database._none)])
except KeyError:
raise ValueError("Unknown value '%s' for '%s'" %
(kwargs.get(k, input_database._none), k))
theory_requested = kwargs.get(_theory)
for i, (field, info) in enumerate(infos.items()):
if not info:
continue
error_msg = info.pop(input_database._error_msg, None)
try:
info[_theory] = {theory_requested: info[_theory][theory_requested]}
except KeyError:
return (
"There is no preset for\n'%s'" %
(info.get(input_database._desc, field)) +
"with theory code '%s'." % theory_requested +
("\n--> " + error_msg if error_msg else
"\nThis does not mean that you cannot use this model with that "
"theory code; just that we have not implemented this yet."))
# Add non-translatable parameters (in info["theory"][classy|camb][params])
if _params not in info:
info[_params] = odict()
info[_params].update((info[_theory][theory_requested]
or odict()).pop(_params, odict()))
# Remove the *derived* parameters mentioned by the likelihoods that
# are already *sampled* by some part of the model
if field.startswith("like_") and _params in info:
remove_derived = []
for p in info[_params]:
if any([(p in info_part[_params])
for info_part in list(infos.values())[:i]]):
remove_derived += [p]
for p in remove_derived:
info[_params].pop(p)
# Prepare sampler info
info_sampler = deepcopy(
input_database.sampler.get(kwargs.get(_sampler), {}))
if info_sampler:
sampler_name = list(info_sampler[_sampler])[0]
info_sampler[_sampler][
sampler_name] = info_sampler[_sampler][sampler_name] or {}
# Add recommended options for samplers
for info in infos.values():
this_info_sampler = info.pop(_sampler, {})
if sampler_name in this_info_sampler:
info_sampler[_sampler][sampler_name].update(
this_info_sampler[sampler_name])
# Reorder, to have the *parameters* shown in the correct order, and *merge*
all_infos = [info_sampler] + [
infos[k] for k in kwargs_likes[::-1] + kwargs_params[::-1]
]
comments = [info.pop(input_database._comment, None) for info in all_infos]
comments = [c for c in comments if c]
[info.pop(input_database._desc, None) for info in all_infos]
merged = merge_info(*all_infos)
# Simplify parameter infos
for p, info in merged[_params].items():
merged[_params][p] = reduce_info_param(info)
# Translate from Planck param names
planck_to_theo = get_default_info(
theory_requested, _theory)[_theory][theory_requested][_p_renames]
if kwargs.get("planck_names", False):
merged[_theory][
theory_requested] = merged[_theory][theory_requested] or {}
merged[_theory][theory_requested]["use_planck_names"] = True
else:
merged_params_translated = odict([
translate(p, info, planck_to_theo)
for p, info in merged[_params].items()
])
merged[_params] = merged_params_translated
if get_comments and comments:
merged[input_database._comment] = comments
return merged
def test_prior_inherit_nonegiven():
updated_info, products = run(test_info_common)
likname = list(test_info_common[_likelihood].keys())[0]
default_info = get_default_info(likname, _likelihood)
assert updated_info[_prior] == default_info[_prior]
def test_prior_inherit_nonegiven():
updated_info, _ = run(test_info_common)
likname = list(test_info_common["likelihood"])[0]
default_info = get_default_info(likname, "likelihood")
assert updated_info["prior"] == default_info["prior"]
from copy import deepcopy
from collections import OrderedDict as odict
from six import string_types
import numpy as np
from cobaya.input import merge_info
from cobaya.conventions import _theory, _params, _p_drop, _p_alias
from cobaya.input import get_default_info
import input_database
planck_to_classy = get_default_info("classy", _theory)[_theory]["classy"]["planck_to_classy"]
planck_to_camb = get_default_info("camb", _theory)[_theory]["camb"]["planck_to_camb"]
def translate(p, info=None, dictionary=None, add_alias=False):
dictionary = dictionary or {}
# Ignore if dropped
if not (info if hasattr(info, "keys") else {}).get(_p_drop, False):
p_old = p
p = dictionary.get(p, p)
if hasattr(info, "keys") and p_old != p:
pre_aliases = np.atleast_1d(info.get(_p_alias, [])).tolist()
info.update({_p_alias: pre_aliases + [p_old]})
# Try to modify lambda parameters too!
if isinstance(info, string_types):
if info.startswith("lambda"):
arguments = info.split(":")[0].split()[1:]
if not isinstance(arguments, string_types):
arguments = "".join(arguments)
arguments = arguments.split(",")
arguments_t = [translate(pi, dictionary=dictionary)[0] for pi in arguments]