def validate_user_constants(*allow_types):
return All(
has_keys_of_type(six.string_types),
coerce_string_keys_to_text_type,
{Extra: Any(*allow_types)},
)
def validate_user_constants(*allow_types):
return All(
has_keys_of_type(str),
{Extra: Any(*allow_types)},
)
raise ConfigError(
"DependentSamplers depend on undefined quantities: " +
bad_symbols)
# 2: Circular dependencies
bad_symbols = ", ".join(sorted(unevaluated_dependents.keys()))
raise ConfigError(
"Circularly dependent DependentSamplers detected: " +
bad_symbols)
sample_list.append(sample_dict)
return sample_list
# Used by NumericalGrader
schema_user_functions_no_random = All(has_keys_of_type(six.string_types),
coerce_string_keys_to_text_type,
{Extra: is_callable})
# Used by FormulaGrader and friends
schema_user_functions = All(
has_keys_of_type(six.string_types),
coerce_string_keys_to_text_type,
{
Extra:
Any(is_callable, All([is_callable], Coerce(SpecificFunctions)),
FunctionSamplingSet)
},
)
def construct_functions(default_functions, user_funcs):
sample_dict, functions, suffixes)
del unevaluated_dependents[symbol]
progress_made = True
if not progress_made:
bad_symbols = ", ".join(sorted(unevaluated_dependents.keys()))
raise ConfigError(
"Circularly dependent DependentSamplers detected: " +
bad_symbols)
sample_list.append(sample_dict)
return sample_list
schema_user_functions = All(
has_keys_of_type(str),
{
Extra:
Any(is_callable, All([is_callable], Coerce(SpecificFunctions)),
FunctionSamplingSet)
},
)
def construct_functions(default_functions, user_funcs):
"""
Constructs functions for use in sampling math expressions.
Arguments:
default_funcs: a dict mapping function names (strings) to functions
user_funcs: a dict mapping function names (strings) to functions OR