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