SYMBOL INDEX (586 symbols across 50 files) FILE: ambrosia/designer/designer.py class Designer (line 50) | class Designer(yaml.YAMLObject, ABToolAbstract, metaclass=ABMetaClass): method set_first_errors (line 192) | def set_first_errors(self, first_type_errors: types.StatErrorType) -> ... method set_second_errors (line 198) | def set_second_errors(self, second_type_errors: types.StatErrorType) -... method set_sizes (line 204) | def set_sizes(self, sizes: types.SampleSizeType) -> None: method set_effects (line 210) | def set_effects(self, effects: types.EffectType) -> None: method set_dataframe (line 216) | def set_dataframe(self, dataframe: types.PassedDataType) -> None: method set_method (line 225) | def set_method(self, method: str) -> None: method set_metrics (line 228) | def set_metrics(self, metrics: str) -> None: method __init__ (line 234) | def __init__( method __getstate__ (line 255) | def __getstate__(self): method from_yaml (line 269) | def from_yaml(cls, loader: yaml.Loader, node: yaml.Node): method __dataframe_handler (line 274) | def __dataframe_handler(handler: SimpleDesigner, parameter: str, **kwa... method __theory_design (line 289) | def __theory_design(label: str, args: types._UsageArgumentsType, **kwa... method __empiric_design (line 314) | def __empiric_design(label: str, args: types._UsageArgumentsType, **kw... method __binary_design (line 335) | def __binary_design(label: str, args: types._UsageArgumentsType, **kwa... method __pre_design (line 361) | def __pre_design(label: str, args: types._UsageArgumentsType, **kwargs... method run (line 375) | def run( function load_from_config (line 484) | def load_from_config(yaml_config: str, loader: type = yaml.Loader) -> De... function design (line 499) | def design( function design_binary_size (line 582) | def design_binary_size( function design_binary_effect (line 663) | def design_binary_effect( function design_binary_power (line 750) | def design_binary_power( function design_binary (line 837) | def design_binary( FILE: ambrosia/designer/handlers.py class TheoryHandler (line 45) | class TheoryHandler(SimpleDesigner): method size_design (line 50) | def size_design(self, **kwargs) -> pd.DataFrame: method effect_design (line 53) | def effect_design(self, **kwargs) -> pd.DataFrame: method power_design (line 56) | def power_design(self, **kwargs) -> pd.DataFrame: class EmpiricHandler (line 60) | class EmpiricHandler(SimpleDesigner): method size_design (line 65) | def size_design(self, **kwargs) -> pd.DataFrame: method effect_design (line 68) | def effect_design(self, **kwargs) -> pd.DataFrame: method power_design (line 71) | def power_design(self, **kwargs) -> pd.DataFrame: function calc_prob_control_class (line 79) | def calc_prob_control_class(table: types.PassedDataType, metric: types.M... FILE: ambrosia/preprocessing/aggregate.py class AggregatePreprocessor (line 27) | class AggregatePreprocessor(AbstractFittableTransformer): method __mode_calculation (line 59) | def __mode_calculation(values: pd.Series) -> Any: method __simple_agg (line 66) | def __simple_agg(values: pd.Series) -> Any: method __transform_agg_param (line 73) | def __transform_agg_param(aggregation_method: types.MethodType) -> typ... method __transform_params (line 84) | def __transform_params(dataframe: pd.DataFrame, aggregation_params: Di... method __init__ (line 95) | def __init__(self, categorial_method: types.MethodType = "mode", real_... method __real_case_step (line 102) | def __real_case_step( method __categorial_case_step (line 115) | def __categorial_case_step( method __empty_args_step (line 128) | def __empty_args_step( method get_params_dict (line 143) | def get_params_dict(self) -> Dict: method load_params_dict (line 150) | def load_params_dict(self, params: Dict) -> None: method fit (line 169) | def fit( method transform (line 217) | def transform( method fit_transform (line 240) | def fit_transform( FILE: ambrosia/preprocessing/cuped.py class Cuped (line 29) | class Cuped(AbstractVarianceReducer): method __init__ (line 115) | def __init__(self, verbose: bool = True) -> None: method __str__ (line 121) | def __str__(self) -> str: method __call__ (line 124) | def __call__(self, y: np.ndarray, X: np.ndarray) -> np.ndarray: method get_params_dict (line 129) | def get_params_dict(self) -> Dict: method load_params_dict (line 144) | def load_params_dict(self, params: Dict) -> None: method fit (line 163) | def fit( method transform (line 200) | def transform( method fit_transform (line 229) | def fit_transform( class MultiCuped (line 261) | class MultiCuped(AbstractVarianceReducer): method __init__ (line 352) | def __init__(self, verbose: bool = True) -> None: method __str__ (line 358) | def __str__(self) -> str: method __call__ (line 361) | def __call__(self, y: np.ndarray, X: np.ndarray) -> np.ndarray: method get_params_dict (line 366) | def get_params_dict(self) -> Dict: method load_params_dict (line 381) | def load_params_dict(self, params: Dict) -> None: method fit (line 400) | def fit( method transform (line 444) | def transform( method fit_transform (line 474) | def fit_transform( FILE: ambrosia/preprocessing/ml_var_reducer.py class MLVarianceReducer (line 36) | class MLVarianceReducer(AbstractVarianceReducer): method __set_scorer (line 114) | def __set_scorer(self, scores: Optional[Dict[str, Callable]]): method __create_model (line 123) | def __create_model(self) -> None: method __init__ (line 136) | def __init__( method __str__ (line 150) | def __str__(self) -> str: method __call__ (line 153) | def __call__(self, y: np.ndarray, X: np.ndarray) -> np.ndarray: method _verbose_score (line 163) | def _verbose_score(self, dataframe: pd.DataFrame, prediction: np.ndarr... method _check_load_params (line 168) | def _check_load_params(self, params: Dict) -> None: method get_params_dict (line 175) | def get_params_dict(self) -> Dict: method load_params_dict (line 193) | def load_params_dict(self, params: Dict) -> None: method store_params (line 209) | def store_params(self, config_store_path: Path, model_store_path: Path... method load_params (line 226) | def load_params(self, config_load_path: Path, model_load_path: Path) -... method fit (line 241) | def fit( method transform (line 275) | def transform( method fit_transform (line 305) | def fit_transform( FILE: ambrosia/preprocessing/preprocessor.py class Preprocessor (line 40) | class Preprocessor: method __len__ (line 100) | def __len__(self) -> int: method __init__ (line 103) | def __init__(self, dataframe: pd.DataFrame, verbose: bool = True) -> N... method data (line 108) | def data(self, copy: bool = True): method aggregate (line 126) | def aggregate( method robust (line 176) | def robust( method iqr (line 215) | def iqr( method boxcox (line 247) | def boxcox( method log (line 278) | def log( method cuped (line 307) | def cuped( method multicuped (line 344) | def multicuped( method linearize (line 381) | def linearize( method transformations (line 425) | def transformations(self) -> List: method store_transformations (line 436) | def store_transformations(self, store_path: Path) -> None: method load_transformations (line 461) | def load_transformations(self, load_path: Path) -> None: method apply_transformations (line 482) | def apply_transformations(self) -> pd.DataFrame: method transform_from_config (line 498) | def transform_from_config(self, load_path: Path) -> pd.DataFrame: FILE: ambrosia/preprocessing/robust.py class RobustPreprocessor (line 30) | class RobustPreprocessor(AbstractFittableTransformer): method __str__ (line 73) | def __str__(self) -> str: method __init__ (line 76) | def __init__(self, verbose: bool = True) -> None: method get_params_dict (line 89) | def get_params_dict(self) -> Dict: method load_params_dict (line 104) | def load_params_dict(self, params: Dict) -> None: method __wrap_alpha (line 123) | def __wrap_alpha(self, alpha: Union[float, Iterable]) -> np.ndarray: method __check_tail (line 137) | def __check_tail(self, tail: str) -> str: method __calculate_quantiles (line 142) | def __calculate_quantiles( method fit (line 158) | def fit( method transform (line 193) | def transform(self, dataframe: pd.DataFrame, inplace: bool = False) ->... method fit_transform (line 237) | def fit_transform( class IQRPreprocessor (line 272) | class IQRPreprocessor(AbstractFittableTransformer): method __str__ (line 311) | def __str__(self) -> str: method __init__ (line 314) | def __init__(self, verbose: bool = True) -> None: method get_params_dict (line 322) | def get_params_dict(self) -> Dict: method load_params_dict (line 337) | def load_params_dict(self, params: Dict) -> None: method __calculate_params (line 356) | def __calculate_params( method fit (line 364) | def fit( method transform (line 390) | def transform(self, dataframe: pd.DataFrame, inplace: bool = False) ->... method fit_transform (line 429) | def fit_transform( FILE: ambrosia/preprocessing/transformers.py class BoxCoxTransformer (line 30) | class BoxCoxTransformer(AbstractFittableTransformer): method __str__ (line 59) | def __str__(self) -> str: method __init__ (line 62) | def __init__( method __calculate_lambda_ (line 72) | def __calculate_lambda_( method get_params_dict (line 82) | def get_params_dict(self) -> Dict: method load_params_dict (line 97) | def load_params_dict(self, params: Dict) -> None: method fit (line 116) | def fit( method transform (line 142) | def transform(self, dataframe: pd.DataFrame, inplace: bool = False) ->... method fit_transform (line 171) | def fit_transform( method inverse_transform (line 199) | def inverse_transform(self, dataframe: pd.DataFrame, inplace: bool = F... class LogTransformer (line 229) | class LogTransformer(AbstractFittableTransformer): method __str__ (line 253) | def __str__(self) -> str: method __init__ (line 256) | def __init__(self) -> None: method get_params_dict (line 263) | def get_params_dict(self) -> Dict: method load_params_dict (line 272) | def load_params_dict(self, params: Dict) -> None: method fit (line 287) | def fit( method transform (line 312) | def transform(self, dataframe: pd.DataFrame, inplace: bool = False) ->... method fit_transform (line 338) | def fit_transform( method inverse_transform (line 367) | def inverse_transform(self, dataframe: pd.DataFrame, inplace: bool = F... class LinearizationTransformer (line 391) | class LinearizationTransformer(AbstractFittableTransformer): method __str__ (line 419) | def __str__(self) -> str: method __init__ (line 422) | def __init__(self) -> None: method get_params_dict (line 429) | def get_params_dict(self) -> Dict: method load_params_dict (line 438) | def load_params_dict(self, params: Dict) -> None: method fit (line 445) | def fit( method transform (line 477) | def transform(self, dataframe: pd.DataFrame, inplace: bool = False) ->... method fit_transform (line 494) | def fit_transform( FILE: ambrosia/spark_tools/empiric.py function inject_effect (line 41) | def inject_effect(dataframe: types.SparkDataFrame, column: types.ColumnN... function evaluate_criterion (line 66) | def evaluate_criterion( function calc_empiric_power (line 117) | def calc_empiric_power( function get_table_power (line 183) | def get_table_power( function optimize_group_size (line 251) | def optimize_group_size( function get_table_size (line 298) | def get_table_size( function optimize_effect (line 362) | def optimize_effect( function get_table_effect (line 404) | def get_table_effect( FILE: ambrosia/spark_tools/split_tools.py function unite_spark_tables (line 32) | def unite_spark_tables(*dataframes: types.SparkDataFrame) -> types.Spark... function add_hash_column (line 45) | def add_hash_column( function get_hash_split (line 73) | def get_hash_split( function add_to_required_size (line 101) | def add_to_required_size( function get_split (line 139) | def get_split( FILE: ambrosia/spark_tools/stat_criteria.py class ABSparkCriterion (line 34) | class ABSparkCriterion(ABStatCriterion): method _init_cache (line 39) | def _init_cache(self) -> None: method __init__ (line 43) | def __init__(self, cache_parameters: bool = True) -> None: method _delete_cached_data_parameters (line 47) | def _delete_cached_data_parameters(self) -> None: method _calc_and_cache_data_parameters (line 50) | def _calc_and_cache_data_parameters(self, *args, **kwargs) -> None: method _recalc_cache (line 56) | def _recalc_cache(self, *args, **kwargs) -> None: method _check_clear_cache (line 60) | def _check_clear_cache(self) -> None: method _check_effect (line 64) | def _check_effect(self, effect_type: str) -> None: method get_results (line 67) | def get_results( class TtestIndCriterionSpark (line 86) | class TtestIndCriterionSpark(ABSparkCriterion): method __calc_and_cache_data_parameters (line 95) | def __calc_and_cache_data_parameters( method _apply_delta_method (line 104) | def _apply_delta_method( method calculate_pvalue (line 122) | def calculate_pvalue( method calculate_effect (line 150) | def calculate_effect( method calculate_conf_interval (line 169) | def calculate_conf_interval( class TtestRelativeCriterionSpark (line 200) | class TtestRelativeCriterionSpark(ABSparkCriterion): method _rename_col (line 210) | def _rename_col(column: str, group: str) -> str: method _calc_and_cache_data_parameters (line 213) | def _calc_and_cache_data_parameters( method calculate_pvalue (line 240) | def calculate_pvalue( method calculate_conf_interval (line 258) | def calculate_conf_interval( method calculate_effect (line 268) | def calculate_effect( FILE: ambrosia/spark_tools/stratification.py class Stratification (line 30) | class Stratification(ab_abstract.StratificationUtil): method fit (line 36) | def fit(self, dataframe: types.SparkDataFrame, columns: Optional[Itera... method strat_sizes (line 50) | def strat_sizes(self) -> Dict[int, int]: FILE: ambrosia/spark_tools/theory.py function get_stats_from_table (line 28) | def get_stats_from_table(dataframe: types.SparkDataFrame, column: types.... function design_groups_size (line 40) | def design_groups_size( function design_effect (line 79) | def design_effect( function design_power (line 116) | def design_power( function ttest_spark (line 153) | def ttest_spark( FILE: ambrosia/splitter/handlers.py function add_data_pandas (line 44) | def add_data_pandas(dataframe: pd.DataFrame, splitted_dataframe: pd.Data... function add_data_spark (line 68) | def add_data_spark( function add_data_to_splitted (line 101) | def add_data_to_splitted( function handle_full_split (line 134) | def handle_full_split( function data_shape (line 150) | def data_shape(dataframe: types.PassedDataType) -> int: function split_data_handler (line 162) | def split_data_handler(**kwargs) -> types.SplitterResult: FILE: ambrosia/splitter/splitter.py class Splitter (line 42) | class Splitter(yaml.YAMLObject, ABToolAbstract, metaclass=ABMetaClass): method set_dataframe (line 181) | def set_dataframe(self, dataframe: Optional[types.PassedDataType]) -> ... method set_id_column (line 185) | def set_id_column(self, id_column: Optional[str]) -> None: method set_group_size (line 189) | def set_group_size(self, groups_size: Optional[int]) -> None: method set_test_group_ids (line 193) | def set_test_group_ids(self, test_group_ids: types.IndicesType) -> None: method set_fit_columns (line 197) | def set_fit_columns(self, fit_columns: types.ColumnNamesType) -> None: method set_strat_columns (line 201) | def set_strat_columns(self, strat_columns: types.ColumnNamesType) -> N... method __init__ (line 204) | def __init__( method __getstate__ (line 223) | def __getstate__(self): method from_yaml (line 235) | def from_yaml(cls, loader: yaml.Loader, node: yaml.Node): method run (line 239) | def run( function load_from_config (line 350) | def load_from_config(yaml_config: str, loader: type = yaml.Loader) -> Sp... function split (line 364) | def split( FILE: ambrosia/tester/binary_result_evaluation.py function binary_absolute_result (line 33) | def binary_absolute_result( function binary_relative_confidence_interval (line 80) | def binary_relative_confidence_interval( function binary_relative_result (line 117) | def binary_relative_result( FILE: ambrosia/tester/handlers.py function filter_spark_and_make_groups (line 19) | def filter_spark_and_make_groups( class PandasCriteria (line 38) | class PandasCriteria(enum.Enum): class SparkCriteria (line 45) | class SparkCriteria(enum.Enum): class TheoreticalTesterHandler (line 52) | class TheoreticalTesterHandler: method __init__ (line 53) | def __init__( method _correct_criterion (line 73) | def _correct_criterion(self, criterion: tp.Any) -> bool: method _raise_correct_criterion (line 76) | def _raise_correct_criterion(self, criterion: tp.Any) -> None: method get_criterion (line 80) | def get_criterion(self, criterion: str, data_example: types.SparkOrPan... method _set_kwargs (line 89) | def _set_kwargs(self): method solve (line 104) | def solve(self) -> types._SubResultType: FILE: ambrosia/tester/tester.py class Tester (line 58) | class Tester(ABToolAbstract): method set_experiment_results (line 204) | def set_experiment_results(self, experiment_results: types.ExperimentR... method set_errors (line 207) | def set_errors(self, first_type_errors: types.StatErrorType) -> None: method set_metrics (line 213) | def set_metrics(self, metrics: types.MetricNamesType) -> None: method set_dataframe (line 219) | def set_dataframe( method __init__ (line 240) | def __init__( method __filter_data (line 270) | def __filter_data( method __bootstrap_result (line 303) | def __bootstrap_result( method __binary_result (line 336) | def __binary_result( method __theory_handler (line 353) | def __theory_handler( method __pre_run (line 374) | def __pre_run(method: str, args: types._UsageArgumentsType, **kwargs) ... method __apply_first_stage_multitest_correction (line 419) | def __apply_first_stage_multitest_correction( method __apply_second_stage_multitest_correction (line 431) | def __apply_second_stage_multitest_correction( method as_table (line 443) | def as_table(dict_result: types.TesterResult) -> pd.DataFrame: method run (line 476) | def run( function test (line 614) | def test( FILE: ambrosia/tools/_lib/_bin_ci_aide.py function __helper_calc_empirical_power (line 23) | def __helper_calc_empirical_power(conf_interval: types.ManyIntervalType)... function __helper_bin_search_for_size (line 44) | def __helper_bin_search_for_size( function __helper_bin_search_for_delta (line 107) | def __helper_bin_search_for_delta( FILE: ambrosia/tools/_lib/_bootstrap_tools.py class EmpiricSolution (line 20) | class EmpiricSolution: method __init__ (line 25) | def __init__(self, power_calulation: Callable, desired_power: float, v... method power (line 33) | def power(self, **kwargs) -> float: class EmpiricSizeSolution (line 37) | class EmpiricSizeSolution(EmpiricSolution): method calc_upper_bound (line 42) | def calc_upper_bound(self, **kwargs) -> int: method calc_binary (line 48) | def calc_binary(self, **kwargs) -> int: class EmpiricEffectSolution (line 55) | class EmpiricEffectSolution(EmpiricSolution): method calc_upper_bound (line 60) | def calc_upper_bound(self, **kwargs) -> float: method calc_binary (line 64) | def calc_binary(self, **kwargs) -> int: FILE: ambrosia/tools/_lib/_selection_aide.py class Selector (line 25) | class Selector: method __init__ (line 30) | def __init__( method set_params (line 39) | def set_params(self, params: Tuple[Any, ...]) -> None: method iterate_params (line 43) | def iterate_params(self) -> Tuple[Tuple[Any, ...], List[Any]]: method handle_numeric (line 53) | def handle_numeric(report: pd.DataFrame, as_numeric: bool) -> None: method get_table_size (line 58) | def get_table_size(self, as_numeric: bool = False) -> pd.DataFrame: method get_table_effect (line 68) | def get_table_effect(self, as_numeric: bool = False) -> pd.DataFrame: FILE: ambrosia/tools/_lib/_tools_aide.py function __helper_generate_bootstrap_samples (line 26) | def __helper_generate_bootstrap_samples( function __helper_inject_effect (line 42) | def __helper_inject_effect( function __helper_get_power_for_bootstraped (line 66) | def __helper_get_power_for_bootstraped( function estimate_power (line 100) | def estimate_power(power_function: Callable, **kwargs_power) -> float: function helper_bin_search_upper_bound_size (line 110) | def helper_bin_search_upper_bound_size( function helper_bin_searh_upper_bound_effect (line 131) | def helper_bin_searh_upper_bound_effect(power_function: Callable, power_... function helper_binary_search_optimal_effect (line 144) | def helper_binary_search_optimal_effect( function helper_binary_search_effect_with_injection (line 175) | def helper_binary_search_effect_with_injection( function helper_binary_search_optimal_size (line 199) | def helper_binary_search_optimal_size( FILE: ambrosia/tools/ab_abstract_component.py class ABMetaClass (line 33) | class ABMetaClass(ABCMeta, YAMLObjectMetaclass): class ABToolAbstract (line 40) | class ABToolAbstract(ABC): method run (line 47) | def run(self): method _prepare_arguments (line 53) | def _prepare_arguments(_args: _PrepareArgumentsType) -> types._UsageAr... class AbstractFittableTransformer (line 84) | class AbstractFittableTransformer(ABC): method __init__ (line 94) | def __init__(self): method _check_fitted (line 97) | def _check_fitted(self) -> None: method _check_cols (line 101) | def _check_cols(self, dataframe: pd.DataFrame, columns: types.ColumnNa... method get_params_dict (line 107) | def get_params_dict(self) -> Dict: method load_params_dict (line 113) | def load_params_dict(self, params: Dict) -> None: method fit (line 124) | def fit(self): method transform (line 130) | def transform(self): method fit_transform (line 136) | def fit_transform(self): method store_params (line 141) | def store_params(self, store_path: Path) -> None: method load_params (line 151) | def load_params(self, load_path: Path) -> None: class AbstractVarianceReducer (line 163) | class AbstractVarianceReducer(AbstractFittableTransformer): method __call__ (line 191) | def __call__(self, y: np.ndarray, X: np.ndarray) -> np.ndarray: # pyl... method __init__ (line 201) | def __init__(self, verbose: bool = True) -> None: method _return_result (line 206) | def _return_result( method _verbose (line 220) | def _verbose(self, old_variance: float, new_variance: float) -> None: function choose_on_table (line 229) | def choose_on_table(alternatives: List[Any], dataframe) -> Any: class DataframeHandler (line 240) | class DataframeHandler: method _handle_cases (line 242) | def _handle_cases(__func_pandas: Callable, __func_spark: Callable, *ar... method _handle_on_table (line 251) | def _handle_on_table( class SimpleDesigner (line 262) | class SimpleDesigner(ABC, DataframeHandler): method size_design (line 270) | def size_design(self, **kwargs) -> pd.DataFrame: method effect_design (line 274) | def effect_design(self, **kwargs) -> pd.DataFrame: method power_design (line 278) | def power_design(self, **kwargs) -> pd.DataFrame: class EmptyStratValue (line 282) | class EmptyStratValue(Enum): class StratificationUtil (line 286) | class StratificationUtil(ABC): method __init__ (line 292) | def __init__(self): method fit (line 296) | def fit(self, dataframe: types.SparkOrPandas, columns) -> None: method strat_sizes (line 300) | def strat_sizes(self) -> Dict[Any, int]: method is_trained (line 303) | def is_trained(self) -> bool: method empty_strat (line 309) | def empty_strat(self) -> bool: method _check_fit (line 315) | def _check_fit(self) -> None: method groups (line 322) | def groups(self): method size (line 332) | def size(self) -> int: method get_group_sizes (line 346) | def get_group_sizes(self, group_size: int) -> Dict[Any, int]: class StatCriterion (line 370) | class StatCriterion(ABC): method calculate_pvalue (line 376) | def calculate_pvalue(self, group_a: Iterable[float], group_b: Iterable... class ABStatCriterion (line 380) | class ABStatCriterion(StatCriterion): method _send_type_error_msg (line 388) | def _send_type_error_msg(cls): method calculate_effect (line 393) | def calculate_effect(self, group_a: Iterable[float], group_b: Iterable... method calculate_conf_interval (line 397) | def calculate_conf_interval( method _make_ci (line 402) | def _make_ci(self, left_ci: np.ndarray, right_ci: np.ndarray, alternat... method get_results (line 407) | def get_results( FILE: ambrosia/tools/back_tools.py function create_seed_sequence (line 12) | def create_seed_sequence(length: int, entropy: Optional[Union[int, Itera... function tqdm_joblib (line 36) | def tqdm_joblib(tqdm_object): function handle_nested_multiprocessing (line 58) | def handle_nested_multiprocessing( function wrap_cols (line 81) | def wrap_cols(cols: types.ColumnNamesType) -> types.ColumnNamesType: FILE: ambrosia/tools/bin_intervals.py class BinomTwoSampleCI (line 34) | class BinomTwoSampleCI(ABC): method __init__ (line 77) | def __init__(self): method __wald_ci (line 81) | def __wald_ci( method __yule_ci (line 100) | def __yule_ci( method __bayes_conjugate_beta (line 128) | def __bayes_conjugate_beta( method __square_eq_newcombe (line 155) | def __square_eq_newcombe(p_est: float, m: int, quantile: float) -> typ... method __newcombe_ci (line 170) | def __newcombe_ci( method __recentered_ci (line 202) | def __recentered_ci( method calculate_pvalue (line 221) | def calculate_pvalue( method confidence_interval (line 281) | def confidence_interval( function get_table_power_on_size_and_conversions (line 386) | def get_table_power_on_size_and_conversions( function get_table_power_on_size_and_delta (line 452) | def get_table_power_on_size_and_delta( function iterate_for_sample_size (line 536) | def iterate_for_sample_size( function get_table_sample_size_on_effect (line 575) | def get_table_sample_size_on_effect( function iterate_for_delta (line 635) | def iterate_for_delta( function get_table_effect_on_sample_size (line 675) | def get_table_effect_on_sample_size( FILE: ambrosia/tools/configs.py class AmbrosiaEnum (line 19) | class AmbrosiaEnum(enum.Enum): method _check_for_existing_members (line 24) | def _check_for_existing_members(): method check_value_in_enum (line 32) | def check_value_in_enum(cls, value: tp.Any) -> bool: method get_all_enum_values (line 36) | def get_all_enum_values(cls) -> tp.List[str]: method raise_if_value_incorrect_enum (line 40) | def raise_if_value_incorrect_enum(cls, value: tp.Any) -> None: class Alternatives (line 46) | class Alternatives(AmbrosiaEnum): class Effects (line 52) | class Effects(AmbrosiaEnum): FILE: ambrosia/tools/decorators.py function filter_kwargs (line 5) | def filter_kwargs(func): function tqdm_parallel_decorator (line 18) | def tqdm_parallel_decorator(func): FILE: ambrosia/tools/empirical_tools.py function inject_effect (line 35) | def inject_effect( function estim_stat_criterion_power (line 94) | def estim_stat_criterion_power( function get_bs_stat (line 137) | def get_bs_stat(sample: np.ndarray, stat: str = "mean", N: int = 1000, r... function get_bs_sample_stat (line 169) | def get_bs_sample_stat( function make_bootstrap (line 227) | def make_bootstrap( function eval_error (line 291) | def eval_error( class BootstrapStats (line 359) | class BootstrapStats: method __init__ (line 381) | def __init__(self, bootstrap_size: int = 10000, metric: Union[str, Cal... method __handle_str_metric (line 406) | def __handle_str_metric(self, bootstrap_a: np.ndarray, bootstrap_b: np... method __handle_std_value (line 417) | def __handle_std_value(self) -> float: method __handle_sampling (line 428) | def __handle_sampling( method fit (line 445) | def fit(self, group_a: Iterable[float], group_b: Iterable[float], rand... method min_of_distrbution (line 471) | def min_of_distrbution(self) -> float: method max_of_distribution (line 479) | def max_of_distribution(self) -> float: method confidence_interval (line 488) | def confidence_interval( method pvalue_criterion (line 526) | def pvalue_criterion(self, alternative: str = "two-sided") -> float: FILE: ambrosia/tools/import_tools.py class NotInstalledPackage (line 24) | class NotInstalledPackage(Exception): method __init_subclass__ (line 27) | def __init_subclass__(cls, default_message: str) -> None: method __init__ (line 31) | def __init__(self, *args, **kwargs): class PysparkNotInstalled (line 38) | class PysparkNotInstalled(NotInstalledPackage, default_message="Install ... function get_installed_package_names (line 42) | def get_installed_package_names() -> tp.List[str]: function check_package (line 46) | def check_package(package_name: str) -> bool: function spark_installed (line 50) | def spark_installed() -> bool: function check_spark_installed (line 54) | def check_spark_installed() -> tp.NoReturn: FILE: ambrosia/tools/knn.py class NMTree (line 34) | class NMTree: method __init__ (line 39) | def __init__(self, points: np.ndarray, payload: np.ndarray, ef_search:... method query_batch (line 65) | def query_batch( FILE: ambrosia/tools/log.py function info_log (line 27) | def info_log(message: str): class RobustLogger (line 32) | class RobustLogger: method verbose (line 39) | def verbose(prev_stats: Dict[str, float], new_stats: Dict[str, float],... method verbose_list (line 49) | def verbose_list( method __calculate_stats (line 62) | def __calculate_stats(values: np.ndarray) -> Dict[str, float]: method get_stats (line 71) | def get_stats( FILE: ambrosia/tools/pvalue_tools.py function calculate_point_effect_by_delta_method (line 25) | def calculate_point_effect_by_delta_method( function calc_statistic_for_delta_method (line 51) | def calc_statistic_for_delta_method( function calculate_pvalue_by_delta_method (line 65) | def calculate_pvalue_by_delta_method( function check_alternative (line 123) | def check_alternative(alternative: str) -> None: function corrected_alpha (line 133) | def corrected_alpha(alpha: Union[float, np.ndarray], alternative: str) -... function choose_from_bounds (line 143) | def choose_from_bounds( function calculate_intervals_by_delta_method (line 162) | def calculate_intervals_by_delta_method( function calculate_pvalue_by_interval (line 222) | def calculate_pvalue_by_interval( FILE: ambrosia/tools/split_tools.py function check_ids_duplicates (line 36) | def check_ids_duplicates( function get_integer_salt (line 52) | def get_integer_salt(salt: Optional[str]) -> int: function encode_id (line 67) | def encode_id(enc_id: Any, salt: str, hash_function: Union[str, Callable... function get_simple_split (line 112) | def get_simple_split( function get_hash_split (line 141) | def get_hash_split( function get_metric_split (line 211) | def get_metric_split( function get_dim_decrease_split (line 259) | def get_dim_decrease_split( function make_labels_for_groups (line 299) | def make_labels_for_groups(groups_number: int) -> List[str]: function add_to_required_size (line 323) | def add_to_required_size( function get_split (line 349) | def get_split( FILE: ambrosia/tools/stat_criteria.py function get_results_dict (line 27) | def get_results_dict(alpha: float, pvalue: float, effect: float, conf_in... function get_calc_effect_ttest (line 34) | def get_calc_effect_ttest(group_a: np.ndarray, group_b: np.ndarray, effe... class TtestIndCriterion (line 46) | class TtestIndCriterion(ABStatCriterion): method calculate_pvalue (line 53) | def calculate_pvalue(self, group_a: np.ndarray, group_b: np.ndarray, e... method calculate_effect (line 62) | def calculate_effect(self, group_a: np.ndarray, group_b: np.ndarray, e... method _build_intervals_absolute (line 65) | def _build_intervals_absolute( method calculate_conf_interval (line 84) | def calculate_conf_interval( method get_results (line 103) | def get_results( class TtestRelCriterion (line 121) | class TtestRelCriterion(ABStatCriterion): method calculate_pvalue (line 128) | def calculate_pvalue(self, group_a: np.ndarray, group_b: np.ndarray, e... method calculate_effect (line 137) | def calculate_effect(self, group_a: np.ndarray, group_b: np.ndarray, e... method _build_intervals_absolute (line 140) | def _build_intervals_absolute( method calculate_conf_interval (line 161) | def calculate_conf_interval( method get_results (line 182) | def get_results( class MannWhitneyCriterion (line 202) | class MannWhitneyCriterion(ABStatCriterion): method calculate_pvalue (line 209) | def calculate_pvalue(self, group_a: np.ndarray, group_b: np.ndarray, e... method calculate_effect (line 215) | def calculate_effect(self, group_a: np.ndarray, group_b: np.ndarray, e... method calculate_conf_interval (line 221) | def calculate_conf_interval( class WilcoxonCriterion (line 237) | class WilcoxonCriterion(ABStatCriterion): method calculate_pvalue (line 244) | def calculate_pvalue(self, group_a: np.ndarray, group_b: np.ndarray, e... method calculate_effect (line 250) | def calculate_effect(self, group_a: np.ndarray, group_b: np.ndarray, e... method calculate_conf_interval (line 256) | def calculate_conf_interval( class ShapiroCriterion (line 270) | class ShapiroCriterion(StatCriterion): FILE: ambrosia/tools/stratification.py class Stratification (line 23) | class Stratification(ab_abstract.StratificationUtil): method __init__ (line 61) | def __init__(self, threshold: Optional[int] = None, verbose: bool = Fa... method fit (line 76) | def fit(self, dataframe: pd.DataFrame, columns: Optional[List[Any]] = ... method strat_sizes (line 102) | def strat_sizes(self) -> Dict[Any, int]: method __corresponding_strat (line 113) | def __corresponding_strat(test_id: Iterable, strat_id: Iterable) -> List: method get_test_inds (line 119) | def get_test_inds(self, test_id: Iterable, id_column: Any = None) -> D... FILE: ambrosia/tools/theoretical_tools.py function get_stats (line 37) | def get_stats(values: Iterable[float], ddof: int = 1) -> Tuple[float, fl... function get_table_stats (line 44) | def get_table_stats(data: pd.DataFrame, column: types.ColumnNameType) ->... function check_encode_alternative (line 51) | def check_encode_alternative(alternative: str) -> str: function unbiased_to_sufficient (line 63) | def unbiased_to_sufficient(std: float, size: int) -> float: function check_target_type (line 71) | def check_target_type( function stabilize_effect (line 87) | def stabilize_effect( function destabilize_effect (line 106) | def destabilize_effect( function get_sample_size (line 125) | def get_sample_size( function get_minimal_determinable_effect (line 188) | def get_minimal_determinable_effect( function get_power (line 249) | def get_power( function get_table_sample_size (line 311) | def get_table_sample_size( function design_groups_size (line 390) | def design_groups_size( function get_minimal_effects_table (line 443) | def get_minimal_effects_table( function design_effect (line 528) | def design_effect( function get_power_table (line 593) | def get_power_table( function design_power (line 679) | def design_power( function get_ttest_info_from_stats (line 744) | def get_ttest_info_from_stats( function get_ttest_info (line 757) | def get_ttest_info(group_a: np.ndarray, group_b: np.ndarray, alpha: np.n... function apply_delta_method_by_stats (line 782) | def apply_delta_method_by_stats( function apply_delta_method (line 841) | def apply_delta_method( function ttest_1samp_from_stats (line 894) | def ttest_1samp_from_stats( FILE: ambrosia/tools/tools.py function bootstrap_over_statistical_population (line 34) | def bootstrap_over_statistical_population( function get_errors (line 114) | def get_errors( function get_empirical_table_power (line 206) | def get_empirical_table_power( function optimize_group_size (line 312) | def optimize_group_size( function calculate_group_size (line 464) | def calculate_group_size( function get_group_sizes (line 550) | def get_group_sizes( function get_empirical_table_sample_size (line 642) | def get_empirical_table_sample_size( function optimize_mde (line 739) | def optimize_mde( function calculate_empirical_mde (line 876) | def calculate_empirical_mde( function get_empirical_mde (line 962) | def get_empirical_mde( function get_empirical_mde_table (line 1054) | def get_empirical_mde_table( FILE: ambrosia/tools/type_checks.py function check_type_decorator (line 27) | def check_type_decorator(type_checker=lambda set_value: set_value): function none_check_decorator (line 47) | def none_check_decorator(function): function check_type_dataframe (line 65) | def check_type_dataframe(dataframe: types.PassedDataType) -> types.Passe... function check_type_id_column (line 80) | def check_type_id_column(id_column: types.ColumnNameType) -> types.Colum... function check_type_id_columns (line 88) | def check_type_id_columns(id_columns: types.ColumnNamesType) -> types.Co... function check_type_group_size (line 98) | def check_type_group_size(groups_size: int) -> int: function check_type_test_group_ids (line 108) | def check_type_test_group_ids(test_group_ids: types.IndicesType) -> type... function check_type_fit_columns (line 116) | def check_type_fit_columns(fit_columns: types.ColumnNamesType) -> types.... function check_type_strat_columns (line 126) | def check_type_strat_columns(strat_columns: types.ColumnNamesType) -> ty... function check_type_salt (line 136) | def check_type_salt(salt: str) -> str: function check_split_method_value (line 144) | def check_split_method_value(split_method: str) -> str: function check_metric_method_value (line 155) | def check_metric_method_value(method_metric: str) -> None: function check_norm_value (line 166) | def check_norm_value(norm: str) -> None: FILE: ambrosia/types.py class PySparkStub (line 28) | class PySparkStub: FILE: tests/conftest.py function local_spark_session (line 16) | def local_spark_session() -> None: function simple_binary_retention_table (line 27) | def simple_binary_retention_table() -> pd.DataFrame: function ltv_and_retention_dataset (line 37) | def ltv_and_retention_dataset() -> pd.DataFrame: function designer_simple_table (line 49) | def designer_simple_table(simple_binary_retention_table): function designer_ltv (line 61) | def designer_ltv(ltv_and_retention_dataset): function designer_ltv_spark (line 73) | def designer_ltv_spark(local_spark_session, ltv_and_retention_dataset): function results_ltv_retention_conversions (line 84) | def results_ltv_retention_conversions() -> pd.DataFrame: function tester_spark_ltv_ret (line 94) | def tester_spark_ltv_ret(local_spark_session, results_ltv_retention_conv... function tester_on_ltv_retention (line 105) | def tester_on_ltv_retention(results_ltv_retention_conversions): function stratification_table (line 119) | def stratification_table() -> pd.DataFrame: function stratificator (line 129) | def stratificator(stratification_table): function answer_ids_strat (line 140) | def answer_ids_strat(stratificator) -> Dict: function id_for_b_strat (line 155) | def id_for_b_strat(stratification_table) -> np.ndarray: function answer_ids_strat_column (line 164) | def answer_ids_strat_column(stratificator) -> Dict: function data_split (line 179) | def data_split() -> pd.DataFrame: function data_index_split (line 189) | def data_index_split() -> pd.DataFrame: function splitter_ltv_spark (line 202) | def splitter_ltv_spark(local_spark_session, ltv_and_retention_dataset): function data_variance_lin (line 213) | def data_variance_lin() -> pd.DataFrame: function data_nonlin_var (line 223) | def data_nonlin_var() -> pd.DataFrame: function data_for_agg (line 233) | def data_for_agg() -> pd.DataFrame: function robust_moments (line 244) | def robust_moments() -> pd.DataFrame: FILE: tests/test_aggregate.py function test_inst (line 9) | def test_inst(): function test_aggregation_by_agg_params (line 14) | def test_aggregation_by_agg_params(data_for_agg): function test_agg_params_priority (line 34) | def test_agg_params_priority(data_for_agg): function test_aggregation_by_week (line 58) | def test_aggregation_by_week(data_for_agg): function test_aggregate_load_store (line 73) | def test_aggregate_load_store(data_for_agg): FILE: tests/test_cuped.py function test_cuped_instance (line 13) | def test_cuped_instance(): function test_multicuped_instance (line 21) | def test_multicuped_instance(): function test_cuped_decrease_var (line 30) | def test_cuped_decrease_var(covariate_column, data_variance_lin): function test_multi_cuped (line 55) | def test_multi_cuped(columns, data_variance_lin): function test_equal_multi_simple (line 70) | def test_equal_multi_simple(column, data_variance_lin): function test_load_store_params (line 87) | def test_load_store_params(Model, factor, data_variance_lin): FILE: tests/test_designer.py function test_instance (line 16) | def test_instance(): function test_constructors (line 24) | def test_constructors(ltv_and_retention_dataset): function test_corret_type (line 42) | def test_corret_type(designer_simple_table, designer_ltv): function test_run_theory (line 65) | def test_run_theory(param_to_design, expected_value, designer): function test_as_numeric (line 84) | def test_as_numeric(param_to_design, method, size, ltv_and_retention_dat... function test_every_type_run (line 106) | def test_every_type_run(to_design, method, effects, sizes, designer_ltv): function test_binary (line 120) | def test_binary(to_design, effects, sizes, designer_ltv, designer_simple... function test_design_function (line 130) | def test_design_function(ltv_and_retention_dataset, designer_ltv): function test_design_binary_function (line 150) | def test_design_binary_function(to_design, effects, sizes, beta, method,... function test_run_theory_spark (line 176) | def test_run_theory_spark(param_to_design, expected_value, designer): function test_empiric_spark (line 195) | def test_empiric_spark(param_to_design, designer): function test_not_available_dataframe (line 206) | def test_not_available_dataframe(): function test_more_alpha_less_size (line 222) | def test_more_alpha_less_size(designer_ltv, method, metric): function test_designer_load_from_config (line 239) | def test_designer_load_from_config(ltv_and_retention_dataset): function test_alternative_parameter (line 265) | def test_alternative_parameter(to_design, method, effects, sizes, design... function test_groups_ratio_parameter (line 302) | def test_groups_ratio_parameter(to_design, method, effects, sizes, desig... FILE: tests/test_ml_variance_reducer.py function test_instance (line 16) | def test_instance(): function test_ml_reduce_variance (line 35) | def test_ml_reduce_variance(data_nonlin_var, columns): function test_store_load_catboost (line 47) | def test_store_load_catboost(data_nonlin_var): FILE: tests/test_preprocessor.py function test_init (line 13) | def test_init(data_nonlin_var): function test_cuped_sequential (line 23) | def test_cuped_sequential(data_nonlin_var): function test_full_sequential (line 38) | def test_full_sequential(data_nonlin_var): function test_load_store_methods (line 55) | def test_load_store_methods(data_nonlin_var): function test_transform_from_config (line 77) | def test_transform_from_config(data_nonlin_var): function test_store_load_config (line 101) | def test_store_load_config(data_for_agg): function test_linearize_basic (line 124) | def test_linearize_basic(data_nonlin_var): function test_linearize_formula (line 135) | def test_linearize_formula(data_nonlin_var): function test_linearize_in_chain (line 149) | def test_linearize_in_chain(data_nonlin_var): function test_linearize_load_store (line 163) | def test_linearize_load_store(data_nonlin_var): function test_linearize_default_name (line 182) | def test_linearize_default_name(data_nonlin_var): FILE: tests/test_robust.py function test_robust_constructor (line 16) | def test_robust_constructor(): function test_robust (line 34) | def test_robust(tail, column_names, alpha, transf_name, data_nonlin_var,... function test_robust_load_store (line 49) | def test_robust_load_store(data_nonlin_var, robust_moments): function test_iqr_constructor (line 68) | def test_iqr_constructor(): function test_iqr (line 84) | def test_iqr(column_names, transf_name, data_nonlin_var, robust_moments): function test_iqr_load_store (line 99) | def test_iqr_load_store(data_nonlin_var, robust_moments): FILE: tests/test_splitter.py function test_instance (line 15) | def test_instance(): function test_constructors (line 23) | def test_constructors(results_ltv_retention_conversions): function test_setter_method (line 35) | def test_setter_method(): function test_all_inputs_metric (line 52) | def test_all_inputs_metric(strat_columns, fit_columns, groups_size, data... function test_split_hash_stable (line 71) | def test_split_hash_stable(strat_columns, groups_size, salt, id_column, ... function test_many_groups_split (line 94) | def test_many_groups_split(groups_size, groups_number, method, strat_col... function test_index_metric (line 113) | def test_index_metric(groups_size, groups_number, data_index_split): function test_fixed_b_group (line 130) | def test_fixed_b_group(groups_size, method, id_column, strat_columns, da... function test_split_function (line 155) | def test_split_function(strat_columns, groups_size, salt, id_column, fit... function test_full_split (line 178) | def test_full_split(ltv_and_retention_dataset, factor, method, strat_col... function test_spark_split (line 195) | def test_spark_split(method, groups_number, strat_columns, splitter_ltv_... function test_full_split_spark (line 209) | def test_full_split_spark(ltv_and_retention_dataset, splitter_ltv_spark,... function test_splitter_load_from_config (line 222) | def test_splitter_load_from_config(ltv_and_retention_dataset): function test_duplication_exception (line 244) | def test_duplication_exception(id_column): function test_duplication_exception_spark (line 263) | def test_duplication_exception_spark(local_spark_session, ltv_and_retent... FILE: tests/test_stratification.py function test_instance (line 10) | def test_instance(): function test_fit (line 19) | def test_fit(stratification_table): function test_strat_sizes (line 34) | def test_strat_sizes(stratificator): function test_test_ids (line 51) | def test_test_ids(ids, column, answer, stratificator): function test_groups_size (line 60) | def test_groups_size(group_size, stratificator): FILE: tests/test_tester.py function check_eq (line 11) | def check_eq(a: float, b: float, eps: float = 1e-5) -> bool: function check_eq_int (line 19) | def check_eq_int(i1, i2) -> bool: function test_instance (line 24) | def test_instance(): function test_constructors (line 32) | def test_constructors(results_ltv_retention_conversions): function test_correct_type (line 48) | def test_correct_type(effect_type, as_table, tester_on_ltv_retention): function test_every_type_run (line 59) | def test_every_type_run(effect_type, method, tester_on_ltv_retention): function check_pvalue_for_interval (line 68) | def check_pvalue_for_interval(interval: Tuple, pvalue: float, alpha: flo... function test_coinf_interval_absolute (line 85) | def test_coinf_interval_absolute(method, alpha, metrics, criterion, test... function test_coinf_interval_relative (line 102) | def test_coinf_interval_relative(method, alpha, metrics, alternative, te... function test_coinf_interval_bin_abs (line 124) | def test_coinf_interval_bin_abs(alpha, metrics, interval_type, alternati... function test_coinf_interval_bin_rel (line 148) | def test_coinf_interval_bin_rel(alpha, metrics, alternative, tester_on_l... function test_standalone_test_function (line 173) | def test_standalone_test_function( function test_criteria_ttest_different (line 199) | def test_criteria_ttest_different(effect_type): function test_kwargs_passing_theory (line 217) | def test_kwargs_passing_theory(criterion, metrics, alternative, tester_o... function test_kwargs_passing_empiric (line 229) | def test_kwargs_passing_empiric(metrics, alternative, tester_on_ltv_rete... function test_kwargs_passing_binary (line 251) | def test_kwargs_passing_binary(interval_type, tester_on_ltv_retention): function get_ci_pvalue (line 264) | def get_ci_pvalue(tester_on_ltv_retention, alternative: str, idx: int = ... function calc_intervals_pvalue (line 274) | def calc_intervals_pvalue(tester_on_ltv_retention, idx: int = 0, **run_k... function check_bound_intervals (line 284) | def check_bound_intervals(int_center, int_less, int_gr, left_bound: floa... function test_alternative_change_binary (line 296) | def test_alternative_change_binary(effect_type, interval_type, tester_on... function test_alternative_change_th (line 313) | def test_alternative_change_th(effect_type, criterion, tester_on_ltv_ret... function test_spark_tester (line 334) | def test_spark_tester(tester_spark_ltv_ret, tester_on_ltv_retention, alt... function test_paired_bootstrap (line 351) | def test_paired_bootstrap(effect_type, alternative): function test_metric_func_constructor (line 390) | def test_metric_func_constructor(results_ltv_retention_conversions): function test_metric_func_run (line 409) | def test_metric_func_run(method, results_ltv_retention_conversions): function test_metric_func_overrides_constructor (line 431) | def test_metric_func_overrides_constructor(results_ltv_retention_convers... function test_metric_func_bootstrap (line 448) | def test_metric_func_bootstrap(results_ltv_retention_conversions): FILE: tests/test_transformers.py function test_boxcox_constructor (line 16) | def test_boxcox_constructor(): function test_boxcox (line 32) | def test_boxcox(column_names, transf_name, data_nonlin_var, robust_momen... function test_boxcox_load_store (line 47) | def test_boxcox_load_store(data_nonlin_var, robust_moments): function test_boxcox_inverse (line 72) | def test_boxcox_inverse(column_names, data_nonlin_var): function test_log_constructor (line 84) | def test_log_constructor(): function test_logarithm (line 100) | def test_logarithm(column_names, transf_name, data_nonlin_var, robust_mo... function test_logarithm_load_store (line 115) | def test_logarithm_load_store(data_nonlin_var, robust_moments): function test_logarithm_inverse (line 140) | def test_logarithm_inverse(column_names, data_nonlin_var):