ictonyx.exceptions

Exception classes and error types.

Custom exception classes for the ictonyx library.

This module defines all exception types used throughout ictonyx, providing clear error categorization, context information, and better debugging experience.

exception ictonyx.exceptions.IctonyxError(message, context=None)

Bases: Exception

Base exception class for ictonyx library.

Provides common functionality for all ictonyx exceptions including context tracking and enhanced error reporting.

Parameters:

• message (str)

• context (Dict[str, Any] | None)

add_context(key, value)

Add contextual information to the exception.

Parameters:

• key (str)

• value (Any)

Return type:

IctonyxError

get_context_summary()

Get a formatted summary of the error context.

Return type:

str

exception ictonyx.exceptions.DataValidationError(message, data_info=None, validation_rule=None)

Bases: IctonyxError, ValueError

Raised when data validation fails.

Inherits from ValueError for compatibility with existing error handling that expects ValueError for invalid data.

Parameters:

• message (str)

• data_info (Dict[str, Any] | None)

• validation_rule (str | None)

classmethod for_splits(test_split, val_split)

Factory method for split validation errors.

Parameters:

• test_split (float)

• val_split (float)

Return type:

DataValidationError

classmethod for_empty_dataset(dataset_name, expected_size=None)

Factory method for empty dataset errors.

Parameters:

• dataset_name (str)

• expected_size (int | None)

Return type:

DataValidationError

exception ictonyx.exceptions.ModelError(message, model_info=None, operation=None, model_state=None)

Bases: IctonyxError

Raised when model-related operations fail.

Includes information about the model state and operation that failed.

Parameters:

• message (str)

• model_info (Dict[str, Any] | None)

• operation (str | None)

• model_state (str | None)

classmethod training_failed(model_type, epoch=None, error_details=None)

Factory method for training failures.

Parameters:

• model_type (str)

• epoch (int | None)

• error_details (str | None)

Return type:

ModelError

classmethod prediction_failed(model_type, input_shape=None, error_details=None)

Factory method for prediction failures.

Parameters:

• model_type (str)

• input_shape (tuple | None)

• error_details (str | None)

Return type:

ModelError

exception ictonyx.exceptions.ExperimentError(message, experiment_info=None, run_id=None, stage=None, failure_count=None)

Bases: IctonyxError

Raised when experiment execution fails.

Tracks experiment state, run information, and failure patterns.

Parameters:

• message (str)

• experiment_info (Dict[str, Any] | None)

• run_id (int | None)

• stage (str | None)

• failure_count (int | None)

classmethod high_failure_rate(failed_runs, total_runs, threshold=0.5)

Factory method for high failure rate errors.

Parameters:

• failed_runs (int)

• total_runs (int)

• threshold (float)

Return type:

ExperimentError

classmethod resource_exhausted(resource_type, run_id=None)

Factory method for resource exhaustion errors.

Parameters:

• resource_type (str)

• run_id (int | None)

Return type:

ExperimentError

exception ictonyx.exceptions.StatisticalTestError(message, test_info=None, data_summary=None, suggestion=None)

Bases: IctonyxError, ValueError

Raised when statistical test prerequisites aren’t met.

Provides detailed information about what validation failed and suggestions for remediation.

Parameters:

• message (str)

• test_info (Dict[str, Any] | None)

• data_summary (Dict[str, Any] | None)

• suggestion (str | None)

classmethod insufficient_data(test_name, sample_size, minimum_required=3)

Factory method for insufficient data errors.

Parameters:

• test_name (str)

• sample_size (int)

• minimum_required (int)

Return type:

StatisticalTestError

classmethod invalid_distribution(test_name, issue, data_properties=None)

Factory method for distribution assumption violations.

Parameters:

• test_name (str)

• issue (str)

• data_properties (Dict[str, Any] | None)

Return type:

StatisticalTestError

exception ictonyx.exceptions.ConfigurationError(message, config_info=None, invalid_params=None, valid_options=None)

Bases: IctonyxError

Raised when configuration validation fails.

Helps users understand what configuration options are invalid and provides guidance on valid alternatives.

Parameters:

• message (str)

• config_info (Dict[str, Any] | None)

• invalid_params (List[str] | None)

• valid_options (Dict[str, Any] | None)

classmethod invalid_parameter(param_name, param_value, valid_options=None, valid_range=None)

Factory method for invalid parameter errors.

Parameters:

• param_name (str)

• param_value (Any)

• valid_options (List[Any] | None)

• valid_range (tuple | None)

Return type:

ConfigurationError

ictonyx.exceptions.validate_not_empty(data, name, min_size=1)

Utility function to validate data is not empty.

Parameters:

• name (str)

• min_size (int)

ictonyx.exceptions.validate_splits(test_split, val_split)

Utility function to validate train/val/test splits.

Parameters:

• test_split (float)

• val_split (float)

ictonyx.exceptions.validate_statistical_input(data, name, min_samples=3)

Utility function to validate data for statistical tests.

Parameters:

• name (str)

• min_samples (int)