Crate deep_causality_discovery Copy item path Source analyze_config causal_discovery_config cdl_config data_csv_config data_loader_config data_parquet_config data_preprocess_config feature_selector_config mrmr_config surd_config AnalyzeConfig Configuration for the analysis phase of the CDL pipeline. CDL The core builder for the Causal Discovery Language (CDL) pipeline. CdlBuilder CdlConfig The master configuration struct for a CDL pipeline. CdlEffect CdlEffectWitness A witness type that “fixes” the Error (E) and Warning Log (WLog) types
for CdlEffect, implementing the HKT and HKT3 traits. CdlReport Aggregates all significant findings from a CDL pipeline execution. CdlWarningLog ConsoleFormatter A concrete implementation of ProcessResultFormatter that formats an analysis for display in the console. CsvConfig Configuration for loading data from a CSV file. CsvDataLoader A concrete implementation of ProcessDataLoader for reading data from CSV files. DataDiscretizer A concrete implementation of DataPreprocessor that discretizes continuous data into bins. Finalized Final state (marker). MissingValueImputer A pre-processor for handling missing numerical data in a CausalTensor. MrmrConfig Configuration for the MRMR (Max-Relevance, Min-Redundancy) feature selector. MrmrFeatureSelector A concrete implementation of the FeatureSelector trait that uses the MRMR algorithm. NoData Initial state of the CDL pipeline, with no data loaded. OptionNoneDataCleaner ParquetConfig Configuration for loading data from a Parquet file. ParquetDataLoader A concrete implementation of ProcessDataLoader for reading data from Parquet files. PreprocessConfig Configuration for a data discretization pre-processing step. ProcessAnalysis A wrapper struct holding the results of an analysis as a vector of strings. ProcessFormattedResult A wrapper struct holding the final, formatted output of the CDL pipeline. SurdCausalDiscovery A concrete implementation of the CausalDiscovery trait using the SURD algorithm. SurdConfig Configuration for the SURD (Synergistic, Unique, Redundant Decomposition) algorithm. SurdResultAnalyzer An implementation of ProcessResultAnalyzer for SurdResult. WithAnalysis State after the raw causal results have been analyzed. WithCausalResults State after a causal discovery algorithm has been run. WithCleanedData State after data has been cleaned. WithData State after data has been successfully loaded. WithFeatures State after feature selection has been applied. AnalyzeError BinningStrategy CausalDiscoveryConfig An enum representing the configuration for a specific causal discovery algorithm. CausalDiscoveryError CdlError CdlWarning ColumnSelector DataCleaningError DataLoaderConfig An enum representing the configuration for a specific data loader. DataLoadingError FeatureSelectError FeatureSelectorConfig An enum representing the configuration for a specific feature selection algorithm. FinalizeError MaxOrder Defines the maximum order of interactions to consider in the SURD analysis. PreprocessError CausalDiscovery Defines the contract for causal discovery algorithms. DataCleaner DataLoader Defines the contract for loading data from a source into a CausalTensor. DataPreprocessor Defines the contract for data pre-processing steps. FeatureSelector Defines the contract for feature selection algorithms. ProcessResultAnalyzer Defines the contract for analyzing the raw results of a causal discovery algorithm. ProcessResultFormatter Defines the contract for formatting an analysis into a final output string. mrmr_features_selector Selects features using the mRMR (Maximum Relevance, Minimum Redundancy) algorithm. surd_states_cdl Decomposes mutual information into its Synergistic, Unique, and Redundant components
for each state of the target variable, based on the SURD-states algorithm,
specifically designed to handle input tensors with Option<f64> values.