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    Application_Orchestrator["Application Orchestrator"]
    Data_Manager_Simulator["Data Manager & Simulator"]
    Matching_Algorithms["Matching Algorithms"]
    Feature_Transformer["Feature Transformer"]
    Balance_Evaluator["Balance Evaluator"]
    Results_Visualizer["Results Visualizer"]
    Application_Orchestrator -- "manages workflow for" --> Data_Manager_Simulator
    Application_Orchestrator -- "initiates execution of" --> Matching_Algorithms
    Data_Manager_Simulator -- "provides raw data to" --> Feature_Transformer
    Data_Manager_Simulator -- "provides raw data to" --> Results_Visualizer
    Feature_Transformer -- "transforms data from" --> Data_Manager_Simulator
    Feature_Transformer -- "supplies processed data to" --> Matching_Algorithms
    Feature_Transformer -- "supplies processed data to" --> Balance_Evaluator
    Matching_Algorithms -- "consumes processed data from" --> Feature_Transformer
    Matching_Algorithms -- "requests evaluation from" --> Balance_Evaluator
    Matching_Algorithms -- "generates outcomes for" --> Results_Visualizer
    Balance_Evaluator -- "evaluates processed data from" --> Feature_Transformer
    Balance_Evaluator -- "provides metrics to" --> Matching_Algorithms
    Results_Visualizer -- "displays raw data from" --> Data_Manager_Simulator
    Results_Visualizer -- "displays outcomes from" --> Matching_Algorithms
    Results_Visualizer -- "displays metrics from" --> Balance_Evaluator
    click Application_Orchestrator href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/pybalance/Application Orchestrator.md" "Details"
    click Data_Manager_Simulator href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/pybalance/Data Manager & Simulator.md" "Details"
    click Matching_Algorithms href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/pybalance/Matching Algorithms.md" "Details"
    click Feature_Transformer href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/pybalance/Feature Transformer.md" "Details"
    click Balance_Evaluator href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/pybalance/Balance Evaluator.md" "Details"
    click Results_Visualizer href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/pybalance/Results Visualizer.md" "Details"
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Component Details

This graph illustrates the high-level architecture of the pybalance project, a library designed for causal inference matching. It depicts the primary components involved in data handling, feature transformation, various matching algorithms, balance evaluation, and result visualization, all orchestrated by a central application flow.

Application Orchestrator

The central control unit, responsible for initiating the application's workflow, managing data flow, and coordinating the execution of matching, balance calculation, and visualization processes.

Related Classes/Methods:

  • pybalance.bin.main (full file reference)

Data Manager & Simulator

Handles all aspects of data, including loading, splitting, and managing datasets. It also provides functionalities for generating synthetic data for testing and simulation.

Related Classes/Methods:

Matching Algorithms

Contains the core logic for various matching strategies (Propensity Score, Linear Programming, Genetic Algorithm). It processes data to find optimal matches and relies on balance metrics for optimization.

Related Classes/Methods:

Feature Transformer

Provides a suite of tools for preprocessing raw data features into suitable formats for downstream components, including encoding, binning, and cross-term generation.

Related Classes/Methods:

Balance Evaluator

Implements various metrics to quantify the balance and similarity between matched populations, crucial for assessing matching quality and guiding iterative algorithms.

Related Classes/Methods:

Results Visualizer

Generates graphical representations of data characteristics, matching outcomes, and the historical progression of balance metrics for analysis and reporting.

Related Classes/Methods:

FAQ