Skip to content

on_boarding.md

Latest commit

 

History

History
157 lines (127 loc) · 22.8 KB

on_boarding.md

File metadata and controls

157 lines (127 loc) · 22.8 KB
graph LR
    Core_Data_Structures["Core Data Structures"]
    Data_Ingestion["Data Ingestion"]
    Chromatogram_Processing["Chromatogram Processing"]
    Dataset_Management_Analysis["Dataset Management & Analysis"]
    Serialization_Utilities["Serialization Utilities"]
    Data_Ingestion -- "creates" --> Core_Data_Structures
    Chromatogram_Processing -- "operates on" --> Core_Data_Structures
    Dataset_Management_Analysis -- "manages" --> Core_Data_Structures
    Dataset_Management_Analysis -- "orchestrates" --> Chromatogram_Processing
    Core_Data_Structures -- "uses" --> Serialization_Utilities
    Dataset_Management_Analysis -- "uses" --> Serialization_Utilities
    click Core_Data_Structures href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/MOCCA/Core Data Structures.md" "Details"
    click Data_Ingestion href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/MOCCA/Data Ingestion.md" "Details"
    click Chromatogram_Processing href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/MOCCA/Chromatogram Processing.md" "Details"
    click Dataset_Management_Analysis href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/MOCCA/Dataset Management & Analysis.md" "Details"
    click Serialization_Utilities href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/MOCCA/Serialization Utilities.md" "Details"
Loading

CodeBoardingDemoContact

Component Details

The MOCCA project provides a comprehensive framework for chromatographic data analysis. Its main flow involves ingesting raw instrument data into well-defined core data structures. These structures are then subjected to a series of processing steps, including baseline correction, peak detection, and deconvolution, orchestrated by the Chromatogram Processing component. For multi-sample analysis, the Dataset Management & Analysis component handles collections of processed chromatograms, applies global settings, and performs higher-level tasks like component clustering. Throughout the system, a dedicated Serialization Utilities component ensures that complex data objects can be efficiently stored and retrieved.

Core Data Structures

Defines the fundamental data structures for representing 2D chromatographic data, individual chromatograms, and derived entities like peaks, deconvolved peaks, components, and compounds. These structures serve as the primary data carriers throughout the MOCCA system.

Related Classes/Methods:

Data Ingestion

Responsible for parsing raw chromatographic data from various instrument-specific formats (e.g., Chemstation, Labsolutions) into the internal Core Data Structures. It also provides access to example datasets for testing and demonstration.

Related Classes/Methods:

Chromatogram Processing

Provides the core functionalities for processing individual chromatograms, including baseline correction, peak detection (finding, splitting, merging), and deconvolution of overlapping peaks using various algorithms and peak models.

Related Classes/Methods:

Dataset Management & Analysis

Manages collections of Chromatogram objects, applies processing settings across multiple datasets, and performs higher-level analytical tasks such as clustering components to identify common compounds.

Related Classes/Methods:

Serialization Utilities

Provides generic utility functions for converting complex Python objects into dictionary representations, enabling their serialization and deserialization for persistence or data exchange.

Related Classes/Methods:

FAQ