Welcome to the documentation of the HDF5_BLS project!

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About HDF5_BLS

The HDF5_BLS project is a Python package allowing users to store Brillouin Light Scattering relevant data in a single HDF5 file. The package is designed to integrate in existing Python workflows, to be minimally constrained, and to be as easy to use as possible. The package is meant to answer three main specifications:

• Simplicity: Make it easy to store and retrieve data from a single file.

• Universality: Allow all modalities to be stored in a single file, while unifying the metadata associated to the data.

• Unification: Allow and develop unified data processing tools to be used on BLS data.

A project aiming at unifying and standardizing the storage of Brillouin Light Scattering (BLS) data in a HDF5 files, and to develop unified tools to process these data.

This documentation is intended to help users to understand the project and to use it in their own workflows.

GitHub repository: https://github.com/bio-brillouin/HDF5_BLS

For any question, please contact the main developer of the project: Pierre Bouvet

The project

• The project in a nutshell
  • The strategy for unifying the field of Brillouin Light Scattering (BLS) data
  • A quick overview
  • File format limitations
  • Storing different datasets in the file format
• Project development
  • Project specification sheet
  • Project structure
  • Project timeline
  • User interfaces
• Quickstart
  • Spirit of the project
  • Installation
  • Usage
    • Integration to workflow
    • Extracting the data from the HDF5 file
    • Importing external data
• The file format
  • A single measure
  • A single measure with physical meaning
  • Multiple measures stored in the same file
  • Multiple measures stored with their results
  • Multiple measures stored with their results and algorithms
• Normalization rules for the BioBrillouin community
  • Normalization rules for attributes
    • The Brillouin_type Attributes
    • Hierarchical strorage of attributes
    • Attribute type
    • Organization of the attributes
      • Prefix
      • Units
    • Storing analysis and treatment processes performed with the HDF5_BLS package
    • Storing custom data processing code and visualization code
  • Normalization rules for datasets
    • General guidelines
    • Hierarchical storage of abscissa datasets
    • Clarification on dataset shapes
    • Uniform sampling examples
      • Series of measures on a 1D array
      • Series of measures on a 2D grid
  • Normalization rules for organizing HDF5 files

User Guide

• The HDF5_BLS package
  • Installation and presentation
    • Installation
      • With pip
      • From source
    • Presentation
  • The Wrapper object
  • Adding data to the HDF5 file (from script)
    • General approach to adding data to the HDF5 file
    • Exception 1: Adding treated data
    • Exception 2: Adding an abscissa
  • Importing data from external files
    • General approach for importing data
  • Adding and merging HDF5 files
  • Attributes
    • Using NormalizedAttributes
    • Adding Attributes to a Wrapper
    • Validation and Recommended Values
    • Exporting the Nomenclature
    • Bulk Import of Attributes
  • Tutorial
    • HDF5_BLS Library: Comprehensive Researcher Tutorial
      • Methods Index
    • 1. Initialization: Starting a Session
    • 2. Organizing the Hierarchy
    • 3. Adding Data and Metadata
      • Common Derived Methods
      • Using Derived Methods for raw data, PSD and frequency arrays
      • Using Derived Methods for treated data
      • Using Derived Methods for abscissa arrays
      • Adding Metadata (Attributes)
      • The Underlying Method behind all the derived methods for adding things to the file: add_dictionary
    • 4. Merging files
      • Combining Datasets (combine_datasets)
    • 5. Inspection and Visualization
    • 6. Accessing Data
    • 7. Export
    • 8. Error Handling Reference
• Data Processing with HDF5_BLS
  • Specifications
  • Organization of the modules
    • HDF5_BLS_analyse
    • HDF5_BLS_treat
  • Usage points common to both modules
  • Using the HDF5_BLS_analyse module
    • Example with a VIPA spectrometer
  • Using the HDF5_BLS_treat module
    • Example
• The HDF5_BLS_analyse package
  • Installation and presentation
    • Installation
      • With pip
      • From source
    • Presentation
• The HDF5_BLS_treat package
  • Installation and presentation
    • Installation
      • With pip
      • From source
    • Presentation

GUI

• Managing Attributes with the GUI
  • Adding Attributes
  • Removing Attributes
  • Exporting the Standardized List

Developer Guide

• Presentation of the project for developers
  • Structure of the GitHub repository
  • Documentation
  • Docstrings
• Setting up the development environment on Visual Studio Code
  • Setting up VS Code for Python development
    • Installing VS Code
    • Installing Python extension in VS Code
  • Creating your own GitHub branch and copy of the HDF5_BLS repository
    • Installing the Git extension in VS Code
    • Creating the HDF5_BLS repository locally
    • Creating the virtual environment
    • Clone the GitHub repository
    • Branching the main repository of the project
    • Install the packages in editable mode
    • Adding the paths to the sources of the three packages to the Python interpreter of the VS Code workspace
  • Creating the repository for your scripts
    • Create your local repository for using the HDF5_BLS package
    • Create the virtual environment of your repository
    • Install the packages in editable mode
    • Adding the paths to the sources of the three packages to the Python interpreter of the VS Code workspace
• Adding a new file format to the HDF5_BLS library

API

• HDF5_BLS
  • HDF5_BLS.Wrapper
  • HDF5_BLS.load_data
  • HDF5_BLS.errors
• HDF5_BLS_analyse
  • HDF5_BLS_analyse.Analyse_backend
  • HDF5_BLS_analyse.Analyse_general
  • HDF5_BLS_analyse.Analyse_VIPA
• HDF5_BLS_treat
  • HDF5_BLS_treat.Treat_backend
  • HDF5_BLS_treat.Models
  • HDF5_BLS_treat.TreatmentError
  • HDF5_BLS_treat.Treat