Getting Started

MassFlow is a modular computational framework for Mass Spectrometry Imaging (MSI) and Mass Spectrometry (MS) data, providing efficient data reading, preprocessing, and management capabilities. Note: This project is still under development. Please refer to the code comments in the dev branch. Technical documentation is for reference only.

Prerequisites

• uv (Python project management tool)

Get the Source Code

It is recommended to obtain the repository via:

• Clone (Recommended):

  git clone https://github.com/NeoNexusX/MassFlow.git
  cd MassFlow

• Fork then Clone (For contributing):

  git fork https://github.com/NeoNexusX/MassFlow.git
  # Then clone your Fork

• Download ZIP: Click GitHub "Code" → "Download ZIP" and extract locally.

Set up Python Environment

close conda first:
  conda deactivate

uv install part:
  https://docs.astral.sh/uv/getting-started/installation/

For Example :
  Linux && Macos :
  curl -LsSf https://astral.sh/uv/install.sh | sh 
  Windows:
  powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Install dependencies:
uv sync 

uv pip install -e .

Run Examples and Tests

Tests use the pytest framework. See: https://docs.pytest.org/en/stable/

Run all tests:

uv run pytest

Run a specific test:

uv run pytest tests/test_read.py

If the virtual environment managed by uv is already activated, you can omit uv run:

pytest tests/test_read.py

Example Code Snippet:

# Quick snippet: Read .imzML and plot occupancy mask
from massflow.module.ms_module import MS
from massflow.module.ms_data_manager_imzml import MSDataManagerImzML

FILE_PATH = "data/your_file.imzML"
ms = MS()
with MSDataManagerImzML(ms=ms, target_locs=[(1, 1), (50, 50)], filepath=FILE_PATH) as manager:
    manager.load_full_data_from_file()
    manager.inspect_data()
    ms.plot_ms_mask()

The code above demonstrates MSI/MS data reading and basic visualization. Logs are output to logs/.

Common Commands

Documentation build commands:

• Build static site: npm run docs:build
• Preview built site: npm run docs:preview

Next Steps

• Contribution Guide: /en/contribution
• Naming Conventions: /en/naming-conventions
• Data Structures: /en/ms-data-structures
• Noise Reduction: /en/noise_reduction
• Baseline Correction: /en/baseline_correction
• Collaboration Guide: /en/collaboration_guide
• More documents...