Introduction¶

plotfig is a Python library designed specifically for scientific data visualization, dedicated to providing efficient, easy-to-use, and beautiful plotting tools for cognitive neuroscience researchers. This project is developed based on mainstream visualization libraries in the industry—matplotlib, surfplot, and plotly, integrating their powerful features to meet the complex plotting needs in neuroscience and brain connectomics across various scenarios.

Project Structure¶

The project adopts a modular design, containing the following main functional modules:

• bar.py: Bar chart plotting, suitable for comparative display of grouped data.
• matrix.py: General matrix visualization, supporting multiple color schemes and annotation methods.
• correlation.py: Correlation matrix visualization, facilitating analysis of correlation distributions between variables.
• circos.py: Circos plot visualization, suitable for planar display of connections between brain regions.
• brain_surface.py: Brain surface visualization, enabling plotting of 3D brain surface atlas structures.
• brain_connection.py: Glass brain connectivity visualization, supporting complex brain network structure display.

Features¶

• The plotfig API has a simple design with flexible parameters, making it suitable for researchers and data analysts to quickly integrate into their data analysis workflows.
• Its modular architecture facilitates future feature expansion and custom development.
• Combined with matplotlib, it supports vector graphics, high-resolution bitmap, and interactive HTML output, suitable for paper publication and academic presentation.

Fun fact: All elements of a figure¹.