Autoplot

AutoPlot is a Mac-native scientific workspace designed for plotting and exploratory data analysis. It empowers users to import tabular datasets, define variables, and generate a wide array of visualizations including X&Y plots, histograms, heat maps, correlation matrices, and 3D plots. The application also facilitates running fits and composing publication-quality figures with vector export capabilities. The development of AutoPlot was driven by the repetitive nature of data analysis workflows. Scientists and researchers often found themselves exporting data, opening notebooks, and pasting extensive plotting and fitting code, only to tweak parameters and re-run the entire process. This manual, time-consuming "plumbing" detracted from the core analytical work. AutoPlot aims to streamline this by automating the code generation and execution, allowing users to focus on the insights derived from their data. Key features of AutoPlot include its comprehensive plotting capabilities. Users can create standard X&Y plots, histograms, Probability Density Functions (PDFs), and Complementary Cumulative Distribution Functions (CCDFs). For more advanced analysis, it supports custom fits, heat maps with Gaussian-mixture fitting, 3D surface plots, and correlation matrices. Specialized tooling for power-law analysis, including log-binned fits and FSS collapse, is also integrated. Another significant aspect is its interactive visualization engine. Leveraging Metal-backed GPU rendering, AutoPlot ensures that 3D scenes and correlation networks remain interactive even with full-sized datasets. This means users can rotate, zoom, and re-fit data without experiencing delays from redrawing, maintaining a fluid workflow. The application also offers robust data manipulation and AI-driven assistance. In "Agent mode," users can describe analyses, and the app generates and runs the corresponding Python code, building cards, variables, and fits within the workspace. Every generated script requires user confirmation before execution, and accepted code is saved for reproducibility. "File Operations mode" allows for sandboxed manipulation of files within a specified folder, such as skipping headers or splitting data, acting as a replacement for command-line tools. AutoPlot's approach emphasizes user control and data privacy. All algorithms, whether pre-constructed or AI-generated, run directly on the user's device. The AI assistant only processes data headers and returns Python code that is executed locally. This ensures that raw data never leaves the user's Mac, providing a secure environment for analysis. The benefits for users include a significant reduction in the time spent on repetitive coding tasks, enabling faster iteration and exploration of data. The interactive visualizations and publication-ready export options streamline the process of creating and sharing findings. The focus on local data processing enhances security and privacy. Concrete use cases for AutoPlot include researchers who need to quickly generate publication-quality figures from experimental data, data scientists performing exploratory data analysis on large datasets, and anyone who wants to automate repetitive data manipulation and visualization tasks without extensive coding. It's particularly useful for analyzing complex datasets where interactive 3D plots and correlation matrices are essential. AutoPlot is a native macOS application, requiring macOS 15+. The product is free to use. While specific integrations are not detailed, the output is designed to be compatible with standard scientific Python libraries, and vector exports can be edited in applications like Pixelmator. In summary, AutoPlot provides a powerful, integrated environment for scientific data analysis and visualization on macOS, combining AI-driven code generation with high-performance rendering and a strong emphasis on user privacy and workflow efficiency.