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 Screenshot of LabPlot of 2022 | |
| Original author(s) | Stefan Gerlach |
|---|---|
| Developer(s) | KDE |
| Initial release | 2001; 24 years ago (2001) (version 0.1, under the name QPlot) 2003; 22 years ago (2003) (version 1.0, renamed to LabPlot) |
| Stable release | 2.11.1 / 16 July 2024; 5 months ago (2024-07-16) |
| Repository | invent |
| Written in | C, C++ |
| Operating system | Microsoft Windows OS X Linux FreeBSD Haiku |
| Type | Scientific plotting Data analysis Curve fitting Regression analysis Statistical analysis Data processing Plot digitization Notebook interface Real-time data |
| License | GPL-2.0-or-later |
| Website | labplot |
LabPlot is a free and open-source, cross-platform computer program for interactive scientific plotting, curve fitting, nonlinear regression, data processing and data analysis. LabPlot is available, under the GPL-2.0-or-later license, for Windows, macOS, Linux, FreeBSD and Haiku operating systems.
It has a graphical user interface, a command-line interface and an interactive and animated notebook interface to mathematical and statistical packages and programming languages.
Features
General features
LabPlot is a project-based data management, visualization and analysis tool with a tree-like structure for organizing objects. It features data containers like Spreadsheets and Matrices, and a Worksheet for flexible visualization. The program offers Notes for annotations, undo history, autosave, and locale-sensitive features. It supports command-line parameters, multiple color schemes, and customizable layouts through a window docking system.
Data visualization
LabPlot is a data visualization and analysis tool designed for large datasets. It offers a wide range of 2D plotting options, including scatter plots, line plots, bar plots, histograms, box plots, rug plots, KDE plots, Q-Q plots, Pareto plots, sparklines and Lollipop plots. The software supports multiple axes, flexible positioning of elements, and smooth navigation. It provides various color map options, user-defined themes, and advanced features like LaTeX support.
Data analysis and statistics
The program features a column statistics spreadsheet that details statistical properties and excels in regression analysis with both linear and non-linear curve fitting using the Levenberg–Marquardt algorithm, supporting numerous predefined and user-defined models. It includes Maximum likelihood estimation for fitting various statistical distributions and offers advanced data processing like baseline subtraction, data reduction (line simplification) with e.g. the Ramer–Douglas–Peucker algorithm, numerical differentiation and integration, and data smoothing. Sophisticated signal processing functions such as Fourier transforms and filtering, Hilbert transforms, convolution, and correlation analyses are supported. Quick statistical previews and visualizations are available for quantitative and categorical data. Enhanced functionality includes a mathematical expression parser and a function values dialog with syntax highlighting for complex data generation and manipulation.
Notebook interface
Labplot features an interactive and animated computational notebook that integrates with mathematics and statistics packages and programming languages like Python, R, Julia, Maxima, GNU Octave, Scilab, SageMath, KAlgebra, Qalculate!, Lua. It supports multiple notebooks and languages simultaneously. Users can create interactive plots from notebook variables and display statistics and plots directly from the context menu. The program offers Markdown and LaTeX support. It can read Jupyter and Cantor projects, provides syntax highlighting, integrated help, and supports exporting notebooks to PDF.
Data import and export
LabPlot offers a set of features for data handling and analysis. It has no practical limits on data size other than the physical constraints of a computer. LabPlot supports importing various file formats like CSV, Microsoft Excel, ODF, SAS, SPSS, MATLAB, SQL, JSON, binary files, HDF5, MQTT, FITS, NetCDF, ROOT (CERN), LTspice, Ngspice. Real-time data can be read through Unix/ UDP/ TCP sockets and serial ports. Users can export data to formats such as PDF, PNG, JPG, SVG, and BMP, or directly to the clipboard, and print notes, worksheets, and plots. Data can be exported to CSV, Microsoft Excel, SQL databases, and LaTeX tables. The drag and drop functionality and templates for import filters simplify the process. Sharing the project via email, Nextcloud, etc. directly from the main menu is also supported. Additionally, the program includes nearly 2000 real-world data sets.
Plot digitization
LabPlot can extract and analyze data from image files across various coordinate systems. It supports error bar analysis and offers both manual and automated data extraction methods. The software can process multiple curves from a single image, includes basic image editing tools, and integrates extracted data into spreadsheets for immediate use.
Data generation and processing
LabPot offers a suite of features for data management and analysis in spreadsheets. It adheres to Tidy Data principles, supports various data types, and provides sorting and search capabilities. The software includes tools for data transformation, normalization, and standardization, as well as random number generation and sampling methods. It offers functionality to restructure pivoted data, selectively drop or mask data, and create heat map visualizations with color-vision deficiency friendly options.
Documentation
LabPlot features a user guide, tutorials, and instructional videos to facilitate learning. Users can access project examples and educational data sets. The software includes a gallery of plots with downloadable project files. It is available in multiple languages.
History
LabPlot was initiated by Stefan Gerlach, a scientist and IT administrator at the University of Konstanz.
Community
The LabPlot team promotes a collaborative community through various communication channels. The developers support the idea of mentorship of students and actively participate in such programs as the Season of KDE (SoK) or Google Summer of Code .
User privacy
LabPlot is designed to be compliant with KDE Telemetry Policy, which forbids the usage of unique identification.
External links
See also
- List of statistical software
- List of information graphics software
- Comparison of numerical-analysis software
References
- "LabPlot 2.11.1 – LabPlot". 16 July 2024.
- "LabPlot features". LabPlot Team. 28 July 2024.
- "Homepage of Dr. Stefan Gerlach". Theoretische Physik Uni Konstanz. 30 June 2016.
- "LabPlot Support". LabPlot Team. 28 July 2024.
- "The Season of KDE (SoK)". KDE. 28 July 2024.
- "Google Summer of Code Program 2024". Google. 28 July 2024.
- "KDE Telemetry Policy". KDE. 28 July 2024.
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