LabPlot: Difference between revisions

Revision as of 03:26, 17 August 2024

Revision as of 09:18, 17 August 2024

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{{Short description|Application for interactive graphing and analysis of scientific data}}

{{notability|date=July 2024}}

{{Infobox software

| name = LabPlot

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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'''<ref>{{Cite web|title=LabPlot features|date=28 July 2024|url=https://labplot.kde.org/features/|publisher=LabPlot Team}}</ref> ==

== 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 | autosave]], and locale-sensitive features. It supports [[command-line interface | 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 plot | scatter plots]], [[line chart | line plots]], [[bar chart | bar plots]], [[histogram | histograms]], [[box plot | box plots]], [[rug plot | rug plots]], [[Kernel density estimation | KDE plots]], [[Q-Q plot | Q-Q plots]], [[Pareto chart | Pareto plots]], [[sparkline | 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 [[probability distribution | statistical distributions]] and offers advanced data processing like [[noise reduction | baseline subtraction]], data reduction (line simplification) with e.g. the [[Ramer–Douglas–Peucker algorithm]], [[numerical differentiation]] and [[numerical integration | integration]], and [[smoothing | data smoothing]]. Sophisticated [[signal processing]] functions such as [[Fourier transform | Fourier transforms and filtering]], [[Hilbert transform | Hilbert transforms]], [[convolution]], and [[correlation | 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 [[notebook interface | computational notebook]] that integrates with mathematics and statistics packages and programming languages like [[Python (programming language) | Python]], [[R (programming language) | R]], [[Julia (programming language) | Julia]], [[Maxima (software) | Maxima]], [[GNU Octave]], [[Scilab]], [[SageMath]], [[KAlgebra]], [[Qalculate!]], [[Lua (programming language) | 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 [[Project_Jupyter#Jupyter_Notebook | Jupyter]] and [[Cantor (software) | 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 [[Comma-separated values | CSV]], [[Microsoft Excel]], [[OpenDocument | ODF]], [[SAS (software) | SAS]], [[SPSS]], [[MATLAB]], [[SQL]], [[JSON]], [[binary file | binary files]], [[hierarchical data format | HDF5]], [[MQTT]], [[FITS]], [[NetCDF]], [[ROOT | ROOT (CERN)]], [[LTspice]], [[Ngspice]]. [[Real-time data]] can be read through Unix/[[User datagram protocol | UDP]]/[[Transmission Control Protocol | TCP]] sockets and [[serial port | serial ports]]. Users can export data to formats such as [[PDF]], [[PNG]], [[JPG]], [[SVG]], and [[BMP file format | BMP]], or directly to the clipboard, and print notes, worksheets, and plots. Data can be exported to [[Comma-separated values | 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 (statistics) | data transformation]], [[normalization (statistics) | normalization]], and [[feature scaling | standardization]], as well as [[random number generation]] and [[sampling (statistics) | sampling methods]]. It offers functionality to restructure pivoted data, selectively drop or mask data, and create [[heat map]] visualizations with [[color blindness | 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]].<ref>{{Cite web|title=Homepage of Dr. Stefan Gerlach|date=30 June 2016|url=http://theorie.physik.uni-konstanz.de/gerlach/|publisher=Theoretische Physik Uni Konstanz}}</ref>

== Community ==

The LabPlot team promotes a collaborative community through various communication channels.<ref>{{Cite web|title=LabPlot Support|date=28 July 2024|url=https://labplot.kde.org/support/|publisher=LabPlot Team}}</ref> The developers support the idea of [[mentorship]] of students and actively participate in such programs as the Season of KDE (SoK)<ref>{{Cite web|title=The Season of KDE (SoK)|date=28 July 2024|url=https://mentorship.kde.org/blog/2024-01-15-sok-24-welcome/|publisher=KDE}}</ref> or [[Google Summer of Code]] <ref>{{Cite web|title=Google Summer of Code Program 2024|date=28 July 2024|url=https://summerofcode.withgoogle.com/programs/2024/organizations/kde-community|publisher=Google}}</ref>.

== User privacy ==

LabPlot is designed to be compliant with [[KDE]] Telemetry Policy, which forbids the usage of unique identification.<ref>{{Cite web|title=KDE Telemetry Policy|date=28 July 2024|url=https://community.kde.org/Policies/Telemetry_Policy|publisher=KDE}}</ref>

== External links ==

* [https://labplot.kde.org LabPlot Homepage]

==See also==

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==References==

{{Reflist}}

== External links ==

* [https://labplot.kde.org LabPlot Homepage]

* [https://nlnet.nl/project/LabPlot/ NLnet Foundation grant]

{{KDE}}