.. _application_features: LabPlot Features ================= .. contents:: General Features ----------------- - Project based management of data - Tree-like organization of created objects - Quick navigation, searching and filtering of objects using the Project Explorer - Easy customization of objects and methods using the Properties Explorer - Folders support for a better object management - Spreadsheet and Matrix – data-container serving as the data source used in data analysis and visualization - Spreadsheet linking to synchronize the number of rows across multiple spreadsheets - Worksheet – area for placing different visualization objects (plots, labels, images, etc) supporting different layouts, zooming and navigation mode - Notes – a text container which can simply be used to write comments into a project - The undo history dialog - Locale-sensitive functionality - Autosave to prevent potential data loss - Support for CLI parameters (e.g. to start LabPlot directly in the Presenter Mode) - Support for multiple application color schemes, including dark themes - Customizable application layouts using a full featured window docking system Data Visualization ------------------- - High-quality, interactive and very fast data visualization optimized for large data sets - Arbitrary number of plots in the plot area - Highly configurable and publication-quality 2D Plots: scatter plots, line plots, histograms, box plots, bar plots, rug plots, KDE plots, Q-Q plots, Lollipop plots - Support for multiple, freely positionable axes, inverse axis scales and multiple ranges for plots - Smooth and fast zooming and navigation modes for plots - Function plotting with Cartesian, Polar and Parametric equations - Customizable and positionable plot legends, text labels, info elements, images, reference lines and reference ranges for plots - Color Maps Browser with an extensive support for scientific and color-vision deficiency friendly color schemes like ColorBrewer, ColorCET, Scientific Colour Maps, cocean, viridis - Multiple default and user-defined themes for Worksheets and plots, including Edward Tufte’s ‘Maximal Data, Minimal ink’ theme, - User-defined plot templates that make it easy to create and customize plots that are intended to be used multiple times - Cursor – tool to measure positions and distances in plots - Dynamic Presenter Mode for worksheets with the full-screen mode and the navigation panel - Sparklines in the header of a spreadsheet - Preview panel for all available worksheets in the project - Support for Latex syntax in plot labels, plot titles, Computational Notebooks and multiple dialogs - A possibility to use multiple LaTeX engines (LuaLaTex, pdfLaTex, LaTex) Data Analysis and Statistics -------------------------------- - Column statistics spreadsheet – child spreadsheet showing various statistical properties of the parent spreadsheet - Linear and non-linear regression analysis and curve fitting, support for several predefined and user-defined fit models – Basic Functions like polynomial, power or exponential; Peak Functions like Gaussian, Cauchy-Lorentz, Pseudo-Voigt, hyperbolic secant, logistic; Growth Functions like Gompertz, Hill, Gudermann, inverse tangent, logistic and error functions; Statistical Functions like Gaussian, exponential, power, log-normal, binomial, Poisson, Rayleigh, Landau, Pareto, Weibull and many more - Maximum Likelihood estimation for fitting statistical distributions like Gaussian Poisson, Exponential, Laplace, Binomial, Cauchy-Lorentz and more - Baseline subtraction (background correction) with the asymmetrically re-weighted penalized least squares (arPLS) algorithm - Data reduction by removing data points using multiple algorithms (Douglas-Peucker, Visvalingam-Whyatt, Reumann-Witkam, Opheim, Lang and other algorithms) - Numerical differentiation (up to the 6th order) and numerical integration (rectangular, trapezoid and Simpson methods) - Smoothing of data with moving average, Savitzky-Golay and percentile filter methods - Interpolation of data, support for many methods (linear, polynomial, splines, piecewise cubic Hermite polynomial, etc.) - Fourier transform of the input data with support for many different window functions (Welch, Hann, Hamming, Blackman, etc.) - Fourier Filter – low-pass, high-pass, band-pass and band-reject filters of different types (Butterworth, Chebyshev I+II, Legendre, Bessel-Thomson) - Hilbert Transform including envelope - Convolution and de-convolution of data sets (sampling interval, linear/circular, normalization, wrap, standard kernel) - Auto-correlation and cross-correlation of data sets (sampling interval, linear/circular, normalization) - Quick statistical previews available in spreadsheets that consist of multiple location, dispersion and shape measures for quantitative and categorical data and statistical plots like histograms, KDE plots, Q-Q plots, box plots, Pareto plot - Extensive parser for mathematical expressions supporting a great number of functions and constants used for data generation in spreadsheets and further data analysis and visualization - Function values dialog (editor) with the syntax highlighting and support for reference to arbitrary cells of columns and other moving functions Computational Notebooks ------------------------ - An interactive and animated front-end to powerful mathematics and statistics packages and programming languages like Maxima, Octave, R, Scilab, Sage, KAlgebra, Qalculate!, Python, Julia, Lua - Support for using multiple notebooks and languages at the same time - Notebook variables holding array-like data (Maxima lists, Python lists and tuples, etc.) can be used as the source for interactive plots - Ability to show variable statistics and to plot data from the context menu in the project explorer for variables created in a Notebook - Extensive edition capability - Support for plotting - Markdown and LaTeX syntax - Ability to read Jupyter and Cantor projects - Syntax highlighting - Integrated help for CAS systems and programming languages (downloading, searching, navigating documentation etc.) - Support for exporting Notebooks to PDF Plot Digitization ------------------- - Easy extraction of data from external image files - Cartesian, polar, logarithmic and ternary coordinate system - Symmetric and asymmetric error bars - Manual point-by-point extraction of data points or (semi-)automated extraction of curve segments - Multiple curves on the image can be read - Basic image editing capabilities to reduce the image information to the relevant minimum - Extracted data is added to a spreadsheet and is directly ready to use Data Generation and Processing ------------------------------- - Support for Tidy Data in spreadsheets, i.e. variables are stored in columns, each observation is stored in a row and the values for each observation is stored in its respective cell - Quantitative and categorical data types: Integer, Double, Big Integer (64 bit), Date and Time, Text (Categorical) - Data sorting - Extended search and replace with the support for regular expressions - Data transformation, normalization and standardization - Random number generation with support for multiple probability distributions - Data sampling (random and periodic methods) - Data ‘flattening’ – converting pivoted data to the column-based format - Support for dropping and masking of data in spreadsheets - Heatmap formatting with the support for scientific and color-vision deficiency friendly color maps Documentation and Support -------------------------- - Extensive user manual and tutorials - Short, instructional video tutorials - Project examples and educational data sets available through LabPlot’s dialogs - Relation type based gallery of plots with downloadable project files - LabPlot is an open-source project offered in multiple languages - Available for Windows, macOS, Linux, FreeBSD and Haiku - LabPlot team offers multiple channels of communication