Composable data visualisation library for web with a data-first approach now powered by WebAssembly

JavaScript library that makes managing the data behind client-side visualisations easy

A scientific charting library focused on performance optimised real-time data visualisation at 25 Hz update rates for data sets with a few 10 thousand up to 5 million data points.

The InteractiveVis project, funded by JISC from May to September 2012, aims to allow easy creation of interactive visualisations for geospatial and network data using native web technologies (HTML5, CSS3, and SVG) and allow these visualisations to be self-contained so that they may run entirely offline in ebooks and other media. The project will survey existing solutions and build the necessary components to fill in missing features and smooth over incompatibilities in between existing libraries. The project will further provide online hosted wizards to allow for the easy creation of these interactive visualizations. All code is open source and released under the GNU GPL v3 license.

Data visualisations using Om and JavaScript libraries

A library to find and visualise the most interesting slices in multidimensional data

Repository of small data analysis and visualisation projects to try out libraries and create new types of visualisations. Mostly using Python.

A Repository consisting of various visualisation libraries and tools

Clojure Data Visualisation library, based on Statistiker and D3

A SA:MP UI library for rendering progress bars used to visualise all manner of data from health to a countdown timer.

# XFEM_Fracture2D ### Description This is a Matlab program that can be used to solve fracture problems involving arbitrary multiple crack propagations in a 2D linear-elastic solid based on the principle of minimum potential energy. The extended finite element method is used to discretise the solid continuum considering cracks as discontinuities in the displacement field. To this end, a strong discontinuity enrichment and a square-root singular crack tip enrichment are used to describe each crack. Several crack growth criteria are available to determine the evolution of cracks over time; apart from the classic maximum tension (or hoop-stress) criterion, the minimum total energy criterion and the local symmetry criterion are implemented implicitly with respect to the discrete time-stepping. ### Key features * *Fast:* The stiffness matrix and the force vector (i.e. the equations' system) and the enrichment tracking data structures are updated at each time step only with respect to the changes in the fracture topology. This ultimately results in the major part of the computational expense in the solution to the linear system of equations rather than in the post-processing of the solution or in the assembly and updating of the equations. As Matlab offers fast and robust direct solvers, the computational times are reasonably fast. * *Robust.* Suitable for multiple crack propagations with intersections. Furthermore, the stress intensity factors are computed robustly via the interaction integral approach (with the inclusion of the terms to account for crack surface pressure, residual stresses or strains). The minimum total energy criterion and the principle of local symmetry are implemented implicitly in time. The energy release rates are computed based on the stiffness derivative approach using algebraic differentiation (rather than finite differencing of the potential energy). On the other hand, the crack growth direction based on the local symmetry criterion is determined such that the local mode-II stress intensity factor vanishes; the change in a crack tip kink angle is approximated using the ratio of the crack tip stress intensity factors. * *Easy to run.* Each job has its own input files which are independent form those of all other jobs. The code especially lends itself to running parametric studies. Various results can be saved relating to the fracture geometry, fracture mechanics parameters, and the elastic fields in the solid domain. Extensive visualisation library is available for plotting results. ### Instructions 1. Get started by running the demo to showcase some of the capabilities of the program and to determine if it can be useful for you. At the Matlab's command line enter: ```Matlab >> RUN_JOBS.m ``` This will execute a series of jobs located inside the *jobs directory* `./JOBS_LIBRARY/`. These jobs do not take very long to execute (around 5 minutes in total). 2. Subsequently, you can pick one of the jobs inside `./JOBS_LIBRARY/` by defining the job title: ```Matlab >> job_title = 'several_cracks/edge/vertical_tension' ``` 3. Then you can open all the relevant scripts for this job as follows: ```Matlab >> open_job ``` The following input scripts for the *job* will be open in the Matlab's editor: 1. `JOB_MAIN.m`: This is the job's main script. It is called when executing `RUN_JOB` (or `RUN_JOBS`) and acts like a wrapper. Notably, it can serve as a convenient interface to run parametric studies and to save intermediate simulation results. 2. `Input_Scope.m`: This defines the scope of the simulation. From which crack growth criteria to use, to what to compute and what results to show via plots and/or movies. To put it simply, the script is a bunch of "switches" that tell the program what the user wants to be done. 3. `Input_Material.m`: Defines the material's elastic properties in different regions or layers (called "phases") of the computational domain. Moreover, it defines the fracture toughness of the material (assumed to be constant in all material phases). 4. `Input_Crack.m`: Defines the initial crack geometry. 5. `Input_BC.m`: Defines boundary conditions, such as displacements, tractions, crack surface pressure (assumed to be constant in all cracks), body loads (e.g. gravity, pre-stress or pre-strain). 6. `Mesh_make.m`: In-house structured mesh generator for rectangular domains using either linear triangle or bilinear quadrilateral elements. It is possible to mesh horizontal layers using different mesh sizes. 7. `Mesh_read.m`: Gmsh based mesh reader for version-1 mesh files. Of course you can use your own mesh reader provided the output variables are of the correct format (see later). 8. `Mesh_file.m`: Specifies the mesh input file (.msh). At the moment, only Gmsh mesh files of version-1 are allowed. ### Mesh_file.m A mesh file needs to be able to output the following data or variables: * `mNdCrd`: Node coordinates, size = `[nNdStd, 2]` * `mLNodS`: Element connectivities, size = `[nElemn,nLNodS]` * `vElPhz`: Element material phase (or region) ID's, size = `[nElemn,1]` * `cBCNod`: cell of boundary nodes, cell size = `{nBound,1}`, cell element size = `[nBnNod,2]` Example mesh files are located in `./JOBS_LIBRARY/`. Gmsh version-1 file format is described [here](http://www.manpagez.com/info/gmsh/gmsh-2.4.0/gmsh_60.php). ### Additional notes * global variables are defined in `.\Routines_AuxInput\Declare_Global.m` * External libraries are `.\Other_Libs\distmesh` and `.\Other_Libs\mesh2d` ### References Two external meshing libraries are used for the local mesh refinement and remeshing at the crack tip during crack propagation or prior to a crack intersection with another crack or with a boundary of the domain. Specifically, these libraries, which are located in `.\Other_Libs\`, are the following: * [*mesh2d*](https://people.sc.fsu.edu/~jburkardt/m_src/mesh2d/mesh2d.html) by Darren Engwirda * [*distmesh*](http://persson.berkeley.edu/distmesh/) by Per-Olof Persson and Gilbert Strang. ### Issues and Support For support or questions please email [sutula.danas@gmail.com](mailto:sutula.danas@gmail.com). ### Authors Danas Sutula, University of Luxembourg, Luxembourg. If you find this code useful, we kindly ask that you consider citing us. * [Minimum energy multiple crack propagation](http://hdl.handle.net/10993/29414)

Explore audio and images with one line of code. Python plotting library for data visualisation.

Arduino library for sending data to MegunoLink visualisers and useful components

Comparison of Python packages and libraries for visualising geospatial vector data: applications for Smarter Cities.

Data visualisation library, written in Rust

Audioviz is a simple and easy to use library that helps you visualise raw audio-data

iOS library for analysing/visualising audio data at real-time

The aim is to try and build some interactive log visualisations using dash in notebooks and demonstrate what is possible (and also what the limitations are) using dash on subsurface data. Ultimately it would be good to try and collate all the examples into a library of templates to share after the Hackathon :swung: I have put together a quick Google Sheet with some initial ideas, so feel free to either pick one that interests you or add something to the list that you think would be fun to make, all ideas welcome.

Example integration of xsens-mti library with STM32F4 discovery. Data visualisations with Electric UI.

A data visualisation animation made with Processing library

Python library unifying Positron Emission Particle Tracking (PEPT) research, including tracking, simulation, data analysis and visualisation tools.

R package for visualising high-dimensional categorical data. Fully ggplot compatible implementation for the diceplot plotting library

Exploring 118 wells of 1 MM+ rows and 29 columns of wireline petrophysical data using the Pandas library. Analysed & Visualised wireline logs petrophysical dataset using - Pandas, Numpy, Matplotlib, Plotly & seaborn libraries Discovered insights of wireline logs quality & interpretation (missing data and imbalance class

Quick data visualisation in terminal console (csv/tsv/etc). A small R library for use outside R. Scatter, bar, and histogram plots are supported.

Use pandas, Data visualisation libraries(Matplotlib or Seaborn) to establish conclusions about a dataset.

Javascript library to browse, visualise, and access, data from an OGC Sensor Observation Service.

An open source time series analysis library for processing, analyzing, visualising and forecasting time series data

Notebook, data and Dash app used in talk on visualisation libraries

No description available

An Arduino Library to facilitate serial communication with the xIMU3 GUI data visualisation software.