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Grafana: The open and composable observability platform
Faster answers, predictable costs, and no lock-in built by the team helping to make observability accessible to anyone.
Grafana is the open source analytics & monitoring solution for every database.
PyNanoLab contains a variety of tools to complete the data analysis, statistics, curve fitting, and basic machine learning application. Visualization in pynanolab is based on matplotlib. The setup tools is desinged to control and set-up all the details of the figure with a GUI.
The purpose of the SCiDA Pro program is to help with processing solar cell production data. It has the following features:
- Able to handle large data sets in a fast way (e.g. plotting 100k cell data takes a few seconds)
- Easy data filtering
- Easy generation of a data summary report
- Extensive data plotting features
- Cross-platform (Windows/Linux/MacOS)
- Supports multiple languages
Olex2 is visualisation software for small-molecule crystallography developed at Durham University/EPSRC. It provides comprehensive tools for crystallographic model manipulation for the end user and an extensible development framework for programmers. The project has been supported by Olexsys Ltd since 2010.
An intuitive molecular editor and visualization tool
Avogadro is an advanced molecular editor designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science and related areas. It offers a flexible rendering framework and a powerful plugin architecture.
Martus Solutions provides seamless budgeting, reporting, and forecasting tools that integrate with accounting systems for real-time financial insights
Martus' collaborative and easy-to-use budgeting and reporting platform will save you hundreds of hours each year. It's designed to make the entire budgeting process easier and create unlimited financial transparency.
MIVF - Medical Imaging and Visualization Factory,
is a framework for medical applications. It supplies a platform, in which image processing and 3D visualization algorithms can be employed as reusable components (functional modules or plugins).