Open Source Python Data Visualization Software - Page 7

HyperTools is a library for visualizing and manipulating high-dimensional data in Python. It is built on top of matplotlib (for plotting), seaborn (for plot styling), and scikit-learn (for data manipulation). Functions for plotting high-dimensional datasets in 2/3D. Static and animated plots. Simple API for customizing plot styles. Set of powerful data manipulation tools including hyperalignment, k-means clustering, normalizing and more. Support for lists of Numpy arrays, Pandas dataframes, text or (mixed) lists. Applying topic models and other text vectorization methods to text data. HyperTools is designed to facilitate dimensionality reduction-based visual explorations of high-dimensional data. The basic pipeline is to feed in a high-dimensional dataset (or a series of high-dimensional datasets) and, in a single function call, reduce the dimensionality of the dataset(s) and create a plot.

Analysis software for Nbody/SPH or SPH simulations (e.g. performed with Gadget II). See http://sourceforge.net/apps/wordpress/hyplot/about and http://sourceforge.net/apps/trac/hyplot/wiki for more information.

math lib for .NET. n-dim arrays, complex numbers, linear algebra, FFT, sorting, cells- and logical arrays as well as 3D plotting classes help developing algorithms on every platform supporting .NET. Sources from SVN, binaries: http://ilnumerics.net

IPyPlot is a small python package offering fast and efficient plotting of images inside Python Notebooks. It's using IPython with HTML for faster, richer and more interactive way of displaying big numbers of images.

IVuPy is a set of Python bindings for the Coin3D C++ class libraries which serve to create software for 3D visualization in science and engineering. IVuPy aims to be a solid basis for large Python programs for 3D visualization and data analysis.

This is a collection of different little tools written in MATLAB, JAVA, Python. They all have to to do with Imaging & Microscopy for life science research and related topics or problems. Some of them are meant to be used with ImageJ and MicroManager.

InkPlot is an extension (plugin) for the SVG Editor Inkscape to insert graphs from Gnuplot. It allows you to - preview the graph - add it as SVG into Inkscape - edit already generated graphs - use a preamble file for reusable style and commands - customize default settings in a config file

Project moved to https://codelv.com/projects/inkcut/ Code move to https://github.com/codelv/inkcut/ Forum moved to https://inkcut.org/

*Project home now moved to Google Code.* Numerical computing and plotting tools for IronPython.

The enhanced Python fork of JILL, Julia Installer for Linux (and every other platform), Light.

"JSBSim Python Bindings" is a Python wrapper around the open source flight dynamics model JSBSim (http://jsbsim.sourceforge.net/). It allows to use most of the JSBSim C++ API from the Python programming language.

Jupytab allows you to explore in Tableau data which is generated dynamically by a Jupyter Notebook. You can thus create Tableau data sources in a very flexible way using all the power of Python. This is achieved by having Tableau access data through a web server created by Jupytab.

A framework for visualization.

KALE (Kubeflow Automated pipeLines Engine) is a project that aims at simplifying the Data Science experience of deploying Kubeflow Pipelines workflows. Kubeflow is a great platform for orchestrating complex workflows on top Kubernetes and Kubeflow Pipeline provides the mean to create reusable components that can be executed as part of workflows. The self-service nature of Kubeflow make it extremely appealing for Data Science use, at it provides an easy access to advanced distributed jobs orchestration, re-usability of components, Jupyter Notebooks, rich UIs and more. Still, developing and maintaining Kubeflow workflows can be hard for data scientists, who may not be experts in working orchestration platforms and related SDKs. Additionally, data science often involve processes of data exploration, iterative modelling and interactive environments (mostly Jupyter notebook).

Karesansui is an open-source virtualization management application made in Japan. It's smart graphical user interface lowers your management cost, and brings a total management/audit solution for both physical and virtual servers. Full featured RESTful interface allows customizing and integration with other management/billing systems.

Krisk brings Echarts to the Python Data Science Ecosystem, and helpful tools for high-level statistical interactive visualization.

MBDyn_sim_suite is a collection of free pre&post-processing tools and simulation models for the open-source multi-body analysis software MBDyn forming a general purpose simulation environment for structural dynamics with an emphasis on wind turbines.

MCNPydE is a Python library for extracting data from MCNP output file. It requires Python, Matplotlib and Numpy. It is a data reduction tool for MCNP output for ease of results analysis and viewing.

Mainly a browser for medical patients documents. For now, it works for displaying radiology images in DICOM format. It supports Query/Retrieve. Build on Python, wxPython and ZODB.

The Model Interaction Environment for Neuroscience provides tools for development, searching, editing, execution, and visualization of biophysical models, abstract mathematical models, and experimental protocols used in neuroscience research.

A High-Order Multi-Variate Approximation Scheme for Arbitrary Data Sets, C implementation of the method described in http://web.mit.edu/qiqi/www/paper/interpolation.pdf, with Python and Fortran interfaces.

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).

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model management, and "dnn" is the acronym of deep neural network. We implement a universal converter to convert DL models between frameworks, which means you can train a model with one framework and deploy it with another. During the model conversion, we generate some code snippets to simplify later retraining or inference. We provide a model collection to help you find some popular models. We provide a model visualizer to display the network architecture more intuitively. We provide some guidelines to help you deploy DL models to another hardware platform.

MSCViewer is a tool intended for debugging of control flows in concurrent, distributed systems. The tool loads logs generated by various entities in the system and visualize a sequence diagram chart for events and interactions. The diagram is fully interactive: entity can be added/removed from the diagram and shuffled; events can be filtered, searched, highlighted and annotated with comments. MSCViewer features integration with a Python interpreter which allows writing Python scripts interacting with the model. This powerful feature can be used to automate validatation of distributed control flows, integrate with graphing infrastructure, etc.

MVS - Math Visualization System (See description on homepage)