Open Source Python Data Visualization Software - Page 13

--UPDATE-- New Version is now integrated in the official PyMOL plugin repository! --UPDATE-- The BNI (Beyond Normal Interaction)- Tools is a plug in for the PyMOL molecular visualization system which adds additional functionalities and presets to the PyMOL GUI and also adds useful extended commands.

Visualize and analyze 3D data files using 2D colorplots. Inspired by spyview. Written in python.

Fitta is a program for making and plotting statistical fits, simple and weighted fit, high quality plots thanks to the matplotlib library

is a interactive molecular visualisation program designed especially designed for coarse-grained simulation of non-spherical particles. Ellipsoids (Gay-Berne), disks, and custom shaped uniaxial particle (e.g. pear-shaped particles) can be represented.

Python based webservice to manage and display information from some fiber-GISes.

A toolbox of open source geospatial essentials

This is a collection of Python functions, with which data can be exported from the Python environment to a file which can be viewed in GoogleEarth.

Geo-Spatial Data Viewer (GSDView) is a lightweight viewer for geo-spatial data and products. It is written in python and Qt4 and uses the GDAL library. GSDView is modular and has a simple plug-in architecture.

Harkay un software desarrollado en Python para la administraccion de un firewall de acceso a internet diseñado teniendo en cuenta su facilidad de uso y potencia. La politica por defecto es denegar todo habilitando puntualmente lo que se desea.

Python project with goal to provide FOSS library to extract, analyse and visualise data in a 3D fashion. The instance will connect to a data source, ods sheet, csv, sql DB, pyodbc the instance will analyse and/or transform the data to be presented to the visualisation functionality the instance will visualise the data in a 3D fashion, likely using third party FOSS

This is the public icram.de code repository filled with code/code-snippets and other useful stuff.

Small python script that can visualize Inter Process Communication on Linux. It can create a graph of TCP and Unix sockets, pipes and also process hierarchy. Short (59 sec) demo visualizing ssh client connecting to ssh server on the same Ubuntu host: http://youtu.be/8XFKwzkexQY Longer (2 min 13 sec) demo visualizing ZoneMinder surveillance solution operation (stopping, starting, enabling and viewing camera): http://youtu.be/kM7klE61Ibk Tested on Ubuntu 14.10 and Debian 7. Quick start on Ubuntu/Debian: # apt-get install graphviz python-pygraphviz # ./ipcvis.py

Create charts with Python in a very similar way to creating charts using Chart.js. The charts created are fully configurable, interactive, and modular and are displayed directly in the output of the cells of your jupyter notebook environment. Charts are fully interactive, you can hover it to display tooltips and select the information you want to see directly from the output cell of your notebook. All the types of charts present in Chart.js are exposed in ipychart. Even complex features such as mixed-types charts are available. Charts are highly customizable and all Chart.js options are available in ipychart. You have complete control over the appearance of your chart.

Yet another GUI for Kernel-based Virtual Machines.

Python software package for 3D tracking of leg joints in walking insects. Published as Bender et al., PLoS ONE, 2010 (http://dx.doi.org/10.1371/journal.pone.0013617)

L(atex)equation aims to be the simplest latex to bitmap converter there is. Its goals are: simple gui, simple install, mac + windows + ubuntu binaries and it just should work.

TODO

Messy datasets? Missing values? missingno provides a small toolset of flexible and easy-to-use missing data visualizations and utilities that allows you to get a quick visual summary of the completeness (or lack thereof) of your dataset. Just pip install missingno to get started. This quickstart uses a sample of the NYPD Motor Vehicle Collisions Dataset dataset. The msno.matrix nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion. At a glance, date, time, the distribution of injuries, and the contribution factor of the first vehicle appear to be completely populated, while geographic information seems mostly complete, but spottier. The sparkline at right summarizes the general shape of the data completeness and points out the rows with the maximum and minimum nullity in the dataset. This visualization will comfortably accommodate up to 50 labelled variables.

nb-clean cleans Jupyter notebooks of cell execution counts, metadata, outputs, and (optionally) empty cells, preparing them for committing to version control. It provides both a Git filter and pre-commit hook to automatically clean notebooks before they're staged, and can also be used with other version control systems, as a command line tool, and as a Python library. It can determine if a notebook is clean or not, which can be used as a check in your continuous integration pipelines. nb-clean can also be used as a pre-commit hook. You may prefer this to the Git filter if your project already uses the pre-commit framework. Note that the Git filter and pre-commit hook work differently, with different effects on your working directory. The pre-commit hook operates on the notebook on disk, cleaning the copy in your working directory. The Git filter cleans notebooks as they are added to the index, leaving the copy in your working directory dirty.

NCVTK: A VTK-based tool to visualize data stored in the NetCDF file format.

This toolbox generates automatically a vtk-visualization for an ode (Open Dynamics Engine) simulation under Python. You only have to define the simulation space and world and forward these entities to the visualization. That's all... Install also via pip possible: pip install odeViz

openSim is a software platform for the creation, simulation and visualization of system dynamics models.

Real-time data visualization. Graphically view your data as it's being generated. Peakster is a very intuitive GUI written entirely in Python, which monitors data at regular intervals and uses gnuplot to render 2D, 3D and superimposed plots.

Portable Plot is a pure ansi/iso c++ plot library that makes the construction of native plot widgets easy.

pyEBSD-GUI is a free software to post-process Electron Backscatter Diffraction (EBSD) data, inducing IPF mapping, image quality mapping, phase mapping etc, plotting pole figure, data segmentation, statistic analysis of the misorientation distribution etc. The software is written by python, and it supports both script and graphic user interface (GUI). pyEBSD V1.0 will be released soon.