NumPy vs. PyQtGraph vs. Python vs. blanket.js Comparison Chart

PyQtGraph is a pure-python graphics and GUI library built on PyQt/PySide and NumPy. It is intended for use in mathematics/scientific/engineering applications. Despite being written entirely in python, the library is very fast due to its heavy leverage of NumPy for number crunching and Qt's GraphicsView framework for fast display. PyQtGraph is distributed under the MIT open-source license. Basic 2D plotting in interactive view boxes. Line and scatter plots. Data can be panned/scaled by mouse. Fast drawing for real-time data display and interaction. Displays most data types (int or float; any bit depth; RGB, RGBA, or luminance). Functions for slicing multidimensional images at arbitrary angles (great for MRI data). Rapid update for video display or real-time interaction. Image display with interactive lookup tables and level control. Mesh rendering with isosurface generation. Interactive viewports rotate/zoom with mouse. Basic 3D scenegraph for easier programming.

A seamless JavaScript code coverage library. Blanket.js is a code coverage tool for JavaScript that aims to be easy to install, easy to use, and easy to understand. Blanket.js can be run seamlessly or can be customized for your needs. JavaScript code coverage compliments your existing JavaScript tests by adding code coverage statistics (which lines of your source code are covered by your tests). Parsing the code using Esprima and node-falafel, and instrumenting the file by adding code tracking lines. Connecting to hooks in the test runner to output the coverage details after the tests have been completed. A Grunt plugin has been created to allow you to use Blanket like a "traditional" code coverage tool (creating instrumented copies of physical files, as opposed to live-instrumenting). Runs the QUnit-based Blanket report headlessly using PhantomJS. Results are displayed on the console, and the task will cause Grunt to fail if any of your configured coverage thresholds are not met.