background preloader



OpenCV on iOS - GPU usage HelpMeViz - Helping people with everyday data visualizations VerbalExpressions/JSVerbalExpressions Selected Tools positive lookahead | Jump Point Search Explained <p><strong>Please note:</strong> this post contains SVG diagrams rendered with javascript. Please view it in a browser to see all the content.</p> There are several related algorithms for finding the shortest path on a uniform-cost 2D grid. The Jump Point Search algorithm, introduced by Daniel Harabor and Alban Grastien, is one such way of making pathfinding on a rectangular grid more efficient. I am assuming familiarity with the A* search algorithm, and more generally, Dijkstra’s for pathfinding. For these examples, I’m assuming pathfinding on a regular square grid where horizontal and vertical movement costs 1 and diagonal movement costs √2̅. Try It Out You can play with A* and JPS here. Path Expansion and Symmetry Reduction During each iteration of A*, we expand our search in the best known direction. In the research paper, Harabor and Grastien call these “symmetric paths” because they’re effectively identical. Expanding Intelligently Looking Ahead Horizontally and Vertically Notes

What I Learned Recreating One Chart Using 24 Tools Back in May of this year, I set myself a challenge: I wanted to try as many applications and libraries and programming languages in the field of data visualization as possible. To compare these tools on a level playing field, I recreated the same scatterplot (also called a bubble chart) with all of them. Based on the results, I published two listicles: One for data vis applications and one for data vis libraries and programming languages. An overview of all the tools I tried can be found in this Google Spreadsheet. Full disclosure: My experiment was highly influenced by the tools I already knew before I started trying new ones. Here’s a GIF of me recreating the same chart with 12 different apps: And here’s a picture of all the different outcomes of the charting libraries: Let’s start! There Are No Perfect Tools, Just Good Tools for People with Certain Goals Data visualization is a communication form used by many subfields, e.g. science, business and of course journalism. Analysis vs.

ios - Bluetooth Low Energy - updating a characteristic value repeatedly BYOB If you want to build your own BoosterPack or LaunchPad kit, visit to access the resources needed to get started. LaunchPad & BoosterPack Standard This standard defines the physical & electrical specifications of all TI MCU LaunchPad Evaluation Platforms. This standard is also meant to be applied to all BoosterPack plug-in modules made by TI and third parties, however, TI cannot guarantee compliance for third party kits. Following this standard can maximize success in creating a LaunchPad that will support the BoosterPack ecosystem. Introduction Disclaimer It is important to note that this standard ensures only physical and electrical compatability between a LaunchPad baseboard and a BoosterPack plugin module. Additionally, this document does not guarantee cross-compatability/stackability of multiple BoosterPacks. TI recommends that you use the smallest footprint that fits your requirements when creating a new BoosterPack to ensure maximum reusability. Definitions Part Number:

• Instagram Developer Documentation