![]() ICYMI Python on Microcontrollers Newsletter: The Python powered synth is here #Python #ICYMI « Adafruit Industries – Makers, hackers, artists, designers and engineers! on Making an IoT Badge – #badgelife going corporate.Seif on How-To: Installing JDeveloper on Your Mac.» DevNexus 2019 links aclairefication on Developer Experience: How Do We Improve.vineet sharma on How-To: Installing JDeveloper on Your Mac.Playing at work promotes discovery, opens door to innovation.User Research at the Forefront of Technology.Developing concept products that embrace emerging technologies.Making an IoT Badge – #badgelife going corporate.I’m looking forward to what Fun With Maps you come up with next! So I added some other bits and pieces, and “a bit” of glow and, hey presto the Tron-alike Alameda 3000!Īs you say it would be cool to layer some more interesting data on top of this. That’s about 800k points and 450k triangles, but modern GPUs can sling that around without too many issues. Unsurprisingly, the wireframe ( ) looks pretty much the same as your SVG outline. Inspired by your beautiful map, I thought I’d run Alameda through my workflow and see what happens. Then I use a tweaked version of the plugin to import it into the engine and dynamically generate the mesh data. Open Street Map data’s super-fun to play around with isn’t it! I’ve been using it to build realistic 3d environments in Unreal Engine. Census data and apply it to my own maps to reveal hidden patterns. ![]() In my next installment of Fun With Maps, I will learn how to tap into U.S. The possibilities, both for business and personal uses, are endless. The abundance of open source mapping data, and tools like OSM and Mapzen, allow anyone to make their own maps. This is the problem with open source data: it’s free but often incomplete. Some features did come with metadata that allowed me to identify fire stations, hospitals, gas stations, schools, etc.) but the coverage was spotty. I created a Mapzen account and downloaded Alameda OSM data to check it out. GeoJSON is just an ordinary JSON file with a standardized structure that associates metadata with boundary paths in a consistent way. Like many recent open source mapping tools, Mapzen exports data in a format called GeoJSON. They charge for polished products and high-volume data, but small amounts of data for personal projects are often free. Mapzen is a commercial site which packages open source street map data and does much of the dirty work for you. If you don’t want to reverse engineer your own map using only SVG paths, there are alternatives. The negative space around buildings is eloquent. ![]() Even if you strip away all other paths, the building outlines alone nicely trace the overall shape of the island and even local features like lagoons and streets. ![]() I now discover that there are 20,199 individual structures on the island: houses, detached garages, businesses, apartment buildings, etc. I have only to pause the movie, note the index where one section ends and the next begins, and separate it all into distinct piles. The land features (low tide boundaries, lagoons, airport runways, etc.) are in one section, building footprints in the next, streets after that, labels after that. When I hit play the result is moving spotlight which reveals how the paths are ordered.įortunately there is a discernible order. I take a tour of my data by making a quick NodeBox movie: I slice 100 paths at a time and shift the starting point with each frame. To do this I find the island’s outline path feeding that into a Delete node removes everything outside it. My first step is to get rid of that corner of Oakland and all the gunk outside the main island. There is no metadata from here on out I have to reverse engineer everything myself. When I import this file into NodeBox and ungroup it I have nothing but 37,688 individual vector paths.
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