2d:null 2e:["$","title",null,{"children":"Imitation Game 🖐 | Matt Dzugan | Observable"}] 33:T41c,Orientation = { var o = []; for(var x=0; x d3.max(x))); var minValue = d3.min(M.map(x => d3.min(x))); var colorscale = d3.scaleLinear().domain([0,125,135,255]).range([color1,color1,color2,color2]); for (var i = 0; i < imgData.data.length; i += 4) { //var myvalue = M[Math.floor(i/4/w)][i/4 % w]; var myvalue = M[i/4 % w][Math.floor(i/4/w)]; if(method=='phase'){ var alpha = 255*((myvalue+1000*Math.PI) % (2*Math.PI))/(2*Math.PI); }else if(method=='cos'){ var alpha = 255*(Math.cos(myvalue)); }else if(method=='id'){ var alpha = 255*myvalue; }else if(method=='scale'){ var alpha = 255*(myvalue-minValue)/(maxValue-minValue); } imgData.data[i+0] = 72;//39; rgb(95, 39, 205) rgb(72, 52, 212) imgData.data[i+1] = 52;//60; imgData.data[i+2] = 212;//177; imgData.data[i+3] = alpha; if(method=='d3scale'){ var mycolorrgb = d3.rgb(colorscale(myvalue)); imgData.data[i+0] = mycolorrgb.r; imgData.data[i+1] = mycolorrgb.g; imgData.data[i+2] = mycolorrgb.b; imgData.data[i+3] = 255; } } context.putImageData(imgData,0,0); }36:[{"id":"3b13283d312d56ab2035cb5f726e44ae3e9eb50b9b39ff03a136c2b3ceb87933b59dda754110aadc4ac0d4e31f6f8d938724b0b163380b7fdd33b4b3ae9f8689","href":"https://static.observableusercontent.com/files/3b13283d312d56ab2035cb5f726e44ae3e9eb50b9b39ff03a136c2b3ceb87933b59dda754110aadc4ac0d4e31f6f8d938724b0b163380b7fdd33b4b3ae9f8689","name":"Screen Shot 2021-01-02 at 9.29.14 PM.png","type":"image/png","lastModified":1609781038405.768,"size":3451795}] 31:{"id":"5241b6e0b8b1bf16","slug":"imitation-game","title":"Imitation Game 🖐","thumbnail":"4427be74d089e84d106de630dd7ca20509318535583e8107bb9631a6c0d56e91","access_level":"public","create_time":"$D2020-12-15T04:22:53.322Z","update_time":"$D2021-12-28T16:47:08.455Z","view_time":null,"first_public_time":"$D2021-01-03T18:46:14.215Z","has_unpublished_edits":null,"fork":false,"stars":13,"starred":false,"owner":{"type":"team","id":"5d1c5c48a3939518","login":"mattdzugan","name":"Matt Dzugan","avatar_url":"https://avatars-next.observableusercontent.com/5e6f59dbd54952c1978225f1a7fdc6abf438d0beee68bf8df8be4f097380b46a","tier":"starter_2024","bio":""},"version":1201,"publish_version":1201,"role":null,"authored":false,"authors":[{"type":"individual","id":"e4c2116dac28a624","login":"mattdzugan","name":"Matt Dzugan","avatar_url":"https://avatars-next.observableusercontent.com/5e6f59dbd54952c1978225f1a7fdc6abf438d0beee68bf8df8be4f097380b46a","tier":null,"bio":""}],"members":[{"type":"individual","id":"e4c2116dac28a624","login":"mattdzugan","name":"Matt Dzugan","avatar_url":"https://avatars-next.observableusercontent.com/5e6f59dbd54952c1978225f1a7fdc6abf438d0beee68bf8df8be4f097380b46a","tier":null,"role":"editor"}],"comments":[{"id":"8fa5cbe2f9c7b91f","reply_to_id":null,"content":"Love this! 👏👏 The pattern of spirals in fig 7b of the second paper reminds me of theta functions. https://en.wikipedia.org/wiki/Theta_function","create_time":"$D2021-01-04T18:38:26.530Z","update_time":null,"resolved":false,"user":{"type":"individual","id":"908c4be2279a714e","login":"rreusser","name":"Ricky Reusser","avatar_url":"https://avatars-next.observableusercontent.com/fa41989f47bb986723af5b9c22176cb503748426f56e565000ea93acd9eab86c","tier":null}}],"custom_thumbnail":true,"trashed":false,"lapsed":null,"subscribed":null,"forks":3,"collection":{"id":"4b59f6295f5463d9","slug":"genuary-2021","title":"Genuary 2021","owner":{"id":"5d1c5c48a3939518","login":"mattdzugan","name":"Matt Dzugan"}},"type":"notebook","body":{"titling":"auto","title":"Imitation Game 🖐","cells":[{"id":0,"value":"md`\n# Imitation Game 🖐\n## Genuary 2021: Day 3 -- Make Something Human\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":11,"value":"md`I used this notebook to create my entry for [Day 3](https://genuary2021.github.io/prompts) of [Genuary](https://genuary2021.github.io/). _(See my [collection of entries here](https://observablehq.com/collection/@mattdzugan/genuary-2021))_\n\nThe prompt is: \\`Make Something Human\\`\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1196,"value":"image1 = FileAttachment(\"Screen Shot 2021-01-02 at 9.29.14 PM.png\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":73,"value":"md`\n_disclaimer_: I don't actually know anything about fingerprint analysis. It seems like a really cool field with lots of smart people. I knew I wanted to generate fingerprints for this project, so I just looked for papers and I found [this one](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.479.5982&rep=rep1&type=pdf) and [this one](http://biometrics.cse.msu.edu/Publications/Fingerprint/FengJain_FpReconstruct_PAMI10.pdf) which i used as guides for this notebook.\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1168,"value":"viewof minutaie_slider = {\n const phrases = [\n 'Lots of Random dead-ends (minutae)',\n 'A Few Random dead-ends (minutae)',\n 'somewhere in the middle',\n 'Mostly clean lines',\n 'Very clean lines',\n ];\n \n return slider({\n value: 1, min: 0, max: 1, step: 0.25,\n display: v => phrases[v*4]\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1133,"value":"viewof color1 = radio({\n title: 'Select a Fingerprint Color!',\n options: [\n { label: '🖐️', value: '#ffcc40' }, // 255 205 64\n { label: '🖐🏻', value: '#fee5c8' }, // 254 229 200\n { label: '🖐🏼', value: '#e2be9a' }, // 226 190 154\n { label: '🖐🏽', value: '#c2936b' }, // 194 147 107\n { label: '🖐🏾', value: '#9e673f' }, // 158 103 63\n { label: '🖐🏿', value: '#5b463b' }, // 91 70 59\n ],\n value: '#ffcc40'\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1132,"value":"{\n \n //await visibility();\n const context0 = DOM.context2d(w, h);\n imshow(context0, LowResPrint, w, h, 'id');\n\n \n var context = DOM.context2d(width, width, 1);\n context.drawImage(context0.canvas, 0, 0, w, h, 0, 0, width, width);\n var {data: rgba} = context.getImageData(0, 0, width, width);\n var data = new Float64Array(width * width);\n var Matrix_D = [];\n for (var rr=0; rr