Viewing Program

Program Data

Program thumbnail for "{props.program.title}"

Title	Not so easy money
ID	6634753220886528
Created	4 years ago, 1610239942581
Updated	2 years ago, 1678651235426
Code	/** * Click the mouse to start/stop the cylinder's X & Y axes rotations. * Press LEFT and RIGHT keys for Z axis rotation. * * Evolved from https://www.khanacademy.org/computing/computer-programming/programming-games-visualizations/programming-3d-shapes/a/rotating-3d-shapes * * An explanation of texturing can be found at * https://www.khanacademy.org/cs/texture/6560556621660160 / /* * PNG to image converter. AFAIK, this program does not * violate KA policies. * * Set pngString to the base64 string representing a PNG * encoded picture. This program will convert it to an * image and display that image. * * To convert (Wikipedia) pictures to a base64 PNG string, see * https://www.khanacademy.org/computer-programming/w/5639130759528448 * * Most of the code in this program was ported from * https://github.com/devongovett/png.js/ / { var heads64 = heads64 \|\| 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"; } / defines the variable heads64 / { var tails64 = tails64 \|\| 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"; } / defines the variable tails64 / var newUintArray = function(a) { if (typeof a === "number") { return new Array(a); } else { return a.slice(); } }; var atob = function(text) { / Convert an ASCII base64 string into binary data. / var s = text.split(","); text = s[s.length - 1]; / strip away header / if (false) { / Avoiding some complaints on some browsers... / text = text.replace(/\s/g, ""); if(!(/^[a-z0-9\+\/\s]+\={0,2}$/i.test(text)) \|\| text.length % 4 > 0){ throw new Error("Not a base64-encoded string."); } text = text.replace(/=/g, ""); } var digits = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/", a, b, c, x, y, result = []; for (var i = 0; i < text.length; result.push(a, b, c)){ x = digits.indexOf(text[i++]); y = digits.indexOf(text[i++]); a = x << 2 \| y >> 4; x = digits.indexOf(text[i++]); b = (y & 0x0f) << 4 \| x >> 2; y = digits.indexOf(text[i++]); c = (x & 3) << 6 \| y; } return result; }; / * Extracted from pdf.js * https://github.com/andreasgal/pdf.js * * Copyright (c) 2011 Mozilla Foundation * * Contributors: Andreas Gal <gal@mozilla.com> * Chris G Jones <cjones@mozilla.com> * Shaon Barman <shaon.barman@gmail.com> * Vivien Nicolas <21@vingtetun.org> * Justin D'Arcangelo <justindarc@gmail.com> * Yury Delendik * * Permission is hereby granted, free of charge, to any person obtaining a * copy of this software and associated documentation files (the "Software"), * to deal in the Software without restriction, including without limitation * the rights to use, copy, modify, merge, publish, distribute, sublicense, * and/or sell copies of the Software, and to permit persons to whom the * Software is furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL * THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER * DEALINGS IN THE SOFTWARE. / var DecodeStream = (function() { var constructor = function() { this.pos = 0; this.bufferLength = 0; this.eof = false; this.buffer = null; }; constructor.prototype = { ensureBuffer: function /decodestream_ensureBuffer/(requested) { var buffer = this.buffer; //var current = buffer ? buffer.byteLength : 0; xxxx var current = buffer ? buffer.length : 0; if (requested < current) { return buffer; } var size = 512; while (size < requested) { size <<= 1; } var buffer2 = newUintArray(size); for (var i = 0; i < current; ++i) { buffer2[i] = buffer[i]; } this.buffer = buffer2; return this.buffer; }, getBytes: function /decodestream_getBytes/(length) { var pos = this.pos; var end; if (length) { this.ensureBuffer(pos + length); var end = pos + length; while (!this.eof && this.bufferLength < end) { this.readBlock(); } var bufEnd = this.bufferLength; if (end > bufEnd) { end = bufEnd; } } else { while (!this.eof) { this.readBlock(); } var end = this.bufferLength; } this.pos = end; //return this.buffer.subarray(pos, end); xxxx return this.buffer.slice(pos, end); }, }; return constructor; })(); var FlateStream = (function() { var error = function (e) { throw new Error(e); }; var codeLenCodeMap = newUintArray( [ 16, 17, 18, 0, 8, 7, 9, 6, 10, 5, 11, 4, 12, 3, 13, 2, 14, 1, 15 ]); var lengthDecode = newUintArray( [ 0x00003, 0x00004, 0x00005, 0x00006, 0x00007, 0x00008, 0x00009, 0x0000a, 0x1000b, 0x1000d, 0x1000f, 0x10011, 0x20013, 0x20017, 0x2001b, 0x2001f, 0x30023, 0x3002b, 0x30033, 0x3003b, 0x40043, 0x40053, 0x40063, 0x40073, 0x50083, 0x500a3, 0x500c3, 0x500e3, 0x00102, 0x00102, 0x00102 ]); var distDecode = newUintArray( [ 0x00001, 0x00002, 0x00003, 0x00004, 0x10005, 0x10007, 0x20009, 0x2000d, 0x30011, 0x30019, 0x40021, 0x40031, 0x50041, 0x50061, 0x60081, 0x600c1, 0x70101, 0x70181, 0x80201, 0x80301, 0x90401, 0x90601, 0xa0801, 0xa0c01, 0xb1001, 0xb1801, 0xc2001, 0xc3001, 0xd4001, 0xd6001 ]); var fixedLitCodeTab = [newUintArray( [ 0x70100, 0x80050, 0x80010, 0x80118, 0x70110, 0x80070, 0x80030, 0x900c0, 0x70108, 0x80060, 0x80020, 0x900a0, 0x80000, 0x80080, 0x80040, 0x900e0, 0x70104, 0x80058, 0x80018, 0x90090, 0x70114, 0x80078, 0x80038, 0x900d0, 0x7010c, 0x80068, 0x80028, 0x900b0, 0x80008, 0x80088, 0x80048, 0x900f0, 0x70102, 0x80054, 0x80014, 0x8011c, 0x70112, 0x80074, 0x80034, 0x900c8, 0x7010a, 0x80064, 0x80024, 0x900a8, 0x80004, 0x80084, 0x80044, 0x900e8, 0x70106, 0x8005c, 0x8001c, 0x90098, 0x70116, 0x8007c, 0x8003c, 0x900d8, 0x7010e, 0x8006c, 0x8002c, 0x900b8, 0x8000c, 0x8008c, 0x8004c, 0x900f8, 0x70101, 0x80052, 0x80012, 0x8011a, 0x70111, 0x80072, 0x80032, 0x900c4, 0x70109, 0x80062, 0x80022, 0x900a4, 0x80002, 0x80082, 0x80042, 0x900e4, 0x70105, 0x8005a, 0x8001a, 0x90094, 0x70115, 0x8007a, 0x8003a, 0x900d4, 0x7010d, 0x8006a, 0x8002a, 0x900b4, 0x8000a, 0x8008a, 0x8004a, 0x900f4, 0x70103, 0x80056, 0x80016, 0x8011e, 0x70113, 0x80076, 0x80036, 0x900cc, 0x7010b, 0x80066, 0x80026, 0x900ac, 0x80006, 0x80086, 0x80046, 0x900ec, 0x70107, 0x8005e, 0x8001e, 0x9009c, 0x70117, 0x8007e, 0x8003e, 0x900dc, 0x7010f, 0x8006e, 0x8002e, 0x900bc, 0x8000e, 0x8008e, 0x8004e, 0x900fc, 0x70100, 0x80051, 0x80011, 0x80119, 0x70110, 0x80071, 0x80031, 0x900c2, 0x70108, 0x80061, 0x80021, 0x900a2, 0x80001, 0x80081, 0x80041, 0x900e2, 0x70104, 0x80059, 0x80019, 0x90092, 0x70114, 0x80079, 0x80039, 0x900d2, 0x7010c, 0x80069, 0x80029, 0x900b2, 0x80009, 0x80089, 0x80049, 0x900f2, 0x70102, 0x80055, 0x80015, 0x8011d, 0x70112, 0x80075, 0x80035, 0x900ca, 0x7010a, 0x80065, 0x80025, 0x900aa, 0x80005, 0x80085, 0x80045, 0x900ea, 0x70106, 0x8005d, 0x8001d, 0x9009a, 0x70116, 0x8007d, 0x8003d, 0x900da, 0x7010e, 0x8006d, 0x8002d, 0x900ba, 0x8000d, 0x8008d, 0x8004d, 0x900fa, 0x70101, 0x80053, 0x80013, 0x8011b, 0x70111, 0x80073, 0x80033, 0x900c6, 0x70109, 0x80063, 0x80023, 0x900a6, 0x80003, 0x80083, 0x80043, 0x900e6, 0x70105, 0x8005b, 0x8001b, 0x90096, 0x70115, 0x8007b, 0x8003b, 0x900d6, 0x7010d, 0x8006b, 0x8002b, 0x900b6, 0x8000b, 0x8008b, 0x8004b, 0x900f6, 0x70103, 0x80057, 0x80017, 0x8011f, 0x70113, 0x80077, 0x80037, 0x900ce, 0x7010b, 0x80067, 0x80027, 0x900ae, 0x80007, 0x80087, 0x80047, 0x900ee, 0x70107, 0x8005f, 0x8001f, 0x9009e, 0x70117, 0x8007f, 0x8003f, 0x900de, 0x7010f, 0x8006f, 0x8002f, 0x900be, 0x8000f, 0x8008f, 0x8004f, 0x900fe, 0x70100, 0x80050, 0x80010, 0x80118, 0x70110, 0x80070, 0x80030, 0x900c1, 0x70108, 0x80060, 0x80020, 0x900a1, 0x80000, 0x80080, 0x80040, 0x900e1, 0x70104, 0x80058, 0x80018, 0x90091, 0x70114, 0x80078, 0x80038, 0x900d1, 0x7010c, 0x80068, 0x80028, 0x900b1, 0x80008, 0x80088, 0x80048, 0x900f1, 0x70102, 0x80054, 0x80014, 0x8011c, 0x70112, 0x80074, 0x80034, 0x900c9, 0x7010a, 0x80064, 0x80024, 0x900a9, 0x80004, 0x80084, 0x80044, 0x900e9, 0x70106, 0x8005c, 0x8001c, 0x90099, 0x70116, 0x8007c, 0x8003c, 0x900d9, 0x7010e, 0x8006c, 0x8002c, 0x900b9, 0x8000c, 0x8008c, 0x8004c, 0x900f9, 0x70101, 0x80052, 0x80012, 0x8011a, 0x70111, 0x80072, 0x80032, 0x900c5, 0x70109, 0x80062, 0x80022, 0x900a5, 0x80002, 0x80082, 0x80042, 0x900e5, 0x70105, 0x8005a, 0x8001a, 0x90095, 0x70115, 0x8007a, 0x8003a, 0x900d5, 0x7010d, 0x8006a, 0x8002a, 0x900b5, 0x8000a, 0x8008a, 0x8004a, 0x900f5, 0x70103, 0x80056, 0x80016, 0x8011e, 0x70113, 0x80076, 0x80036, 0x900cd, 0x7010b, 0x80066, 0x80026, 0x900ad, 0x80006, 0x80086, 0x80046, 0x900ed, 0x70107, 0x8005e, 0x8001e, 0x9009d, 0x70117, 0x8007e, 0x8003e, 0x900dd, 0x7010f, 0x8006e, 0x8002e, 0x900bd, 0x8000e, 0x8008e, 0x8004e, 0x900fd, 0x70100, 0x80051, 0x80011, 0x80119, 0x70110, 0x80071, 0x80031, 0x900c3, 0x70108, 0x80061, 0x80021, 0x900a3, 0x80001, 0x80081, 0x80041, 0x900e3, 0x70104, 0x80059, 0x80019, 0x90093, 0x70114, 0x80079, 0x80039, 0x900d3, 0x7010c, 0x80069, 0x80029, 0x900b3, 0x80009, 0x80089, 0x80049, 0x900f3, 0x70102, 0x80055, 0x80015, 0x8011d, 0x70112, 0x80075, 0x80035, 0x900cb, 0x7010a, 0x80065, 0x80025, 0x900ab, 0x80005, 0x80085, 0x80045, 0x900eb, 0x70106, 0x8005d, 0x8001d, 0x9009b, 0x70116, 0x8007d, 0x8003d, 0x900db, 0x7010e, 0x8006d, 0x8002d, 0x900bb, 0x8000d, 0x8008d, 0x8004d, 0x900fb, 0x70101, 0x80053, 0x80013, 0x8011b, 0x70111, 0x80073, 0x80033, 0x900c7, 0x70109, 0x80063, 0x80023, 0x900a7, 0x80003, 0x80083, 0x80043, 0x900e7, 0x70105, 0x8005b, 0x8001b, 0x90097, 0x70115, 0x8007b, 0x8003b, 0x900d7, 0x7010d, 0x8006b, 0x8002b, 0x900b7, 0x8000b, 0x8008b, 0x8004b, 0x900f7, 0x70103, 0x80057, 0x80017, 0x8011f, 0x70113, 0x80077, 0x80037, 0x900cf, 0x7010b, 0x80067, 0x80027, 0x900af, 0x80007, 0x80087, 0x80047, 0x900ef, 0x70107, 0x8005f, 0x8001f, 0x9009f, 0x70117, 0x8007f, 0x8003f, 0x900df, 0x7010f, 0x8006f, 0x8002f, 0x900bf, 0x8000f, 0x8008f, 0x8004f, 0x900ff ]), 9]; var fixedDistCodeTab = [newUintArray( [ 0x50000, 0x50010, 0x50008, 0x50018, 0x50004, 0x50014, 0x5000c, 0x5001c, 0x50002, 0x50012, 0x5000a, 0x5001a, 0x50006, 0x50016, 0x5000e, 0x00000, 0x50001, 0x50011, 0x50009, 0x50019, 0x50005, 0x50015, 0x5000d, 0x5001d, 0x50003, 0x50013, 0x5000b, 0x5001b, 0x50007, 0x50017, 0x5000f, 0x00000 ]), 5]; var constructor = function(bytes) { //var bytes = stream.getBytes(); var bytesPos = 0; var cmf = bytes[bytesPos++]; var flg = bytes[bytesPos++]; if (cmf === -1 \|\| flg === -1) { error('Invalid header in flate stream'); } if ((cmf & 0x0f) !== 0x08) { error('Unknown compression method in flate stream'); } if ((((cmf << 8) + flg) % 31) !== 0) { error('Bad FCHECK in flate stream'); } if (flg & 0x20) { error('FDICT bit set in flate stream'); } this.bytes = bytes; this.bytesPos = bytesPos; this.codeSize = 0; this.codeBuf = 0; DecodeStream.call(this); }; constructor.prototype = Object.create(DecodeStream.prototype); constructor.prototype.getBits = function(bits) { var codeSize = this.codeSize; var codeBuf = this.codeBuf; var bytes = this.bytes; var bytesPos = this.bytesPos; var b; while (codeSize < bits) { if (typeof (b = bytes[bytesPos++]) === 'undefined') { error('Bad encoding in flate stream'); } codeBuf \|= b << codeSize; codeSize += 8; } b = codeBuf & ((1 << bits) - 1); this.codeBuf = codeBuf >> bits; this.codeSize = codeSize -= bits; this.bytesPos = bytesPos; return b; }; constructor.prototype.getCode = function(table) { var codes = table[0]; var maxLen = table[1]; var codeSize = this.codeSize; var codeBuf = this.codeBuf; var bytes = this.bytes; var bytesPos = this.bytesPos; while (codeSize < maxLen) { var b; if (typeof (b = bytes[bytesPos++]) === 'undefined') { error('Bad encoding in flate stream'); } codeBuf \|= (b << codeSize); codeSize += 8; } var code = codes[codeBuf & ((1 << maxLen) - 1)]; var codeLen = code >> 16; var codeVal = code & 0xffff; if (codeSize === 0 \|\| codeSize < codeLen \|\| codeLen === 0) { error('Bad encoding in flate stream'); } this.codeBuf = (codeBuf >> codeLen); this.codeSize = (codeSize - codeLen); this.bytesPos = bytesPos; return codeVal; }; constructor.prototype.generateHuffmanTable = function(lengths) { var n = lengths.length; // find max code length var maxLen = 0; for (var i = 0; i < n; ++i) { if (lengths[i] > maxLen) { maxLen = lengths[i]; } } // build the table var size = 1 << maxLen; var codes = newUintArray(size); for (var len = 1, code = 0, skip = 2; len <= maxLen; ++len, code <<= 1, skip <<= 1) { for (var val = 0; val < n; ++val) { if (lengths[val] === len) { // bit-reverse the code var code2 = 0; var t = code; for (var i = 0; i < len; ++i) { code2 = (code2 << 1) \| (t & 1); t >>= 1; } // fill the table entries for (var i = code2; i < size; i += skip) { codes[i] = (len << 16) \| val; } ++code; } } } return [codes, maxLen]; }; constructor.prototype.readBlock = function() { var i; / hoisted by blyon / var repeat = function(stream, array, len, offset, what) { var repeat = stream.getBits(len) + offset; while (repeat-- > 0) { array[i++] = what; } }; // read block header var hdr = this.getBits(3); if (hdr & 1) { this.eof = true; } hdr >>= 1; if (hdr === 0) { // uncompressed block var bytes = this.bytes; var bytesPos = this.bytesPos; var b; if (typeof (b = bytes[bytesPos++]) === 'undefined') { error('Bad block header in flate stream'); } var blockLen = b; if (typeof (b = bytes[bytesPos++]) === 'undefined') { error('Bad block header in flate stream'); } blockLen \|= (b << 8); if (typeof (b = bytes[bytesPos++]) === 'undefined') { error('Bad block header in flate stream'); } var check = b; if (typeof (b = bytes[bytesPos++]) === 'undefined') { error('Bad block header in flate stream'); } check \|= (b << 8); if (check !== (~blockLen & 0xffff)) { error('Bad uncompressed block length in flate stream'); } this.codeBuf = 0; this.codeSize = 0; var bufferLength = this.bufferLength; var buffer = this.ensureBuffer(bufferLength + blockLen); var end = bufferLength + blockLen; this.bufferLength = end; for (var n = bufferLength; n < end; ++n) { if (typeof (b = bytes[bytesPos++]) === 'undefined') { this.eof = true; break; } buffer[n] = b; } this.bytesPos = bytesPos; return; } var litCodeTable; var distCodeTable; if (hdr === 1) { // compressed block, fixed codes litCodeTable = fixedLitCodeTab; distCodeTable = fixedDistCodeTab; } else if (hdr === 2) { // compressed block, dynamic codes var numLitCodes = this.getBits(5) + 257; var numDistCodes = this.getBits(5) + 1; var numCodeLenCodes = this.getBits(4) + 4; // build the code lengths code table var codeLenCodeLengths = Array(codeLenCodeMap.length); var i = 0; while (i < numCodeLenCodes) { codeLenCodeLengths[codeLenCodeMap[i++]] = this.getBits(3); } var codeLenCodeTab = this.generateHuffmanTable(codeLenCodeLengths); // build the literal and distance code tables var len = 0; var i = 0; var codes = numLitCodes + numDistCodes; var codeLengths = new Array(codes); while (i < codes) { var code = this.getCode(codeLenCodeTab); if (code === 16) { repeat(this, codeLengths, 2, 3, len); } else if (code === 17) { repeat(this, codeLengths, 3, 3, len = 0); } else if (code === 18) { repeat(this, codeLengths, 7, 11, len = 0); } else { codeLengths[i++] = len = code; } } litCodeTable = this.generateHuffmanTable(codeLengths.slice(0, numLitCodes)); distCodeTable = this.generateHuffmanTable(codeLengths.slice(numLitCodes, codes)); } else { error('Unknown block type in flate stream'); } var buffer = this.buffer; var limit = buffer ? buffer.length : 0; var pos = this.bufferLength; while (true) { var code1 = this.getCode(litCodeTable); if (code1 < 256) { if (pos + 1 >= limit) { buffer = this.ensureBuffer(pos + 1); limit = buffer.length; } buffer[pos++] = code1; continue; } if (code1 === 256) { this.bufferLength = pos; return; } code1 -= 257; code1 = lengthDecode[code1]; var code2 = code1 >> 16; if (code2 > 0) { code2 = this.getBits(code2); } var len = (code1 & 0xffff) + code2; code1 = this.getCode(distCodeTable); code1 = distDecode[code1]; code2 = code1 >> 16; if (code2 > 0) { code2 = this.getBits(code2); } var dist = (code1 & 0xffff) + code2; if (pos + len >= limit) { buffer = this.ensureBuffer(pos + len); limit = buffer.length; } for (var k = 0; k < len; ++k, ++pos) { buffer[pos] = buffer[pos - dist]; } } }; return constructor; })(); / # MIT LICENSE # Copyright (c) 2011 Devon Govett # # Permission is hereby granted, free of charge, to any person obtaining a copy of this # software and associated documentation files (the "Software"), to deal in the Software # without restriction, including without limitation the rights to use, copy, modify, merge, # publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons # to whom the Software is furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all copies or # substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING # BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND # NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, # DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. / var PNG = (function() { var APNG_BLEND_OP_OVER, APNG_BLEND_OP_SOURCE, APNG_DISPOSE_OP_BACKGROUND, APNG_DISPOSE_OP_NONE, APNG_DISPOSE_OP_PREVIOUS, makeImage, scratchCanvas, scratchCtx; var PNG = function(data) { var chunkSize, colors, delayDen, delayNum, frame, i, index, key, section, short, text, _i, _j, _ref; this.pos = 8; this.palette = []; this.imgData = []; this.transparency = {}; this.animation = null; this.text = {}; this.data = data = newUintArray(data); frame = null; var getColors = function() { switch (this.colorType) { case 0: case 3: case 4: return 1; case 2: case 6: return 3; } }; var colorSpace = function() { switch (this.colors) { case 1: return 'DeviceGray'; case 3: return 'DeviceRGB'; } }; var getSection = function() { var _i, _results; _results = []; for (i = _i = 0; _i < 4; i = ++_i) { _results.push(String.fromCharCode(this.data[this.pos++])); } return _results; }; while (true) { chunkSize = this.readUInt32(); section = getSection.call(this).join(''); switch (section) { case 'IHDR': this.width = this.readUInt32(); this.height = this.readUInt32(); this.bits = this.data[this.pos++]; this.colorType = this.data[this.pos++]; this.compressionMethod = this.data[this.pos++]; this.filterMethod = this.data[this.pos++]; this.interlaceMethod = this.data[this.pos++]; break; case 'acTL': this.animation = { numFrames: this.readUInt32(), numPlays: this.readUInt32() \|\| Infinity, frames: [] }; break; case 'PLTE': this.palette = this.read(chunkSize); break; case 'fcTL': if (frame) { this.animation.frames.push(frame); } this.pos += 4; frame = { width: this.readUInt32(), height: this.readUInt32(), xOffset: this.readUInt32(), yOffset: this.readUInt32() }; delayNum = this.readUInt16(); delayDen = this.readUInt16() \|\| 100; frame.delay = 1000 delayNum / delayDen; frame.disposeOp = this.data[this.pos++]; frame.blendOp = this.data[this.pos++]; frame.data = []; break; case 'IDAT': case 'fdAT': if (section === 'fdAT') { this.pos += 4; chunkSize -= 4; } data = (frame ? frame.data : 0) \|\| this.imgData; for (i = _i = 0; 0 <= chunkSize ? _i < chunkSize : _i > chunkSize; i = 0 <= chunkSize ? ++_i : --_i) { data.push(this.data[this.pos++]); } break; case 'tRNS': this.transparency = {}; switch (this.colorType) { case 3: this.transparency.indexed = this.read(chunkSize); short = 255 - this.transparency.indexed.length; if (short > 0) { for (i = _j = 0; 0 <= short ? _j < short : _j > short; i = 0 <= short ? ++_j : --_j) { this.transparency.indexed.push(255); } } break; case 0: this.transparency.grayscale = this.read(chunkSize)[0]; break; case 2: this.transparency.rgb = this.read(chunkSize); } break; case 'tEXt': text = this.read(chunkSize); index = text.indexOf(0); key = String.fromCharCode.apply(String, text.slice(0, index)); this.text[key] = String.fromCharCode.apply(String, text.slice(index + 1)); break; case 'IEND': if (frame) { this.animation.frames.push(frame); } this.colors = getColors.call(this); this.hasAlphaChannel = (_ref = this.colorType) === 4 \|\| _ref === 6; colors = this.colors + (this.hasAlphaChannel ? 1 : 0); this.pixelBitlength = this.bits * colors; this.colorSpace = colorSpace.call(this); this.imgData = newUintArray(this.imgData); return; default: this.pos += chunkSize; } this.pos += 4; if (this.pos > this.data.length) { throw new Error("Incomplete or corrupt PNG file"); } } return; }; PNG.prototype.read = function(bytes) { var i, _i, _results; _results = []; for (i = _i = 0; 0 <= bytes ? _i < bytes : _i > bytes; i = 0 <= bytes ? ++_i : --_i) { _results.push(this.data[this.pos++]); } return _results; }; APNG_DISPOSE_OP_NONE = 0; APNG_DISPOSE_OP_BACKGROUND = 1; APNG_DISPOSE_OP_PREVIOUS = 2; APNG_BLEND_OP_SOURCE = 0; APNG_BLEND_OP_OVER = 1; PNG.prototype.readUInt32 = function() { var b1, b2, b3, b4; b1 = this.data[this.pos++] << 24; b2 = this.data[this.pos++] << 16; b3 = this.data[this.pos++] << 8; b4 = this.data[this.pos++]; return b1 \| b2 \| b3 \| b4; }; PNG.prototype.readUInt16 = function() { var b1, b2; b1 = this.data[this.pos++] << 8; b2 = this.data[this.pos++]; return b1 \| b2; }; PNG.prototype.decodePixels = function(data) { var byte, c, col, i, left, length, p, pa, paeth, pb, pc, pixelBytes, pixels, pos, row, scanlineLength, upper, upperLeft, _i, _j, _k, _l, _m; if (! data) { data = this.imgData; } if (data.length === 0) { return newUintArray(0); } data = new FlateStream(data); data = data.getBytes(); pixelBytes = this.pixelBitlength / 8; scanlineLength = pixelBytes * this.width; pixels = newUintArray(scanlineLength * this.height); length = data.length; row = 0; pos = 0; c = 0; while (pos < length) { switch (data[pos++]) { case 0: for (i = _i = 0; _i < scanlineLength; i = _i += 1) { pixels[c++] = data[pos++]; } break; case 1: for (i = _j = 0; _j < scanlineLength; i = _j += 1) { byte = data[pos++]; left = i < pixelBytes ? 0 : pixels[c - pixelBytes]; pixels[c++] = (byte + left) % 256; } break; case 2: for (i = _k = 0; _k < scanlineLength; i = _k += 1) { byte = data[pos++]; col = (i - (i % pixelBytes)) / pixelBytes; upper = row && pixels[(row - 1) * scanlineLength + col * pixelBytes + (i % pixelBytes)]; pixels[c++] = (upper + byte) % 256; } break; case 3: for (i = _l = 0; _l < scanlineLength; i = _l += 1) { byte = data[pos++]; col = (i - (i % pixelBytes)) / pixelBytes; left = i < pixelBytes ? 0 : pixels[c - pixelBytes]; upper = row && pixels[(row - 1) * scanlineLength + col * pixelBytes + (i % pixelBytes)]; pixels[c++] = (byte + Math.floor((left + upper) / 2)) % 256; } break; case 4: for (i = _m = 0; _m < scanlineLength; i = _m += 1) { byte = data[pos++]; col = (i - (i % pixelBytes)) / pixelBytes; left = i < pixelBytes ? 0 : pixels[c - pixelBytes]; if (row === 0) { upper = upperLeft = 0; } else { upper = pixels[(row - 1) * scanlineLength + col * pixelBytes + (i % pixelBytes)]; upperLeft = col && pixels[(row - 1) * scanlineLength + (col - 1) * pixelBytes + (i % pixelBytes)]; } p = left + upper - upperLeft; pa = Math.abs(p - left); pb = Math.abs(p - upper); pc = Math.abs(p - upperLeft); if (pa <= pb && pa <= pc) { paeth = left; } else if (pb <= pc) { paeth = upper; } else { paeth = upperLeft; } pixels[c++] = (byte + paeth) % 256; } break; default: println("Oh Noes!!!"); throw new Error("Invalid filter algorithm: " + data[pos - 1]); } row++; } return pixels; }; PNG.prototype.decodePalette = function() { var c, i, length, palette, pos, ret, transparency, _i, _ref, _ref1; palette = this.palette; transparency = this.transparency.indexed \|\| []; ret = newUintArray((transparency.length \|\| 0) + palette.length); pos = 0; length = palette.length; c = 0; for (i = _i = 0, _ref = palette.length; _i < _ref; i = _i += 3) { ret[pos++] = palette[i]; ret[pos++] = palette[i + 1]; ret[pos++] = palette[i + 2]; ret[pos++] = (_ref1 = transparency[c++]) ? _ref1 : 255; } return ret; }; PNG.prototype.copyToImageData = function(imageData, pixels) { var alpha, colors, data, i, input, j, k, length, palette, v, _ref; colors = this.colors; palette = null; alpha = this.hasAlphaChannel; if (this.palette.length) { palette = (_ref = this._decodedPalette) ? _ref : this._decodedPalette = this.decodePalette(); colors = 4; alpha = true; } data = imageData.data \|\| imageData; length = data.length; input = palette \|\| pixels; i = j = 0; if (colors === 1) { while (i < length) { k = palette ? pixels[i / 4] * 4 : j; v = input[k++]; data[i++] = v; data[i++] = v; data[i++] = v; data[i++] = alpha ? input[k++] : 255; j = k; } } else { while (i < length) { k = palette ? pixels[i / 4] * 4 : j; data[i++] = input[k++]; data[i++] = input[k++]; data[i++] = input[k++]; data[i++] = alpha ? input[k++] : 255; j = k; } } }; PNG.prototype.decode = function() { var ret = newUintArray(this.width * this.height * 4); this.copyToImageData(ret, this.decodePixels()); return ret; }; PNG.prototype.decodeFrames = function(ctx) { var frame, i, imageData, pixels, _i, _len, _ref, _results; if (!this.animation) { return; } _ref = this.animation.frames; _results = []; for (i = _i = 0, _len = _ref.length; _i < _len; i = ++_i) { frame = _ref[i]; imageData = ctx.createImageData(frame.width, frame.height); pixels = this.decodePixels(newUintArray(frame.data)); this.copyToImageData(imageData, pixels); frame.imageData = imageData; _results.push(frame.image = makeImage(imageData)); } return _results; }; PNG.prototype.render = function(canvas) { var ctx, data; if (canvas._png) { canvas._png.stopAnimation(); } canvas._png = this; canvas.width = this.width; canvas.height = this.height; ctx = canvas.getContext("2d"); if (this.animation) { this.decodeFrames(ctx); return this.animate(ctx); } else { data = ctx.createImageData(this.width, this.height); this.copyToImageData(data, this.decodePixels()); return ctx.putImageData(data, 0, 0); } }; /* convert this PNG into a Processing.js image / PNG.prototype.toImage = function() { var img = createGraphics(this.width, this.height, JAVA2D); img.background(0, 0, 0, 0); var bits = img.get(); var src = bits.sourceImg; this.render(src); img.image(bits, 0, 0); return img; }; return PNG; })(); var string2Image = function(s, x, y, d) { var cache = string2Image.cache = string2Image.cache \|\| {}; if (! cache[s]) { var binaryData = atob(s); var png = new PNG(binaryData); var img = png.toImage(); var q = createGraphics(img.width, img.height, JAVA2D); var mask = createGraphics(img.width, img.height, JAVA2D); mask.background(0); mask.fill(255); mask.noStroke(); mask.ellipse(mask.width/2 - 3, mask.height/2, d, d); mask = mask.get(); image(mask, width/2, height/2); q.background(1, 2, 3, 0); img = img.get(); img.mask(mask); q.image(img); q = q.get(); var face = cache[s] = createGraphics(d, d, JAVA2D); face.background(1, 2, 3, 0); face.imageMode(CENTER); face.image(q, face.width/2 + 2, face.height/2); } return cache[s]; }; var headsImg = string2Image(heads64, 197, 200, 294); var tailsImg = string2Image(tails64, 198, 199, 285); / Coin's properties... / var coinDepth = 20; var coinRadius = 100; var phrases = [ "Be the change that you wish to see in the world", "• •", "If not now, when?", "• •", "Khan Academy", "• •" ]; / Versor copied from https://www.khanacademy.org/cs/cam/4592485916508160 /* * Constructor function for a Versor, which is a * quaternion of magnitude one. Versors are useful * for very fast rotations, no gimbal lock, * easy accumulation of rotations, and efficient * inverses. See: * https://en.wikipedia.org/wiki/Quaternions_and_spatial_rotation * and for idiots, see: * http://run.usc.edu/cs520-s12/quaternions/quaternions-cs520.pdf / var Versor = (function() { var tau = (cos(PI) < 0) ? TWO_PI : 360; / KA silliness / var abs = Math.abs; var cosine = Math.cos; var sine = Math.sin; var arccos = Math.acos; var orbitEpsilon = 1/1024; var epsilon = 1/1024/1024; / * Firstly, additional PVector cross product method that does not * leak memory at Khan Academy because the caller specifies where * the results are placed. Computes and returns (this ⨯ b). resutls * can be any PVector (including this and b) or nothing at all. / PVector.prototype.crossRes = function(b, results) { results = results \|\| new PVector(); results.set( this.y b.z - this.z * b.y, this.z * b.x - this.x * b.z, this.x * b.y - this.y * b.x); return results; }; /* * Constructor. Actually constructs a quaternion. * It is up to the caller to insure magnitude one. / var Versor = function(x, y, z, w) { PVector.call(this); this.init.apply(this, arguments); }; Versor.prototype = Object.create(PVector.prototype); / (re)Initial value of this. / Versor.prototype.init = function(x, y, z, w) { if (arguments.length === 0) { / identity quaternion: / this.x = this.y = this.z = 0; this.w = 1; } else if (arguments.length > 1) { this.set(x, y, z); this.w = w \|\| 0; } else { this.set(x); this.w = x.w \|\| 0; } return this; }; / Return the string representation of this. / Versor.prototype.toString = function() { return "[[" + this.x + "," + this.y + "," + this.z + "]," + this.w + "]"; }; / * Return the inverse of this Versor. Since (if?) this * magnitude is one, then the inverse is this conjugate. * * Returns a static result. Use it immediately, then forget. / Versor.prototype.inverse = function() { var inv = this.conjugate \|\| (this.conjugate = new Versor()); inv.x = -this.x; inv.y = -this.y; inv.z = -this.z; inv.w = this.w; return inv; }; / * Pre-multiply this by r (another Versor). * Specifically, this = (r)(this). / Versor.prototype.apply = function(r) { var q = this, a = r.w, b = r.x, c = r.y, d = r.z, e = q.w, f = q.x, g = q.y, h = q.z; q.w = ae - bf - cg - dh; q.x = af + be + ch - dg; q.y = ag - bh + ce + df; q.z = ah + bg - cf + de; return q; }; / * Rotate a single point(s) p, in place, by this Versor. * p = qpq' or (0, v') = (0, v + q₀t + q⨯t) where * t = 2q⨯v and q₀ is this w property. See * https://en.wikipedia.org/wiki/Conversion_between_quaternions_and_Euler_angles#Vector_Rotation / Versor.prototype.rotateV = function() { var qw = this.w, qx = this.x, qy = this.y, qz = this.z; for (var l = arguments.length, i = 0; i < l; i++) { var p = arguments[i]; / t = 2(q ⨯ v) / var tx = 2 (qy * p.z - qz * p.y), ty = 2 * (qz * p.x - qx * p.z), tz = 2 * (qx * p.y - qy * p.x); /* v' = v + q₀t + (q ⨯ t) / p.x += qw tx + qy * tz - qz * ty; p.y += qw * ty + qz * tx - qx * tz; p.z += qw * tz + qx * ty - qy * tx; } return arguments[0]; }; /* * Same as rotateV above, but applied to an ARRAY of nodes relative * to the origin, and converts the quaternion to a rotation matrix. * The results are in-place, or placed in each node's rp property. * (Actually faster after an expensive setup. See * https://en.wikipedia.org/wiki/Quaternions_and_spatial_rotation ) / Versor.prototype.rotateA = function(nodes, origin, rp, postOrigin) { postOrigin = postOrigin \|\| origin; var qr = this.w, qi = this.x, qj = this.y, qk = this.z, r11 = 1 - 2(qjqj + qkqk), r12 = 0 + 2(qiqj - qkqr), r13 = 0 + 2(qiqk + qjqr), r21 = 0 + 2(qiqj + qkqr), r22 = 1 - 2(qiqi + qkqk), r23 = 0 + 2(qjqk - qiqr), r31 = 0 + 2(qiqk - qjqr), r32 = 0 + 2(qjqk + qiqr), r33 = 1 - 2(qiqi + qjqj), ox = origin.x, oy = origin.y, oz = origin.z, pox = postOrigin.x, poy = postOrigin.y, poz = postOrigin.z; for (var l = nodes.length, n = 0; n < l; n++) { var node = nodes[n], x = node.x - ox, y = node.y - oy, z = node.z - oz, results = (rp) ? (node[rp] \|\| (node[rp] = new PVector())) : node; results.x = r11x + r12y + r13z + pox; results.y = r21x + r22y + r23z + poy; results.z = r31x + r32y + r33z + poz; } return nodes; }; / * Return a Versor such that its rotates point src * to point dest. That is, dest === results.rotateV(src) * Parameters src, dest, and up must be normalized. See * https://gamedev.stackexchange.com/questions/15070/orienting-a-model-to-face-a-target / Versor.getRotation = function(src, dest, up, results) { var dot = src.dot(dest); if (dot > 1-epsilon) { / +1 dot product means pointing exactly where we want! / results.init(); / identity quaternion / } else if (dot < -1+epsilon) { / * -1 dot product means pointing in the * opposite direction. Rotate by the * half angle of 180° wrt up axis. / results.init(up); / results.mult(sine(tau / 4)) is a noop / results.w = 0; / same as w = cosine(tau / 4) / } else { var theta2 = arccos(dot) / 2; / half angle between src and dest / results = src.crossRes(dest, results); / rotation axis / results.normalize(); results.mult(sine(theta2)); results.w = cosine(theta2); } return results; }; / * Returns a versor that describes a circular 3D orbit around the * origin, running through point p0 and (optionally) as close as * possible to p1. If p1 is unspecificed or colinear with p0 and * the origin, then a random orbit is chosen through p0. The points * origin, p0, and p1 define a plane that slices the sphere * centered at the origin in half. So the orbit is a great circle. * * (Optional) delta is the arc angle between each point of the * orbit. So one degree (the default) will generate 360 points * in an orbit. * * The orbit's points are generated by repeatedly applying * the versor to p0. e.g. versor.rotateV(p0) sets p0 to * the next point of the orbit. / Versor.circularOrbit = function(p0, p1, delta) { delta = delta \|\| tau / 360; var orbit = new Versor(); while (true) { var cross = p1 && p0.crossRes(p1, orbit); var crossMag = p1 && (orbitEpsilon round(cross.mag() / orbitEpsilon)); if (crossMag) { break; } p1 = new PVector(random(-1, 1), random(-1, 1), random(-1, 1)); } orbit.normalize(); orbit.mult(sin(delta / 2)); orbit.w = cos(delta / 2); return orbit; }; return Versor; })(); var versor = new Versor(); /* Rotate all nodes relative to origin around the (unit) axis by angle theta. / var axisRotate = function(theta, axis, nodes, origin) { versor.init(axis); versor.mult(sin(theta/2)); versor.w = cos(theta/2); versor.rotateA(nodes, origin); }; / * Give every object a "new" method that works around * the Khan Academy leak. / function whatNewDoes() { var obj = Object.create(this.prototype); this.apply(obj, arguments); return obj; } Object.constructor.prototype.new = whatNewDoes; (function(PVector) { / * Khan Academy leaks objects. Here is a PVector "patch" that * can mitigate PVector leaks iff the programmer invokes * PVector.new() * instead of "new PVector()". / / Reimplement the get method to call PVector.new(). / function get() { return PVector.new(this.x, this.y, this.z); } PVector.prototype.get = get; / Reimplement the cross method to call PVector.new(). / function cross(v) { var ax = this.x, ay = this.y, az = this.z; return PVector.new(ayv.z - azv.y, azv.x - axv.z, axv.y - ayv.x); } PVector.prototype.cross = cross; / * Rewrite static function to invoke PVector.new(). Why the * static method was not robotically generated is a mystery. / function sub(v1, v2) { return PVector.new(v1.x - v2.x, v1.y - v2.y, v1.z - v2.z); } PVector.sub = sub; / Rewrite static function to invoke PVector.new(). / function fromAngle(angle, v) { v = v \|\| PVector.new(); v.x = cos(angle); v.y = sin(angle); return v; } PVector.fromAngle = fromAngle; / Rewrite static function to invoke PVector.new(). / function random3D(v) { var angle = Math.random() TWO_PI; var vz = Math.random() * 2 - 1; var mult = Math.sqrt(1 - vz * vz); var vx = mult * Math.cos(angle); var vy = mult * Math.sin(angle); if (! v) { v = PVector.new(vx, vy, vz); } else { v.set(vx, vy, vz); } return v; } PVector.random3D = random3D; /* Rewrite static function to invoke PVector.new(). / function lerp(v1, v2, amt) { var retval = PVector.new(v1.x, v1.y, v1.z); retval.lerp(v2, amt); return retval; } PVector.lerp = lerp; / Let's also fix a real bug in Processing.js PVectors... / function angleBetween(a, b) { var cosine = a.dot(b) / (a.mag() b.mag()); return acos(constrain(cosine, -1, 1)); } PVector.angleBetween = angleBetween; })(PVector); /* Patches PVector leaks... / / * Constructor for 2D rendering matrix which inherits from * the Processing.js rendering matrices, PMatrix2D. The * only documentation for PMatrix2D is the code found at * https://raw.github.com/processing-js/processing-js/v1.4.8/processing.js / var RMatrix2D = (function() { var isArray = Array.isArray; var aTan2 = atan2; var abs = Math.abs; var sqrt = Math.sqrt; var orthogEpsilon = 1/1024/16; var epsilon = 1/1024/1024/1024; / Constructor function. Objects inherit everything from PMatrix2D / function RMatrix2D() { PMatrix2D.apply(this, arguments); this.mops = Object.new(); this.eigenVector1 = PVector.new(); this.eigenVector2 = PVector.new(); } / * Inherited PMatrix2D properties include: * elements: a six element array of numbers * set: function takes another PMatrix2D, an array, or six numbers * get: function replaced by RMatrix2D.prototype.get * reset: function sets this to the identity matrix * translate: function * determinant: function * invert: inverts the matrix in place; returns a success boolean * scale: function * apply: function this = this * argument(s); matrix multiplication * preApply: function this = argument(s) * this; matrix multiplication * mult: function(source, target) arguments are PVectors or arrays * rotate: function * print: function like printMatrix * Others that are avoided are: * array: function returns a new array of this.elements * multX: function, computes only the X tansformation of a point * multY: function, computes only the Y tansformation of a point * skewX: function (doesn't work) * skewY: function (doesn't work) * shearX: function(angle) (doesn't work and is replaced) * shearY: function(angle) (doesn't work and is replaced) * transpose: function, does nothing! * rotateZ: invokes rotate * invRotateZ: function() undo rotateZ * invTranslate: function undo translate * invScale: function undo scale / RMatrix2D.prototype = Object.create(PMatrix2D.prototype); RMatrix2D.prototype.resetMatrix = PMatrix2D.prototype.reset; / alias / RMatrix2D.prototype.printMatrix = PMatrix2D.prototype.print; / alias / RMatrix2D.prototype.transform = PMatrix2D.prototype.mult; / alias / / Return a clone of this. / function get() { return RMatrix2D.new(this); } RMatrix2D.prototype.get = get; / Set the values of this RMatix2D. Avoids KA leaks and loop detector. / function setMatrix(src) { var S; if (src instanceof PMatrix2D) { S = src.elements; } else if (arguments.length === 6) { S = arguments; } else if (isArray(src)) { S = src; } else { throw "RMatrix2D.prototype.set: invalid arguments!"; } var E = this.elements = this.elements \|\| []; E.length = 0; E.push(S[0], S[1], S[2], S[3], S[4], S[5]); } RMatrix2D.prototype.set = setMatrix; / Provide the same functionality as pushMatrix() as a method. / function push() { this.stack = this.stack \|\| []; / NB: Array.new() does not work / this.stack.push(this.get()); } RMatrix2D.prototype.push = RMatrix2D.prototype.pushMatrix = push; / Provide the same functionality as popMatrix() as a method. / function pop() { var stack = this.stack; if (stack && stack.length > 0) { this.set(stack.pop()); } } RMatrix2D.prototype.pop = RMatrix2D.prototype.popMatrix = pop; / * Shear this RMatrix2D on the X axis by the stated angle. * Interface and definition inspired by P5.js. / function shearX(angle) { var t = tan(angle); var rm = RMatrix2D.new(1, t, 0, 0, 1, 0); this.apply(rm); } RMatrix2D.prototype.shearX = shearX; / Shear this RMatrix2D on the Y axis by the stated angle. / function shearY(angle) { var t = tan(angle); var rm = RMatrix2D.new(1, 0, 0, t, 1, 0); this.apply(rm); } RMatrix2D.prototype.shearY = shearY; / * Return the inverse of this matrix. Caller provides * a target results matrix or is provided a STATIC * property of this matrix. / function inverse(results) { var E = this.elements, e0 = E[0], e1 = E[1], e2 = E[2], e3 = E[3], e4 = E[4], e5 = E[5]; var d = this.determinant(); if (abs(d) < epsilon) { throw "No matrix inverse possible!"; } d = 1 / d; results = results \|\| (this.inverted = this.inverted \|\| RMatrix2D.new()); results.elements.length = 0; results.elements.push( e4 d, e1 * -d, (e1 * e5 - e4 * e2) * d, e3 * -d, e0 * d, (e3 * e2 - e0 * e5) * d ); return results; } RMatrix2D.prototype.inverse = inverse; /* * Compute this 2×2 matrix's eigenvalues and UNIT eigenvectors. See * http://www.math.harvard.edu/archive/21b_fall_04/exhibits/2dmatrices/index.html * for formulas. / function eigen() { var ev1 = this.eigenVector1; var ev2 = this.eigenVector2; var E = this.elements, e0 = E[0], e1 = E[1], e3 = E[3], e4 = E[4]; var halfTrace = (e0 + e4) / 2; var discrim = halfTrace halfTrace - this.determinant(); discrim = (discrim < epsilon) ? 0 : sqrt(discrim); var lamda1 = this.lamda1 = halfTrace + discrim; var lamda2 = this.lamda2 = halfTrace - discrim; if (abs(e3) > epsilon) { ev1.set(lamda1 - e4, e3, 0); ev2.set(lamda2 - e4, e3, 0); } else if (abs(e1) > epsilon) { ev1.set(e1, lamda1 - e0, 0); ev2.set(e1, lamda2 - e0, 0); } else if (abs(e0 - lamda1) < epsilon) { ev1.set(1, 0, 0); ev2.set(0, 1, 0); return; } else { ev2.set(1, 0, 0); ev1.set(0, 1, 0); return; } ev1.normalize(); ev2.normalize(); } RMatrix2D.prototype.eigen = eigen; var myV = RMatrix2D.new(); var myP = RMatrix2D.new(); /* * Find the Singular Value Decomposition of this. Parameters * are all required RMatrix2D output targets. So this = U×S×VT. * Returns true on success. See section 8.1 of * https://datajobs.com/data-science-repo/SVD-Tutorial-[Kirk-Baker].pdf / function svd(U, S, VT) { / Degenerate matrices (collinear vectors) are a big fail. / if (abs(this.determinant()) < epsilon) { return false; } var E = this.elements, a = E[0], b = E[1], c = E[3], d = E[4]; / Special (simple) case for orthogonal vectors. / if (abs(ab + cd) < orthogEpsilon) { var magX = sqrt(aa + cc); var magY = sqrt(bb + dd); U.set( a/magX, b/magY, 0, c/magX, d/magY, 0 ); S.set( magX, 0, 0, 0, magY, 0); VT.resetMatrix(); / VT = Identity matrix / return true; } / U is derived from the eigenvector of EE' / myP.set(a, c, 0, b, d, 0); / sets myP = E' / myP.preApply(this); myP.eigen(); var u1 = myP.eigenVector1, u2 = myP.eigenVector2; U.set(u1.x, u2.x, 0, u1.y, u2.y, 0); / S diag is 1/sqrt of the eigenvalues / S.set(sqrt(myP.lamda1), 0, 0, 0, sqrt(myP.lamda2), 0); / * V = [v1, v2] where the column vectors * v1 = (1/sqrt(lamda1))·E'·u1 and * v2 = (1/sqrt(lamda2))·E'·u2. / var V = myV; myP.set(a, c, 0, b, d, 0); / myP = E' / myP.transform(u1, u1); u1.div(S.elements[0]); myP.transform(u2, u2); u2.div(S.elements[4]); V.set(u1.x, u2.x, 0, u1.y, u2.y, 0); / * Multiply U and V by minusOne if U does not appear to be a * valid rotation matrix. minusOne × minusOne === Identity, so * U×S×V remains the same. minusOne = [ -1, 0, 0, 0, 1, 0 ]. This * is the same as negating each X column vector of the two matrices. / U = U.elements; V = V.elements; if (U[0] U[4] <= 0) { U[0] = -1; U[3] = -1; V[0] = -1; V[3] = -1; } VT.set(V[0], V[3], 0, V[1], V[4], 0); /* VT = V' / return true; } RMatrix2D.prototype.svd = svd; var myU = RMatrix2D.new(); var myS = RMatrix2D.new(); var myVT = RMatrix2D.new(); var rotReflect = RMatrix2D.new(); var tuY = PVector.new(); / * This method provides the arguments to translate, * rotate, and scale that can reconstruct a rendering * matrix. Results parameter is returned. If no results * parameter is given then a STATIC object is returned. * Will return null on failure. See applyMopsToPJS() * for HOW to apply the transformations. / function reconstitute(results) { var matrix = this; if (! matrix.determinant) { return null; // more KA silliness } var atan2 = aTan2; var mops = results \|\| matrix.mops; var E = matrix.elements; mops.tx = E[2]; mops.ty = E[5]; if (matrix.determinant() < 0) { / * A negative determinant means that the Y axis * is a negative angle from X axis in a universe * where the Y axis must be a positive angle from X axis. * So, find the SVD of a similar "positive" matrix whose * X column vector is collinear with the X axis, and * whose Y column vector is reflected by the X axis. / var a = E[0], b = E[1], c = E[3], d = E[4]; tuY.set(b, d, 0); mops.rot0 = atan2(c, a); / rotation FROM X axis / tuY.rotate(-mops.rot0); / normalize tuX & tuV back TO X axis. / rotReflect.set(sqrt(aa + cc), tuY.x, 0, 0, -tuY.y, 0); matrix = rotReflect; mops.initSy = -1; / reconcile reflection, -tuY.y / } else { mops.rot0 = 0; / no rotation / mops.initSy = 1; / no reflection / } / Now, factor matrix into three matrices... / if (! matrix.svd(myU, myS, myVT)) { return null; } / * Since matrix = U×S×VT, compute arguments to rotate and * scale that can reconstruct matrix. Do the first rotate... / mops.rot1 = atan2(myU.elements[3], myU.elements[0]); / Then do a scale. / mops.sx = myS.elements[0]; mops.sy = myS.elements[4]; / Finally do another rotate. / mops.rot2 = atan2(myVT.elements[3], myVT.elements[0]); return mops; } RMatrix2D.prototype.reconstitute = reconstitute; / * Static function applies the results of the reconstitute() * method to THE Processing.js rendering matrix. The only * way to do that is via a series of tranformation calls. * Returns true if mops. / function applyMopsToPJS(mops) { if (mops) { void((mops.tx \|\| mops.ty) && translate(mops.tx, mops.ty)); void(mops.rot0 && rotate(mops.rot0)); void((mops.initSy !== 1) && scale(1, mops.initSy)); void(mops.rot1 && rotate(mops.rot1)); void((mops.sx !== 1 \|\| mops.sy !== 1) && scale(mops.sx, mops.sy)); void(mops.rot2 && rotate(mops.rot2)); return true; } } RMatrix2D.applyMopsToPJS = applyMopsToPJS; / * Apply this RMatrix2D to THE Processing.js rendering matrix. * Returns true iff successful. / function applyMopsToPJS() { return RMatrix2D.applyMopsToPJS(this.reconstitute()); } RMatrix2D.prototype.applyMopsToPJS = applyMopsToPJS; / * (The Holy Grail.) * Static function applies the RMatrix2D rm to THE * Processing.js rendering matrix. If you want to SET * the Processing.js matrix, then invoke resetMatrix() * prior to invoking this function. Returns true iff * successful. / function applyMatrix(/ rm /) { var rm = arguments[0]; / KA silliness / return rm.applyMopsToPJS(); } RMatrix2D.applyMatrix = applyMatrix; / * Static function that converts the string * produced by Processing.js printMatrix to a * RMatrix2D object. KA printMatrix() outputs * six numbers on two lines that look like * a b c * d e f * You should pass ONE string that looks like * a b c d e f * where the numbers are separated by blanks. * Optional parameter results is where the result * are placed and returned. It must be a RMatrix2. * If none is provided then a new one is created. / function string2RMatrix(s, results) { try { / more KA silliness / results = results \|\| RMatrix2D.new(); var token = s.split(" "); var num = results.elements; for (var n = 0, i = 0; (n < 6) && (i < token.length); i++) { var f = parseFloat(token[i]); if (f > f - 1) { / f is really a (useful) number / num[n++] = f; } } if (n !== 6) { println("Expected six, but got " + n + " numbers!"); } return results; } catch(err) {} } RMatrix2D.string2RMatrix = string2RMatrix; / Names of extremely interesting Processing.js functions. / RMatrix2D.transforms = [ "translate", "scale", "rotate", "pushMatrix", "popMatrix", "resetMatrix" ]; / * This static function returns a RMatrix2D that * reflects the transformation operations performed * on the Processiong.js transformation functions. * Sane people will most likely invoke this after a * resetMatrix(). * The Interpose parameter is the Interpose library that * knows how to capture calls to Processing.js. Get that * library at * https://www.khanacademy.org/cs/i/5992045511049216 / function mirrorPJS(Interpose) { var mirror = RMatrix2D.new(); / * This interpose-function invokes the equivalent * method in the RMatrix2D object "mirror" that * reflects the Processing.js rendering matrix. / function mirrorMatrixOp() { var mirroredFunction = mirror[this.name]; if (mirroredFunction && mirroredFunction.apply) { / * This should ALWAYS be the case, but life with the * KA live-editor and resetMatrix is really tough. / mirroredFunction.apply(mirror, arguments); } } / Interpose plumbing... / RMatrix2D.transforms.forEach( function(val) { Interpose.push(val, mirrorMatrixOp); }); / Undo method. The method itself disappears... / function breakMirror() { RMatrix2D.transforms.forEach( function(val) { Interpose.pop(val); }); delete mirror.breakMirror; } mirror.breakMirror = breakMirror; return mirror; } RMatrix2D.mirrorPJS = mirrorPJS; return RMatrix2D; // last edited 2023.03.11 })(); / RMatrix2D is a constructor copied from www.khanacademy.org/cs/mr/3793059675 / var mops, rm = new RMatrix2D(); var tuX = new PVector(); / transformed unit X vector / var tuY = new PVector(); / transformed unit Y vector / var backgroundColor = color(94, 4, 74); var sideColor = lerpColor(-1579033, -2236963, 0.5); var tX = width/2; var tY = height/2; var node0 = new PVector(0, 0, coinDepth/2); var node1 = new PVector(coinRadius, 0, coinDepth/2); var node2 = new PVector(0, coinRadius, coinDepth/2); var heads = { nodes: [node0, node1, node2], color: sideColor, img: headsImg }; var node3 = new PVector(0, 0, -coinDepth/2); var node4 = new PVector(coinRadius, 0, -coinDepth/2); var node5 = new PVector(0, -coinRadius, -coinDepth/2); var tails = { nodes: [node3, node4, node5], color: sideColor, img: tailsImg, other: heads}; heads.other = tails; var nodes = [node0, node1, node2, node3, node4, node5]; / Library for engraving on the size of a coin / var Engraving = (function(radius, depth, fontName) { fontName = fontName \|\| "monoSpace"; var fontSize = 0.65 depth; var font = createFont(fontName, fontSize); textFont(font, fontSize); var engraving = []; var tau = (cos(PI) < 0) ? TWO_PI : 360; var erm = new RMatrix2D(); /* * Constructor for engraving (a single character) on the side of coin. * Assumes that the font and its size are currently set. / var Engraving = function(theta, txt) { this.txt = txt; var pos = this.pos = new PVector(radiuscos(theta), radiussin(theta), 0); this.ux = new PVector(cos(theta - tau/4), sin(theta - tau/4), 0); this.uy = new PVector(0, 0, -1); this.ux.add(pos); this.uy.add(pos); nodes.push(pos, this.ux, this.uy); engraving.push(this); }; / * Engrave txt by rendering at coordinate (0, 0), * presumibly with textAlign() / var engrave = function(txt) { text(txt, 0, 0); text(txt, 0, 0); / bold! / }; / * Engrave this txt. Fill has been set, and * assumes textAlign(CENTER, CENTER). / Engraving.prototype.draw = function() { var origin = this.pos; if (origin.z > 0) { tuX.set(this.ux); tuX.sub(origin); tuX.normalize(); tuY.set(this.uy); tuY.sub(origin); tuY.normalize(); erm.set(tuX.x, tuY.x, origin.x, tuX.y, tuY.y, origin.y); pushMatrix(); RMatrix2D.applyMatrix(erm); engrave(this.txt); popMatrix(); } }; / Render all the engravings. / Engraving.draw = function() { textAlign(CENTER, CENTER); textFont(font, fontSize); for (var i = engraving.length; --i >= 0; ) { var e = engraving[i]; if (e.pos.z > 0) { e.draw(); } } }; / Computes total width by summing individual widths. / var myTextWidth = function(txt) { for (var sum = 0, i = 0; i < txt.length; i++) { sum += textWidth(txt[i]); } return sum; }; / * Return the implied subtended circlular arc, given the length. * theta/tau = len/circumference, or * theta = len/circumference * tau / var subtendedAngle = function(len) { return len / TWO_PI / radius tau; }; /* * Set up engraving for a multi-character phrase, starting * at theta. Assumes that the font and size has been set. / Engraving.phrase = function(theta, phrase) { for (var sub, i = phrase.length; --i >= 0; theta += sub) { var c = phrase[i]; if (c !== " ") { new Engraving(theta, c); } sub = subtendedAngle(myTextWidth(c)); } }; / Layout all phrases. Assumes that the font and size has been set. / Engraving.phrases = function() { if (arguments.length === 1 && Array.isArray(arguments[0])) { return Engraving.phrases.apply(null, arguments[0]); } textAlign(CENTER, CENTER); textFont(font, fontSize); for (var slop = TWO_PI radius, i = 0; i < arguments.length; i++) { slop -= myTextWidth(arguments[i]); } slop /= arguments.length; var theta = tau/4 - subtendedAngle(myTextWidth(arguments[0])) / 2; for (i = 0; i < arguments.length; i++) { Engraving.phrase(theta, arguments[i]); theta += subtendedAngle(myTextWidth(arguments[i]) + slop); } }; return Engraving; })(coinRadius, coinDepth); Engraving.phrases(phrases); /* * Draw a circle at the origin. The stroke and fill * have already been set. * * If the img argument is passed, then render it at * the origin. Assumes imageMode(CENTER). / var circle = function(img) { var d = coinRadius 2; ellipse(0, 0, d, d); if (img) { image(img, 0, 0, d, d); } }; /* * Draw one cyclinder face. The stroke and fill have already * been set. Optional texture image is also drawn. / var drawFace = function(face, img) { / render the circle / pushMatrix(); translate(face.nodes[0].x, face.nodes[0].y); RMatrix2D.applyMopsToPJS(mops); circle(img); popMatrix(); }; / * Draw the cylinder's side, given its tail. * The side's stroke and fill colors have been set. / var drawCylinderSide = function(tail) { var origin = tail.nodes[0], ox = origin.x, oy = origin.y; var heads = tail.other.nodes[0], hx = heads.x, hy = heads.y; / * Set vector (dx, dy) to the perpendicular of the vector * between heads and origin, with magnitude coinRadius. / var dy = hx - ox; var dx = oy - hy; var mag = sqrt(dxdx + dydy); dx = coinRadius/mag; dy = coinRadius/mag; / The view of the side is a quad with the following coordinates: / var ax = ox + dx, ay = oy + dy; var bx = hx + dx, by = hy + dy; var cx = hx - dx, cy = hy - dy; var dx = ox - dx, dy = oy - dy; / Fill(?) with noStroke... / pushStyle(); noStroke(); quad(ax, ay, bx, by, cx, cy, dx, dy); popStyle(); / Stroke (maybe)... / line(ax, ay, bx, by); line(cx, cy, dx, dy); fill(130); Engraving.draw(); }; / * Draw the cylinder, by drawing its three parts in * the correct order. / var drawCylinder = function() { var bottom = (heads.nodes[0].z > tails.nodes[0].z) ? tails : heads; var top = (bottom === tails) ? heads : tails; var n = top.nodes, origin = n[0]; / tuX = normailze(n[1] - n[0]) / tuX.set(n[1]); tuX.sub(origin); tuX.div(coinRadius); / tuY = normalize(n[2] - n[0]) / tuY.set(n[2]); tuY.sub(origin); tuY.div(coinRadius); rm.set( tuX.x, tuY.x, 0, tuX.y, tuY.y, 0 ); mops = rm.reconstitute(mops); stroke(100); fill(sideColor); drawFace(bottom); drawCylinderSide(bottom); fill(top.color); drawFace(top, top.img); }; / Rotate all points around the z-axis. / var rotateZ3D = function(theta) { if ((theta /= 2)) { versor.init(0, 0, sin(theta), cos(theta)); versor.rotateV.apply(versor, nodes); } }; / Rotate all points around the y-axis. / var rotateY3D = function(theta) { if ((theta /= 2)) { versor.init(0, sin(theta), 0, cos(theta)); versor.rotateV.apply(versor, nodes); } }; / Rotate all points around the x-axis. / var rotateX3D = function(theta) { if ((theta /= 2)) { versor.init(sin(theta), 0, 0, cos(theta)); versor.rotateV.apply(versor, nodes); } }; var coinOrig = new PVector(); var coinAxis = new PVector(); / * Compute the current realities of the coin. * All (optional) arguments are results PVectors. / var coinGeometry = function(origin, x, y, z) { var h = heads.nodes, h0 = h[0]; if (origin) { origin.set(h0); origin.add(tails.nodes[0]); origin.div(2); / position vector / } if (z) { z.set(h0); z.sub(tails.nodes[0]); z.normalize(); } if (y) { y.set(h[2]); y.sub(h0); y.normalize(); } if (x) { x.set(h[1]); x.sub(h0); x.normalize(); } }; / Rotate the coin around its z-axis. / var rotateCoinZ = function(theta) { if (theta) { coinGeometry(coinOrig, null, null, coinAxis); axisRotate(theta, coinAxis, nodes, coinOrig); } }; / Rotate the coin around its y-axis. / var rotateCoinY = function(theta) { if (theta) { coinGeometry(coinOrig, null, coinAxis); axisRotate(theta, coinAxis, nodes, coinOrig); } }; / Rotate the coin around its x-axis. / var rotateCoinX = function(theta) { if (theta) { coinGeometry(coinOrig, coinAxis); axisRotate(theta, coinAxis, nodes, coinOrig); } }; / Like draw(), called to render the picture canvas. / var render = function() { pushMatrix(); translate(tX, tY); background(backgroundColor); drawCylinder(); popMatrix(); }; var moving = false; / Called by Processing.js when the mouse has been clicked. / mouseClicked = function() { moving = !moving; }; / Called by Processing.js when the mouse has moved. / mouseMoved = function() { if (moving) { var d = pmouseX - mouseX; if (d) { rotateCoinY(-d); } d = pmouseY - mouseY; if (d) { rotateCoinX(d); } render(); } }; / Called by Processing.js when a key has been typed. / keyPressed = function() { if (keyCode === RIGHT) { rotateCoinZ(+2); } else if (keyCode === LEFT) { rotateCoinZ(-2); } render(); }; noStroke(); imageMode(CENTER); / All images are drawn at the origin */ render(); // I am honored any time anybody uses my code for any purpose. // Copy freely! All my programs are at // https://www.khanacademy.org/profile/BobLyon/programs // I can be reached at Robert.B.Lyon@gmail.com
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Type	PJS
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Height	400
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Author Nick	Bob Lyon
Author Name	BobLyon
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Archive Data

Added	10 months ago, 1739460142697
Updated	10 months ago, 1739460148183
Source Deleted	unknown