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/*
example.js
this node script will serve a web-page with an interactive neural net
instruction
1. save this script as example.js
2. run the shell command:
$ npm install fann-lite && node example.js
3. open a browser to http://localhost:1337
4. edit or paste script in browser to interact with the neural net
*/
/*jslint
browser: true,
maxerr: 8,
maxlen: 96,
node: true,
nomen: true,
stupid: true
*/
(function (local) {
'use strict';
// run node js-env code
(function () {
// require modules
local.fs = require('fs');
local.http = require('http');
local.path = require('path');
local.url = require('url');
// init assets
local['/'] = (String() +
/* jslint-ignore-begin */
'<!DOCTYPE html>\n' +
'<html>\n' +
'<head>\n' +
'<meta charset="UTF-8">\n' +
'<title>\n' +
'fann-lite [2015.6.1-a]\n' +
'</title>\n' +
'<link rel="stylesheet" href="/assets/utility2.css">\n' +
'<style>\n' +
'* {\n' +
'box-sizing: border-box;\n' +
'}\n' +
'body {\n' +
'background-color: #fff;\n' +
'font-family: Helvetical Neue, Helvetica, Arial, sans-serif;\n' +
'}\n' +
'body > div {\n' +
'margin-top: 20px;\n' +
'}\n' +
'textarea {\n' +
'font-family: monospace;\n' +
'height: 32em;\n' +
'width: 100%;\n' +
'}\n' +
'.csslintOutputPre {\n' +
'color: #f00;\n' +
'}\n' +
'.fannOutputPre {\n' +
'color: #f00;\n' +
'}\n' +
'.testReportDiv {\n' +
'display: none;\n' +
'}\n' +
'</style>\n' +
'</head>\n' +
'<body>\n' +
'<div class="ajaxProgressDiv" style="display: none;">\n' +
'<div class="ajaxProgressBarDiv ajaxProgressBarDivLoading" >loading</div>\n' +
'</div>\n' +
'<h1 >fann-lite [2015.6.1-a]</h1>\n' +
'<h3>pure javascript version of fann (fast artificial neural net library) with zero npm-dependencies (compiled from emscripten)</h3>\n' +
'<div>edit or paste script below to\n' +
'<a href="http://leenissen.dk/fann/html/files2/gettingstarted-txt.html" target="_blank">\n' +
'eval</a>\n' +
'</div>\n' +
'<textarea class="fannInputTextarea">\n' +
'// test\n' +
'local.ann = local.fann.create_standard(3, 2, 3, 1);\n' +
'local.data = local.fann\n' +
'.create_train_from_array(4, 2, 1, [-1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, -1]);\n' +
'local.fann\n' +
'.set_activation_function_hidden(local.ann, local.fann.ACTIVATION_SIGMOID_SYMMETRIC);\n' +
'local.fann.set_activation_function_output(local.ann, 5);\n' +
'local.fann.train_on_data(local.ann, local.data, 5000, 1000, 0.001);\n' +
'console.log("1 xor 1 -> " + local.fann.run(local.ann, [1, 1]));\n' +
'console.log("1 xor 0 -> " + local.fann.run(local.ann, [1, -1]));\n' +
'console.log("0 xor 1 -> " + local.fann.run(local.ann, [-1, 1]));\n' +
'</textarea>\n' +
'<pre class="fannOutputPre"></pre>\n' +
'<div class="testReportDiv"></div>\n' +
'<script src="/assets/fann.js"></script>\n' +
'<script src="/assets/utility2.js"></script>\n' +
'<script>\n' +
'window.utility2 = window.utility2 || {};\n' +
'window.utility2.envDict = {\n' +
'npm_package_description: "pure javascript version of fann (fast artificial neural net library) with zero npm-dependencies (compiled from emscripten)",\n' +
'npm_package_name: "fann-lite",\n' +
'npm_package_version: "2015.6.1-a"\n' +
'};\n' +
'document.querySelector(\n' +
'".fannInputTextarea"\n' +
').addEventListener("keyup", window.fann.fannInputTextarea);\n' +
'window.fann.fannInputTextarea();\n' +
'</script>\n' +
'<script src="/test/test.js"></script>\n' +
'</body>\n' +
'</html>\n' +
/* jslint-ignore-end */
String()).replace((/\{\{envDict\.\w+?\}\}/g), function (match0) {
switch (match0) {
case '{{envDict.npm_package_description}}':
return 'this is an example module';
case '{{envDict.npm_package_name}}':
return 'example-module';
case '{{envDict.npm_package_version}}':
return '0.0.1';
default:
return '';
}
});
local['/assets/fann.js'] = local.fann['/assets/fann.js'];
local['/assets/utility2.css'] = '';
local['/assets/utility2.js'] = '';
local['/test/test.js'] = '';
// create server
local.server = local.http.createServer(function (request, response) {
switch (local.url.parse(request.url).pathname) {
// serve assets
case '/':
case '/assets/fann.js':
case '/assets/utility2.css':
case '/assets/utility2.js':
case '/test/test.js':
response.end(local[local.url.parse(request.url).pathname]);
break;
// default to 404 Not Found
default:
response.statusCode = 404;
response.end('404 Not Found');
}
});
Eif (process.env.npm_config_server_port) {
return;
}
// start server
local.serverPort = 1337;
console.log('server starting on port ' + local.serverPort);
local.server.listen(local.serverPort, function () {
// this internal build-code will screen-capture the server
// and then exit
if (process.env.MODE_BUILD === 'testExampleJs') {
console.log('server stopping on port ' + local.serverPort);
require(
process.env.npm_config_dir_utility2 + '/index.js'
).phantomScreenCapture({
url: 'http://localhost:' + local.serverPort
}, process.exit);
}
});
}());
}((function () {
'use strict';
var local;
// run shared js-env code
(function () {
// init local
local = {};
local.modeJs = (function () {
try {
return module.exports &&
typeof process.versions.node === 'string' &&
typeof require('http').createServer === 'function' &&
'node';
} catch (errorCaughtNode) {
return typeof navigator.userAgent === 'string' &&
typeof document.querySelector('body') === 'object' &&
'browser';
}
}());
// init global
local.global = local.modeJs === 'browser'
? window
: global;
// init fann-lite
local.fann = local.modeJs === 'browser'
? window.fann
: (function () {
try {
return require('fann-lite');
} catch (errorCaught) {
return require('./fann.js');
}
}());
// export local
module.exports = local;
}());
return local;
}()))); |