Syntax Highlight/Format C#, Java, PHP Code in Blogger

The method I used to put syntax highlighted code in my blog is to use the "Code Format" tool provided by Manoli.net. It works fine but I am just lazy to convert my code every time I post a new entry.

I then try to find another solution. One option is to use SyntaxHighlighter, a Java Script library that does all the syntax highlight jobs for you.

After installation, one problem I faced is that all the "new line" I wrote in "Edit Html" of Compose Page in Blogger are converted to "
". That's not very nice : (

Like everytime, I performed a search and found a good solution here, Using SyntaxHighlighter on BLOGGER. The purpose of additional script is to convert all the "
" found in the code to "new line" chracter. It works fine and here is my sample of highlighted Java code.

(Of course, I will not use silly program like Hello World for this :D )

And here is the result:

<br />//Write this method<br /><br /> public static int[] ranking(double[][] train, double[][] test, int[] trainrank) {<br /><br /> int numInput = train[0].length, numHidden = train[0].length, numOut = 1;<br /> double eta = 0.25, alpha = 0.5, smallwt = 0.5;<br /><br /> double[] hidden = new double[numHidden + 1];<br /> double[] deltaH = new double[numHidden + 1];<br /> double[] output = new double[numOut + 1];<br /> double[] deltaO = new double[numOut + 1];<br /> double[][] weightIH = new double[numInput + 1][numHidden + 1];<br /> double[][] deltaIH = new double[numInput + 1][numHidden + 1];<br /> double[][] weightHO = new double[numHidden + 1][numOut + 1];<br /> double[][] deltaHO = new double[numHidden + 1][numOut + 1];<br /><br /> // Initialize<br /> for (int i = 1; i <= numInput; i++) {<br /> for (int j = 1; j <= numHidden; j++) {<br /> weightIH[i][j] = 2.0 * (Math.random() - 0.5) * smallwt;<br /> deltaIH[i][j] = 2.0 * (Math.random() - 0.5) * smallwt;<br /> }<br /> }<br /><br /> for (int i = 0; i <= numHidden; i++) {<br /> for (int j = 0; j <= numOut; j++) {<br /> weightHO[i][j] = 2.0 * (Math.random() - 0.5) * smallwt;<br /> deltaHO[i][j] = 2.0 * (Math.random() - 0.5) * smallwt;<br /> }<br /> }<br /><br /> // Normalize Rank<br /> int numRank = trainrank.length;<br /> double[] normalRank = new double[numRank];<br /> for (int i = 0; i < trainrank.length; i++) {<br /> normalRank[i] = trainrank[i] * 1.0 / (numRank);<br /><br /> System.out.println("normalRank = " + normalRank[i]);<br /> }<br /><br /> // Begin Training<br /> for (int epoch = 0; epoch <= 3000; epoch++) {<br /><br /> // Randomizing train data order<br /> int[] shuffle = new int[train.length];<br /> for (int i = 0; i < shuffle.length; i++) {<br /> shuffle[i] = i;<br /> }<br /> for (int i = 0; i < train.length; i++) {<br /> int p = (int) (Math.random() * train.length);<br /> int tmp = shuffle[i];<br /> shuffle[i] = shuffle[p];<br /> shuffle[p] = tmp;<br /> }<br /><br /> double error = 0.0;<br /><br /> for (int t = 0; t < train.length; t++) {<br /> int p = shuffle[t];<br /><br /> // Calculate Hidden Units activations<br /> for (int i = 1; i <= numHidden; i++) {<br /> double sum = weightIH[0][i];<br /> for (int j = 1; j <= numInput; j++) {<br /> sum += train[p][j - 1] * weightIH[j][i];<br /> }<br /> hidden[i] = 1.0 / (1.0 + Math.exp(-sum));<br /> }<br /><br /> for (int i = 1; i <= numOut; i++) {<br /> double sum = weightHO[0][i];<br /> for (int j = 1; j <= numHidden; j++) {<br /> sum += hidden[j] * weightHO[j][i];<br /> }<br /> output[i] = 1.0 / (1.0 + Math.exp(-sum));<br /><br /> error += 0.5 * (normalRank[p] - output[i]) * (normalRank[p] - output[i]);<br /> deltaO[i] = (normalRank[p] - output[i]) * output[i] * (1.0 - output[i]);<br /><br /> }<br /><br /> // Back Propagate<br /> for (int i = 1; i <= numHidden; i++) {<br /> double sum = 0.0;<br /> for (int j = 1; j <= numOut; j++) {<br /> sum += weightHO[i][j] * deltaO[j];<br /> }<br /> deltaH[i] = sum * hidden[i] * (1.0 - hidden[i]);<br /> }<br /><br /> // Update weightIH<br /> for (int i = 1; i <= numHidden; i++) {<br /> deltaIH[0][i] = eta * deltaH[i] + alpha * deltaIH[0][i];<br /> weightIH[0][i] += deltaIH[0][i];<br /> for (int j = 1; j <= numInput; j++) {<br /> deltaIH[j][i] = eta * train[p][j - 1] * deltaH[i] + alpha * deltaIH[j][i];<br /> weightIH[j][i] += deltaIH[j][i];<br /> }<br /> }<br /><br /> // Update weightHO<br /> for (int i = 1; i <= numOut; i++) {<br /> deltaHO[0][i] = eta * deltaO[i] + alpha * deltaHO[0][i];<br /> weightHO[0][i] += deltaHO[0][i];<br /> for (int j = 1; j <= numHidden; j++) {<br /> deltaHO[j][i] = eta * hidden[j] * deltaO[i] + alpha * deltaHO[j][i];<br /> weightHO[j][i] += deltaHO[j][i];<br /> }<br /> }<br /> }<br /><br /> if (epoch % 100 == 0) {<br /> System.out.println("Epoch #" + epoch + " Error = " + error);<br /> }<br /><br /> if (error < 0.01) {<br /> System.out.println("Training Completed!");<br /> break;<br /> }<br /> }<br /><br /> // Get result;<br /><br /> double[] testRealRank = new double[test.length];<br /> for (int p = 0; p < test.length; p++) {<br /><br /> // Calculate Hidden Units activations<br /> for (int i = 1; i <= numHidden; i++) {<br /> double sum = weightIH[0][i];<br /> for (int j = 1; j <= numInput; j++) {<br /> sum += test[p][j - 1] * weightIH[j][i];<br /> }<br /> hidden[i] = 1.0 / (1.0 + Math.exp(-sum));<br /> }<br /><br /> // Calculate Output Units <br /> for (int i = 1; i <= numOut; i++) {<br /> double sum = weightHO[0][i];<br /> for (int j = 1; j <= numHidden; j++) {<br /> sum += hidden[j] * weightHO[j][i];<br /> }<br /> output[i] = 1.0 / (1.0 + Math.exp(-sum));<br /> }<br /><br /> testRealRank[p] = output[1];<br /> }<br /><br /> int[] testRank = getRank(testRealRank);<br /> return testRank;<br /> }<br /><br /> public static int[] getRank(double[] normRank) {<br /> int[] newRank<br /> = new int[normRank.length];<br /> boolean[] flag =<br /> new boolean[normRank.length];<br /> <br /> for (int i = 1; i <= newRank.length; i++) {<br /> <br /> double min = Double.MAX_VALUE;<br /> int minPos = -1;<br /> for (int j = 0; j < newRank.length; j++) {<br /> if (!flag[j] && (normRank[j] < min)) {<br /> min = normRank[j];<br /> minPos = j;<br /> }<br /> }<br /> <br /> newRank[minPos] = i;<br /> flag[minPos] = true;<br /> }<br /> return newRank;<br /> }<br />

Simple, isn't it ?