info.michael-simons.eu

import org.apache.poi.ss.formula.OperationEvaluationContext;
import org.apache.poi.ss.formula.eval.EvaluationException;
import org.apache.poi.ss.formula.eval.NumberEval;
import org.apache.poi.ss.formula.eval.OperandResolver;
import org.apache.poi.ss.formula.eval.ValueEval;
import org.apache.poi.ss.formula.functions.FreeRefFunction;
 
/**
 * Java Implementation of http://support.microsoft.com/kb/827358/en-us implementing 
 * Apache POIs {@link FreeRefFunction} to be used as a user defined function.
 * 
 * Mathematics found here: 
 * https://gist.github.com/kmpm/1211922/
 * https://gist.github.com/kmpm/1211922/raw/a11e0dfc9fab493bcdadc669f3213d11f1897ebf/norminv.js
 * 
 * Register for a given workbook with:
 * 
    <code>
		final UDFFinder udfs = new DefaultUDFFinder(new String[]{ "MS_NormInv" }, new FreeRefFunction[]{ new NormInv() }) ;        
		workbook.addToolPack(new AggregatingUDFFinder(new UDFFinder[] {udfs}));
    </code>
 * @author michael.simons
 */
public class NormInv implements FreeRefFunction {
	public ValueEval evaluate(ValueEval[] args, OperationEvaluationContext ec) {		
		try {
			final ValueEval p = OperandResolver.getSingleValue(args[0], ec.getRowIndex(), ec.getColumnIndex()) ;
			final ValueEval mu = OperandResolver.getSingleValue(args[1], ec.getRowIndex(), ec.getColumnIndex()) ;
			final ValueEval sigma = OperandResolver.getSingleValue(args[2], ec.getRowIndex(), ec.getColumnIndex()) ;			
			return new NumberEval(this.compute(OperandResolver.coerceValueToDouble(p), OperandResolver.coerceValueToDouble(mu), OperandResolver.coerceValueToDouble(sigma)));
		} catch (EvaluationException e) {
			return e.getErrorEval();
		}			 		
	}
 
	/**
	 * Original C++ implementation found at http://www.wilmott.com/messageview.cfm?catid=10&threadid=38771
	 * C# implementation found at http://weblogs.asp.net/esanchez/archive/2010/07/29/a-quick-and-dirty-implementation-of-excel-norminv-function-in-c.aspx
	 *    Compute the quantile function for the normal distribution.
	 *
	 *    For small to moderate probabilities, algorithm referenced
	 *    below is used to obtain an initial approximation which is
	 *    polished with a final Newton step.
	 *    For very large arguments, an algorithm of Wichura is used.
	 *
	 *  REFERENCE
	 *
	 *    Beasley, J. D. and S. G. Springer (1977).
	 *    Algorithm AS 111: The percentage points of the normal distribution,
	 *    Applied Statistics, 26, 118-121.
	 *
	 *     Wichura, M.J. (1988).
	 *     Algorithm AS 241: The Percentage Points of the Normal Distribution.
	 *     Applied Statistics, 37, 477-484.
	 * @param p
	 * @param mu
	 * @param sigma
	 * @return
	 */
	public double compute(double p, double mu, double sigma) {
		if(p < 0 || p > 1) 
			throw new RuntimeException("The probality p must be bigger than 0 and smaller than 1");		
		if(sigma < 0)
			throw new RuntimeException("The standard deviation sigma must be positive");
		if(p == 0)
			return Double.NEGATIVE_INFINITY;		
		if(p == 1)
			return Double.POSITIVE_INFINITY;		
		if(sigma == 0)
			return mu;		
		double  q, r, val;
 
		q = p - 0.5;
 
		/* 0.075 <= p <= 0.925 */
		if(Math.abs(q) <= .425) {
			r = .180625 - q * q;
			val =
		         q * (((((((r * 2509.0809287301226727 +
		                    33430.575583588128105) * r + 67265.770927008700853) * r +
		                  45921.953931549871457) * r + 13731.693765509461125) * r +
		                1971.5909503065514427) * r + 133.14166789178437745) * r +
		              3.387132872796366608)
		         / (((((((r * 5226.495278852854561 +
		                  28729.085735721942674) * r + 39307.89580009271061) * r +
		                21213.794301586595867) * r + 5394.1960214247511077) * r +
		              687.1870074920579083) * r + 42.313330701600911252) * r + 1);
		}
		/* closer than 0.075 from {0,1} boundary */
		else {
		     /* r = min(p, 1-p) < 0.075 */
			 if (q > 0) {
				 r = 1 - p;
			 } else {
				 r = p;
			 }
 
			 r = Math.sqrt(-Math.log(r));
			 /* r = sqrt(-log(r))  < ==>  min(p, 1-p) = exp( - r^2 ) */
 
			 if (r < = 5) { /* <==> min(p,1-p) >= exp(-25) ~= 1.3888e-11 */
				 r += -1.6;
				 val = (((((((r * 7.7454501427834140764e-4 +
		                     .0227238449892691845833) * r + .24178072517745061177) *
		                   r + 1.27045825245236838258) * r +
		                  3.64784832476320460504) * r + 5.7694972214606914055) *
		                r + 4.6303378461565452959) * r +
		               1.42343711074968357734)
		              / (((((((r *
		                       1.05075007164441684324e-9 + 5.475938084995344946e-4) *
		                      r + .0151986665636164571966) * r +
		                     .14810397642748007459) * r + .68976733498510000455) *
		                   r + 1.6763848301838038494) * r +
		                  2.05319162663775882187) * r + 1);
			 } else { /* very close to  0 or 1 */
				 r += -5;
				 val = (((((((r * 2.01033439929228813265e-7 +
		                     2.71155556874348757815e-5) * r +
		                    .0012426609473880784386) * r + .026532189526576123093) *
		                  r + .29656057182850489123) * r +
		                 1.7848265399172913358) * r + 5.4637849111641143699) *
		               r + 6.6579046435011037772)
		              / (((((((r *
		                       2.04426310338993978564e-15 + 1.4215117583164458887e-7) *
		                      r + 1.8463183175100546818e-5) * r +
		                     7.868691311456132591e-4) * r + .0148753612908506148525)
		                   * r + .13692988092273580531) * r +
		                  .59983220655588793769) * r + 1);
		      }
 
		      if (q < 0.0) {
		          val = -val;
		      }
		  }
 
		  return mu + sigma * val;		
	}
}

mysqldump -uroot -proot --opt --routines --add-drop-database --default-character-set=utf8 --create-options --all-databases | \ 
bzip2 > backup.sql.bz2

mysqldump -uroot -proot --opt --routines --add-drop-database --default-character-set=utf8 --create-options --databases db1 db2 | \ 
bzip2 > backup.sql.bz2

bzcat backup.sql.bz2 | mysql -uroot -proot -D db1 -o

bzcat backup.sql.bz2 | mysql -uroot -proot

import java.text.Normalizer;
import java.text.Normalizer.Form;
 
public class NormalizerExample {	
	public static void main(String[] args) {
		String s = Normalizer.normalize("Á", Form.NFD);
		System.out.println("Decomposed:");
		for(int i=0;i<s.length();++i)
			System.out.println(Integer.toHexString((int)s.charAt(i)));
		s = Normalizer.normalize(s, Form.NFC);
		System.out.println("Composed:");
		for(int i=0;i<s.length();++i)
			System.out.println(Integer.toHexString((int)s.charAt(i)));
	}
}

String name = "Die Ärzte 2013!";
 
// Decompose unicode characters
String slug = Normalizer.normalize(name.toLowerCase(), Form.NFD)
// replace all combining diacritical marks and also everything that isn't a word or a whitespace character
	.replaceAll("\\p{InCombiningDiacriticalMarks}|[^\\w\\s]", "")
// replace all occurences of whitespaces or dashes with one single whitespace 
	.replaceAll("[\\s-]+", " ")
// trim the string
	.trim()
// and replace all blanks with a dash
	.replaceAll("\\s", "-");

if(Modernizr.touch)
	content.touchwipe({
	     wipeLeft: function() { $.fancybox.next(); },
	     wipeRight: function() { $.fancybox.prev() },		     
	     min_move_x: 20,
	     min_move_y: 20,
	     preventDefaultEvents: true
	});