ahmetaa

class SliderSample  {

  SliderMenu sliderMenu;
  final List<String> menuItems;

  SliderSample() : menuItems = const["Apple", "Banana", "Cherry", "Durian"] {}

  void ready() {
    document.query("#status").innerHTML = "Slider Menu Sample App";
    sliderMenu = new SliderMenu(menuItems, (selectedText) {

ahmetaa

package hashash;


public class IntIntLinearProbing {

    private final int INITIAL_SIZE = 8;
    private final double DEFAULT_LOAD_FACTOR = .7;
    private int modulo = INITIAL_SIZE - 1;
    int[] keys;
    int[] values;

ahmetaa

/** modified - shortened Jenkins 32 */
int _hash(List<int> key, int seed) {
  int h1 = seed;
  for (int i in key) {
    h1 += i;
    h1 += (h1 << 10);
    h1 ^= (h1 >> 6);
  }
  return h1 & 0x7fffffff;

ahmetaa

#!/usr/bin/perl
#Author: Haşim Sak @ Department of Computer Engineering - Boğaziçi University.
#Email: hasim.sak@gmail.com
#Version: 1.0
#Date: August 17, 2007
#Description: This program implements an averaged perceptron based morphological disambiguation system for Turkish text.
#             You can find the most up to date version at http://www.cmpe.boun.edu.tr/~hasim.
#             For more information, you can see readme.txt and read the following paper.
#             Haşim Sak, Tunga Güngör, and Murat Saraçlar. Morphological disambiguation of Turkish text with perceptron algorithm.
#             In CICLing 2007, volume LNCS 4394, pages 107-118, 2007.

ahmetaa

import 'dart:math';
import 'dart:scalarlist';

main() {
  print("Generating 10 40-length vector");
  List<List<double>> dataSmall = getData(10,40);  
  perfGaussian(dataSmall);
  perfSimdGaussian(dataSmall);  
  print("Generating 100000 40-length vector");  
  List<List<double>> dataLarge = getData(100000,40);

ahmetaa

main() {
  print("Merhaba Dünya");
}


import 'dart:html';

void main() {
  query("#ornek_yazi_id").text = "Merhaba Dünya";
}

ahmetaa

import 'dart:math';
import 'dart:typeddata';

main() {
  print("Generating 10 40-length vector");
  GaussData g = new GaussData.random(4);
  InputData dataSmall = new InputData.random(4,4);  
  perfList(g, dataSmall);
  perfTyped(g, dataSmall);
  perfSIMD(g, dataSmall);

ahmetaa

library gmm;

import 'dart:math';

class DiagonalGaussian {

  List<double> means;
  List<double> variances;
  List<double> negativeHalfPrecisions;
  double logPrecomputedDistance;

ahmetaa

import 'dart:math';
import 'dart:typeddata';

main() {
  print("Generating 4 4-length vector");
  GaussData g = new GaussData.random(4);
  InputData dataSmall = new InputData.random(4,4);  
  perfList(g, dataSmall);
  perfTyped(g, dataSmall);
  perfSIMD(g, dataSmall);

ahmetaa

import java.util.Arrays;

public class PositiveIntMap {

    static final int INITIAL_SIZE = 8;
    static final double DEFAULT_LOAD_FACTOR = 0.5;

    // This is the size-1 of the key and value array length. Array length is a value power of two
    private int modulo = INITIAL_SIZE - 1;