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Working from home

# Daniel Kohlsdorfdkohlsdorf

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Working from home
Created May 17, 2016
Merko
View Merko.txt
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Last active May 26, 2017
General Sequence Alignment
View Alignment.scala
 class Alignment[A]( init: (Int, Int) => Double, rank: (Double, Double, Double, A, A) => Double ) { def score(x: Array[A], y: Array[A]): Double = { val n = x.size val m = y.size val dp = Array.ofDim[Double](n + 1, m + 1)
Created Jun 13, 2018
View InfiniteCalm.ipynb
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Created Jun 27, 2018
Union Find Data Structure
View UnionFind.java
 public class UnionFind { private int id[]; private int count; public UnionFind(int N) { count = N; id = new int[N]; for(int i = 0; i < N; i++) {
Created Aug 16, 2018
Simple iSAX Implementation
View iSax.py
 import numpy as np import scipy.stats as stats def generate_split(n_char, mu = 0.0, std = 1.0): return stats.norm.ppf(np.arange(1, n_char) / n_char, mu, std) def convert(x, splits, cardinality): n = len(x) chars = np.zeros(n, dtype=np.int) for i in range(0, n):
Created Apr 1, 2015
Extract Local Interest Points from a spectrogram
View Audio Interest Point
 package processing.signals; import java.util.ArrayList; /** * Extract all local features from current spectrogram * * @author Daniel Kohlsdorf */ public class LocalFeatureExtractor {
Last active Mar 13, 2019
Implements a set on an integer
View BitSet.java
 public class BitSet { private int set = 0; public void add(int position) { int mask = 1 << position; set = set | mask; }
Last active Mar 13, 2019
Heap
View Heap.java
 import java.util.Arrays; /** * Implements a size limited heap * * @author Daniel Kohlsdorf */ public class Heap { private double heap[];
Last active Mar 13, 2019
Merge As In Mergesort
View Merge.java
 import java.util.Arrays; /** * Merge as in MergeSort * * @author Daniel Kohlsdorf */ public class Merge { public static int[] merge(int x[], int y[]) {
Last active Mar 13, 2019
K Means Clustering
View KMeans.java
 import java.util.Random; public class KMeans { public static double distance(double x[], double y[]) { int D = x.length; double distance = 0; for(int i = 0; i < D; i++) { distance += Math.pow(x[i] - y[i], 2);
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