public static void demo1()
{
// Gamma distribution
// define distribution parameters
double mean = 5;
double variance = 1.5;
double alpha = mean * mean / variance;
double lambda = 1 / (variance / mean);
// for tests and debugging use a random engine with CONSTANT seed --> deterministic and reproducible results
RandomEngine engine = new MersenneTwister();
// your favourite distribution goes here
AbstractDistribution dist = new Gamma(alpha, lambda, engine);
// collect random numbers and print statistics
int size = 100000;
var numbers = new DoubleArrayList(size);
for (int i = 0; i < size; i++)
{
numbers.Add(dist.NextDouble());
}
DynamicBin1D bin = new DynamicBin1D();
bin.AddAllOf(numbers);
Console.WriteLine(bin);
}
public virtual void AddAllOfFromTo(DoubleArrayList list, int from, int to)
{
for (int i = from; i <= to; i++)
{
Add(list[i]);
}
}
/// <summary>
/// Adds the part of the specified list between indexes <i>from</i> (inclusive) and <i>to</i> (inclusive) to the receiver.
/// </summary>
/// <param name="values">the list of which elements shall be added.</param>
/// <param name="from">the index of the first element to be added (inclusive).</param>
/// <param name="to">the index of the last element to be added (inclusive).</param>
public void AddAllOfFromTo(DoubleArrayList values, int from, int to)
{
//buffer.AddAllOfFromTo(values, from, to);
buffer.AddAllOfFromTo(values, from, to);
this.isSorted = false;
}
/// <summary>
/// Finds the first and last indexes of a specific element within a sorted list.
/// <summary>
/// <returns>int[]</returns>
/// <param name="list">cern.colt.list.DoubleArrayList</param>
/// <param name="element">the element to search for</param>
protected static IntArrayList BinaryMultiSearch(DoubleArrayList list, double element)
{
int index = list.BinarySearch(element);
if (index < 0)
{
return(null); //not found
}
int from = index - 1;
while (from >= 0 && list[from] == element)
{
from--;
}
from++;
int to = index + 1;
while (to < list.Count && list[to] == element)
{
to++;
}
to--;
return(new IntArrayList(new int[] { from, to }));
}
public virtual double Moment(int k, double c)
{
if (k < 0)
{
throw new ArgumentException(Cern.LocalizedResources.Instance().Exception_KMustBePositive);
}
//checkOrder(k);
if (!HasSumOfPowers(k))
{
return(Double.NaN);
}
int maxOrder = System.Math.Min(k, GetMaxOrderForSumOfPowers());
DoubleArrayList sumOfPows = new DoubleArrayList(maxOrder + 1);
sumOfPows.Add(Size);
sumOfPows.Add(Sum);
sumOfPows.Add(SumOfSquares);
for (int i = 3; i <= maxOrder; i++)
{
sumOfPows.Add(GetSumOfPowers(i));
}
return(Descriptive.Moment(k, c, Size, sumOfPows.ToArray()));
}
/// <summary>
/// Computes the specified quantile elements over the values previously added.
/// </summary>
/// <param name="phis">the quantiles for which elements are to be computed. Each phi must be in the interval (0.0,1.0]. <tt>phis</tt> must be sorted ascending.</param>
/// <returns>the approximate quantile elements.</returns>
public override DoubleArrayList QuantileElements(DoubleArrayList phis)
{
if (precomputeEpsilon <= 0.0)
{
return(base.QuantileElements(phis));
}
int quantilesToPrecompute = (int)Utils.EpsilonCeiling(1.0 / precomputeEpsilon);
/*
* if (phis.Count > quantilesToPrecompute) {
* // illegal use case!
* // we compute results, but loose explicit approximation guarantees.
* return base.QuantileElements(phis);
* }
*/
//select that quantile from the precomputed set that corresponds to a position closest to phi.
phis = phis.Copy();
double e = precomputeEpsilon;
for (int index = phis.Size; --index >= 0;)
{
double phi = phis[index];
int i = (int)System.Math.Round(((2.0 * phi / e) - 1.0) / 2.0); // finds closest
i = System.Math.Min(quantilesToPrecompute - 1, System.Math.Max(0, i));
double augmentedPhi = (e / 2.0) * (1 + 2 * i);
phis[index] = augmentedPhi;
}
return(base.QuantileElements(phis));
}
public void Trim(int s, int l)
{
DoubleArrayList elems = SortedElements;
Clear();
AddAllOfFromTo(elems, s, elems.Size - 1 - l);
}
/// <summary>
/// Computes the specified quantile elements over the values previously added.
/// </summary>
/// <param name="phis">the quantiles for which elements are to be computed. Each phi must be in the interval [0.0,1.0]. <tt>phis</tt> must be sorted ascending.</param>
/// <returns>the approximate quantile elements.</returns>
public virtual DoubleArrayList QuantileElements(DoubleArrayList phis)
{
/*
* //check parameter
*/
List <Double> sortedPhiList = phis.Copy().ToList();
sortedPhiList.Sort();
if (!phis.Equals(sortedPhiList))
{
throw new ArgumentException(Cern.LocalizedResources.Instance().Exception_PhisMustBeAscending);
}
//System.out.println("starting to augment missing values, if necessary...");
phis = PreProcessPhis(phis);
long[] triggerPositions = new long[phis.Size];
long totalSize = this.bufferSet.TotalSize;
for (int i = phis.Size; --i >= 0;)
{
triggerPositions[i] = Utils.EpsilonCeiling(phis[i] * totalSize) - 1;
}
//System.out.println("triggerPositions="+cern.colt.Arrays.ToString(triggerPositions));
//System.out.println("starting to determine quantiles...");
//System.out.println(bufferSet);
DoubleBuffer[] fullBuffers = bufferSet.GetFullOrPartialBuffers();
double[] quantileElements = new double[phis.Size];
//do the main work: determine values at given positions in sorted sequence
return(new DoubleArrayList(bufferSet.GetValuesAtPositions(fullBuffers, triggerPositions)));
}
/// <summary>
/// Fills the specified array of doubles with random numbers in the interval [0,1).
/// </summary>
/// <param name="array">An array of double-precision floating point numbers.</param>
public void Fill(DoubleArrayList array)
{
for (int i = 0; i < array.Count; i++)
{
array[i] = NextDouble();
}
}
/// <summary>
/// Initializes a new instance of the <see cref="Vector2D"/> class with the specified coordinates.
/// </summary>
/// <param name="coordinates">An array containing the coordinate parameters.</param>
public Vector2D(DoubleArrayList coordinates)
{
Debug.Assert(coordinates != null);
Debug.Assert(coordinates.Count >= 2);
_x = coordinates[0];
_y = coordinates[1];
}
/// <summary>
/// Constructs and returns a new buffer with the given target.
/// </summary>
/// <param name="target">the target to flush to.</param>
/// <param name="capacity">the number of points the buffer shall be capable of holding before overflowing and flushing to the target.</param>
public DoubleBuffer(IDoubleBufferConsumer target, int capacity)
{
this.target = target;
this.capacity = capacity;
this.elements = new double[capacity];
this.list = new DoubleArrayList(elements);
this.size = 0;
}
/// <summary>
/// Initializes a new instance of the <see cref="Matrix2D"/> structure with the specified values.
/// </summary>
/// <param name="elements">An array containing the matrix values in row-major order.</param>
public Matrix2D(DoubleArrayList elements)
{
Debug.Assert(elements != null);
Debug.Assert(elements.Count >= 4);
_m11 = elements[0]; _m12 = elements[1];
_m21 = elements[2]; _m22 = elements[3];
}
/// <summary>
/// Initializes a new instance of the <see cref="Vector3"/> class with the specified coordinates.
/// </summary>
/// <param name="coordinates">An array containing the coordinate parameters.</param>
public Vector3(DoubleArrayList coordinates)
: base()
{
Debug.Assert(coordinates != null);
Debug.Assert(coordinates.Count >= 3);
m_X = coordinates[0];
m_Y = coordinates[1];
m_Z = coordinates[2];
}
/// <summary>
/// Initializes a new instance of the <see cref="Matrix3F"/> structure with the specified values.
/// </summary>
/// <param name="elements">An array containing the matrix values in row-major order.</param>
public Matrix3D(DoubleArrayList elements)
{
Debug.Assert(elements != null);
Debug.Assert(elements.Count >= 9);
_m11 = elements[0]; _m12 = elements[1]; _m13 = elements[2];
_m21 = elements[3]; _m22 = elements[4]; _m23 = elements[5];
_m31 = elements[6]; _m32 = elements[7]; _m33 = elements[8];
}
/// <summary>
/// Adds a value to the receiver.
/// </summary>
/// <param name="elements"></param>
/// <param name="from"></param>
/// <param name="to"></param>
public void AddAllOfFromTo(DoubleArrayList elements, int from, int to)
{
if (!isAllocated)
{
Allocate(); // lazy buffer allocation can safe memory.
}
values.AddAllOfFromTo(elements, from, to);
this.isSorted = false;
}
/// <summary>
/// Constructs and returns an empty bin; implicitly calls {@link #setFixedOrder(Boolean) setFixedOrder(false)}.
/// </summary>
public DynamicBin1D() : base()
{
this.Clear();
this._elements = new DoubleArrayList();
this._sortedElements = new DoubleArrayList(0);
this.FixedOrder = false;
this.HasSumOfLogarithms = true;
this.HasSumOfInversions = true;
}
/// <summary>
/// Initializes a new instance of the <see cref="Vector4"/> class with the specified coordinates.
/// </summary>
/// <param name="coordinates">An array containing the coordinate parameters.</param>
public Vector4(DoubleArrayList coordinates)
{
Debug.Assert(coordinates != null);
Debug.Assert(coordinates.Count >= 4);
_x = coordinates[0];
_y = coordinates[1];
_z = coordinates[2];
_w = coordinates[3];
}
/// <summary>
/// Adds all elements of the specified list to the receiver.
/// </summary>
/// <param name="list">the list of which all elements shall be added.</param>
public void AddAllOf(DoubleArrayList list)
{
int listSize = list.Size;
if (this.size + listSize >= this.capacity)
{
Flush();
}
this.target.AddAllOf(list);
}
/// <summary>
/// Initializes a new instance of the <see cref="Matrix4F"/> structure with the specified values.
/// </summary>
/// <param name="elements">An array containing the matrix values in row-major order.</param>
public Matrix4D(DoubleArrayList elements)
{
Debug.Assert(elements != null);
Debug.Assert(elements.Count >= 16);
_m11 = elements[0]; _m12 = elements[1]; _m13 = elements[2]; _m14 = elements[3];
_m21 = elements[4]; _m22 = elements[5]; _m23 = elements[6]; _m24 = elements[7];
_m31 = elements[8]; _m32 = elements[9]; _m33 = elements[10]; _m34 = elements[11];
_m41 = elements[12]; _m42 = elements[13]; _m43 = elements[14]; _m44 = elements[15];
}
/// <summary>
/// Adds the part of the specified list between indexes <tt>from</tt> (inclusive) and <tt>to</tt> (inclusive) to the receiver.
/// </summary>
/// <param name="values">the list of which elements shall be added.</param>
/// <param name="from">the index of the first element to be added (inclusive).</param>
/// <param name="to">the index of the last element to be added (inclusive).</param>
public void AddAllOfFromTo(DoubleArrayList values, int from, int to)
{
/*
* // the obvious version, but we can do quicker...
* double[] theValues = values.ToArray();
* int theSize=values.Count;
* for (int i=0; i<theSize; ) add(theValues[i++]);
*/
double[] valuesToAdd = values.Elements;
int k = this.bufferSet.NumberOfElements;
int bufferSize = k;
double[] bufferValues = null;
if (currentBufferToFill != null)
{
bufferValues = currentBufferToFill.Values.Elements;
bufferSize = currentBufferToFill.Size;
}
for (int i = from - 1; ++i <= to;)
{
if (SampleNextElement())
{
if (bufferSize == k)
{ // full
if (bufferSet.GetFirstEmptyBuffer() == null)
{
Collapse();
}
NewBuffer();
if (!currentBufferToFill.IsAllocated)
{
currentBufferToFill.Allocate();
}
currentBufferToFill.IsSorted = false;
bufferValues = currentBufferToFill.Values.Elements;
bufferSize = 0;
}
bufferValues[bufferSize++] = valuesToAdd[i];
if (bufferSize == k)
{ // full
currentBufferToFill.Values.SetSize(bufferSize);
currentBufferToFill = null;
}
}
}
if (this.currentBufferToFill != null)
{
this.currentBufferToFill.Values.SetSize(bufferSize);
}
this.totalElementsFilled += to - from + 1;
}
public void assignLabels( LingoProcessingContext context, DoubleMatrix2D stemCos, IntIntOpenHashMap filteredRowToStemIndex, DoubleMatrix2D phraseCos )
{
PreprocessingContext preprocessingContext = context.preprocessingContext;
int firstPhraseIndex = preprocessingContext.allLabels.firstPhraseIndex;
int [] labelsFeatureIndex = preprocessingContext.allLabels.featureIndex;
int [] mostFrequentOriginalWordIndex = preprocessingContext.allStems.mostFrequentOriginalWordIndex;
int desiredClusterCount = stemCos.columns();
IntArrayList clusterLabelFeatureIndex = new IntArrayList(
desiredClusterCount);
DoubleArrayList clusterLabelScore = new DoubleArrayList(desiredClusterCount);
for (int label = 0; label < desiredClusterCount; label++)
{
Pair<int, int> stemMax = max(stemCos);
Pair<int, int> phraseMax = max(phraseCos);
if (stemMax == null && phraseMax == null)
{
break;
}
double stemScore = stemMax != null ? stemCos.getQuick(stemMax.objectA,
stemMax.objectB) : -1;
double phraseScore = phraseMax != null ? phraseCos.getQuick(
phraseMax.objectA, phraseMax.objectB) : -1;
if (phraseScore > stemScore)
{
phraseCos.viewRow(phraseMax.objectA).assign(0);
phraseCos.viewColumn(phraseMax.objectB).assign(0);
stemCos.viewColumn(phraseMax.objectB).assign(0);
clusterLabelFeatureIndex.add(labelsFeatureIndex[phraseMax.objectA
+ firstPhraseIndex]);
clusterLabelScore.add(phraseScore);
}
else
{
stemCos.viewRow(stemMax.objectA).assign(0);
stemCos.viewColumn(stemMax.objectB).assign(0);
if (phraseCos != null)
{
phraseCos.viewColumn(stemMax.objectB).assign(0);
}
clusterLabelFeatureIndex
.add(mostFrequentOriginalWordIndex[filteredRowToStemIndex
.get(stemMax.objectA)]);
clusterLabelScore.add(stemScore);
}
}
context.clusterLabelFeatureIndex = clusterLabelFeatureIndex.toArray();
context.clusterLabelScore = clusterLabelScore.toArray();
}
protected new DoubleArrayList PreProcessPhis(DoubleArrayList phis)
{
if (beta > 1.0)
{
phis = phis.Copy();
for (int i = phis.Size; --i >= 0;)
{
phis[i] = (2 * phis[i] + beta - 1) / (2 * beta);
}
}
return(phis);
}
/// <summary>
/// This method was created in VisualAge.
/// <summary>
/// <returns>double[]</returns>
/// <param name="values">cern.it.hepodbms.primitivearray.DoubleArrayList</param>
/// <param name="phis">double[]</param>
public static DoubleArrayList ObservedEpsilonsAtPhis(DoubleArrayList phis, ExactDoubleQuantileFinder exactFinder, IDoubleQuantileFinder approxFinder, double desiredEpsilon)
{
DoubleArrayList epsilons = new DoubleArrayList(phis.Count);
for (int i = phis.Count; --i >= 0;)
{
double epsilon = ObservedEpsilonAtPhi(phis[i], exactFinder, approxFinder);
epsilons.Add(epsilon);
if (epsilon > desiredEpsilon) Console.WriteLine("Real epsilon = " + epsilon + " is larger than desired by " + (epsilon - desiredEpsilon));
}
return epsilons;
}
/// <summary>
/// 3-d OLAP cube operator; Fills all cells of the given vectors into the given histogram.
/// If you use Hep.Aida.Ref.Converter.ToString(histo) on the result, the OLAP cube of x-"column" vsd y-"column" vsd z-"column", summing the weights "column" will be printed.
/// For example, aggregate sales by product by region by time.
/// <p>
/// Computes the distinct values of x and y and z, yielding histogram axes that capture one distinct value per bin.
/// Then fills the histogram.
/// </summary>
/// <param name="x"></param>
/// <param name="y"></param>
/// <param name="z"></param>
/// <param name="weights"></param>
/// <returns>the histogram containing the cube.</returns>
/// <excption cref="ArgumentException">if <i>x.Count != y.Count || x.Count != z.Count || x.Count != weights.Count</i>.</excption>
public static Hep.Aida.IHistogram3D cube(DoubleMatrix1D x, DoubleMatrix1D y, DoubleMatrix1D z, DoubleMatrix1D weights)
{
if (x.Size != y.Size || x.Size != z.Size || x.Size != weights.Size)
{
throw new ArgumentException("vectors must have same size");
}
var epsilon = 1.0E-9;
var distinct = new DoubleArrayList();
var vals = new double[x.Size];
var sorted = new DoubleArrayList(vals);
// compute distinct values of x
vals = x.ToArray(); // copy x into vals
sorted.Sort();
Cern.Jet.Stat.Descriptive.Frequencies(sorted, distinct, null);
// since bins are right-open [from,to) we need an additional dummy bin so that the last distinct value does not fall into the overflow bin
if (distinct.Count > 0)
{
distinct.Add(distinct[distinct.Count - 1] + epsilon);
}
distinct.TrimToSize();
Hep.Aida.IAxis xaxis = new Hep.Aida.Ref.VariableAxis(distinct.ToArray());
// compute distinct values of y
vals = y.ToArray();
sorted.Sort();
Cern.Jet.Stat.Descriptive.Frequencies(sorted, distinct, null);
// since bins are right-open [from,to) we need an additional dummy bin so that the last distinct value does not fall into the overflow bin
if (distinct.Count > 0)
{
distinct.Add(distinct[distinct.Count - 1] + epsilon);
}
distinct.TrimToSize();
Hep.Aida.IAxis yaxis = new Hep.Aida.Ref.VariableAxis(distinct.ToArray());
// compute distinct values of z
vals = z.ToArray();
sorted.Sort();
Cern.Jet.Stat.Descriptive.Frequencies(sorted, distinct, null);
// since bins are right-open [from,to) we need an additional dummy bin so that the last distinct value does not fall into the overflow bin
if (distinct.Count > 0)
{
distinct.Add(distinct[distinct.Count - 1] + epsilon);
}
distinct.TrimToSize();
Hep.Aida.IAxis zaxis = new Hep.Aida.Ref.VariableAxis(distinct.ToArray());
Hep.Aida.IHistogram3D histo = new Hep.Aida.Ref.Histogram3D("Cube", xaxis, yaxis, zaxis);
return(Histogram(histo, x, y, z, weights));
}
/// <summary>
/// Computes the specified quantile elements over the values previously added.
/// </summary>
/// <param name="phis">the quantiles for which elements are to be computedd Each phi must be in the interval [0.0,1.0]d <i>phis</i> must be sorted ascending.</param>
/// <returns>the exact quantile elements.</returns>
public DoubleArrayList QuantileElements(DoubleArrayList phis)
{
this.Sort();
return(Cern.Jet.Stat.Descriptive.Quantiles(this.buffer, phis));
/*
* int bufferSize = (int) this.Count;
* double[] quantileElements = new double[phis.Count];
* for (int i=phis.Count; --i >=0;) {
* int rank=(int)Utils.epsilonCeiling(phis.Get(i)*bufferSize) -1;
* quantileElements[i]=buffer.Get(rank);
* }
* return new DoubleArrayList(quantileElements);
*/
}
public override DoubleArrayList QuantileElements(DoubleArrayList phis)
{
/*
* The KNOWN quantile finder reads off quantiles from FULL buffers only.
* Since there might be a partially full buffer, this method first satisfies this constraint by temporarily filling a few +infinity, -infinity elements to make up a full block.
* This is in full conformance with the explicit approximation guarantees.
*
* For those of you working on online apps:
* The approximation guarantees are given for computing quantiles AFTER N elements have been filled, not for intermediate displays.
* If you have one thread filling and another thread displaying concurrently, you will note that in the very beginning the infinities will dominate the display.
* This could confuse users, because, of course, they don't expect any infinities, even if they "disappear" after a short while.
* To prevent panic exclude phi's close to zero or one in the early phases of processing.
*/
DoubleBuffer partial = this.BufferSet.GetPartialBuffer();
int missingValues = 0;
if (partial != null)
{ // any auxiliary infinities needed?
missingValues = BufferSet.BufferSize - partial.Size;
if (missingValues <= 0)
{
throw new InvalidOperationException("Oops! illegal missing values.");
}
//System.out.println("adding "+missingValues+" infinity elements...");
this.AddInfinities(missingValues, partial);
//determine beta (N + Infinity values = beta * N)
this.beta = (this.TotalElementsFilled + missingValues) / (double)this.TotalElementsFilled;
}
else
{
this.beta = 1.0;
}
DoubleArrayList quantileElements = base.QuantileElements(phis);
// restore state we were in before.
// remove the temporarily added infinities.
if (partial != null)
{
RemoveInfinitiesFrom(missingValues, partial);
}
// now you can continue filling the remaining values, if any.
return(quantileElements);
}
public Boolean RemoveAllOf(DoubleArrayList list)
{
Boolean changed = this.Elements.RemoveAll(list);
if (changed)
{
ClearAllMeasures();
InvalidateAll();
//this.Size() = 0;
if (FixedOrder)
{
this.SortedElements.RemoveAll(list);
this.isSorted = true;
}
}
return(changed);
}
/// <summary>
/// Constructs a matrix with a given number of rows and columns.
/// All entries are initially <i>0</i>.
/// </summary>
/// <param name="rows">the number of rows the matrix shall have.</param>
/// <param name="columns">the number of columns the matrix shall have.</param>
/// <exception cref="ArgumentException">if <i>rows < 0 || columns < 0 || (double)columns * rows > int.MaxValue</i>.</exception>
public RCDoubleMatrix2D(int rows, int columns) : base(null)
{
try
{
Setup(rows, columns);
}
catch (ArgumentException exc)
{ // we can hold rows*columns>int.MaxValue cells !
if (!"matrix too large".Equals(exc.Message))
{
throw exc;
}
}
Indexes = new IntArrayList();
Values = new DoubleArrayList();
Starts = new int[rows + 1];
}
public override String ToString()
{
StringBuilder buf = new StringBuilder(base.ToString());
DoubleArrayList distinctElements = new DoubleArrayList();
IntArrayList freq = new IntArrayList();
Frequencies(distinctElements, freq);
if (distinctElements.Size < 100)
{ // don't cause unintended floods
buf.Append("Distinct elements: " + distinctElements + "\n");
buf.Append("Frequencies: " + freq + "\n");
}
else
{
buf.Append("Distinct elements & frequencies not printed (too many).");
}
return(buf.ToString());
}
public override void AddAllOfFromTo(DoubleArrayList list, int from, int to)
{
base.AddAllOfFromTo(list, from, to);
if (_sumOfPowers != null)
{
//int max_k = this.min_k + this.SumOfPowers.Length-1;
Descriptive.IncrementalUpdateSumsOfPowers(list, from, to, 3, GetMaxOrderForSumOfPowers(), ref _sumOfPowers);
}
if (this.HasSumOfInversions)
{
this.SumOfInversions += Descriptive.SumOfInversions(list, from, to);
}
if (this.HasSumOfLogarithms)
{
this.SumOfLogarithms += Descriptive.SumOfLogarithms(list, from, to);
}
}
public override void AddAllOfFromTo(DoubleArrayList list, int from, int to)
{
//if (this.arguments == null) setUpCache();
lock (arguments) {
// prepare arguments
arguments[0] = this.min;
arguments[1] = this.max;
arguments[2] = this.sum;
arguments[3] = this.sum_xx;
Descriptive.IncrementalUpdate(list, from, to, ref arguments);
// store the new parameters back
this.min = arguments[0];
this.max = arguments[1];
this.sum = arguments[2];
this.sum_xx = arguments[3];
this.size += to - from + 1;
}
}
