| public Set ( IBaseObject item, int index ) : void | ||
| item | IBaseObject | /// The item. /// |
| index | int | /// The index. /// |
| return | void | |
/// <summary>
/// The create.
/// </summary>
/// <param name="source">
/// The source.
/// </param>
/// <param name="link">
/// The link.
/// </param>
/// <returns>
/// The <see cref="Chain"/>.
/// </returns>
/// <exception cref="ArgumentException">
/// Thrown if link is unacceptable.
/// </exception>
public static Chain Create(Chain source, Link link)
{
if (link != Link.Start && link != Link.End && link != Link.CycleEnd && link != Link.CycleStart)
{
throw new ArgumentException("Unknown link", "link");
}
var result = new Chain(source.GetLength());
Alphabet sourceAlphabet = source.Alphabet;
var entries = new int[sourceAlphabet.Cardinality];
var intervals = new int[sourceAlphabet.Cardinality][];
for (int j = 0; j < sourceAlphabet.Cardinality; j++)
{
var intervalsManager = new CongenericIntervalsManager(source.CongenericChain(j));
intervals[j] = intervalsManager.GetIntervals(link);
}
for (int i = 0; i < source.GetLength(); i++)
{
var elementIndex = sourceAlphabet.IndexOf(source[i]);
int entry = entries[elementIndex]++;
var interval = intervals[elementIndex][entry];
result.Set(new ValueInt(interval), i);
}
return result;
}
public void Initialize()
{
testChain = new Chain(8);
testChain.Set((ValueString)"A", 0);
testChain.Set((ValueString)"G", 1);
testChain.Set((ValueString)"T", 2);
testChain.Set((ValueString)"A", 3);
testChain.Set((ValueString)"A", 4);
testChain.Set((ValueString)"G", 5);
testChain.Set((ValueString)"T", 6);
testChain.Set((ValueString)"C", 7);
}
/// <summary>
/// Method that creates chain of "first occurrences of different elements".
/// </summary>
/// <param name="source">
/// Source chain.
/// </param>
/// <returns>/
/// Dissimilar chain.
/// </returns>
public static Chain Create(BaseChain source)
{
var result = new Chain(source.GetLength());
Alphabet sourceAlphabet = source.Alphabet;
var entries = new int[sourceAlphabet.Cardinality];
for (int i = 0; i < source.GetLength(); i++)
{
int elementIndex = sourceAlphabet.IndexOf(source[i]);
int entry = ++entries[elementIndex];
result.Set(new ValueInt(entry), i);
}
return result;
}
public void MarkovChainNotCongenericDynamicOneRangTwoTest()
{
// using mock of random generator
IGenerator generator = new MockGenerator();
// rank of markov chain is 2 (each element depends on one previous element)
int markovChainRank = 2;
// heterogeneity is 1 (there are 2 models - for odd and even positions)
int notCongenericRank = 1;
// creating markov chain
// MarkovChainNotCongenericDynamic<Chain, Chain> MarkovChain = new MarkovChainNotCongenericDynamic<Chain, Chain>(markovChainRank, notCongenericRank, generator);
// length of generated sequence
int length = 12;
// teaching markov chain (TeachingMethod.None means there is no preprocessing)
// MarkovChain.Teach(TestChain, TeachingMethod.None);
// Chain Temp = MarkovChain.Generate(length);
/**
* Внутри неоднородной марковской цепи существует n однородных марковских цепей. n - порядок неоднородности цепи
* порядок данных однородных цепей равен порядку неоднородной цепи
* однородные цепи используются по очереди как при обучении так и при генерации.
*
* В данном тесте внутри неоднородной марковской цепи есть 2 однородные цепи.
* Матрицы переходных вероятностей (в скобках указано кол-во входений при обучении) в них такие
*
* 1. Sequence
* first level (unconditional probability)
*
* a| 1/2 (3) |
* b| 1/3 (2) |
* c| 1/6 (1) |
* d| 0 (0) |
*
* second level (conditional probability taking into account 1 previous element)
*
* | a | b | с | d |
* ---|------|------|------|------|
* a |0,3(1)| 0(0) |0,3(1)|0,3(1)|
* ---|------|------|------|------|
* b |0,5(1)|0,5(1)| 0(0) | 0(0) |
* ---|------|------|------|------|
* c | 1(1) | 0(0) | 0(0) | 0(0) |
* ---|------|------|------|------|
* d | 0(0) | 0(0) | 0(0) | 0(0) |
* ---|------|------|------|------|
*
* 2. Sequence
* first level (unconditional probability)
*
* a| 2/5 (2) |
* b| 1/5 (1) |
* c| 1/5 (1) |
* d| 1/5 (1) |
*
* second level (conditional probability taking into account 1 previous element)
*
* | a | b | с | d |
* ---|------|------|------|------|
* a |0,5(1)| 0(0) |0,5(1)| 0(0) |
* ---|------|------|------|------|
* b | 1(1) | 0(0) | 0(0) | 0(0) |
* ---|------|------|------|------|
* c | 0(0) | 1(1) | 0(0) | 0(0) |
* ---|------|------|------|------|
* d | 0(0) | 1(1) | 0(0) | 0(0) |
* ---|------|------|------|------|
*
*
* During teaching pairs are added as folowing
* |-| |-| |-| |-| |-| <>- In second markov chain
* a d b a a c b b a a c a
* |_| |_| |_| |_| |_| |_| <>- In first markov chain
*
*/
// expected result of generation
var result = new Chain(12);
result.Set((ValueString)"b", 0); // 1 chain. вероятность по первому уровню. выпало 0,77 Получаем b
result.Set((ValueString)"a", 1); // 2 chain. вероятность по второму уровню. выпало 0.15 Получаем a
result.Set((ValueString)"c", 2); // 1 chain. вероятность по второму уровню. выпало 0.96 Получаем с
result.Set((ValueString)"b", 3); // 2 chain. вероятность по второму уровню. выпало 0.61 Получаем b
result.Set((ValueString)"a", 4); // 1 chain. вероятность по второму уровню. выпало 0.15 Получаем a
result.Set((ValueString)"c", 5); // 2 chain. вероятность по второму уровню. выпало 0.85 Получаем c
result.Set((ValueString)"a", 6); // 1 chain. вероятность по второму уровню. выпало 0.67 Получаем a
result.Set((ValueString)"c", 7); // 2 chain. вероятность по второму уровню. выпало 0.51 Получаем c
result.Set((ValueString)"a", 8); // 1 chain. вероятность по второму уровню. выпало 0.71 Получаем a
result.Set((ValueString)"a", 9); // 2 chain. вероятность по второму уровню. выпало 0.2 Получаем a
result.Set((ValueString)"c", 10); // 1 chain. вероятность по второму уровню. выпало 0.77 Получаем с
result.Set((ValueString)"b", 11); // 2 chain. вероятность по второму уровню. выпало 0.15 Получаем b
}
public void Initialize()
{
// Creating sequence containing 12 elements.
// |a|d|b|a|a|c|b|b|a|a|c|a|
testChain = new Chain(12);
testChain.Set((ValueString)"a", 0);
testChain.Set((ValueString)"d", 1);
testChain.Set((ValueString)"b", 2);
testChain.Set((ValueString)"a", 3);
testChain.Set((ValueString)"a", 4);
testChain.Set((ValueString)"c", 5);
testChain.Set((ValueString)"b", 6);
testChain.Set((ValueString)"b", 7);
testChain.Set((ValueString)"a", 8);
testChain.Set((ValueString)"a", 9);
testChain.Set((ValueString)"c", 10);
testChain.Set((ValueString)"a", 11);
secondTestChain = new Chain(12);
secondTestChain.Set((ValueString)"a", 0);
secondTestChain.Set((ValueString)"a", 1);
secondTestChain.Set((ValueString)"a", 2);
secondTestChain.Set((ValueString)"a", 3);
secondTestChain.Set((ValueString)"a", 4);
secondTestChain.Set((ValueString)"a", 5);
secondTestChain.Set((ValueString)"b", 6);
secondTestChain.Set((ValueString)"a", 7);
secondTestChain.Set((ValueString)"a", 8);
secondTestChain.Set((ValueString)"a", 9);
secondTestChain.Set((ValueString)"b", 10);
secondTestChain.Set((ValueString)"a", 11);
}
public void GetBinaryIntervalIncompleteChainTest()
{
// A C A _ C C _ A A A C C A
// A _ A _ _ _ _ A A A _ _ A
// _ C _ _ C C _ _ _ _ C C _
var chain = new Chain(13);
chain.Set(elements["A"], 0);
chain.Set(elements["C"], 1);
chain.Set(elements["A"], 2);
chain.Set(elements["C"], 4);
chain.Set(elements["C"], 5);
chain.Set(elements["A"], 7);
chain.Set(elements["A"], 8);
chain.Set(elements["A"], 9);
chain.Set(elements["C"], 10);
chain.Set(elements["C"], 11);
chain.Set(elements["A"], 12);
var intervalManager = chain.GetRelationIntervalsManager(elements["A"], elements["C"]);
Assert.AreEqual(1, intervalManager.GetBinaryInterval(1));
Assert.AreEqual(2, intervalManager.GetBinaryInterval(2));
Assert.AreEqual(-1, intervalManager.GetBinaryInterval(3));
Assert.AreEqual(-1, intervalManager.GetBinaryInterval(4));
Assert.AreEqual(1, intervalManager.GetBinaryInterval(5));
Assert.AreEqual(-1, intervalManager.GetBinaryInterval(6));
Assert.AreEqual(-1, intervalManager.GetBinaryInterval(7));
intervalManager = chain.GetRelationIntervalsManager(elements["C"], elements["A"]);
Assert.AreEqual(1, intervalManager.GetBinaryInterval(1));
Assert.AreEqual(-1, intervalManager.GetBinaryInterval(2));
Assert.AreEqual(2, intervalManager.GetBinaryInterval(3));
Assert.AreEqual(-1, intervalManager.GetBinaryInterval(4));
Assert.AreEqual(1, intervalManager.GetBinaryInterval(5));
Assert.AreEqual(-1, intervalManager.GetBinaryInterval(6));
}
public ActionResult Index(
long[] matterIds,
int[] characteristicTypeLinkIds,
int? languageId,
int? translatorId,
int notationId,
int length,
int step,
bool delta,
bool fourier,
bool growingWindow,
bool autocorrelation)
{
return Action(() =>
{
var characteristicNames = new string[characteristicTypeLinkIds.Length];
var partNames = new List<string>[matterIds.Length];
var starts = new List<int>[matterIds.Length];
var lengthes = new List<int>[matterIds.Length];
var chains = new Chain[matterIds.Length];
var mattersCharacteristics = new object[matterIds.Length];
var calculators = new List<IFullCalculator>();
var links = new List<Link>();
matterIds = matterIds.OrderBy(m => m).ToArray();
var matters = db.Matter.Where(m => matterIds.Contains(m.Id)).ToDictionary(m => m.Id);
for (int k = 0; k < matterIds.Length; k++)
{
long matterId = matterIds[k];
Nature nature = db.Matter.Single(m => m.Id == matterId).Nature;
long sequenceId;
switch (nature)
{
case Nature.Literature:
sequenceId = db.LiteratureSequence.Single(l => l.MatterId == matterId
&& l.NotationId == notationId
&& l.LanguageId == languageId
&& l.TranslatorId == translatorId).Id;
break;
default:
var id = notationId;
sequenceId = db.CommonSequence.Single(c => c.MatterId == matterId
&& c.NotationId == id).Id;
break;
}
chains[k] = commonSequenceRepository.ToLibiadaChain(sequenceId);
}
foreach (int characteristicTypeLinkId in characteristicTypeLinkIds)
{
string className = characteristicTypeLinkRepository.GetCharacteristicType(characteristicTypeLinkId).ClassName;
calculators.Add(CalculatorsFactory.CreateFullCalculator(className));
links.Add(characteristicTypeLinkRepository.GetLibiadaLink(characteristicTypeLinkId));
}
for (int i = 0; i < chains.Length; i++)
{
CutRule cutRule = growingWindow
? (CutRule)new CutRuleWithFixedStart(chains[i].GetLength(), step)
: new SimpleCutRule(chains[i].GetLength(), step, length);
CutRuleIterator iter = cutRule.GetIterator();
List<Chain> fragments = new List<Chain>();
partNames[i] = new List<string>();
starts[i] = new List<int>();
lengthes[i] = new List<int>();
while (iter.Next())
{
var fragment = new Chain(iter.GetEndPosition() - iter.GetStartPosition());
for (int k = 0; iter.GetStartPosition() + k < iter.GetEndPosition(); k++)
{
fragment.Set(chains[i][iter.GetStartPosition() + k], k);
}
fragments.Add(fragment);
partNames[i].Add(fragment.ToString());
starts[i].Add(iter.GetStartPosition());
lengthes[i].Add(fragment.GetLength());
}
var fragmentsData = new FragmentData[fragments.Count];
for (int k = 0; k < fragments.Count; k++)
{
var characteristics = new double[calculators.Count];
for (int j = 0; j < calculators.Count; j++)
{
characteristics[j] = calculators[j].Calculate(fragments[k], links[j]);
}
fragmentsData[k] = new FragmentData(characteristics, fragments[k].ToString(), starts[i][k], fragments[k].GetLength());
}
double[][] differenceData = null;
double[][] fourierData = null;
double[][] autocorrelationData = null;
if (delta)
{
differenceData = CalculateDifference(fragmentsData.Select(f => f.Characteristics).ToArray());
}
if (fourier)
{
fourierData = FastFourierTransform.CalculateFastFourierTransform(fragmentsData.Select(f => f.Characteristics).ToArray());
}
if (autocorrelation)
{
autocorrelationData = AutoCorrelation.CalculateAutocorrelation(fragmentsData.Select(f => f.Characteristics).ToArray());
}
mattersCharacteristics[i] = new { matterName = matters[matterIds[i]].Name, fragmentsData, differenceData, fourierData, autocorrelationData };
}
for (int l = 0; l < characteristicTypeLinkIds.Length; l++)
{
characteristicNames[l] = characteristicTypeLinkRepository.GetCharacteristicType(characteristicTypeLinkIds[l]).Name;
}
var characteristicsList = new SelectListItem[characteristicTypeLinkIds.Length];
for (int k = 0; k < characteristicTypeLinkIds.Length; k++)
{
characteristicNames[k] = characteristicTypeLinkRepository.GetCharacteristicName(characteristicTypeLinkIds[k], notationId);
characteristicsList[k] = new SelectListItem
{
Value = k.ToString(),
Text = characteristicNames[k],
Selected = false
};
}
string notationName = db.Notation.Single(n => n.Id == notationId).Name;
var result = new Dictionary<string, object>
{
{ "characteristics", mattersCharacteristics },
{ "notationName", notationName },
{ "starts", starts },
{ "partNames", partNames },
{ "lengthes", lengthes },
{ "characteristicNames", characteristicNames },
{ "matterIds", matterIds },
{ "characteristicsList", characteristicsList }
};
return new Dictionary<string, object> { { "data", JsonConvert.SerializeObject(result) } };
});
}
/// <summary>
/// The generate chain.
/// </summary>
/// <param name="alphabet">
/// Generated sequence alphabet.
/// </param>
/// <param name="i">
/// The i.
/// </param>
/// <param name="length">
/// Generated sequence length.
/// </param>
/// <returns>
/// The <see cref="Chain"/>.
/// </returns>
private Chain GenerateChain(Alphabet alphabet, int i, int length)
{
// next sequence
var chain = new Chain(length);
// Переменная для хранения остатка от деления на основание системы счисления (Мощность алфавита)
int temp = i;
// index of currently generated sequence
int index = 0;
// cycle through elements
for (int j = length - 1; j >= 0; j--)
{
var element = (int)(temp / Math.Pow(alphabet.Cardinality, j));
chain.Set(alphabet[element], index);
temp = (int)(temp % Math.Pow(alphabet.Cardinality, j));
index++;
}
return chain;
}