/// <summary>
/// The get subsequence characteristic.
/// </summary>
/// <param name="subsequenceId">
/// The subsequence id.
/// </param>
/// <param name="characteristicLinkId">
/// The characteristic type link id.
/// </param>
/// <param name="windowSize">
/// The window size.
/// </param>
/// <param name="step">
/// The step.
/// </param>
/// <returns>
/// The <see cref="string"/>.
/// </returns>
public string GetSubsequenceCharacteristic(
long subsequenceId,
short characteristicLinkId,
int windowSize,
int step)
{
Chain chain;
IFullCalculator calculator;
Link link;
using (var db = new LibiadaWebEntities())
{
var characteristicTypeLinkRepository = FullCharacteristicRepository.Instance;
FullCharacteristic characteristic =
characteristicTypeLinkRepository.GetCharacteristic(characteristicLinkId);
calculator = FullCalculatorsFactory.CreateCalculator(characteristic);
link = characteristicTypeLinkRepository.GetLinkForCharacteristic(characteristicLinkId);
var subsequenceExtractor = new SubsequenceExtractor(db);
Subsequence subsequence = db.Subsequence.Single(s => s.Id == subsequenceId);
chain = subsequenceExtractor.GetSubsequenceSequence(subsequence);
}
CutRule cutRule = new SimpleCutRule(chain.Length, step, windowSize);
CutRuleIterator iterator = cutRule.GetIterator();
var fragments = new List <Chain>();
while (iterator.Next())
{
int start = iterator.GetStartPosition();
int end = iterator.GetEndPosition();
var fragment = new List <IBaseObject>();
for (int k = 0; start + k < end; k++)
{
fragment.Add(chain[start + k]);
}
fragments.Add(new Chain(fragment));
}
var characteristics = new double[fragments.Count];
for (int k = 0; k < fragments.Count; k++)
{
characteristics[k] = calculator.Calculate(fragments[k], link);
}
return(JsonConvert.SerializeObject(characteristics));
}
public ActionResult Index(
long[] matterIds,
short[] characteristicLinkIds,
int length,
int step,
bool delta,
bool fourier,
bool growingWindow,
bool autocorrelation,
Notation notation,
Language?language,
Translator?translator,
PauseTreatment?pauseTreatment,
bool?sequentialTransfer,
ImageOrderExtractor?trajectory)
{
return(CreateTask(() =>
{
var characteristicNames = new string[characteristicLinkIds.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 IFullCalculator[characteristicLinkIds.Length];
var links = new Link[characteristicLinkIds.Length];
matterIds = matterIds.OrderBy(m => m).ToArray();
Dictionary <long, Matter> matters = Cache.GetInstance().Matters.Where(m => matterIds.Contains(m.Id)).ToDictionary(m => m.Id);
for (int k = 0; k < matterIds.Length; k++)
{
long matterId = matterIds[k];
Nature nature = Cache.GetInstance().Matters.Single(m => m.Id == matterId).Nature;
long sequenceId = commonSequenceRepository.GetSequenceIds(new[] { matterId },
notation,
language,
translator,
pauseTreatment,
sequentialTransfer,
trajectory).Single();
chains[k] = commonSequenceRepository.GetLibiadaChain(sequenceId);
}
for (var i = 0; i < characteristicLinkIds.Length; i++)
{
int characteristicLinkId = characteristicLinkIds[i];
FullCharacteristic characteristic = characteristicTypeLinkRepository.GetCharacteristic(characteristicLinkId);
calculators[i] = FullCalculatorsFactory.CreateCalculator(characteristic);
links[i] = characteristicTypeLinkRepository.GetLinkForCharacteristic(characteristicLinkId);
}
for (int i = 0; i < chains.Length; i++)
{
CutRule cutRule = growingWindow
? (CutRule) new CutRuleWithFixedStart(chains[i].Length, step)
: new SimpleCutRule(chains[i].Length, step, length);
CutRuleIterator iterator = cutRule.GetIterator();
var fragments = new List <Chain>();
partNames[i] = new List <string>();
starts[i] = new List <int>();
lengthes[i] = new List <int>();
while (iterator.Next())
{
int start = iterator.GetStartPosition();
int end = iterator.GetEndPosition();
var fragment = new List <IBaseObject>();
for (int k = 0; start + k < end; k++)
{
fragment.Add(chains[i][start + k]);
}
fragments.Add(new Chain(fragment));
partNames[i].Add(fragment.ToString());
starts[i].Add(iterator.GetStartPosition());
lengthes[i].Add(fragment.Count);
}
var fragmentsData = new FragmentData[fragments.Count];
for (int k = 0; k < fragments.Count; k++)
{
var characteristics = new double[calculators.Length];
for (int j = 0; j < calculators.Length; j++)
{
characteristics[j] = calculators[j].Calculate(fragments[k], links[j]);
}
fragmentsData[k] = new FragmentData(characteristics, fragments[k].ToString(), starts[i][k], fragments[k].Length);
}
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 LocalCharacteristicsData(matters[matterIds[i]].Name,
fragmentsData,
differenceData,
fourierData,
autocorrelationData);
}
for (int l = 0; l < characteristicLinkIds.Length; l++)
{
characteristicNames[l] = characteristicTypeLinkRepository.GetCharacteristicName(characteristicLinkIds[l]);
}
var characteristicsList = new SelectListItem[characteristicLinkIds.Length];
for (int k = 0; k < characteristicLinkIds.Length; k++)
{
characteristicNames[k] = characteristicTypeLinkRepository.GetCharacteristicName(characteristicLinkIds[k], notation);
characteristicsList[k] = new SelectListItem
{
Value = k.ToString(),
Text = characteristicNames[k],
Selected = false
};
}
var result = new Dictionary <string, object>
{
{ "characteristics", mattersCharacteristics },
{ "notationName", notation.GetDisplayValue() },
{ "starts", starts },
{ "partNames", partNames },
{ "lengthes", lengthes },
{ "characteristicNames", characteristicNames },
{ "matterIds", matterIds },
{ "characteristicsList", characteristicsList },
{ "aligners", EnumHelper.GetSelectList(typeof(Aligner)) },
{ "distanceCalculators", EnumHelper.GetSelectList(typeof(DistanceCalculator)) },
{ "aggregators", EnumHelper.GetSelectList(typeof(Aggregator)) }
};
return new Dictionary <string, string> {
{ "data", JsonConvert.SerializeObject(result) }
};
}));
}
public ActionResult Index(
long matterId,
short characteristicLinkId,
Notation notation,
int step,
int initialLength,
double accuracy)
{
return(CreateTask(() =>
{
string characteristicName;
string mattersName;
double[] characteristics;
Chain sequence;
IFullCalculator calculator;
Link link;
using (var db = new LibiadaWebEntities())
{
var commonSequenceRepository = new CommonSequenceRepository(db);
mattersName = db.Matter.Single(m => matterId == m.Id).Name;
var sequenceId = db.CommonSequence.Single(c => matterId == c.MatterId && c.Notation == notation).Id;
sequence = commonSequenceRepository.GetLibiadaChain(sequenceId);
var characteristicTypeLinkRepository = FullCharacteristicRepository.Instance;
characteristicName = characteristicTypeLinkRepository.GetCharacteristicName(characteristicLinkId, notation);
FullCharacteristic characteristic = characteristicTypeLinkRepository.GetCharacteristic(characteristicLinkId);
calculator = FullCalculatorsFactory.CreateCalculator(characteristic);
link = characteristicTypeLinkRepository.GetLinkForCharacteristic(characteristicLinkId);
}
// characteristics = SequencesCharacteristicsCalculator.Calculate( new[] { sequenceId }, characteristicLinkId);
CutRule cutRule = new CutRuleWithFixedStart(sequence.Length, step);
Depth depthCaulc = new Depth();
CutRuleIterator iter = cutRule.GetIterator();
var fragments = new List <Chain>();
var partNames = new List <string>();
var lengthes = new List <int>();
var teoreticalDepht = new List <double>();
while (iter.Next())
{
var fragment = new Chain(iter.GetEndPosition() - iter.GetStartPosition());
for (int k = 0; iter.GetStartPosition() + k < iter.GetEndPosition(); k++)
{
fragment.Set(sequence[iter.GetStartPosition() + k], k);
}
fragments.Add(fragment);
partNames.Add(fragment.ToString());
lengthes.Add(fragment.Length);
teoreticalDepht.Add(depthCaulc.Calculate(fragment, Link.Start));
}
characteristics = new double[fragments.Count];
for (int k = 0; k < fragments.Count; k++)
{
characteristics[k] = calculator.Calculate(fragments[k], link);
// fragmentsData[k] = new FragmentData(characteristics, fragments[k].ToString(), starts[i][k], fragments[k].Length);
}
// var predicted = new List<Chain>();
//int[] startingPart = new int[initialLength];
Chain predicted = new Chain(initialLength);
for (int i = 0; i < initialLength; i++)
{
predicted.Set(sequence[i], i);
}
Alphabet alphabet = sequence.Alphabet;
IEnumerator enumerator = alphabet.GetEnumerator();
var sequencePredictionResult = new List <SequencePredictionData>();
for (int i = initialLength; i < sequence.Length; i++)
{
Chain temp = new Chain(i + 1);
for (int j = 0; j < i; j++)
{
temp.Set(predicted[j], j);
}
predicted = temp;
double depth = 0;
/* do
* {
* predicted.Set((IBaseObject)enumerator.Current, i);
* depth = depthCaulc.Calculate(predicted, Link.Start);
* if (System.Math.Abs(depth - teoreticalDepht.ElementAt(i)) <= accuracy)
* {
* break;
* }
* } while (enumerator.MoveNext());*/
IBaseObject predictedLetter = null;
foreach (IBaseObject letter in alphabet)
{
predicted.Set(letter, i);
depth = depthCaulc.Calculate(predicted, Link.Start);
if (System.Math.Abs(depth - teoreticalDepht.ElementAt(i)) <= accuracy)
{
predictedLetter = letter;
break;
}
}
sequencePredictionResult.Add(new SequencePredictionData
{
Fragment = fragments.ElementAt(i).ToString(),
Predicted = /*enumerator.Current.ToString()*/ predicted.ToString(),
ActualCharacteristic = depth,
TheoreticalCharacteristic = teoreticalDepht.ElementAt(i)
});
}
/*int equal = 0;
* for (int i = initialLength; i < sequence.Length; i++)
* {
* if (sequence[i] == predicted[i])
* {
* equal++;
* }
* }
*
*
* double accuracyPercentage = equal / (sequence.Length - initialLength);*/
// TODO: sequence prediction
var result = new Dictionary <string, object>
{
{ "result", sequencePredictionResult }
};
return new Dictionary <string, object>
{
{ "data", JsonConvert.SerializeObject(result) }
};
}));
}
