public void DivikBigData()
{
// path to directory with test project
var path = TestDirectory + "\\hnc1_tumor.txt";
var dataset = new BasicTextDataset(path);
var options = DivikOptions.ForLevels(levels: 2);
var result = _segmentation.Divik(dataset, options);
// Assert
Assert.IsNotNull(result);
}
public void SetUpFixture()
{
var dataset = new BasicTextDataset(_testFilePath);
var options = DivikOptions.ForLevels(levels: 1);
options.MaxK = 2;
options.Caching = false;
options.PlottingPartitions = false;
options.PlottingDecomposition = false;
options.PlottingDecompositionRecursively = false;
options.PlottingRecursively = false;
options.UsingAmplitudeFiltration = false;
_segmentation = new Segmentation();
_result = _segmentation.Divik(dataset, options);
}
public void EqualsAgainstDifferentInstance()
{
var dataset = new BasicTextDataset(_testFilePath);
var options = DivikOptions.ForLevels(levels: 1);
options.MaxK = 2;
options.Caching = false;
options.PlottingPartitions = false;
options.PlottingDecomposition = false;
options.PlottingDecompositionRecursively = false;
options.PlottingRecursively = false;
options.UsingVarianceFiltration = false;
var result = _segmentation.Divik(dataset, options);
Assert.False(condition: result.Equals(_result), message: "Unequal objects not indicated.");
}
public void DivikSimple()
{
double[] mz = { 1, 2, 3, 4 };
double[,] data = { { 1, 1, 1, 1 }, { 2, 2, 2, 2 }, { 2, 2, 2, 2 }, { 1, 1, 1, 1 } };
int[,] coordinates = { { 1, 1 }, { 2, 2 }, { 1, 2 }, { 2, 1 } };
IDataset dataset = new BasicTextDataset(mz, data, coordinates);
var options = DivikOptions.ForLevels(levels: 1);
options.UsingVarianceFiltration = false;
options.UsingAmplitudeFiltration = false;
options.MaxK = 2;
options.Metric = Metric.Euclidean;
var result = _segmentation.Divik(dataset, options);
// Assert
Assert.IsNotNull(result);
}