public void CompleteDiameterTest()
{
// cluster is null
{
ArgumentExceptionAssert.Throw(
() =>
{
var partition = Distance.CompleteDiameter((DoubleMatrix)null);
},
expectedType: typeof(ArgumentNullException),
expectedPartialMessage: ArgumentExceptionAssert.NullPartialMessage,
expectedParameterName: "cluster");
}
// cluster is valid
{
var items = IndexCollection.Range(0, 3);
int numberOfItems = items.Count;
var attributes = IrisDataSet.GetAttributesAsDoubleMatrix()[items, ":"];
var actual = Distance.CompleteDiameter(attributes);
var expected = 0.6480741;
Assert.AreEqual(expected, actual, DoubleMatrixTest.Accuracy);
}
}
public void EuclideanTest()
{
// cluster is null
{
ArgumentExceptionAssert.Throw(
() =>
{
var partition = Distance.Euclidean((DoubleMatrix)null);
},
expectedType: typeof(ArgumentNullException),
expectedPartialMessage: ArgumentExceptionAssert.NullPartialMessage,
expectedParameterName: "cluster");
}
// cluster is valid
{
var items = IndexCollection.Range(0, 3);
int numberOfItems = items.Count;
var attributes = IrisDataSet.GetAttributesAsDoubleMatrix()[items, ":"];
var actual = Distance.Euclidean(attributes);
var expected = DoubleMatrix.Dense(
numberOfItems,
numberOfItems,
new double[] {
0.0000000, 0.5385165, 0.5099020, 0.6480741,
0.5385165, 0.0000000, 0.3000000, 0.3316625,
0.5099020, 0.3000000, 0.0000000, 0.2449490,
0.6480741, 0.3316625, 0.2449490, 0.0000000
},
StorageOrder.RowMajor);
DoubleMatrixAssert.AreEqual(expected, actual, DoubleMatrixTest.Accuracy);
}
}
public void IndexPartitionDaviesBouldinTest()
{
// data is null
{
var target = IrisDataSet.GetClassPredictions();
var partition = IndexPartition.Create(target);
ArgumentExceptionAssert.Throw(
() =>
{
var actual = IndexPartition.DaviesBouldinIndex(null, partition);
},
expectedType: typeof(ArgumentNullException),
expectedPartialMessage: ArgumentExceptionAssert.NullPartialMessage,
expectedParameterName: "data");
}
// partition is null
{
var data = IrisDataSet.GetAttributesAsDoubleMatrix();
ArgumentExceptionAssert.Throw(
() =>
{
var actual = IndexPartition.DaviesBouldinIndex(data, null);
},
expectedType: typeof(ArgumentNullException),
expectedPartialMessage: ArgumentExceptionAssert.NullPartialMessage,
expectedParameterName: "partition");
}
// The first part contains an invalid index
{
var data = IrisDataSet.GetAttributesAsDoubleMatrix();
var target = IrisDataSet.GetClassPredictions();
var partition = IndexPartition.Create(target);
partition[1][0] = 100000;
ArgumentExceptionAssert.Throw(
() =>
{
var actual = IndexPartition.DaviesBouldinIndex(data, partition);
},
expectedType: typeof(ArgumentException),
expectedPartialMessage: ImplementationServices.GetResourceString(
"STR_EXCEPT_INP_PART_CONTAINS_INVALID_INDEX"),
expectedParameterName: "partition");
}
// The second part contains an invalid index
{
var data = IrisDataSet.GetAttributesAsDoubleMatrix();
var target = IrisDataSet.GetClassPredictions();
var partition = IndexPartition.Create(target);
partition[2][0] = 100000;
ArgumentExceptionAssert.Throw(
() =>
{
var actual = IndexPartition.DaviesBouldinIndex(data, partition);
},
expectedType: typeof(ArgumentException),
expectedPartialMessage: ImplementationServices.GetResourceString(
"STR_EXCEPT_INP_PART_CONTAINS_INVALID_INDEX"),
expectedParameterName: "partition");
}
// Valid input
{
var data = IrisDataSet.GetAttributesAsDoubleMatrix();
var target = IrisDataSet.GetClassPredictions();
var partition = IndexPartition.Create(target);
var actual = IndexPartition.DaviesBouldinIndex(
data, partition);
// The expected below was obtained in R as follows:
//
// library(clv)
// data(iris)
// iris.data < -iris[, 1:4]
// # cluster data
// agnes.mod < -agnes(iris.data) # create cluster tree
// v.pred < - as.integer(cutree(agnes.mod, 5)) # "cut" the tree
// intraclust = c("complete", "average", "centroid")
// interclust = c("single", "complete", "average", "centroid", "aveToCent", "hausdorff")
// cls.scatt < -cls.scatt.data(iris.data, v.pred, dist = "euclidean")
// davies1 <- clv.Davies.Bouldin(cls.scatt, intraclust, interclust)
// This is davies1[4,3], corresponding to
// intra = "centroid",
// inter = "centroid".
double expected = 0.685838025870551;
Assert.AreEqual(expected, actual, 1e-3);
}
}
public void IndexPartitionMinimumCentroidTest()
{
// data is null
{
var target = IrisDataSet.GetClassPredictions();
var partition = IndexPartition.Create(target);
ArgumentExceptionAssert.Throw(
() =>
{
var actual = IndexPartition.MinimumCentroidLinkage(null, partition);
},
expectedType: typeof(ArgumentNullException),
expectedPartialMessage: ArgumentExceptionAssert.NullPartialMessage,
expectedParameterName: "data");
}
// partition is null
{
var data = IrisDataSet.GetAttributesAsDoubleMatrix();
ArgumentExceptionAssert.Throw(
() =>
{
var actual = IndexPartition.MinimumCentroidLinkage(data, null);
},
expectedType: typeof(ArgumentNullException),
expectedPartialMessage: ArgumentExceptionAssert.NullPartialMessage,
expectedParameterName: "partition");
}
// The first part contains an invalid index
{
var data = IrisDataSet.GetAttributesAsDoubleMatrix();
var target = IrisDataSet.GetClassPredictions();
var partition = IndexPartition.Create(target);
partition[1][0] = 100000;
ArgumentExceptionAssert.Throw(
() =>
{
var actual = IndexPartition.MinimumCentroidLinkage(data, partition);
},
expectedType: typeof(ArgumentException),
expectedPartialMessage: ImplementationServices.GetResourceString(
"STR_EXCEPT_INP_PART_CONTAINS_INVALID_INDEX"),
expectedParameterName: "partition");
}
// The second part contains an invalid index
{
var data = IrisDataSet.GetAttributesAsDoubleMatrix();
var target = IrisDataSet.GetClassPredictions();
var partition = IndexPartition.Create(target);
partition[2][0] = 100000;
ArgumentExceptionAssert.Throw(
() =>
{
var actual = IndexPartition.MinimumCentroidLinkage(data, partition);
},
expectedType: typeof(ArgumentException),
expectedPartialMessage: ImplementationServices.GetResourceString(
"STR_EXCEPT_INP_PART_CONTAINS_INVALID_INDEX"),
expectedParameterName: "partition");
}
// Valid input
{
var data = IrisDataSet.GetAttributesAsDoubleMatrix();
var target = IrisDataSet.GetClassPredictions();
var partition = IndexPartition.Create(target);
var actual = IndexPartition.MinimumCentroidLinkage(
data, partition);
List <double> linkages = new();
foreach (var leftId in partition.Identifiers)
{
var leftPart = partition[leftId];
var left = data[leftPart, ":"];
foreach (var rightId in partition.Identifiers)
{
if (rightId != leftId)
{
var rightPart = partition[rightId];
var right = data[rightPart, ":"];
linkages.Add(Distance.CentroidLinkage(left, right));
}
}
}
double expected = linkages.Min();
Assert.AreEqual(expected, actual, 1e-4);
}
}
public void AverageLinkageTest()
{
// left is null
{
ArgumentExceptionAssert.Throw(
() =>
{
Distance.AverageLinkage(
left: (DoubleMatrix)null,
right: DoubleMatrix.Identity(2));
},
expectedType: typeof(ArgumentNullException),
expectedPartialMessage: ArgumentExceptionAssert.NullPartialMessage,
expectedParameterName: "left");
}
// right is null
{
ArgumentExceptionAssert.Throw(
() =>
{
Distance.AverageLinkage(
left: DoubleMatrix.Identity(2),
right: (DoubleMatrix)null);
},
expectedType: typeof(ArgumentNullException),
expectedPartialMessage: ArgumentExceptionAssert.NullPartialMessage,
expectedParameterName: "right");
}
// right and left have not the same number of columns
{
ArgumentExceptionAssert.Throw(
() =>
{
Distance.AverageLinkage(
left: DoubleMatrix.Identity(2),
right: DoubleMatrix.Identity(3));
},
expectedType: typeof(ArgumentException),
expectedPartialMessage: string.Format(
ImplementationServices.GetResourceString(
"STR_EXCEPT_PAR_MUST_HAVE_SAME_NUM_OF_COLUMNS"),
"left"),
expectedParameterName: "right");
}
// input is valid
{
var items = IndexCollection.Range(0, 3);
int numberOfItems = items.Count;
var attributes = IrisDataSet.GetAttributesAsDoubleMatrix();
var classes = IrisDataSet.GetClasses();
var partition = IndexPartition.Create(classes);
var left = attributes[partition["virginica"], ":"][items, ":"];
var right = attributes[partition["setosa"], ":"][items, ":"];
var actual = Distance.AverageLinkage(left, right);
var expected = 4.932325;
Assert.AreEqual(expected, actual, DoubleMatrixTest.Accuracy);
}
}