public override AbstractAttributeStruct getAbstractAttribute(Ice.Current __current)
{
ColumnInfo columnInfo = this.getColumnFunctionsPrx().getColumnInfo();
AbstractAttributeStruct result = new AbstractAttributeStruct();
Ferda.Modules.Helpers.Data.Column.TestColumnSelectExpression(
columnInfo.dataMatrix.database.odbcConnectionString,
columnInfo.dataMatrix.dataMatrixName,
columnInfo.columnSelectExpression,
boxModule.StringIceIdentity);
GeneratedAttribute categoriesInfo = getCategoriesInfo(columnInfo);
result.column = columnInfo;
result.categories = categoriesInfo.CategoriesStruct;
//AttributeFunctionsI.TestCategoriesDisjunctivity(sumOfRowMax.categories, boxIdentity);
//This test is useless here (vain / effort / wastage)
result.identifier = boxModule.PersistentIdentity;
result.countOfCategories = categoriesInfo.CategoriesCount;
result.includeNullCategory = categoriesInfo.IncludeNullCategoryName;
result.xCategory = XCategory;
Ferda.Modules.Helpers.Data.Attribute.TestAreCategoriesInCategories(result.categories, new string[] { result.xCategory, result.includeNullCategory } , boxModule.StringIceIdentity);
result.nameInLiterals = NameInLiterals;
return result;
}
/// <summary>
/// Provides functionality of manually prepared attribute box, where is connected
/// BMI column. There are created basic BMI categories (see below) in the result.
/// </summary>
/// <returns></returns>
/// <remarks>
/// <list type="table">
/// <listheader>
/// <term>[kg/m^2]</term>
/// <description><b>en-US</b>; cs-CZ</description>
/// </listheader>
/// <item>
/// <term>< 15 </term>
/// <description><b>Extremely underweight</b>; vyzáblá postava</description>
/// </item>
/// <item>
/// <term>15 - 20</term>
/// <description><b>Underweight</b>; hubená postava</description>
/// </item>
/// <item>
/// <term>20 - 25</term>
/// <description><b>Normal</b>; normální postava</description>
/// </item>
/// <item>
/// <term>25 - 30</term>
/// <description><b>Overweight</b>; postava s nadváhou</description>
/// </item>
/// <item>
/// <term>> 30</term>
/// <description><b>Obese</b>; obézní postava</description>
/// </item>
/// </list>
/// </remarks>
public override Ferda.Modules.Boxes.DataMiningCommon.Attributes.AbstractAttributeStruct getAbstractAttribute(Ice.Current current__)
{
AbstractAttributeStruct result = new AbstractAttributeStruct();
Ferda.Modules.CategoriesStruct categories = new Ferda.Modules.CategoriesStruct();
categories.floatIntervals = new Ferda.Modules.FloatIntervalCategorySeq();
bool isLocalized;
categories.floatIntervals.Add(
boxModule.GetPhrase("ExtremelyUnderweight", out isLocalized),
new Ferda.Modules.FloatIntervalStruct[] {
new Ferda.Modules.FloatIntervalStruct(
Ferda.Modules.BoundaryEnum.Infinity,
Ferda.Modules.BoundaryEnum.Round,
0,
15)
}
);
categories.floatIntervals.Add(
boxModule.GetPhrase("Underweight", out isLocalized),
new Ferda.Modules.FloatIntervalStruct[] {
new Ferda.Modules.FloatIntervalStruct(
Ferda.Modules.BoundaryEnum.Sharp,
Ferda.Modules.BoundaryEnum.Round,
15,
20)
}
);
categories.floatIntervals.Add(
boxModule.GetPhrase("Normal", out isLocalized),
new Ferda.Modules.FloatIntervalStruct[] {
new Ferda.Modules.FloatIntervalStruct(
Ferda.Modules.BoundaryEnum.Sharp,
Ferda.Modules.BoundaryEnum.Round,
20,
25)
}
);
categories.floatIntervals.Add(
boxModule.GetPhrase("Overweight", out isLocalized),
new Ferda.Modules.FloatIntervalStruct[] {
new Ferda.Modules.FloatIntervalStruct(
Ferda.Modules.BoundaryEnum.Sharp,
Ferda.Modules.BoundaryEnum.Round,
25,
30)
}
);
categories.floatIntervals.Add(
boxModule.GetPhrase("Obese", out isLocalized),
new Ferda.Modules.FloatIntervalStruct[] {
new Ferda.Modules.FloatIntervalStruct(
Ferda.Modules.BoundaryEnum.Sharp,
Ferda.Modules.BoundaryEnum.Infinity,
30,
float.MaxValue)
}
);
result.categories = categories;
result.column = this.getColumnInfo();
result.countOfCategories = result.categories.floatIntervals.Count;
result.identifier = boxModule.PersistentIdentity;
result.includeNullCategory = "";
result.nameInLiterals = "BodyMassIndex";
result.xCategory = "";
return result;
}
public double[] GetNumericValues(AbstractAttributeStruct attribute)
{
if (numericValuesCache.ContainsKey(attribute))
return numericValuesCache[attribute];
double[] result;
bool canPass = true;
List<double> valueList = new List<double>();
if (
attribute != null
&& attribute.categories.enums.Count > 0
&& attribute.categories.dateTimeIntervals.Count == 0
&& attribute.categories.floatIntervals.Count == 0
&& attribute.categories.longIntervals.Count == 0
)
{
foreach (DictionaryEntry value in attribute.categories.enums)
{
String[] StringSeq = (String[])value.Value;
if (StringSeq.Length == 1)
{
double doubleResult;
if (Double.TryParse(StringSeq[0], out doubleResult))
{
valueList.Add(doubleResult);
}
else
{
canPass = false;
break;
}
}
else
{
canPass = false;
}
}
}
else
{
canPass = false;
}
if (canPass)
{
result = valueList.ToArray();
}
else
{
result = null;
}
numericValuesCache.Add(attribute, result);
return result;
}
public override AbstractAttributeStruct getAbstractAttribute(Ice.Current __current)
{
AbstractAttributeStruct result = new AbstractAttributeStruct();
result.column = getColumnFunctionsPrx().getColumnInfo();
result.categories = Categories;
Ferda.Modules.Helpers.Data.Attribute.TestCategoriesDisjunctivity(result.categories, boxModule.StringIceIdentity);
result.countOfCategories = Ferda.Modules.Helpers.Data.Attribute.GetCategoriesCount(result.categories);
//Ferda.Modules.Helpers.Data.Attribute.TestCategoriesCount(result.countOfCategories, boxIdentity);
result.identifier = boxModule.PersistentIdentity;
result.includeNullCategory = IncludeNullCategory;
result.xCategory = XCategory;
Ferda.Modules.Helpers.Data.Attribute.TestAreCategoriesInCategories(result.categories, new string[] { result.xCategory, result.includeNullCategory } , boxModule.StringIceIdentity);
result.nameInLiterals = NameInLiterals;
return result;
}