void ClassificationBiasMatrix::ReadSimpleConfusionMatrix (istream& sr,
MLClassListPtr fileClasses
)
{
// 'classes' - The class order that the owner of this object is expecting.
// 'fileClasses' - The order that the classes are stored in the text file.
if ((classes == NULL) || (fileClasses == NULL))
{
KKStr errMsg = "ReadSimpleConfusionMatrix ***ERROR*** The 'Classes' line was never provided.";
runLog.Level (-1) << errMsg << endl;
valid = false;
throw KKException (errMsg);
}
kkint32 classesColIdx = 0;
char buff[10240];
KKStr l;
while (!sr.eof ())
{
sr.getline (buff, sizeof (buff));
l = buff;
l.TrimLeft ();
l.TrimRight ();
if (l.CompareIgnoreCase ("</SimpleConfusionMatrix>") == 0)
break;
KKStr lineName = l.ExtractToken2 ("\t");
if (lineName.CompareIgnoreCase ("DataRow") == 0)
{
if (fileClasses == NULL)
{
KKStr errMsg = "ReadSimpleConfusionMatrix ***ERROR*** 'Classes' was not provided before 'DataRow'.";
runLog.Level (-1) << errMsg << endl;
valid = false;
throw KKException (errMsg);
}
KKStr className = l.ExtractToken2 ("\t");
KKStr data = l.ExtractToken2 ("\t");
MLClassPtr pc = MLClass::CreateNewMLClass (className);
kkint32 classesIdx = classes->PtrToIdx (pc);
kkint32 fileClassesIdx = fileClasses->PtrToIdx (pc);
if (classesIdx < 0)
{
KKStr errMsg = "ReadSimpleConfusionMatrix ***ERROR*** DataRow specifies class[" + className + "] which is not defined by caller";
runLog.Level (-1) << errMsg << endl;
valid = false;
throw KKException (errMsg);
}
if (fileClassesIdx < 0)
{
KKStr errMsg = "ReadSimpleConfusionMatrix ***ERROR*** DataRow specifies class[" + className + "] was not defined in 'Classes' line.";
runLog.Level (-1) << errMsg << endl;
valid = false;
throw KKException (errMsg);
}
kkint32 classesRowIdx = classesIdx;
VectorKKStr dataFields = data.Split (',');
if (dataFields.size () != (kkuint32)numClasses)
{
KKStr errMsg = "ReadSimpleConfusionMatrix ***ERROR*** DataRow Class[" + className + "] number[" + StrFormatInt ((kkint32)dataFields.size (), "ZZZ0") + "] of values provided does not match number of Classes.";
runLog.Level (-1) << errMsg << endl;
valid = false;
throw KKException (errMsg);
}
for (kkint32 c = 0; c < numClasses; c++)
{
pc = fileClasses->IdxToPtr (c);
classesColIdx = classes->PtrToIdx (pc);
VectorKKStr parts = dataFields[c].Split (':');
if (parts.size () > 1)
{
(*counts) [classesRowIdx][classesColIdx] = parts[0].ToDouble ();
(*probabilities)[classesRowIdx][classesColIdx] = parts[1].ToDouble ();
}
}
}
}
} /* ReadSimpleConfusionMatrix */
