private static byte[] GetBytesFromDataView(IHost host, IDataView lookup, string termColumn, string valueColumn)
{
Contracts.AssertValue(host);
host.AssertValue(lookup);
host.AssertNonEmpty(termColumn);
host.AssertNonEmpty(valueColumn);
int colTerm;
int colValue;
var schema = lookup.Schema;
if (!schema.TryGetColumnIndex(termColumn, out colTerm))
{
throw host.ExceptUserArg(nameof(Arguments.TermColumn), "column not found: '{0}'", termColumn);
}
if (!schema.TryGetColumnIndex(valueColumn, out colValue))
{
throw host.ExceptUserArg(nameof(Arguments.ValueColumn), "column not found: '{0}'", valueColumn);
}
// REVIEW: Should we allow term to be a vector of text (each term in the vector
// would map to the same value)?
var typeTerm = schema.GetColumnType(colTerm);
host.CheckUserArg(typeTerm.IsText, nameof(Arguments.TermColumn), "term column must contain text");
var typeValue = schema.GetColumnType(colValue);
var args = new ChooseColumnsTransform.Arguments();
args.Column = new[] {
new ChooseColumnsTransform.Column {
Name = "Term", Source = termColumn
},
new ChooseColumnsTransform.Column {
Name = "Value", Source = valueColumn
},
};
var view = new ChooseColumnsTransform(host, args, lookup);
var saver = new BinarySaver(host, new BinarySaver.Arguments());
using (var strm = new MemoryStream())
{
saver.SaveData(strm, view, 0, 1);
return(strm.ToArray());
}
}
private IDataView WrapPerInstance(RoleMappedData perInst)
{
var idv = perInst.Data;
// Make a list of column names that Maml outputs as part of the per-instance data view, and then wrap
// the per-instance data computed by the evaluator in a ChooseColumnsTransform.
var cols = new List <ChooseColumnsTransform.Column>();
// If perInst is the result of cross-validation and contains a fold Id column, include it.
int foldCol;
if (perInst.Schema.Schema.TryGetColumnIndex(MetricKinds.ColumnNames.FoldIndex, out foldCol))
{
cols.Add(new ChooseColumnsTransform.Column()
{
Source = MetricKinds.ColumnNames.FoldIndex
});
}
// Maml always outputs a name column, if it doesn't exist add a GenerateNumberTransform.
if (perInst.Schema.Name == null)
{
var args = new GenerateNumberTransform.Arguments();
args.Column = new[] { new GenerateNumberTransform.Column()
{
Name = "Instance"
} };
args.UseCounter = true;
idv = new GenerateNumberTransform(Host, args, idv);
cols.Add(new ChooseColumnsTransform.Column()
{
Name = "Instance"
});
}
else
{
cols.Add(new ChooseColumnsTransform.Column()
{
Source = perInst.Schema.Name.Name, Name = "Instance"
});
}
// Maml outputs the weight column if it exists.
if (perInst.Schema.Weight != null)
{
cols.Add(new ChooseColumnsTransform.Column()
{
Name = perInst.Schema.Weight.Name
});
}
// Get the other columns from the evaluator.
foreach (var col in GetPerInstanceColumnsToSave(perInst.Schema))
{
cols.Add(new ChooseColumnsTransform.Column()
{
Name = col
});
}
var chooseArgs = new ChooseColumnsTransform.Arguments();
chooseArgs.Column = cols.ToArray();
idv = new ChooseColumnsTransform(Host, chooseArgs, idv);
return(GetPerInstanceMetricsCore(idv, perInst.Schema));
}
private void RunCore(IChannel ch)
{
Host.AssertValue(ch);
IDataView data = CreateAndSaveLoader();
if (!string.IsNullOrWhiteSpace(Args.Columns))
{
var args = new ChooseColumnsTransform.Arguments();
args.Column = Args.Columns
.Split(new char[] { ',' }, StringSplitOptions.RemoveEmptyEntries).Select(s => new ChooseColumnsTransform.Column()
{
Name = s
}).ToArray();
if (Utils.Size(args.Column) > 0)
{
data = new ChooseColumnsTransform(Host, args, data);
}
}
IDataSaver saver;
if (Args.Saver != null)
{
saver = Args.Saver.CreateComponent(Host);
}
else
{
saver = new TextSaver(Host, new TextSaver.Arguments()
{
Dense = Args.Dense
});
}
var cols = new List <int>();
for (int i = 0; i < data.Schema.ColumnCount; i++)
{
if (!Args.KeepHidden && data.Schema.IsHidden(i))
{
continue;
}
var type = data.Schema.GetColumnType(i);
if (saver.IsColumnSavable(type))
{
cols.Add(i);
}
else
{
ch.Info(MessageSensitivity.Schema, "The column '{0}' will not be written as it has unsavable column type.", data.Schema.GetColumnName(i));
}
}
Host.NotSensitive().Check(cols.Count > 0, "No valid columns to save");
// Send the first N lines to console.
if (Args.Rows > 0)
{
var args = new SkipTakeFilter.TakeArguments()
{
Count = Args.Rows
};
data = SkipTakeFilter.Create(Host, args, data);
}
var textSaver = saver as TextSaver;
// If it is a text saver, utilize a special utility for this purpose.
if (textSaver != null)
{
textSaver.WriteData(data, true, cols.ToArray());
}
else
{
using (MemoryStream mem = new MemoryStream())
{
using (Stream wrapStream = new SubsetStream(mem))
saver.SaveData(wrapStream, data, cols.ToArray());
mem.Seek(0, SeekOrigin.Begin);
using (StreamReader reader = new StreamReader(mem))
{
string result = reader.ReadToEnd();
ch.Info(MessageSensitivity.UserData | MessageSensitivity.Schema, result);
}
}
}
}
protected override void PrintFoldResultsCore(IChannel ch, Dictionary <string, IDataView> metrics)
{
IDataView top;
if (!metrics.TryGetValue(AnomalyDetectionEvaluator.TopKResults, out top))
{
throw Host.Except("Did not find the top-k results data view");
}
var sb = new StringBuilder();
using (var cursor = top.GetRowCursor(col => true))
{
int index;
if (!top.Schema.TryGetColumnIndex(AnomalyDetectionEvaluator.TopKResultsColumns.Instance, out index))
{
throw Host.Except("Data view does not contain the 'Instance' column");
}
var instanceGetter = cursor.GetGetter <ReadOnlyMemory <char> >(index);
if (!top.Schema.TryGetColumnIndex(AnomalyDetectionEvaluator.TopKResultsColumns.AnomalyScore, out index))
{
throw Host.Except("Data view does not contain the 'Anomaly Score' column");
}
var scoreGetter = cursor.GetGetter <Single>(index);
if (!top.Schema.TryGetColumnIndex(AnomalyDetectionEvaluator.TopKResultsColumns.Label, out index))
{
throw Host.Except("Data view does not contain the 'Label' column");
}
var labelGetter = cursor.GetGetter <Single>(index);
bool hasRows = false;
while (cursor.MoveNext())
{
if (!hasRows)
{
sb.AppendFormat("{0} Top-scored Results", _topScored);
sb.AppendLine();
sb.AppendLine("=================================================");
sb.AppendLine("Instance Anomaly Score Labeled");
hasRows = true;
}
var name = default(ReadOnlyMemory <char>);
Single score = 0;
Single label = 0;
instanceGetter(ref name);
scoreGetter(ref score);
labelGetter(ref label);
sb.AppendFormat("{0,-10}{1,12:G4}{2,12}", name, score, label);
sb.AppendLine();
}
}
if (sb.Length > 0)
{
ch.Info(MessageSensitivity.UserData, sb.ToString());
}
IDataView overall;
if (!metrics.TryGetValue(MetricKinds.OverallMetrics, out overall))
{
throw Host.Except("No overall metrics found");
}
// Find the number of anomalies, and the thresholds.
int numAnomIndex;
if (!overall.Schema.TryGetColumnIndex(AnomalyDetectionEvaluator.OverallMetrics.NumAnomalies, out numAnomIndex))
{
throw Host.Except("Could not find the 'NumAnomalies' column");
}
int stratCol;
var hasStrat = overall.Schema.TryGetColumnIndex(MetricKinds.ColumnNames.StratCol, out stratCol);
int stratVal;
bool hasStratVals = overall.Schema.TryGetColumnIndex(MetricKinds.ColumnNames.StratVal, out stratVal);
Contracts.Assert(hasStrat == hasStratVals);
long numAnomalies = 0;
using (var cursor = overall.GetRowCursor(col => col == numAnomIndex ||
(hasStrat && col == stratCol)))
{
var numAnomGetter = cursor.GetGetter <long>(numAnomIndex);
ValueGetter <uint> stratGetter = null;
if (hasStrat)
{
var type = cursor.Schema.GetColumnType(stratCol);
stratGetter = RowCursorUtils.GetGetterAs <uint>(type, cursor, stratCol);
}
bool foundRow = false;
while (cursor.MoveNext())
{
uint strat = 0;
if (stratGetter != null)
{
stratGetter(ref strat);
}
if (strat > 0)
{
continue;
}
if (foundRow)
{
throw Host.Except("Found multiple non-stratified rows in overall results data view");
}
foundRow = true;
numAnomGetter(ref numAnomalies);
}
}
var args = new ChooseColumnsTransform.Arguments();
var cols = new List <ChooseColumnsTransform.Column>()
{
new ChooseColumnsTransform.Column()
{
Name = string.Format(FoldDrAtKFormat, _k),
Source = AnomalyDetectionEvaluator.OverallMetrics.DrAtK
},
new ChooseColumnsTransform.Column()
{
Name = string.Format(FoldDrAtPFormat, _p),
Source = AnomalyDetectionEvaluator.OverallMetrics.DrAtPFpr
},
new ChooseColumnsTransform.Column()
{
Name = string.Format(FoldDrAtNumAnomaliesFormat, numAnomalies),
Source = AnomalyDetectionEvaluator.OverallMetrics.DrAtNumPos
},
new ChooseColumnsTransform.Column()
{
Name = AnomalyDetectionEvaluator.OverallMetrics.ThreshAtK
},
new ChooseColumnsTransform.Column()
{
Name = AnomalyDetectionEvaluator.OverallMetrics.ThreshAtP
},
new ChooseColumnsTransform.Column()
{
Name = AnomalyDetectionEvaluator.OverallMetrics.ThreshAtNumPos
},
new ChooseColumnsTransform.Column()
{
Name = BinaryClassifierEvaluator.Auc
}
};
args.Column = cols.ToArray();
IDataView fold = new ChooseColumnsTransform(Host, args, overall);
string weightedFold;
ch.Info(MetricWriter.GetPerFoldResults(Host, fold, out weightedFold));
}