|
public static convertDistributionMapToSortedArray ( double>.IDictionary |
||
| distribution | double>.IDictionary | current distribution as an JsonArray instance |
| return | JsonArray | |
public static JsonArray convertDistributionMapToSortedArray(IDictionary<object, double> distribution)
{
JsonArray newDistribution = new JsonArray();
string opType = BigML.OpType.Numeric.ToString();
foreach (object key in distribution.Keys)
{
JsonArray element = new JsonArray();
element.Add((JsonValue) key);
element.Add(distribution[key]);
newDistribution.Add(element);
if (isNumericType(key))
{
opType = BigML.OpType.Numeric.ToString();
}
else if (key is string)
{
opType = BigML.OpType.Text.ToString();
}
}
/*
if (distribution != null && distribution.Count > 0)
{
//TODO: SORT newDistribution
foreach (JsonValue element in newDistribution)
{
foreach (JsonValue element1 in newDistribution)
{
if (element == element1)
{
continue;
}
if (OpType.Numeric.Equals(opType))
{
if ( ((double) element[0]) > ((double) element1[0]) )
{
}
}
else if (OpType.Text.Equals(opType))
{
if ( ((double)element[0]) > ((double)element1[0]) )
{
}
}
else
{ // OPTYPE_DATETIME
// TODO: implement this
throw new Exception("Not supported");
}
}
}
}*/
return newDistribution;
}
/// <summary>
/// Returns a distribution formed by grouping the distributions of each predicted node.
/// </summary>
protected internal Dictionary <string, object> getGroupedDistribution(MultiVote multiVoteInstance)
{
Dictionary <object, double> joinedDist = new Dictionary <object, double>();
string distributionUnit = "counts";
Dictionary <object, double> predictionDist;
object distribution;
foreach (Dictionary <object, object> prediction in multiVoteInstance.Predictions)
{
// Equivalent to:
// JSONArray predictionDist = (JSONArray) prediction.get("distribution");
predictionDist = null;
distribution = prediction["distribution"];
if (distribution is IDictionary)
{
predictionDist = (Dictionary <object, double>)distribution;
}
else if ((distribution == null) || (!(distribution is JsonArray)))
{
predictionDist = new Dictionary <object, double>();
}
else
{
predictionDist = Utils.convertDistributionArrayToMap((JsonArray)distribution);
}
// Equivalent to:
// joinedDist = Utils.mergeDistributions(joinedDist, Utils.convertDistributionArrayToMap(predictionDist));
joinedDist = Utils.mergeDistributions(joinedDist, predictionDist);
if ("counts".Equals(distributionUnit) && joinedDist.Count > BINS_LIMIT)
{
distributionUnit = "bins";
}
joinedDist = Utils.mergeBins(joinedDist, BINS_LIMIT);
}
Dictionary <string, object> distributionInfo = new Dictionary <string, object>();
distributionInfo["distribution"] = Utils.convertDistributionMapToSortedArray(joinedDist);
distributionInfo["distributionUnit"] = distributionUnit;
return(distributionInfo);
}
