public static SamplingEntry Divide(ref SamplingEntry oldEntry, double prevUpperLimit, double prevCumulativeWeight, double weightMult, double newUpperLimit)
{
SamplingEntry newEntry = new SamplingEntry();
newEntry.UpperLimit = newUpperLimit;
double newWidth = newUpperLimit - prevUpperLimit;
double oldWidth = oldEntry.UpperLimit - newUpperLimit;
double t = newWidth / (newWidth + oldWidth);
newEntry.Full = oldEntry.Full;
if (oldEntry.Sampler != null)
{
newEntry.Sampler = new IntervalSampler(oldEntry.Sampler, t, clone: false); // Will fix weights of the old sampler as well
newEntry.CumulativeWeight = prevCumulativeWeight + newEntry.Sampler.TotalWeight;
oldEntry.CumulativeWeight = newEntry.CumulativeWeight + oldEntry.Sampler.TotalWeight;
}
else
{
newEntry.Sampler = null;
if (oldEntry.Full)
{
newEntry.CumulativeWeight = oldEntry.CumulativeWeight = prevCumulativeWeight;
}
else
{
newEntry.CumulativeWeight = prevCumulativeWeight + weightMult * newWidth;
oldEntry.CumulativeWeight = newEntry.CumulativeWeight + weightMult * oldWidth;
}
}
return newEntry;
}
public static SamplingEntry Divide(ref SamplingEntry oldEntry, double prevUpperLimit, double prevCumulativeWeight, double weightMult, double newUpperLimit)
{
SamplingEntry newEntry = new SamplingEntry();
newEntry.UpperLimit = newUpperLimit;
double newWidth = newUpperLimit - prevUpperLimit;
double oldWidth = oldEntry.UpperLimit - newUpperLimit;
double t = newWidth / (newWidth + oldWidth);
newEntry.Full = oldEntry.Full;
if (oldEntry.Sampler != null)
{
newEntry.Sampler = new IntervalSampler(oldEntry.Sampler, t, clone: false); // Will fix weights of the old sampler as well
newEntry.CumulativeWeight = prevCumulativeWeight + newEntry.Sampler.TotalWeight;
oldEntry.CumulativeWeight = newEntry.CumulativeWeight + oldEntry.Sampler.TotalWeight;
}
else
{
newEntry.Sampler = null;
if (oldEntry.Full)
{
newEntry.CumulativeWeight = oldEntry.CumulativeWeight = prevCumulativeWeight;
}
else
{
newEntry.CumulativeWeight = prevCumulativeWeight + weightMult * newWidth;
oldEntry.CumulativeWeight = newEntry.CumulativeWeight + weightMult * oldWidth;
}
}
return(newEntry);
}
public SamplingEntry(SamplingEntry other)
{
UpperLimit = other.UpperLimit;
CumulativeWeight = other.CumulativeWeight;
Full = other.Full;
if (other.Sampler == null)
{
Sampler = null;
}
else
{
Sampler = new IntervalSampler(other.Sampler, 1.0, clone: true);
}
}
public SamplingEntry(SamplingEntry other)
{
UpperLimit = other.UpperLimit;
CumulativeWeight = other.CumulativeWeight;
Full = other.Full;
if (other.Sampler == null)
{
Sampler = null;
}
else
{
Sampler = new IntervalSampler(other.Sampler, 1.0, clone: true);
}
}
private void Multiply(double t)
{
m_weightMult *= t;
m_totalWeight *= t;
for (int i = 0; i < m_entries.Count; ++i)
{
SamplingEntry entry = m_entries[i];
entry.CumulativeWeight *= t;
m_entries[i] = entry;
if (entry.Sampler != null)
{
entry.Sampler.Multiply(t);
}
}
}
private IntervalSampler(IntervalSampler other, double t, bool clone)
{
m_min = other.m_min;
m_max = other.m_max;
m_axis = other.m_axis;
m_weightMult = other.m_weightMult;
m_totalWeight = other.m_totalWeight;
m_entries = new List <SamplingEntry>(other.m_entries);
for (int i = 0; i < other.m_entries.Count; ++i)
{
m_entries[i] = new SamplingEntry(other.m_entries[i]);
}
Multiply(t);
// If we are not cloning, we are splitting, so we have to multiply the remnant as well
if (!clone)
{
other.Multiply(1.0 - t);
}
}
private IntervalSampler(IntervalSampler other, double t, bool clone)
{
m_min = other.m_min;
m_max = other.m_max;
m_axis = other.m_axis;
m_weightMult = other.m_weightMult;
m_totalWeight = other.m_totalWeight;
m_entries = new List<SamplingEntry>(other.m_entries);
for (int i = 0; i < other.m_entries.Count; ++i)
{
m_entries[i] = new SamplingEntry(other.m_entries[i]);
}
Multiply(t);
// If we are not cloning, we are splitting, so we have to multiply the remnant as well
if (!clone)
{
other.Multiply(1.0 - t);
}
}
public void Subtract(ref BoundingBoxD originalBox, ref BoundingBoxD bb)
{
double min, max;
SelectMinMax(ref bb, m_axis, out min, out max);
bool minInserted = false;
double prevLimit = m_min;
double cumul = 0.0;
for (int i = 0; i < m_entries.Count; ++i)
{
SamplingEntry entry = m_entries[i];
if (!minInserted)
{
if (entry.UpperLimit >= min)
{
if (entry.UpperLimit == min)
{
minInserted = true;
}
else // (entry.UpperLimit > min)
{
if (prevLimit == min)
{
minInserted = true;
i--;
continue;
}
minInserted = true;
SamplingEntry insertedEntry = SamplingEntry.Divide(ref entry, prevLimit, cumul, m_weightMult, min);
m_entries[i] = entry;
m_entries.Insert(i, insertedEntry);
entry = insertedEntry;
}
}
}
else
{
if (prevLimit < max)
{
if (entry.UpperLimit > max)
{
SamplingEntry insertedEntry = SamplingEntry.Divide(ref entry, prevLimit, cumul, m_weightMult, max);
m_entries[i] = entry;
m_entries.Insert(i, insertedEntry);
entry = insertedEntry;
}
if (entry.UpperLimit <= max)
{
if (entry.Sampler == null)
{
if (m_axis == Base6Directions.Axis.ForwardBackward)
{
entry.Full = true;
entry.CumulativeWeight = cumul;
}
else
{
if (entry.Full == false) // Full entries can be kept as they are
{
Base6Directions.Axis nextAxis = m_axis == Base6Directions.Axis.LeftRight ? Base6Directions.Axis.UpDown : Base6Directions.Axis.ForwardBackward;
double min2, max2;
SelectMinMax(ref originalBox, nextAxis, out min2, out max2);
double range = m_max - m_min;
double volume = m_weightMult * range;
double relativeWidth = (entry.UpperLimit - prevLimit) / range;
double newRange = max2 - min2;
entry.Sampler = new IntervalSampler(min2, max2, (volume * relativeWidth) / newRange, nextAxis);
}
}
}
if (entry.Sampler != null)
{
entry.Sampler.Subtract(ref originalBox, ref bb);
entry.CumulativeWeight = cumul + entry.Sampler.TotalWeight;
}
m_entries[i] = entry;
}
}
else
{
if (entry.Sampler == null)
{
if (entry.Full)
{
entry.CumulativeWeight = cumul;
}
else
{
entry.CumulativeWeight = cumul + (entry.UpperLimit - prevLimit) * m_weightMult;
}
}
else
{
entry.CumulativeWeight = cumul + entry.Sampler.TotalWeight;
}
m_entries[i] = entry;
}
}
prevLimit = entry.UpperLimit;
cumul = entry.CumulativeWeight;
}
m_totalWeight = cumul;
}