/**
- * [`Score`] implementation using channel success probability distributions.
+ * [`ScoreLookUp`] implementation using channel success probability distributions.
*
* Channels are tracked with upper and lower liquidity bounds - when an HTLC fails at a channel,
* we learn that the upper-bound on the available liquidity is lower than the amount of the HTLC.
* These bounds are then used to determine a success probability using the formula from
* Optimally Reliable & Cheap Payment Flows on the Lightning Network* by Rene Pickhardt
* and Stefan Richter [[1]] (i.e. `(upper_bound - payment_amount) / (upper_bound - lower_bound)`).
- *
+ * 6762, 1070
* This probability is combined with the [`liquidity_penalty_multiplier_msat`] and
* [`liquidity_penalty_amount_multiplier_msat`] parameters to calculate a concrete penalty in
* milli-satoshis. The penalties, when added across all hops, have the property of being linear in
* Query the historical estimated minimum and maximum liquidity available for sending a
* payment over the channel with `scid` towards the given `target` node.
*
- * Returns two sets of 8 buckets. The first set describes the octiles for lower-bound
- * liquidity estimates, the second set describes the octiles for upper-bound liquidity
- * estimates. Each bucket describes the relative frequency at which we've seen a liquidity
- * bound in the octile relative to the channel's total capacity, on an arbitrary scale.
- * Because the values are slowly decayed, more recent data points are weighted more heavily
- * than older datapoints.
+ * Returns two sets of 32 buckets. The first set describes the lower-bound liquidity history,
+ * the second set describes the upper-bound liquidity history. Each bucket describes the
+ * relative frequency at which we've seen a liquidity bound in the bucket's range relative to
+ * the channel's total capacity, on an arbitrary scale. Because the values are slowly decayed,
+ * more recent data points are weighted more heavily than older datapoints.
+ *
+ * Note that the range of each bucket varies by its location to provide more granular results
+ * at the edges of a channel's capacity, where it is more likely to sit.
*
- * When scoring, the estimated probability that an upper-/lower-bound lies in a given octile
- * relative to the channel's total capacity is calculated by dividing that bucket's value with
- * the total of all buckets for the given bound.
+ * When scoring, the estimated probability that an upper-/lower-bound lies in a given bucket
+ * is calculated by dividing that bucket's value with the total value of all buckets.
*
- * For example, a value of `[0, 0, 0, 0, 0, 0, 32]` indicates that we believe the probability
- * of a bound being in the top octile to be 100%, and have never (recently) seen it in any
- * other octiles. A value of `[31, 0, 0, 0, 0, 0, 0, 32]` indicates we've seen the bound being
- * both in the top and bottom octile, and roughly with similar (recent) frequency.
+ * For example, using a lower bucket count for illustrative purposes, a value of
+ * `[0, 0, 0, ..., 0, 32]` indicates that we believe the probability of a bound being very
+ * close to the channel's capacity to be 100%, and have never (recently) seen it in any other
+ * bucket. A value of `[31, 0, 0, ..., 0, 0, 32]` indicates we've seen the bound being both
+ * in the top and bottom bucket, and roughly with similar (recent) frequency.
*
* Because the datapoints are decayed slowly over time, values will eventually return to
- * `Some(([0; 8], [0; 8]))`.
+ * `Some(([1; 32], [1; 32]))` and then to `None` once no datapoints remain.
+ *
+ * In order to fetch a single success probability from the buckets provided here, as used in
+ * the scoring model, see [`Self::historical_estimated_payment_success_probability`].
*/
- public Option_C2Tuple_EightU16sEightU16sZZ historical_estimated_channel_liquidity_probabilities(long scid, org.ldk.structs.NodeId target) {
+ public Option_C2Tuple_ThirtyTwoU16sThirtyTwoU16sZZ historical_estimated_channel_liquidity_probabilities(long scid, org.ldk.structs.NodeId target) {
long ret = bindings.ProbabilisticScorer_historical_estimated_channel_liquidity_probabilities(this.ptr, scid, target == null ? 0 : target.ptr);
GC.KeepAlive(this);
GC.KeepAlive(scid);
GC.KeepAlive(target);
if (ret >= 0 && ret <= 4096) { return null; }
- org.ldk.structs.Option_C2Tuple_EightU16sEightU16sZZ ret_hu_conv = org.ldk.structs.Option_C2Tuple_EightU16sEightU16sZZ.constr_from_ptr(ret);
+ org.ldk.structs.Option_C2Tuple_ThirtyTwoU16sThirtyTwoU16sZZ ret_hu_conv = org.ldk.structs.Option_C2Tuple_ThirtyTwoU16sThirtyTwoU16sZZ.constr_from_ptr(ret);
+ if (ret_hu_conv != null) { ret_hu_conv.ptrs_to.AddLast(this); };
+ if (this != null) { this.ptrs_to.AddLast(target); };
+ return ret_hu_conv;
+ }
+
+ /**
+ * Query the probability of payment success sending the given `amount_msat` over the channel
+ * with `scid` towards the given `target` node, based on the historical estimated liquidity
+ * bounds.
+ *
+ * These are the same bounds as returned by
+ * [`Self::historical_estimated_channel_liquidity_probabilities`] (but not those returned by
+ * [`Self::estimated_channel_liquidity_range`]).
+ */
+ public Option_f64Z historical_estimated_payment_success_probability(long scid, org.ldk.structs.NodeId target, long amount_msat, org.ldk.structs.ProbabilisticScoringFeeParameters _params) {
+ long ret = bindings.ProbabilisticScorer_historical_estimated_payment_success_probability(this.ptr, scid, target == null ? 0 : target.ptr, amount_msat, _params == null ? 0 : _params.ptr);
+ GC.KeepAlive(this);
+ GC.KeepAlive(scid);
+ GC.KeepAlive(target);
+ GC.KeepAlive(amount_msat);
+ GC.KeepAlive(_params);
+ if (ret >= 0 && ret <= 4096) { return null; }
+ org.ldk.structs.Option_f64Z ret_hu_conv = org.ldk.structs.Option_f64Z.constr_from_ptr(ret);
if (ret_hu_conv != null) { ret_hu_conv.ptrs_to.AddLast(this); };
if (this != null) { this.ptrs_to.AddLast(target); };
+ if (this != null) { this.ptrs_to.AddLast(_params); };
+ return ret_hu_conv;
+ }
+
+ /**
+ * Constructs a new ScoreLookUp which calls the relevant methods on this_arg.
+ * This copies the `inner` pointer in this_arg and thus the returned ScoreLookUp must be freed before this_arg is
+ */
+ public ScoreLookUp as_ScoreLookUp() {
+ long ret = bindings.ProbabilisticScorer_as_ScoreLookUp(this.ptr);
+ GC.KeepAlive(this);
+ if (ret >= 0 && ret <= 4096) { return null; }
+ ScoreLookUp ret_hu_conv = new ScoreLookUp(null, ret);
+ if (ret_hu_conv != null) { ret_hu_conv.ptrs_to.AddLast(this); };
+ return ret_hu_conv;
+ }
+
+ /**
+ * Constructs a new ScoreUpdate which calls the relevant methods on this_arg.
+ * This copies the `inner` pointer in this_arg and thus the returned ScoreUpdate must be freed before this_arg is
+ */
+ public ScoreUpdate as_ScoreUpdate() {
+ long ret = bindings.ProbabilisticScorer_as_ScoreUpdate(this.ptr);
+ GC.KeepAlive(this);
+ if (ret >= 0 && ret <= 4096) { return null; }
+ ScoreUpdate ret_hu_conv = new ScoreUpdate(null, ret);
+ if (ret_hu_conv != null) { ret_hu_conv.ptrs_to.AddLast(this); };
return ret_hu_conv;
}
* Serialize the ProbabilisticScorer object into a byte array which can be read by ProbabilisticScorer_read
*/
public byte[] write() {
- byte[] ret = bindings.ProbabilisticScorer_write(this.ptr);
+ long ret = bindings.ProbabilisticScorer_write(this.ptr);
GC.KeepAlive(this);
- return ret;
+ if (ret >= 0 && ret <= 4096) { return null; }
+ byte[] ret_conv = InternalUtils.decodeUint8Array(ret);
+ return ret_conv;
}
/**
* Read a ProbabilisticScorer from a byte array, created by ProbabilisticScorer_write
*/
public static Result_ProbabilisticScorerDecodeErrorZ read(byte[] ser, org.ldk.structs.ProbabilisticScoringDecayParameters arg_a, org.ldk.structs.NetworkGraph arg_b, org.ldk.structs.Logger arg_c) {
- long ret = bindings.ProbabilisticScorer_read(ser, arg_a == null ? 0 : arg_a.ptr, arg_b == null ? 0 : arg_b.ptr, arg_c.ptr);
+ long ret = bindings.ProbabilisticScorer_read(InternalUtils.encodeUint8Array(ser), arg_a == null ? 0 : arg_a.ptr, arg_b == null ? 0 : arg_b.ptr, arg_c.ptr);
GC.KeepAlive(ser);
GC.KeepAlive(arg_a);
GC.KeepAlive(arg_b);