The process how we calculate a total probability from the direct and
node probability is modified to give more importance to the direct
probability.
This is important if we know about a recent failure. We should not try
to send over this channel again if we know we can't. Otherwise this can
lead to infinite retrials over the channel, when the probability is
pinned at high probabilities by the other node results.
Having a capacity available is important for liquidity estimation.
* We add a dummy capacity to hop hints. Hop hints specify neither the
capacity nor a maxHTLC size, which is why we assume the channel to
have a high capacity relative to the amount we send.
* We add a capacity to local edges. These channels should always have a
capacity associated with them, even in the neutrino case (a fallback
to maxHTLC is not necessary). This is just for completeness, as the
probability calculation for local channels is done separately.
Implements a new probability estimator based on a probability theory
framework.
The computed probability consists of:
* the direct channel probability, which is estimated based on a
depleted liquidity distribution model, formulas and broader concept derived
after Pickhardt et al. https://arxiv.org/abs/2103.08576
* an extension of the probability model to incorporate knowledge decay
after time for previous successes and failures
* a mixed node probability taking into account successes/failures on other
channels of the node (similar to the apriori approach)
