Negative numbers are not allowed in the Amount class according to documentation: https://docs.corda.net/api/kotlin/corda/net.corda.core.contracts/-amount/
When a ContractState class has an Amount field that can go negative (for example a balance that can be overpaid) what is the best way to represent negative numbers?
You can't have a negative amount in Corda, because you can't pay a negative balance or hold a negative balance into an account.
however you can issue an obligation (iou), You can take a look at the r3 Corda Sample here: https://github.com/roger3cev/obligation-cordapp
Amount is designed to not allow negative amounts. It is prevented from doing so by the following init block:
init {
// Amount represents a static balance of physical assets as managed by the distributed ledger and is not allowed
// to become negative a rule further maintained by the Contract verify method.
// N.B. If concepts such as an account overdraft are required this should be modelled separately via Obligations,
// or similar second order smart contract concepts.
require(quantity >= 0) { "Negative amounts are not allowed: $quantity" }
}
AmountTransfer is available for modelling negative transfers. Alternatively, you can simply make a copy of the Amount class that excludes this init block.
Related
I want to distribute a fee from every transaction to a mapping(address=>uint) of 3000 addresses, evenly.
Now, that is an issue because the function will run out of gas, so I've heard, that instead of a push method, a pull method should be able to pull it off.
So instead, pool all fees together under one single uint and then let each of every 3k address pull their own share.
Now that brings new issues because the pool uint is forever increasing and decreasing (when people take their share out and new incoming fees from transactions) and how can I control one who may only take their share once but still continuously & evenly distributed?
Some direction here would be greatly appreciated on how to solve those distribution issues because my math is far from the strongest asset I possess.
Solved it by having a mapping to store for every user what was the total incoming deposits last time they claimed their share and deduct that from the current total incoming deposits and give their % cut based on the difference if any.
Psuedo Solidity (excluding proper checks & interactions):
uint256 totalRevShare = onDeposit() pub payable {...+=msg.value}
//..in Withdraw Function
...
uint256 unclaimedScope = totalRevShare - LastTotalRevShare[user];
LastTotalRevShare[user] = totalRevShare;
uint256 _userUnclaimedCut = unclaimedScope / totalReceivers;
...
msg.sender.call{value:_userUnclaimedCut}("");
Hope it helps you to move from push to pull functionality.
Real world business is complex, Could I used both linearable + ownerable state implement complex business?
You could in theory implement both interfaces in one state class. However, I'd argue that it doesn't make sense to do so:
OwnableStates are designed to represent things like cash or oil, where it isn't the individual units owned that matters, but rather the total amount. For example, one might need $200 of cash, but they wouldn't need individual notes with specific serial numbers. This is why the node's vault has functionality to extract X amount of a given OwnableState subclass from the vault
LinearStates are the opposite. They represent cases where one unit of a state isn't necessarily equivalent to another unit of the same state, even if they have the same parameters. For example, suppose property ownership is represented by PropertyStates. One property isn't equivalent to another, and you'd never request one hundred properties or $100,000 of property; the identities of the individual properties matter. Therefore a PropertyState would naturally be a LinearState
I've implemented a sensor scheduling problem using OptaPlanner 6.2 that has 1 hard constraint, 1 medium constraint, and 1 soft constraint. The trouble I'm having is that either I can satisfy some of the hard constraints after 30 seconds of or so, and then the solver makes very little progress satisfying them constraints with additional minutes of termination. I don't think the problem is over constrained; I also don't know how to help the local search process significantly increase the score.
My problem is a scheduling one, where I precalculate all possible times (intervals) that a sensor can observe objects prior to solving. I've modeled the problem as follows:
Hard constraint - no intervals can overlap
when
$s1: A( interval!=null,$id: id, $doy : interval.doy, $interval: interval, $sensor: interval.getSensor())
exists A( id > $id, interval!=null, $interval2: interval, $interval2.getSensor() == $sensor, $interval2.getDoy() == $doy, $interval.getStartSlot() <= $interval2.getEndSlot(), $interval.getEndSlot() >= $interval2.getStartSlot() )
then
scoreHolder.addHardConstraintMatch(kcontext,-10000);
Medium constraint - every assignment should have an Interval
when
A(interval==null)
then
scoreHolder.addMediumConstraintMatch(kcontext,-100);
Soft constraint - maximize a property/value in the Interval class
when
$s1: A( interval!=null)
then
scoreHolder.addSoftConstraintMatch(kcontext,-1 * $s1.getInterval().getSomeProperty())
A: entity planning class; each instance is an assignment for a particular object (i.e has an member objectid that corresponds with one in the Interval class)
Interval: planning variable class, all possible intervals (start time, stop time) for the sensor and objects
In A, I restrict access to B instances (intervals) to just those for the object associated with that assignment. For my test case, there are 40000 or so Intervals, but only dozens for each object. There are about 1100 instances of A (so dozens of possible Intervals for each one).
#PlanningVariable(valueRangeProviderRefs = {"intervalRange"},strengthComparatorClass = IntervalStrengthComparator.class, nullable=true)
public Interval getInterval() {
return interval;
}
#ValueRangeProvider(id = "intervalRange")
public List<Interval> getPossibleIntervalList() {
return task.getAvailableIntervals();
}
In my solution class:
//have tried commenting this out since the overall interval list does not apply to all A
#ValueRangeProvider (id="intervalRangeAll")
public List getIntervalList() {
return intervals;
}
#PlanningEntityCollectionProperty
public List<A> getAList() {
return AList;
}
I've reviewed the documentation and tried a lot of things. My problem is somewhat of a cross between the nurserostering and course scheduling examples, which I have looked at. I am using the FIRST_FIT_DECREASING construction heuristic.
What I have tried:
Turning on and off nullable in the planning variable annotation for A.getInterval()
Late acceptance, Tabu, both.
Benchmarking. I wasn't seeing any problems and average
Adding an IntervalChangeFactory as a moveListFactory. Restricting the custom ChangeMove to whether the interval can be accepted or not (i.e. enforcing or not the hard constraint in the IntervalChangeMove.isDoable).
Here is an example one, where most of the hard constraints are not satisfied, but the medium ones are:
[main] INFO org.optaplanner.core.impl.solver.DefaultSolver - Solving started: time spent (202), best score (0hard/-112500medium/0soft), environment mode (REPRODUCIBLE), random (WELL44497B with seed 987654321).
[main] INFO org.optaplanner.core.impl.constructionheuristic.DefaultConstructionHeuristicPhase - Construction Heuristic phase (0) ended: step total (1125), time spent (2296), best score (-9100000hard/0medium/-72608soft).
[main] INFO org.optaplanner.core.impl.localsearch.DefaultLocalSearchPhase - Local Search phase (1) ended: step total (92507), time spent (30000), best score (-8850000hard/0medium/-74721soft).
[main] INFO org.optaplanner.core.impl.solver.DefaultSolver - Solving ended: time spent (30000), best score (-8850000hard/0medium/-74721soft), average calculate count per second (5643), environment mode (REPRODUCIBLE).
So I don't understand is why the hard constraints can't be deal with by the search process. Any my calculate count per second has dropped to below 10000 due to all the tinkering I've done.
If it's not due to the Score trap (see docs, this is the first thing to fix), it's probably because it gets stuck in a local optima and there are no moves that go from 1 feasible solution to another feasible solution except those that don't really change much. There are several ways to deal with that:
Add course-grained moves (but still leave the fine-grained moves such as ChangeMove in!). You can add generic course grained moves (such as the pillar moves) or add a custom Move. Don't start making smarter selectors that try to only select feasible moves, that's a bad idea (as it will kill your ACC or will limit your search space). Just mix in course grained moves (= diversification) to complement the fine grained moves (= intensification).
A better domain model might help too. The Project Job Scheduling and Cheap Time scheduling examples have a domain model which naturally leads to a smaller search space while still allowing all feasible solutions.
Increase Tabu list size, LA size or use a hard constraint in the SA starting temperature. But I presume you've tried that with the benchmarker.
Turn on TRACE logging to see optaplanner's decision making. Only look at the part after it reaches the local optimum.
In the future, I 'll also add Ruin&Recreate moves, which will be far less code than custom moves or a better domain model (but it will be less efficient).
I'm seeing that the individual slice time information from the Private_0019_1029 field of the DICOM header has negative values and sometime only positive values.
I assumed that these times are with respect to the Volume Acquisition time recorded in the header.
Going by that assumption, it would mean that the Acquisition time varies. But upon checking the difference between successive volume acquisition times, I see that it's equal to TR.
So I'm at a loss about what's happening.
I'm trying to look at the raw fMRI data without slice time correction; hence it's necessary to have the individual slice times.
Does the moco series do time shifting in addition to motion correction? (I don't believe it used to, but your experience may show otherwise).
This indicates how their slice timing is measured. Try the computations with the raw and the moco series and see if the times line up. That may give you your answer.
When dealing with private tag, you should really include the Private Vendor ID, in your case the value of tag (0019,0010).
You may also want to have a look at the output of:
gdcmdump --csa input.dcm
This will dump the SIEMENS CSA header directly from the DICOM attribute.
I am curious about the contraints and tradeoffs for generating unique sequence numbers in a distributed and concurrent environment.
Imagine this: I have a system where all it does is give back an unique sequence number every time you ask it. Here is an ideal spec for such a system (constraints):
Stay up under high-load.
Allow as many concurrent connections as possible.
Distributed: spread load across multiple machines.
Performance: run as fast as possible and have as much throughput as possible.
Correctness: numbers generated must:
not repeat.
be unique per request (must have a way break ties if any two request happens at the exact same time).
in (increasing) sequential order.
have no gaps between requests: 1,2,3,4... (effectively a counter for total # requests)
Fault tolerant: if one or more, or all machines went down, it could resume to the state before failure.
Obviously, this is an idealized spec and not all constraints can be satisfied fully. See CAP Theorem. However, I would love to hear your analysis on various relaxation of the constraints. What type of problems will we left with and what algorithms would we use to solve the remaining problems. For example, if we rid of the counter constraint, then the problem becomes much easier: since gaps are allowed, we can just partition the numeric ranges and map them onto different machines.
Any references (papers, books, code) are welcome. I'd also like to keep a list of existing software (open source or not).
Software:
Snowflake: a network service for generating unique ID numbers at high scale with some simple guarantees.
keyspace: a publicly accessible, unique 128-bit ID generator, whose IDs can be used for any purpose
RFC-4122 implementations exist in many languages. The RFC spec is probably a really good base, as it prevents the need for any inter-system coordination, the UUIDs are 128-bit, and when using IDs from software implementing certain versions of the spec, they include a time code portion that makes sorting possible, etc.
If you must be sequential (per machine) but can drop the gap/counter requirments look for an implementation of the Version 1 UUID as specified in RFC 4122.
If you're working in .NET and can eliminate the sequential and gap/counter requirements, just use System.Guids. They implement RFC 4122 Version 4 and are already unique (very low collision probability) across machines and requests. This could be easily implemented as a web service or just used locally.
Here's a high-level idea for an approach that may fulfill all the requirements, albeit with a significant caveat that may not match many use cases.
If you can tolerate having two sequence numbers - a logical one returned immediately; guaranteed unique and ordered but with gaps - and a separate physical one guaranteed to be in sequential order with no gaps and available a short while later - then the solution seems straightforward:
One distributed system that can serve up a high resolution clock + machine id as the logical sequence number
Stream all the logical sequence numbers into a separate distributed system that orders the logical sequence numbers and maps them to the physical sequence numbers.
The mapping from logical to physical can happen on-demand as soon as the second system is done with processing.