
public final class spreadingKt

Method Summary

Modifier and Type	Method	Description
`final Unit`	`addRange(Object v)`
`final Unit`	`addRangeHop()`
`final Unit`	`addRangeWithLag(Object v, Object metric, Object speed)`
`final Unit`	`addRangeWithMetric(Object v, Object metric)`
`final <T extends Any> T`	`boundBroadcast(Boolean region, T null, Boolean source, Object value)`	Constrain the spreading of broadcast function only within a region.
`final <T extends Any> T`	`boundG(Boolean region, T null, Boolean source, T initial, Function1<Unit, Number> metric, Function1<T, T> accumulate)`	Constrain the spreading of G function only within a region.
`final Unit`	`boundDistanceTo(Object region, Object source)`
`final Unit`	`broadcast(Object source, Object value)`
`final Unit`	`broadcastWithMetric(Object source, Object value, Object metric)`
`final Boolean`	`channel(Boolean source, Boolean dest, Number thr)`	Dynamically computes distributed routes between regions of a network, and dynamically adapts to shape and changes of the network topology.
`final Boolean`	`channelWithObstacle(Boolean source, Boolean dest, Boolean obstacle, Number thr)`	Dynamically computes distributed routes between regions of a network, and dynamically adapts to shape and changes of the network topology.
`final Boolean`	`channel2(Boolean source, Object destination, Number width)`	Channel pattern.
`final Boolean`	`channel2WithObstacle(Boolean source, Object destination, Boolean obstacle, Number width)`	Channel pattern.
`final Boolean`	`closerThan(Boolean source, Number range)`
`final Boolean`	`closerThanWithMetric(Boolean source, Function1<Unit, Number> metric, Number range)`
`final Number`	`crfGradient(Boolean source, Number maxHop)`	Self-healing gradient algorithm that reconfigures in O(diameter) time.
`final Number`	`crfGradientWithMetric(Boolean source, Function1<Unit, Number> metric, Number maxHop)`	Self-healing gradient algorithm that reconfigures in O(diameter) time.
`final Number`	`bisGradient(Boolean source, Number radius, Number speed)`	Self-healing gradient algorithm with single-path reaction speed.
`final Number`	`bisGradientWithMetric(Boolean source, Function1<Unit, Number> metric, Number radius, Number speed)`	Self-healing gradient algorithm with single-path reaction speed.
`final Boolean`	`dilate(Boolean region, Number width)`	Dilate a spatial region.
`final Boolean`	`dilateWithMetric(Boolean region, Function1<Unit, Number> metric, Number width)`	Dilate a spatial region.
`final Boolean`	`directProjection(Boolean source, Boolean obstacle)`	Forecast obstacles along a path to the source.
`final Boolean`	`directProjectionWithMetric(Boolean source, Boolean obstacle, Function1<Unit, Number> metric)`	Forecast obstacles along a path to the source.
`final Number`	`distanceBetween(Boolean source, Boolean dest)`	Smallest distance between source and destination devices.
`final Number`	`distanceBetweenWithMetric(Boolean source, Boolean dest, Function1<Unit, Number> metric)`	Smallest distance between source and destination devices.
`final Unit`	`distanceTo(Object source)`
`final Unit`	`distanceToWithMetric(Object source, Object metric)`
`final Unit`	`roundTripTime(Number d)`	Estimate worst propagation time considering a message round trip.
`final Unit`	`flex_distorce(Object minD, Object metric)`
`final Unit`	`flex_slope(Object d, Object nbrD, Object minD, Object metric)`
`final Unit`	`flexGradient(Boolean source, Number epsilon, Number rate, Number range, Number distortion)`	Flex-Gradient.
`final Unit`	`flexGradientWithMetric(Boolean source, Number epsilon, Number rate, Number range, Number distortion, Function1<Unit, Number> metric)`	Flex-Gradient.
`final Unit`	`G(Object source, Object initial, Object metric, Object accumulate)`
`final <T extends Any> T`	`Gnull(T v, T default)`	Wrapper for G error.
`final <T extends Any> T`	`gradcast(Boolean source, T local, Number gradient, Function1<T, T> accumulate)`	Gradcast.
`final <T extends Any> <ERROR CLASS>`	`gradient(Boolean source, T init, Function1<Unit, Number> metric, Function1<T, T> accumulate)`	Spread and extend information with distance from the source region.
`final Unit`	`hopBroadcast(Object source, Object value)`
`final Unit`	`hopDistanceTo(Object source)`
`final <U extends Any, I extends Any, D extends Any, T extends Any> <ERROR CLASS>`	`,T,Function1,Function1)>multiG(<ERROR CLASS> sources, ,T,Function1,Function1)>T init, Function1<Unit, Number> metric, Function1<,T,Function1,Function1)>T, ,T,Function1,Function1)>T> accumulate)`	Run an instance of G from every source.
`final <U extends Any, I extends Any, D extends Any, T extends Any> <ERROR CLASS>`	`,T,Function1,Function1)>multiGradient(<ERROR CLASS> sources, ,T,Function1,Function1)>T init, Function1<Unit, Number> metric, Function1<,T,Function1,Function1)>T, ,T,Function1,Function1)>T> accumulate)`	Spread and extend information with distance from multiple source regions.
`final Number`	`neighborhood()`	Count the number of neighbors.
`final Number`	`nbrDelay()`	Time forward view.
`final Number`	`nbrLag()`	Time backward view.
`final Unit`	`nbrRange()`
`final Unit`	`nbrRangeHop()`
`final Unit`	`nbrRangeLag(Object metric, Object lagMetric, Object speed)`
`final Boolean`	`descend(Boolean source, Number potential)`	Shortest path according to a potential.
`final Boolean`	`rendezvous(Boolean source, Boolean dest)`	Shortest path.
`final Boolean`	`shortestPath(Boolean source, Object destination)`	Dynamically computes the shortest route between regions of a network, and dynamically adapts to shape and changes of the network topology.
`final <T extends Any> T`	`vm(Boolean source, Number range, Function1<Unit, T> f, T null)`	Entry point for a computation.
`final <T extends Any> T`	`vmWithMetric(Boolean source, Function1<Unit, Number> metric, Number range, Function1<Unit, T> f, T null)`	Entry point for a computation.
`final <T extends Any> T`	`voronoiPatitioning(Boolean source, T id)`	Computing a Voronoi partition is an operation that is frequently useful in distributed systems.
`final <T extends Any> T`	`voronoiPatitioningWithMetric(Object seed, T id, Function1<Unit, Number> metric)`	Computing a Voronoi partition is an operation that is frequently useful in distributed systems.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Method Detail
  - addRange
```
 final Unit addRange(Object v)
```
  - addRangeHop
```
 final Unit addRangeHop()
```
  - addRangeWithLag
```
 final Unit addRangeWithLag(Object v, Object metric, Object speed)
```
  - addRangeWithMetric
```
 final Unit addRangeWithMetric(Object v, Object metric)
```
  - boundBroadcast
```
 final <T extends Any> T boundBroadcast(Boolean region, T null, Boolean source, Object value)
```
    Constrain the spreading of broadcast function only within a region.
    
    Parameters:
    
    region - whether the function is spreaded or not
    
    null - default value where f is not spreaded
    
    source - whether the current device is a source
  - boundG
```
 final <T extends Any> T boundG(Boolean region, T null, Boolean source, T initial, Function1<Unit, Number> metric, Function1<T, T> accumulate)
```
    Constrain the spreading of G function only within a region.
    
    Parameters:
    
    region - whether the function is spreaded or not
    
    null - default value where f is not spreaded
    
    source - whether the current device is a source
    
    initial - initial value of the computation
    
    metric - estimate distance from other devices
    
    accumulate - how to manage the value
  - boundDistanceTo
```
 final Unit boundDistanceTo(Object region, Object source)
```
  - broadcast
```
 final Unit broadcast(Object source, Object value)
```
  - broadcastWithMetric
```
 final Unit broadcastWithMetric(Object source, Object value, Object metric)
```
  - channel
```
 final Boolean channel(Boolean source, Boolean dest, Number thr)
```
    Dynamically computes distributed routes between regions of a network, and dynamically adapts to shape and changes of the network topology. The channel is a Boolean field that is true for devices near the shortest route from a given (distributed) source to a (distributed) destination.
    
    Parameters:
    
    source - whether the device is a source
    
    dest - whether the device is a destination
    
    thr - threshold for Double comparison (e.g.
  - channelWithObstacle
```
 final Boolean channelWithObstacle(Boolean source, Boolean dest, Boolean obstacle, Number thr)
```
    Dynamically computes distributed routes between regions of a network, and dynamically adapts to shape and changes of the network topology. The channel is a Boolean field that is true for devices near the shortest route from a given (distributed) source to a (distributed) destination.
    
    Parameters:
    
    source - whether the device is a source
    
    dest - whether the device is a destination
    
    obstacle - whether the device is an obstacle
    
    thr - threshold for Double comparison (e.g.
  - channel2
```
 final Boolean channel2(Boolean source, Object destination, Number width)
```
    Channel pattern.
    
    Parameters:
    
    source - whether the device is a source
    
    width - how much to dilate the channel
  - channel2WithObstacle
```
 final Boolean channel2WithObstacle(Boolean source, Object destination, Boolean obstacle, Number width)
```
    Channel pattern.
    
    Parameters:
    
    source - whether the device is a source
    
    obstacle - whether the device is an obstacle
    
    width - how much to dilate the channel
  - closerThan
```
 final Boolean closerThan(Boolean source, Number range)
```
    Parameters:
    
    source - whether the device is a source
    
    range - range
  - closerThanWithMetric
```
 final Boolean closerThanWithMetric(Boolean source, Function1<Unit, Number> metric, Number range)
```
    Parameters:
    
    source - whether the device is a source
    
    metric - how to estimate the distance
    
    range - range
  - crfGradient
```
 final Number crfGradient(Boolean source, Number maxHop)
```
    Self-healing gradient algorithm that reconfigures in O(diameter) time. Requires euclidean metric.
    
    Parameters:
    
    source - whether the device is a source
    
    maxHop - communication max range
  - crfGradientWithMetric
```
 final Number crfGradientWithMetric(Boolean source, Function1<Unit, Number> metric, Number maxHop)
```
    Self-healing gradient algorithm that reconfigures in O(diameter) time. Requires euclidean metric.
    
    Parameters:
    
    source - whether the device is a source
    
    metric - how to estimate distances without lag
    
    maxHop - communication max range
  - bisGradient
```
 final Number bisGradient(Boolean source, Number radius, Number speed)
```
    Self-healing gradient algorithm with single-path reaction speed.
    
    Parameters:
    
    source - whether the device is a source
    
    radius - communication max range
    
    speed - estimate of single-path speed
  - bisGradientWithMetric
```
 final Number bisGradientWithMetric(Boolean source, Function1<Unit, Number> metric, Number radius, Number speed)
```
    Self-healing gradient algorithm with single-path reaction speed.
    
    Parameters:
    
    source - whether the device is a source
    
    metric - how to estimate distances without lag
    
    radius - communication max range
    
    speed - estimate of single-path speed
  - dilate
```
 final Boolean dilate(Boolean region, Number width)
```
    Dilate a spatial region.
    
    Parameters:
    
    region - whether the device is inside the region
    
    width - how much to dilate
  - dilateWithMetric
```
 final Boolean dilateWithMetric(Boolean region, Function1<Unit, Number> metric, Number width)
```
    Dilate a spatial region.
    
    Parameters:
    
    region - whether the device is inside the region
    
    metric - how to estimate the distance between devices
    
    width - how much to dilate
  - directProjection
```
 final Boolean directProjection(Boolean source, Boolean obstacle)
```
    Forecast obstacles along a path to the source.
    
    Parameters:
    
    source - whether the device is a source
    
    obstacle - whether the device is an obstacle
  - directProjectionWithMetric
```
 final Boolean directProjectionWithMetric(Boolean source, Boolean obstacle, Function1<Unit, Number> metric)
```
    Forecast obstacles along a path to the source.
    
    Parameters:
    
    source - whether the device is a source
    
    obstacle - whether the device is an obstacle
    
    metric - how to estimate neighbors distances
  - distanceBetween
```
 final Number distanceBetween(Boolean source, Boolean dest)
```
    Smallest distance between source and destination devices.
    
    Parameters:
    
    source - whether the current device is a source
    
    dest - whether the current device is a destination
  - distanceBetweenWithMetric
```
 final Number distanceBetweenWithMetric(Boolean source, Boolean dest, Function1<Unit, Number> metric)
```
    Smallest distance between source and destination devices.
    
    Parameters:
    
    source - whether the current device is a source
    
    dest - whether the current device is a destination
    
    metric - estimate distance from other devices
  - distanceTo
```
 final Unit distanceTo(Object source)
```
  - distanceToWithMetric
```
 final Unit distanceToWithMetric(Object source, Object metric)
```
  - roundTripTime
```
 final Unit roundTripTime(Number d)
```
    Estimate worst propagation time considering a message round trip.
    
    Parameters:
    
    d - network diameter
  - flex_distorce
```
 final Unit flex_distorce(Object minD, Object metric)
```
  - flex_slope
```
 final Unit flex_slope(Object d, Object nbrD, Object minD, Object metric)
```
  - flexGradient
```
 final Unit flexGradient(Boolean source, Number epsilon, Number rate, Number range, Number distortion)
```
    Flex-Gradient.
    
    Parameters:
    
    source - whether the device is a source
    
    epsilon - tolerance
    
    rate - communication rate
    
    range - communication range
    
    distortion - distortion
  - flexGradientWithMetric
```
 final Unit flexGradientWithMetric(Boolean source, Number epsilon, Number rate, Number range, Number distortion, Function1<Unit, Number> metric)
```
    Flex-Gradient.
    
    Parameters:
    
    source - whether the device is a source
    
    epsilon - tolerance
    
    rate - communication rate
    
    range - communication range
    
    distortion - distortion
    
    metric - estimate distance from other devices
  - G
```
 final Unit G(Object source, Object initial, Object metric, Object accumulate)
```
  - Gnull
```
 final <T extends Any> T Gnull(T v, T default)
```
    Wrapper for G error. For example: G(aBool, aBool, aMetric, (v) -> { Gnull(v, false) ... } assure that G is not broken in case minHood(..., ...) returns Infinity.
    
    Parameters:
    
    v - value to be checked
    
    default - default value to avoid to broke G
  - gradcast
```
 final <T extends Any> T gradcast(Boolean source, T local, Number gradient, Function1<T, T> accumulate)
```
    Gradcast.
    
    Parameters:
    
    source - whether the device is a source
    
    local - local value
    
    gradient - gradient to follow
    
    accumulate - how to accumulate local values
  - gradient
```
 final <T extends Any> <ERROR CLASS> gradient(Boolean source, T init, Function1<Unit, Number> metric, Function1<T, T> accumulate)
```
    Spread and extend information with distance from the source region.
    
    Parameters:
    
    source - whether the current device is a source
    
    init - initial value of the computation
    
    metric - estimate distance from other devices
    
    accumulate - how to accumulate the value
  - hopBroadcast
```
 final Unit hopBroadcast(Object source, Object value)
```
  - hopDistanceTo
```
 final Unit hopDistanceTo(Object source)
```
  - multiG
```
 final <U extends Any, I extends Any, D extends Any, T extends Any> <ERROR CLASS> ,T,Function1,Function1)>multiG(<ERROR CLASS> sources, ,T,Function1,Function1)>T init, Function1<Unit, Number> metric, Function1<,T,Function1,Function1)>T, ,T,Function1,Function1)>T> accumulate)
```
    Run an instance of G from every source.
    
    Parameters:
    
    sources - list of active sources
    
    init - initial value of the computation
    
    metric - estimate distance from other devices
    
    accumulate - how to accumulate the value
  - multiGradient
```
 final <U extends Any, I extends Any, D extends Any, T extends Any> <ERROR CLASS> ,T,Function1,Function1)>multiGradient(<ERROR CLASS> sources, ,T,Function1,Function1)>T init, Function1<Unit, Number> metric, Function1<,T,Function1,Function1)>T, ,T,Function1,Function1)>T> accumulate)
```
    Spread and extend information with distance from multiple source regions.
    
    Parameters:
    
    sources - list of active sources
    
    init - initial value of the computation
    
    metric - estimate distance from other devices
    
    accumulate - how to accumulate the value
  - neighborhood
```
 final Number neighborhood()
```
    Count the number of neighbors.
  - nbrDelay
```
 final Number nbrDelay()
```
    Time forward view.
  - nbrLag
```
 final Number nbrLag()
```
    Time backward view.
  - nbrRange
```
 final Unit nbrRange()
```
  - nbrRangeHop
```
 final Unit nbrRangeHop()
```
  - nbrRangeLag
```
 final Unit nbrRangeLag(Object metric, Object lagMetric, Object speed)
```
  - descend
```
 final Boolean descend(Boolean source, Number potential)
```
    Shortest path according to a potential.
    
    Parameters:
    
    source - whether the device is a source
    
    potential - potential
  - rendezvous
```
 final Boolean rendezvous(Boolean source, Boolean dest)
```
    Shortest path.
    
    Parameters:
    
    source - whether the device is the source
    
    dest - whether the device is the destination
  - shortestPath
```
 final Boolean shortestPath(Boolean source, Object destination)
```
    Dynamically computes the shortest route between regions of a network, and dynamically adapts to shape and changes of the network topology. The shortest path is a Boolean field that is true for devices near the shortest route from a given (distributed) source to a (distributed) destination.
    
    Parameters:
    
    source - whether the device is the source
  - vm
```
 final <T extends Any> T vm(Boolean source, Number range, Function1<Unit, T> f, T null)
```
    Entry point for a computation.
    
    Parameters:
    
    source - whether the device is a source
    
    range - spreading constraint
    
    f - entry point
    
    null - default value
  - vmWithMetric
```
 final <T extends Any> T vmWithMetric(Boolean source, Function1<Unit, Number> metric, Number range, Function1<Unit, T> f, T null)
```
    Entry point for a computation.
    
    Parameters:
    
    source - whether the device is a source
    
    metric - how to estimate neighbors distances
    
    range - spreading constraint
    
    f - entry point
    
    null - default value
  - voronoiPatitioning
```
 final <T extends Any> T voronoiPatitioning(Boolean source, T id)
```
    Computing a Voronoi partition is an operation that is frequently useful in distributed systems. Given an initial set of seed devices, a Voronoi partition assigns each device to the partition of the nearest seed, effectively breaking the network up into zones of influence around key elements.
    
    Parameters:
    
    source - whether the device is a seed
    
    id - partition id
  - voronoiPatitioningWithMetric
```
 final <T extends Any> T voronoiPatitioningWithMetric(Object seed, T id, Function1<Unit, Number> metric)
```
    Computing a Voronoi partition is an operation that is frequently useful in distributed systems. Given an initial set of seed devices, a Voronoi partition assigns each device to the partition of the nearest seed, effectively breaking the network up into zones of influence around key elements.
    
    Parameters:
    
    id - partition id
    
    metric - how to estimate the distances of the neighbors

Class spreadingKt

Method Summary

Methods inherited from class java.lang.Object

Method Detail

addRange

addRangeHop

addRangeWithLag

addRangeWithMetric

boundBroadcast

boundG

boundDistanceTo

broadcast

broadcastWithMetric

channel

channelWithObstacle

channel2

channel2WithObstacle

closerThan

closerThanWithMetric

crfGradient

crfGradientWithMetric

bisGradient

bisGradientWithMetric

dilate

dilateWithMetric

directProjection

directProjectionWithMetric

distanceBetween

distanceBetweenWithMetric

distanceTo

distanceToWithMetric

roundTripTime

flex_distorce

flex_slope

flexGradient

flexGradientWithMetric

G

Gnull

gradcast

gradient

hopBroadcast

hopDistanceTo

multiG

multiGradient

neighborhood

nbrDelay

nbrLag

nbrRange

nbrRangeHop

nbrRangeLag

descend

rendezvous

shortestPath

vm

vmWithMetric

voronoiPatitioning

voronoiPatitioningWithMetric