phyelds.libraries¶

`phyelds.libraries.device` ¶

Device library: Set of function used to get the device information.

`local_id()` ¶

Get the local id of the device.

Returns:

Type	Description
`int`

`sense(sensor)` ¶

Get the value of the sensor.

Parameters:

Name	Type	Description	Default
`sensor`	`str`	The name of the sensor.	required

Returns:

Type	Description
`Any`	The value of the sensor.

`local_position()` ¶

Get the position of the device.

Returns:

Type	Description
`Tuple[float, float]`	The position of the device.

`store(output, value)` ¶

Store the value in the context.

Parameters:

Name	Type	Description	Default
`output`	`str`	The name of the stored value.	required
`value`	`Any`	The value to be stored.	required

Returns:

Type	Description
`None`

`phyelds.libraries.distances` ¶

This module contains functions to calculate distances between nodes in the neighborhood. These functions may be used by other library to compute system-wise properties

`neighbors_distances()` ¶

Get the distances to the neighbors from the current node.

Returns:

Type	Description
`NeighborhoodField[float]`	the neighborhood representing the distances to the neighbors

`hops_distance()` ¶

Get the hops distance to the neighbors from the current node.

Returns:

Type	Description
`NeighborhoodField[int]`	the neighborhood representing the hops distance to the neighbors

`phyelds.libraries.spreading` ¶

Diffusion (information) library for phyelds This library provides functions for diffusion of information in a network. It includes functions for calculating distances and to braodcast information

`distance_to(source, distances)` ¶

Calculate the distance to a source node in the network.

Parameters:

Name	Type	Description	Default
`source`	`bool`		required
`distances`	`NeighborhoodField[float]`		required

Returns:

Type	Description
`StateT[float]`

`cast_from(source, data, accumulation, distances)` ¶

Cast information from a source node to its neighbors.

Parameters:

Name	Type	Description	Default
`source`	`bool`	the source node to cast from	required
`data`	`T`	the data to cast	required
`accumulation`	`Callable[[T], T]`	the function to accumulate the data	required
`distances`	`NeighborhoodField[float]`	the distances against the neighbors	required

Returns:

Type	Description
`StateT[T]`	the data cast

`broadcast(source, data, distances)` ¶

Broadcast information to the network from a source node.

Parameters:

Name	Type	Description	Default
`source`	`bool`	the source node to broadcast from	required
`data`	`T`	the data to spread	required
`distances`	`NeighborhoodField[float]`	the distances again the neighbors	required

Returns:

Type	Description
`StateT[T]`	the data spread

`phyelds.libraries.collect` ¶

Collect library functions that are used to collect information from the network to source nodes.

`find_parent(potential)` ¶

Find the parent of a path giving a potential neighborhood.

Parameters:

Name	Type	Description	Default
`potential`	`StateT[float]`	The potential value (distance/gradient) at the current node.	required

Returns:

Type	Description
`Optional[int]`	The node ID of the parent (neighbor with min potential), or None if local is min.

`collect_with(potential, local, accumulation)` ¶

Generic collection function that accumulates data from children to parents based on a potential neighborhood.

Parameters:

Name	Type	Description	Default
`potential`	`StateT[float]`	The potential neighborhood used to determine parent-child relationships.	required
`local`	`T`	The local value to start with (and add to).	required
`accumulation`	`Callable[[T, T], T]`	A function to combine two values (e.g., sum, max, union).	required

Returns:

Type	Description
`StateT[T]`	The accumulated state.

`count_nodes(potential)` ¶

Count the number of nodes in the sub-tree defined by the potential neighborhood.

Parameters:

Name	Type	Description	Default
`potential`	`StateT[float]`	The potential field.	required

Returns:

Type	Description
`StateT[int]`	The count of nodes.

`sum_values(potential, local)` ¶

Sum numeric values up the potential gradient.

Parameters:

Name	Type	Description	Default
`potential`	`StateT[float]`	The potential field.	required
`local`	`Union[int, float]`	The local numeric value.	required

Returns:

Type	Description
`StateT[Union[int, float]]`	The sum of values.

`collect_or(potential, local)` ¶

Perform a logical OR collection up the potential gradient. Useful for determining if any node in a subtree satisfies a condition.

Parameters:

Name	Type	Description	Default
`potential`	`float`	The potential field.	required
`local`	`bool`	The local boolean condition.	required

Returns:

Type	Description
`StateT[bool]`	True if any node in the subtree is True.

`phyelds.libraries.gossip` ¶

Gossip Library. Set of operation in order to gossip information between nodes in the network.

`gossip_max(value)` ¶

Gossip the maximum value among the all system

Parameters:

Name	Type	Description	Default
`value`	`float`	The value to gossip.	required

Returns:

Type	Description
`StateT[float]`	The maximum value among the all system.

`gossip_min(value)` ¶

Gossip the minimum value among the all system

Parameters:

Name	Type	Description	Default
`value`	`float`	The value to gossip.	required

Returns:

Type	Description
`StateT[float]`	The minimum value among the all system.

`gossip(value, callback)` ¶

Gossip a value in the network using a callable function to choice the value to gossip.

Parameters:

Name	Type	Description	Default
`value`	`T`	The value to gossip.	required
`callback`	`Callable[..., T]`	The callback function to apply on the value.	required

Returns:

Type	Description
`StateT[T]`	The gossiped value.

`stabilizing_gossip(value, max_diameter, callback)` ¶

Gossip a value in the network using a callable function to choice the value to gossip. This function will stabilize the gossip value by applying the callback function until no changes are made.

Parameters:

Name	Type	Description	Default
`value`	`T`	The value to gossip.	required
`max_diameter`	`int`	The maximum diameter to consider for gossiping.	required
`callback`	`Callable[..., T]`	The callback function to apply on the value.	required

Returns:

Type	Description
`StateT[T]`	The stabilized gossiped value.

`phyelds.libraries.leader_election` ¶

Leader election functionality (self-stabilizing) using UUIDs.

`elect_leaders(area, distances)` ¶

Elect a leader in the network using a random UUID.

Parameters:

Name	Type	Description	Default
`area`	`float`	the area of the network	required
`distances`	`NeighborhoodField[float]`	the distances to the neighbors	required

Returns:

Type	Description
`bool`	the current id of the leader

`random_uuid()` ¶

Generate a random UUID for the node.

Returns:

Type	Description
`Tuple[StateT[float], int]`	the random UUID

`breaking_using_uids(uid, area, distances)` ¶

Break the symmetry using the UUID of the node.

Parameters:

Name	Type	Description	Default
`uid`	`Tuple[StateT[float], int]`	the UUID of the node	required
`area`	`float`	the area of the network	required
`distances`	`NeighborhoodField[float]`	the distances to the neighbors	required

Returns:

Type	Description
`StateT[tuple[float, int]]`	the current id of the leader

`distance_competition(current_distance, area, uid, lead, distances)` ¶

Compare the distance of the current node with the distance of the neighbors. It leverages the fact that the tuple is a symmetric breaker.

Parameters:

Name	Type	Description	Default
`current_distance`	`float`	current distance to the lead	required
`area`	`float`	the maximum distance to the lead	required
`uid`	`Tuple[StateT[float], int]`	the local id of the node	required
`lead`	`StateT[Tuple[float, int]]`	the current lead	required
`distances`	`NeighborhoodField[float]`	the distances to the neighbors	required

Returns:

Type	Description
`StateT[Tuple[float, int]]`	the new lead

`phyelds.libraries.time` ¶

A group of functions based on the notion of time.

`local_time()` ¶

Get the local time of the node.

Returns:

Type	Description
`float`	the local time of the node.

`counter()` ¶

Simple counter function that counts the number of times it is called.

Returns:

Type	Description
`StateT[int]`	a counter that counts the number of times it is called.

`decay(value, rate)` ¶

Apply a decay function to a value

Parameters:

Name	Type	Description	Default
`value`	`float \| int`	the initial value	required
`rate`	`float \| int`	the decay rate	required

Returns:

Type	Description
`StateT[float \| int]`	the decayed value

`phyelds.libraries.utils` ¶

This module contains utility functions and classes for various purposes.

`min_with_default(iterable, default=None)` ¶

Returns the minimum value from an iterable, or a default value if the iterable is empty.

Parameters:

Name	Type	Description	Default
`iterable`	`Any`	a list of values (or any iterable)	required
`default`	`Any`	the default value to return if the iterable is empty	`None`

Returns:

Type	Description
`Any`	the minimum value from the iterable or the default value

phyelds.libraries¶

phyelds.libraries.device ¶

local_id() ¶

sense(sensor) ¶

local_position() ¶

store(output, value) ¶

phyelds.libraries.distances ¶

neighbors_distances() ¶

hops_distance() ¶

phyelds.libraries.spreading ¶

distance_to(source, distances) ¶

cast_from(source, data, accumulation, distances) ¶

broadcast(source, data, distances) ¶

phyelds.libraries.collect ¶

find_parent(potential) ¶

collect_with(potential, local, accumulation) ¶

count_nodes(potential) ¶

sum_values(potential, local) ¶

collect_or(potential, local) ¶

phyelds.libraries.gossip ¶

gossip_max(value) ¶

gossip_min(value) ¶

gossip(value, callback) ¶

stabilizing_gossip(value, max_diameter, callback) ¶

phyelds.libraries.leader_election ¶

elect_leaders(area, distances) ¶

random_uuid() ¶

breaking_using_uids(uid, area, distances) ¶

distance_competition(current_distance, area, uid, lead, distances) ¶

phyelds.libraries.time ¶

local_time() ¶

counter() ¶

decay(value, rate) ¶

phyelds.libraries.utils ¶

min_with_default(iterable, default=None) ¶

`phyelds.libraries.device` ¶

`local_id()` ¶

`sense(sensor)` ¶

`local_position()` ¶

`store(output, value)` ¶

`phyelds.libraries.distances` ¶

`neighbors_distances()` ¶

`hops_distance()` ¶

`phyelds.libraries.spreading` ¶

`distance_to(source, distances)` ¶

`cast_from(source, data, accumulation, distances)` ¶

`broadcast(source, data, distances)` ¶

`phyelds.libraries.collect` ¶

`find_parent(potential)` ¶

`collect_with(potential, local, accumulation)` ¶

`count_nodes(potential)` ¶

`sum_values(potential, local)` ¶

`collect_or(potential, local)` ¶

`phyelds.libraries.gossip` ¶

`gossip_max(value)` ¶

`gossip_min(value)` ¶

`gossip(value, callback)` ¶

`stabilizing_gossip(value, max_diameter, callback)` ¶

`phyelds.libraries.leader_election` ¶

`elect_leaders(area, distances)` ¶

`random_uuid()` ¶

`breaking_using_uids(uid, area, distances)` ¶

`distance_competition(current_distance, area, uid, lead, distances)` ¶

`phyelds.libraries.time` ¶

`local_time()` ¶

`counter()` ¶

`decay(value, rate)` ¶

`phyelds.libraries.utils` ¶

`min_with_default(iterable, default=None)` ¶