pyclustering.gcolor.sync.syncgcolor Class Reference

Oscillatory network based on Kuramoto model with negative and positive connections for graph coloring problem. More...

+ Inheritance diagram for pyclustering.gcolor.sync.syncgcolor:
+ Collaboration diagram for pyclustering.gcolor.sync.syncgcolor:

Public Member Functions

def __init__ (self, graph_matrix, positive_weight, negative_weight, reduction=None)
 Constructor of the oscillatory network syncgcolor for graph coloring problem. More...
 
def process (self, order=0.998, solution=solve_type.FAST, collect_dynamic=False)
 Performs simulation of the network (performs solving of graph coloring problem). More...
 
- Public Member Functions inherited from pyclustering.nnet.sync.sync_network
def __init__ (self, num_osc, weight=1, frequency=0, type_conn=conn_type.ALL_TO_ALL, representation=conn_represent.MATRIX, initial_phases=initial_type.RANDOM_GAUSSIAN, ccore=True)
 Constructor of oscillatory network is based on Kuramoto model. More...
 
def __del__ (self)
 Destructor of oscillatory network is based on Kuramoto model.
 
def sync_order (self)
 Calculates current level of global synchorization (order parameter) in the network. More...
 
def sync_local_order (self)
 Calculates current level of local (partial) synchronization in the network. More...
 
def simulate (self, steps, time, solution=solve_type.FAST, collect_dynamic=True)
 Performs static simulation of Sync oscillatory network. More...
 
def simulate_dynamic (self, order=0.998, solution=solve_type.FAST, collect_dynamic=False, step=0.1, int_step=0.01, threshold_changes=0.0000001)
 Performs dynamic simulation of the network until stop condition is not reached. More...
 
def simulate_static (self, steps, time, solution=solve_type.FAST, collect_dynamic=False)
 Performs static simulation of oscillatory network. More...
 
def get_neighbors (self, index)
 Finds neighbors of the oscillator with specified index. More...
 
def has_connection (self, i, j)
 Returns True if there is connection between i and j oscillators and False - if connection doesn't exist. More...
 
- Public Member Functions inherited from pyclustering.nnet.network
def height (self)
 Height of the network grid (that is defined by amout of oscillators in each column), this value is zero in case of non-grid structure. More...
 
def width (self)
 Width of the network grid, this value is zero in case of non-grid structure. More...
 
def structure (self)
 Type of network structure that is used for connecting oscillators.
 
def __init__ (self, num_osc, type_conn=conn_type.ALL_TO_ALL, conn_repr=conn_represent.MATRIX, height=None, width=None)
 Constructor of the network. More...
 
def __len__ (self)
 Returns size of the network that is defined by amount of oscillators.
 
def has_connection (self, i, j)
 Returns True if there is connection between i and j oscillators and False - if connection doesn't exist. More...
 
def set_connection (self, i, j)
 Couples two specified oscillators in the network with dynamic connections. More...
 
def get_neighbors (self, index)
 Finds neighbors of the oscillator with specified index. More...
 

Detailed Description

Oscillatory network based on Kuramoto model with negative and positive connections for graph coloring problem.

Definition at line 86 of file sync.py.

Constructor & Destructor Documentation

◆ __init__()

def pyclustering.gcolor.sync.syncgcolor.__init__ (   self,
  graph_matrix,
  positive_weight,
  negative_weight,
  reduction = None 
)

Constructor of the oscillatory network syncgcolor for graph coloring problem.

Parameters
[in]graph_matrix(list): Graph represented by matrix.
[in]positive_weight(double): Value of weight of positive connections.
[in]negative_weight(double): Value of weight of negative connections.
[in]reduction(bool): Inverse degree of the processed graph.

Definition at line 92 of file sync.py.

Member Function Documentation

◆ process()

def pyclustering.gcolor.sync.syncgcolor.process (   self,
  order = 0.998,
  solution = solve_type.FAST,
  collect_dynamic = False 
)

Performs simulation of the network (performs solving of graph coloring problem).

Parameters
[in]order(double): Defines when process of synchronization in the network is over, range from 0 to 1.
[in]solution(solve_type): defines type (method) of solving diff. equation.
[in]collect_dynamic(bool): If True - return full dynamic of the network, otherwise - last state of phases.
Returns
(syncnet_analyser) Returns analyser of results of coloring.

Definition at line 154 of file sync.py.


The documentation for this class was generated from the following file: