Model of oscillatory network that is based on the Kuramoto model of synchronization. More...
Public Member Functions | |
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... | |
Model of oscillatory network that is based on the Kuramoto model of synchronization.
CCORE option can be used to use the pyclustering core - C/C++ shared library for processing that significantly increases performance.
def pyclustering.nnet.sync.sync_network.__init__ | ( | self, | |
num_osc, | |||
weight = 1 , |
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frequency = 0 , |
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type_conn = conn_type.ALL_TO_ALL , |
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representation = conn_represent.MATRIX , |
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initial_phases = initial_type.RANDOM_GAUSSIAN , |
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ccore = True |
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) |
Constructor of oscillatory network is based on Kuramoto model.
[in] | num_osc | (uint): Number of oscillators in the network. |
[in] | weight | (double): Coupling strength of the links between oscillators. |
[in] | frequency | (double): Multiplier of internal frequency of the oscillators. |
[in] | type_conn | (conn_type): Type of connection between oscillators in the network (all-to-all, grid, bidirectional list, etc.). |
[in] | representation | (conn_represent): Internal representation of connection in the network: matrix or list. |
[in] | initial_phases | (initial_type): Type of initialization of initial phases of oscillators (random, uniformly distributed, etc.). |
[in] | ccore | (bool): If True simulation is performed by CCORE library (C++ implementation of pyclustering). |
def pyclustering.nnet.sync.sync_network.get_neighbors | ( | self, | |
index | |||
) |
def pyclustering.nnet.sync.sync_network.has_connection | ( | self, | |
i, | |||
j | |||
) |
def pyclustering.nnet.sync.sync_network.simulate | ( | self, | |
steps, | |||
time, | |||
solution = solve_type.FAST , |
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collect_dynamic = True |
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) |
Performs static simulation of Sync oscillatory network.
[in] | steps | (uint): Number steps of simulations during simulation. |
[in] | time | (double): Time of simulation. |
[in] | solution | (solve_type): Type of solution (solving). |
[in] | collect_dynamic | (bool): If True - returns whole dynamic of oscillatory network, otherwise returns only last values of dynamics. |
def pyclustering.nnet.sync.sync_network.simulate_dynamic | ( | self, | |
order = 0.998 , |
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solution = solve_type.FAST , |
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collect_dynamic = False , |
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step = 0.1 , |
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int_step = 0.01 , |
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threshold_changes = 0.0000001 |
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) |
Performs dynamic simulation of the network until stop condition is not reached.
Stop condition is defined by input argument 'order'.
[in] | order | (double): Order of process synchronization, distributed 0..1. |
[in] | solution | (solve_type): Type of solution. |
[in] | collect_dynamic | (bool): If True - returns whole dynamic of oscillatory network, otherwise returns only last values of dynamics. |
[in] | step | (double): Time step of one iteration of simulation. |
[in] | int_step | (double): Integration step, should be less than step. |
[in] | threshold_changes | (double): Additional stop condition that helps prevent infinite simulation, defines limit of changes of oscillators between current and previous steps. |
Definition at line 871 of file sync.py.
Referenced by pyclustering.cluster.hsyncnet.hsyncnet.process(), pyclustering.gcolor.sync.syncgcolor.process(), and pyclustering.cluster.syncnet.syncnet.process().
def pyclustering.nnet.sync.sync_network.simulate_static | ( | self, | |
steps, | |||
time, | |||
solution = solve_type.FAST , |
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collect_dynamic = False |
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) |
Performs static simulation of oscillatory network.
[in] | steps | (uint): Number steps of simulations during simulation. |
[in] | time | (double): Time of simulation. |
[in] | solution | (solve_type): Type of solution. |
[in] | collect_dynamic | (bool): If True - returns whole dynamic of oscillatory network, otherwise returns only last values of dynamics. |
Definition at line 938 of file sync.py.
Referenced by pyclustering.nnet.syncpr.syncpr.simulate(), and pyclustering.nnet.sync.sync_network.simulate().
def pyclustering.nnet.sync.sync_network.sync_local_order | ( | self | ) |
Calculates current level of local (partial) synchronization in the network.
Definition at line 814 of file sync.py.
Referenced by pyclustering.nnet.sync.sync_network.simulate_dynamic().
def pyclustering.nnet.sync.sync_network.sync_order | ( | self | ) |
Calculates current level of global synchorization (order parameter) in the network.
This parameter is tend 1.0 when the oscillatory network close to global synchronization and it tend to 0.0 when desynchronization is observed in the network. Order parameter is calculated using following equation:
where is a average phase coordinate in the network, is an amount of oscillators in the network.
Example: