Hysteresis oscillatory network that uses relaxation oscillators that are represented by objective hysteresis neurons whose output in range [-1, +1]. More...
Public Member Functions | |
def | outputs (self) |
Returns current outputs of neurons. More... | |
def | outputs (self, values) |
Sets outputs of neurons. | |
def | states (self) |
Return current states of neurons. More... | |
def | states (self, values) |
Set current states of neurons. | |
def | __init__ (self, num_osc, own_weight=-4, neigh_weight=-1, type_conn=conn_type.ALL_TO_ALL, type_conn_represent=conn_represent.MATRIX) |
Constructor of hysteresis oscillatory network. More... | |
def | simulate (self, steps, time, solution=solve_type.RK4, collect_dynamic=True) |
Performs static simulation of hysteresis oscillatory network. More... | |
def | simulate_static (self, steps, time, solution=solve_type.RK4, collect_dynamic=False) |
Performs static simulation of hysteresis oscillatory network. 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... | |
Hysteresis oscillatory network that uses relaxation oscillators that are represented by objective hysteresis neurons whose output in range [-1, +1].
Examples:
Definition at line 152 of file hysteresis.py.
def pyclustering.nnet.hysteresis.hysteresis_network.__init__ | ( | self, | |
num_osc, | |||
own_weight = -4 , |
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neigh_weight = -1 , |
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type_conn = conn_type.ALL_TO_ALL , |
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type_conn_represent = conn_represent.MATRIX |
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) |
Constructor of hysteresis oscillatory network.
[in] | num_osc | (uint): Number of oscillators in the network. |
[in] | own_weight | (double): Weight of connection from oscillator to itself - own weight. |
[in] | neigh_weight | (double): Weight of connection between oscillators. |
[in] | type_conn | (conn_type): Type of connection between oscillators in the network. |
[in] | type_conn_represent | (conn_represent): Internal representation of connection in the network: matrix or list. |
Definition at line 222 of file hysteresis.py.
def pyclustering.nnet.hysteresis.hysteresis_network.outputs | ( | self | ) |
Returns current outputs of neurons.
Definition at line 181 of file hysteresis.py.
Referenced by pyclustering.nnet.hysteresis.hysteresis_network.outputs().
def pyclustering.nnet.hysteresis.hysteresis_network.simulate | ( | self, | |
steps, | |||
time, | |||
solution = solve_type.RK4 , |
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collect_dynamic = True |
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) |
Performs static simulation of hysteresis 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. |
Definition at line 282 of file hysteresis.py.
Referenced by pyclustering.gcolor.hysteresis.hysteresisgcolor.process().
def pyclustering.nnet.hysteresis.hysteresis_network.simulate_static | ( | self, | |
steps, | |||
time, | |||
solution = solve_type.RK4 , |
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collect_dynamic = False |
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) |
Performs static simulation of hysteresis 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. |
Definition at line 298 of file hysteresis.py.
Referenced by pyclustering.nnet.hysteresis.hysteresis_network.simulate(), pyclustering.nnet.syncpr.syncpr.simulate(), and pyclustering.nnet.sync.sync_network.simulate().
def pyclustering.nnet.hysteresis.hysteresis_network.states | ( | self | ) |
Return current states of neurons.
Definition at line 202 of file hysteresis.py.
Referenced by pyclustering.nnet.hysteresis.hysteresis_network.states().