pyclustering
0.10.1
pyclustring is a Python, C++ data mining library.

Class represents clustering algorithm SyncNet. More...
Public Member Functions  
def  __init__ (self, sample, radius, conn_repr=conn_represent.MATRIX, initial_phases=initial_type.RANDOM_GAUSSIAN, enable_conn_weight=False, ccore=True) 
Contructor of the oscillatory network SYNC for cluster analysis. More...  
def  __del__ (self) 
Destructor of oscillatory network is based on Kuramoto model.  
def  process (self, order=0.998, solution=solve_type.FAST, collect_dynamic=True) 
Peforms cluster analysis using simulation of the oscillatory network. More...  
def  show_network (self) 
Shows connections in the network. 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  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 nongrid structure. More...  
def  width (self) 
Width of the network grid, this value is zero in case of nongrid 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  set_connection (self, i, j) 
Couples two specified oscillators in the network with dynamic connections. More...  
Class represents clustering algorithm SyncNet.
SyncNet is bioinspired algorithm that is based on oscillatory network that uses modified Kuramoto model. Each attribute of a data object is considered as a phase oscillator.
Example:
Definition at line 146 of file syncnet.py.
def pyclustering.cluster.syncnet.syncnet.__init__  (  self,  
sample,  
radius,  
conn_repr = conn_represent.MATRIX , 

initial_phases = initial_type.RANDOM_GAUSSIAN , 

enable_conn_weight = False , 

ccore = True 

) 
Contructor of the oscillatory network SYNC for cluster analysis.
[in]  sample  (list): Input data that is presented as list of points (objects), each point should be represented by list or tuple. 
[in]  radius  (double): Connectivity radius between points, points should be connected if distance between them less then the radius. 
[in]  conn_repr  (conn_represent): Internal representation of connection in the network: matrix or list. Ignored in case of usage of CCORE library. 
[in]  initial_phases  (initial_type): Type of initialization of initial phases of oscillators (random, uniformly distributed, etc.). 
[in]  enable_conn_weight  (bool): If True  enable mode when strength between oscillators depends on distance between two oscillators. If False  all connection between oscillators have the same strength that equals to 1 (True). 
[in]  ccore  (bool): Defines should be CCORE C++ library used instead of Python code or not. 
Reimplemented in pyclustering.cluster.hsyncnet.hsyncnet.
Definition at line 183 of file syncnet.py.
def pyclustering.cluster.syncnet.syncnet.process  (  self,  
order = 0.998 , 

solution = solve_type.FAST , 

collect_dynamic = True 

) 
Peforms cluster analysis using simulation of the oscillatory network.
[in]  order  (double): Order of synchronization that is used as indication for stopping processing. 
[in]  solution  (solve_type): Specified type of solving diff. equation. 
[in]  collect_dynamic  (bool): Specified requirement to collect whole dynamic of the network. 
Reimplemented in pyclustering.cluster.hsyncnet.hsyncnet.
Definition at line 286 of file syncnet.py.
def pyclustering.cluster.syncnet.syncnet.show_network  (  self  ) 
Shows connections in the network.
It supports only 2d and 3d representation.
Definition at line 336 of file syncnet.py.