class_docstr: !
  @brief Represents SOM parameters.
class_docstr_tok: ["!","@","brief","Represents","SOM","parameters","."]
docstr: !
  @brief Creates SOM parameters.
docstr_tok: ["!","@","brief","Creates","SOM","parameters","."]
code: def __init__(self):
      """!
      @brief Creates SOM parameters.
  
      """
  
      ## Defines an initialization way for neuron weights (random, random in center of the input data, random distributed in data, ditributed in line with uniform grid).
      self.init_type = type_init.uniform_grid
  
      ## Initial radius. If the initial radius is not specified (equals to `None`) then it will be calculated by SOM.
      self.init_radius = None
  
      ## Rate of learning.
      self.init_learn_rate = 0.1
  
      ## Condition that defines when the learining process should be stopped. It is used when the autostop mode is on.
      self.adaptation_threshold = 0.001
  
      ## Seed for random state (by default is `None`, current system time is used).
      self.random_state = None
  
imports: import math
  import random
  import matplotlib.pyplot
  import pyclustering.core.som_wrapper
  from pyclustering.core.wrapper import ccore_library
  from pyclustering.utils import euclidean_distance_square
  from pyclustering.utils.dimension import dimension_info
  from enum import IntEnum
label_desc: Use image node_id 1 to create a new som_parameters object  with example: obj = som_parameters()