class_docstr: !
  @brief Describes parameters of Hodgkin-Huxley Oscillatory Network.
  
  @see hhn_network
class_docstr_tok: ["!","@","brief","Describes","parameters","of","Hodgkin-Huxley","Oscillatory","Network",".","@","see","hhn_network"]
docstr: !
  @brief    Default constructor of parameters for Hodgkin-Huxley Oscillatory Network.
  @details  Constructor initializes parameters by default non-zero values that can be
            used for simple simulation.
docstr_tok: ["!","@","brief","Default","constructor","of","parameters","for","Hodgkin-Huxley","Oscillatory","Network",".","@","details","Constructor","initializes","parameters","by","default","non-zero","values","that","can","be","used","for","simple","simulation","."]
code: def __init__(self):
      """!
      @brief    Default constructor of parameters for Hodgkin-Huxley Oscillatory Network.
      @details  Constructor initializes parameters by default non-zero values that can be
                used for simple simulation.
      """
  
      ## Intrinsic noise.
      self.nu = random.random() * 2.0 - 1.0
  
      ## Maximal conductivity for sodium current.
      self.gNa = 120.0 * (1 + 0.02 * self.nu)
  
      ## Maximal conductivity for potassium current.
      self.gK = 36.0 * (1 + 0.02 * self.nu)
  
      ## Maximal conductivity for leakage current.
      self.gL = 0.3 * (1 + 0.02 * self.nu)
  
      ## Reverse potential of sodium current [mV].
      self.vNa = 50.0
  
      ## Reverse potential of potassium current [mV].
      self.vK = -77.0
  
      ## Reverse potential of leakage current [mV].
      self.vL = -54.4
  
      ## Rest potential [mV].
      self.vRest = -65.0
  
      ## External current [mV] for central element 1.
      self.Icn1 = 5.0
  
      ## External current [mV] for central element 2.
      self.Icn2 = 30.0
  
      ## Synaptic reversal potential [mV] for inhibitory effects.
      self.Vsyninh = -80.0
  
      ## Synaptic reversal potential [mV] for exciting effects.
      self.Vsynexc = 0.0
  
      ## Alfa-parameter for alfa-function for inhibitory effect.
      self.alfa_inhibitory = 6.0
  
      ## Betta-parameter for alfa-function for inhibitory effect.
      self.betta_inhibitory = 0.3
  
      ## Alfa-parameter for alfa-function for excitatory effect.
      self.alfa_excitatory = 40.0
  
      ## Betta-parameter for alfa-function for excitatory effect.
      self.betta_excitatory = 2.0
  
      ## Strength of the synaptic connection from PN to CN1.
      self.w1 = 0.1
  
      ## Strength of the synaptic connection from CN1 to PN.
      self.w2 = 9.0
  
      ## Strength of the synaptic connection from CN2 to PN.
      self.w3 = 5.0
  
      ## Period of time [ms] when high strength value of synaptic connection exists from CN2 to PN.
      self.deltah = 650.0
  
      ## Threshold of the membrane potential that should exceeded by oscillator to be considered as an active.
      self.threshold = -10
  
      ## Affects pulse counter.
      self.eps = 0.16
  
imports: from scipy.integrate import odeint
  from pyclustering.core.wrapper import ccore_library
  import pyclustering.core.hhn_wrapper
  from pyclustering.nnet import *
  from pyclustering.utils import allocate_sync_ensembles
  import numpy
  import random
label_desc: Use image node_id 1 to create a new hhn_parameters object  with example: obj = hhn_parameters()