//--------------------------------------------------------------------
// Simulation of Phasic Activity
// Synapses Distributet in soma, dasal and perisomatc dendrites
// her without run, just to place synapses
// used with an increased nseg of 101 (run() reasonalble only for nseg <11)
//---------------------------------------------------------------------

// ------------Definition of Parameters -------------------------------
// --------------------------------------------------------------------


// Determining Parameters GABA ---------------------------
G_GABA = 0.000169   // synaptic weight according to miniature events 
DECAY_GABA = 37
P_GABA = 0.18
ndend=107 
ngabasyn = 107
gninputs = 2


// seed Values for random generator
seed_GABA = 1  // seed for random function




// ---------Definition of objects -------------------------------------
// --------------------------------------------------------------------


// Objects for Synapses ---------------------------------------------------------
objref gabasyn[ngabasyn]                            // Definition of synapse objects

// random function for localization of synapses
objref rand_gaba_loc

// random function for localization of synapses in which dendrite
objref rand_gaba_dend

// random function for synapses parameters
objref rand_gaba_t

// definition of Vectors for Gaba-Stimulation (t_vec = timestamps t_vecr = sorted timestamps, g_vec = rel conductance)
objref gabastim[ngabasyn], gaba_t_vec[ngabasyn], gaba_t_vecr[ngabasyn], synpulsegaba[ngabasyn]

// Start of Input generation -------------------------------------------

// Initialize Random Functions -----------
rand_gaba_dend = new Random(seed_GABA+4)
rand_gaba_t = new Random(seed_GABA+6)

//Define properties of random Function
rand_gaba_t.uniform(0, 1010101)

// generate Vectors --- (gniputs, aninputs defines number of inputs per synapse) ------
for i = 0, ngabasyn-1 {
  gaba_t_vec[i] = new Vector(gninputs)
  gaba_t_vecr[i] = new Vector(gninputs)
}

printf("\n Pos: ")
// Distribute GABA synapses -----------------------------------------------------------
// Distribute in soma and perisomatic dendrites
for k=0, 8 {
    pos = rand_gaba_dend.uniform (0.0001, 0.999)
    printf("%g = %g,",k, pos)
    dend[0]{
      gabasyn[k] = new gaba(0.2)
      gabasyn[k].tau1 = 0.1
      gabasyn[k].tau2 = DECAY_GABA
      gabasyn[k].P = P_GABA
      }
    }
for k=9, 17 {
    pos = rand_gaba_dend.uniform (0.0001, 0.999)
    printf("%g = %g,",k, pos)
    dend[3]{
      gabasyn[k] = new gaba(pos)
      gabasyn[k].tau1 = 0.1
      gabasyn[k].tau2 = DECAY_GABA
      gabasyn[k].P = P_GABA
      }
    }
for k=18, 26 {
    pos = rand_gaba_dend.uniform (0.0001, 0.999)
    printf("%g = %g,",k, pos)
    dend[8]{
      gabasyn[k] = new gaba(pos)
      gabasyn[k].tau1 = 0.1
      gabasyn[k].tau2 = DECAY_GABA
      gabasyn[k].P = P_GABA
      }
    }
for k=27, 35 {
    pos = rand_gaba_dend.uniform (0.0001, 0.999)
    printf("%g = %g,",k, pos)
    dend[8]{
      gabasyn[k] = new gaba(pos)
      gabasyn[k].tau1 = 0.1
      gabasyn[k].tau2 = DECAY_GABA
      gabasyn[k].P = P_GABA
      }
    }                                         
for k=36, 44 {
    pos = rand_gaba_dend.uniform (0.0001, 0.999)
    printf("%g = %g,",k, pos)
    dend[10]{
      gabasyn[k] = new gaba(pos)
      gabasyn[k].tau1 = 0.1
      gabasyn[k].tau2 = DECAY_GABA
      gabasyn[k].P = P_GABA
      }
    }
for k=45, 53 {
    pos = rand_gaba_dend.uniform (0.0001, 0.999)
    printf("%g = %g,",k, pos)
    apic[10]{
      gabasyn[k] = new gaba(pos)
      gabasyn[k].tau1 = 0.1
      gabasyn[k].tau2 = DECAY_GABA
      gabasyn[k].P = P_GABA
      }
    }
for k=54, 62 {
    pos = rand_gaba_dend.uniform (0.0001, 0.999)
    printf("%g = %g,",k, pos)
    apic[11]{
      gabasyn[k] = new gaba(pos)
      gabasyn[k].tau1 = 0.1
      gabasyn[k].tau2 = DECAY_GABA
      gabasyn[k].P = P_GABA
      }
    }
for k=63, 71 {
    pos = rand_gaba_dend.uniform (0.0001, 0.999)
    printf("%g = %g,",k, pos)
    apic[12]{
      gabasyn[k] = new gaba(pos)
      gabasyn[k].tau1 = 0.1
      gabasyn[k].tau2 = DECAY_GABA
      gabasyn[k].P = P_GABA
      }
    }
for k=72, 80 {
    pos = rand_gaba_dend.uniform (0.0001, 0.999)
    printf("%g = %g,",k, pos)
    apic[13]{
      gabasyn[k] = new gaba(pos)
      gabasyn[k].tau1 = 0.1
      gabasyn[k].tau2 = DECAY_GABA
      gabasyn[k].P = P_GABA
      }
    }
for k=81, 89 {
    pos = rand_gaba_dend.uniform (0.0001, 0.999)
    printf("%g = %g,",k, pos)
    apic[14]{
      gabasyn[k] = new gaba(pos)
      gabasyn[k].tau1 = 0.1
      gabasyn[k].tau2 = DECAY_GABA
      gabasyn[k].P = P_GABA
      }
    }
for k=90, ndend-1 {
    pos = rand_gaba_dend.uniform (0.0001, 0.999)
    printf("%g = %g,",k, pos)
    soma{
      gabasyn[k] = new gaba(pos)
      gabasyn[k].tau1 = 0.1
      gabasyn[k].tau2 = DECAY_GABA
      gabasyn[k].P = P_GABA
      }
    }

printf("\n \n")