removed old notebooks

conf/config_2pop.yml

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+##########################################
+# Simulation parameters
+##########################################
+# disable jit compilation
+DISABLE_JIT: 0
+# number of threads for parallel processing
+NUM_THREADS: 116
+
+# output different prompts for debugging purpose
+VERBOSE: 0
+
+# 1 to save the data to REPO_ROOT/data/simul
+SAVE_DATA: 1
+
+# Time step in s
+DT: 0.001
+# total simulation time in s
+DURATION: 5.0
+# time to start saving simulation files
+T_STEADY: 1.0
+# Saving to files every T_WINDOW
+T_WINDOW: .250
+
+##########################################
+# Parameters for the stimulus presentation
+##########################################
+# stimulus as a cosine shape
+# time for stimulus onset in s 
+T_STIM_ON: 2.0
+# time for stimulus offset in s 
+T_STIM_OFF: 2.5
+# amplitude of the 1st stimulus
+I0: [2.0, 0.0]
+# amplitude of the 2nd stimulus
+I1: [0.0, 0.0]
+# I1: [0.05, 0.0]
+# Phase of the 1st stimulus
+PHI0: 180.0
+# Tuning of the 1st stimulus
+SIGMA0: 1.0
+# Phase difference between 1st/2nd stimuli
+DPHI: 0.25
+
+##########################################
+# Network parameters
+##########################################
+# number of populations
+N_POP: 2
+# number of neurons
+N: 2000
+# number of average presynaptic input (set to 1 if all to all)
+K: 1.0
+# fraction of neuron in each population (must sum to 1)
+frac: [0.75, 0.25]
+
+##########################################
+# Network Dynamic
+##########################################
+# Transfert Function
+# set to 0 for threshold linear, 1 for sigmoid
+TF_TYPE: 1
+
+# Dynamics of the rates
+# set to 0 if instantaneous rates, 1 if exponentially decaying
+RATE_DYN: 1
+# rate time constants in s
+TAU_MEM: [0.02, 0.02]
+
+# Dynamics of the recurrent inputs
+# set to 0 if instantaneous, 1 if exponentially decaying
+SYN_DYN: 0
+# Synaptic time constants for each population
+TAU_SYN: [0.003, 0.002]
+
+# Adding NMDA currents
+IF_NMDA: 0
+# NMDA time constants in s
+TAU_NMDA: [0.2, 0.2]
+
+# Feedforward inputs dynamics
+# set to 0 for instantaneous, 1 to exp decay, 2 adds gaussian noise
+FF_DYN: 2
+# FF time constants in s
+TAU_FF: [0.003, 0.003]
+# Variance of the noise
+VAR_FF: [1.0, 1.0]
+
+# Threshold dynamics
+# set to 0 constant thresholds, 1 to add adaptative thresholds
+THRESH_DYN: 0
+# threshold
+THRESH: [15.00, 15.00]
+# threshold time constants
+TAU_THRESH: [0.1, 0.1]
+
+# Network's gain
+GAIN: 1.0
+
+# Synaptic strengths           
+Jab: [2.0, -1.5, 1.0, -1.0]
+# External inputs strengths
+Iext: [0.5, 0.25]
+# External rate
+M0: 1.0
+
+# To add an attentional switch
+# if BUMP_SWITCH[i] == 1 it sets Iext[i] to zero before stimulus presentation
+BUMP_SWITCH: [1, 1]
+
+########################
+# Plasticity
+########################
+# adds learning
+IF_LEARNING: 0
+# adds short term plasticity
+IF_STP: 0
+
+##############
+# Connectivity
+##############
+# load connectivity matrix
+# from REPO_PATH/data/matrix
+IF_LOAD_MAT: 0
+
+# save connectivity matrix
+IF_SAVE_MAT: 1
+
+# seed for connectivity None or float
+SEED: 1
+# connectivity type
+# STRUCTURE can be 'all', 'all_cos', 'cos', 'spec_cos', 'None'
+
+# By default the matrix is a random sparse matrix Cij
+# 'cos' gives a sparse matrix with strong cosine structure,
+# Pij = (1 + 2 KAPPA cos(theta_ij) / sqrt(Kb)), Cij = 1 with proba Pij
+# 'spec_cos' gives a sparse matrix with weak cosine structure,
+# Pij = (1 + 2 KAPPA cos(theta_ij) / sqrt(Kb)) , Cij = 1 with proba Pij
+# 'all' gives an all to all matrix, Cij = 1/N
+# 'all_cos' gives an all to all with cosine shape,
+# Cij = (1 + 2 KAPPA cos(theta_ij)) / N
+# any other string gives a sparse matrix,
+# Cij = 1 with proba Ka/Na, 0 otherwise
+
+# sets probabilities of connections' shape
+STRUCTURE: ['all_cos', 'all_cos', 'all_cos', 'all_cos']
+# tuning of the recurrent connections
+KAPPA: [0.6, 0.0, 0.6, 0.0]
+# phase of the connectivity
+PHASE: 0.0
+
+# strength of the asymmetries if all to all
+SIGMA: [0.0, 0.0, 0.0, 0.0]
+
+# parameters for computing the mean field
+TOLERANCE: 1.e-12
+MAXITER: 100