In [1]:
import numpy as np
In [16]:
N = 5
beta=1
thresh=0
alpha=0.1
TF=1
Ntrials=500
TrialLength=10;
# Trial 1
InputVal = [0]
InputVal.append(np.zeros((N, TrialLength)))
InputVal[1][0, 2] = 1
OutpVal = [0]
OutpVal.append(np.zeros((N, TrialLength)) + float('Nan'))
OutpVal[1](2,6)=1
OutpVal[1](3,6)=0
# Trial 2
InputVal.append(np.zeros((N, TrialLength)))
InputVal[1][1, 2] = 1
OutpVal.append(np.zeros((N, TrialLength)) + float('Nan'))
OutpVal[2][3, 6] = 1
OutpVal[2][3, 6] = 0
trialTyp = np.ones(Ntrials // 2), np.ones(Ntrials // 2) * 2
In [12]:
x = float('NaN')
In [15]:
OutpVal[1]
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