# and add to the numerator array
numTemp = [df['kp_real'][i], 0]
denTemp = [1., -df['tau_real_1'][i], -df['tau_real_2'][i]]
thetas = [df['theta_real'][i]]
bigU = np.transpose(u)
uSim = np.zeros_like(bigU)
uSim = np.concatenate((np.zeros(thetas[0]), bigU[:-thetas[0]]))
numTemp = np.array(numTemp)
denTemp = np.array(denTemp)
sys = control.tf(numTemp, denTemp, 1)
_, realy, _ = control.forced_response(sys,
U=uSim,
T=np.linspace(0, 599, 600))
plt.plot(sig.gauss_noise(realy, 'variable'), 'green')
for k in range(0, 10):
numgauss = np.random.normal(df['kp_MATLAB'][i],
df['unc_MATLAB'][i] / 2)
dengauss = np.random.normal(df['tau_MATLAB'][i],
df['unc_MATLAB.1'][i] / 2)
numTemp = [numgauss]
denTemp = [1., -dengauss]
thetas = [df['theta_MATLAB'][i]]
bigU = np.transpose(u)
uSim = np.zeros_like(bigU)
if thetas[0] < 1:
thetas[0] = 1
uSim = np.concatenate((np.zeros(thetas[0]), bigU[:-thetas[0]]))
