What is the value of the x^T C^-1 x term at the best-fit point? And what is its value when you reduce C_3 by ten percent?

gistfile1.txt

C3_sample1 = 4e-8
sigma2samples1 = np.linspace(1e-22, 6e-23, num=40)
 
 
# param is our parameter, C_3
Sij = C3_sample1 * norm_matrix[1][None, :, :]
newSij = (1e22)*Sij   # multiply S_ij by 1e12
Nij = sigma2samples1[:, None, None] * id_mat[None, :, :]
newNij = (1e22)*Nij
# Format 7/4pi * param * P_3(M) where param is the parameter we vary, C_l
# Sij.shape = (40, 3072, 3072)
Cij = newSij + newNij
#invCij = np.linalg.inv(Cij)
logdetC = np.linalg.slogdet(Cij)  # returns sign and determinant; use logdetC[1]
# model_fit_terms = m^T C^-1 m
#
# model_fit_terms = np.array([np.dot(tempval.T , np.dot(invCij[i] , tempval) ) 
# for i in range(invCij.shape[0])])
#
model_fit_terms = np.array([np.dot(tempp.T , np.linalg.solve(Cij[i], tempp) ) for i in range(Cij.shape[0]) ]) 
 
print model_fit_terms
 
OUTPUT IS:
 
 
[ -6.54990301e+05  -6.54990301e+05   1.19083809e+05   1.19083809e+05
   1.19083809e+05  -8.52103763e+05  -8.52103763e+05  -8.52103763e+05
  -9.70917894e+05  -9.70917894e+05  -9.70917894e+05  -1.77769621e+06
  -1.77769621e+06  -1.77769621e+06  -3.93333671e+07  -3.93333671e+07
  -3.93333671e+07  -5.58136674e+05  -5.58136674e+05  -5.58136674e+05
  -3.16037652e+06  -3.16037652e+06  -3.16037652e+06  -1.86591114e+04
  -1.86591114e+04  -1.86591114e+04   1.01764609e+06   1.01764609e+06
   1.01764609e+06   1.98358099e+05   1.98358099e+05   1.98358099e+05
  -1.40628207e+06  -1.40628207e+06  -1.40628207e+06  -1.40628207e+06
   5.09936449e+06   5.09936449e+06   5.09936449e+06  -1.73093522e+06]
   
   For 3.6e-08, OUTPUT IS:
   
   
[  216652.36865427   216652.36865427  7229836.39263844  7229836.39263844
  7229836.39263844  4440519.06167877  4440519.06167877  4440519.06167877
  1256311.03694729  1256311.03694729  1256311.03694729  4807585.29728004
  4807585.29728004  4807585.29728004  7138847.36595693  7138847.36595693
  7138847.36595693   850361.20217029   850361.20217029   850361.20217029
 -2355755.45923652 -2355755.45923652 -2355755.45923652 -1296041.99250639
 -1296041.99250639 -1296041.99250639   658522.94116765   658522.94116765
   658522.94116765 -5030606.16602418 -5030606.16602418 -5030606.16602418
  -138380.29050851  -138380.29050851  -138380.29050851  -138380.29050851
 -1138487.77807789 -1138487.77807789 -1138487.77807789 -1134975.40711535]