[SciPy-User] linalg.iterative problem!

[SungHwan Choi]

Hi
I have a trouble with  iterative linear equation solver in sparse linalg

>>> A=np.random.rand(100,100)
>>> b=np.random.rand(100,1)
>>> x1,info=bicg(A,b)
>>> print info
0
>>> x,info=bicg(A,b,x0=x1)
>>> print info
0
Wheather setting guessing value or not,  solutions should be the same if
both calculations were converged.
But x is ridiculous values

>>> x1
array([ -1.23619915e+00,   2.97586147e+00,  -6.14648472e-01,
        -1.60393960e+00,   1.27603461e+00,  -6.71559072e-01,
        -4.57949314e-04,  -2.77060765e-01,  -4.17339328e-01,
         4.58723928e-01,   1.25520390e+00,  -6.43505834e-01,
        -2.50714182e+00,   1.64801812e+00,   3.22769225e-01,
        -3.47764545e+00,  -2.64155124e+00,   8.02161189e-01,
        -2.04397410e-02,   1.78176386e+00,  -2.30534938e+00,
         2.03747784e-01,   4.25741370e-01,   8.92017739e-02,
         7.92235549e-01,   2.05296800e+00,  -5.07849138e-01,
         2.39548767e+00,  -6.75288110e-01,   5.40248358e-01,
        -1.22652305e+00,   1.24128988e+00,   3.55832137e-01,
        -4.94905114e-01,   1.89255642e+00,   1.13032169e+00,
        -1.13126641e+00,  -1.24107851e+00,  -3.50610928e-01,
         1.51242380e+00,   5.93313109e-02,  -1.65542281e+00,
        -1.31457525e+00,  -2.07950912e+00,   2.03842426e+00,
        -1.25129931e+00,  -1.18204676e+00,  -2.84095828e-01,
         1.50420723e+00,  -1.86947284e+00,   3.82634122e-01,
         1.59583715e+00,   2.38088734e+00,  -1.94456801e+00,
        -3.91679300e+00,  -5.82275859e-01,   6.37373111e-01,
         1.50117747e+00,   3.16166509e-01,  -4.80709301e-01,
         2.44748482e-01,   8.46311114e-01,  -3.50561001e-01,
         1.17040825e+00,   8.48462084e-01,   2.26995940e+00,
        -4.02400162e-01,   8.15964837e-02,  -1.17082091e-01,
         5.76520318e-01,   2.68571769e+00,  -8.24618021e-01,
         1.70237224e+00,  -9.51878209e-01,  -1.79056788e+00,
         1.28023233e+00,  -3.06323112e+00,   1.36928031e+00,
        -5.32667426e-01,  -8.76808999e-01,   5.04791986e+00,
         1.02573111e+00,   2.91480759e-01,  -1.65205205e+00,
         2.01570733e+00,  -8.58303160e-01,   1.00844953e+00,
        -1.42026281e+00,  -1.35743978e+00,  -6.98618293e-01,
        -9.64603408e-01,   4.94354222e-01,  -1.56639931e+00,
        -1.00424343e+00,   1.34539380e+00,   8.34746938e-01,
        -1.42944790e-02,   4.11728888e-02,   8.48928870e-01,
        -3.81714583e-01])
>>> x
array([  5.54091698e-06,   1.01097308e-06,  -1.90554231e-07,
         4.72137778e-07,  -1.59217304e-06,  -2.63521296e-06,
         1.82539010e-06,  -3.29784996e-06,   2.11241995e-06,
         3.34528259e-06,  -1.48936133e-06,   4.64833156e-06,
         2.72517397e-06,  -8.68280493e-07,  -1.48461475e-06,
         1.31078987e-06,   1.96827837e-06,   2.43522800e-06,
        -1.81519616e-09,   7.36595257e-07,  -1.68678301e-06,
        -2.36489475e-06,  -9.48767026e-08,  -4.19287423e-07,
        -1.94382913e-06,  -2.85541661e-06,  -2.22431928e-06,
         5.69426787e-07,  -3.20549054e-06,  -4.28991209e-06,
        -2.66204912e-06,  -5.41291369e-07,   1.40179165e-07,
        -7.73036341e-08,  -2.62207353e-06,   3.04217252e-07,
         7.58099103e-06,   1.64647208e-07,  -2.07367685e-06,
         1.07293388e-06,  -2.64252934e-06,   8.43832882e-07,
        -2.09558797e-06,  -2.38424059e-06,  -2.01101471e-06,
         1.14992748e-06,   1.75975671e-06,   3.47029359e-06,
        -1.73474476e-06,   1.63282775e-06,   2.14847352e-06,
        -1.06630511e-07,  -3.71185399e-07,  -6.19298483e-07,
        -4.22283992e-07,   2.87057463e-06,   2.50493018e-07,
         2.38959629e-07,   1.09429464e-06,   2.78931839e-06,
         1.04950522e-06,   1.92574749e-06,   2.16166697e-06,
        -1.49381992e-07,   2.57534472e-06,  -1.80238481e-06,
        -4.48006258e-07,  -4.82004956e-06,  -2.90858804e-06,
         2.36872252e-06,  -5.82462798e-06,   2.28721650e-06,
         4.98778955e-06,   7.42277728e-07,   4.79308235e-06,
         3.32154978e-06,   2.01826593e-06,   1.70133451e-06,
         1.04876888e-06,  -1.66519455e-06,  -2.29374493e-06,
         2.85916887e-06,  -2.92097942e-06,   4.34734275e-07,
         2.09635331e-06,  -1.21218109e-06,  -2.15483189e-06,
        -2.62789759e-06,   5.97557810e-06,  -8.16033223e-07,
         5.59003423e-07,  -1.27845573e-06,  -2.81987257e-06,
        -2.99137673e-06,  -1.68537057e-06,  -1.23698610e-06,
        -1.26839543e-06,  -6.37207587e-08,   3.99191552e-07,
        -1.97820929e-06])

When I set x0, I always get some very small value as solution but I don't
know why it give us original solution

Please, help me if  you have a piece of knowhow to this phenomena

Sincerely
Sunghwan
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