metic methods.

>>> from numpy.linalg import cond
>>> cond(a)
np.float64(8.659885634118668e+17)  # may vary

It is also possible to detect ill-conditioning by inspecting the matrix's
singular values directly. The ratio between the largest and the smallest
singular value is the condition number:

>>> from numpy.linalg import svd
>>> sigma = svd(a, compute_uv=False)  # Do not compute singular vectors
>>> sigma.max()/sigma.min()
8.659885634118668e+17  # may vary

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