Using sparse_a in solve fails

[moorepants]

result = solver.solve(sparse_a=True)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-44-c96f1dfa9907> in <module>()
----> 1 result = solver.solve(sparse_a=True)

/home/moorepants/src/Gait-Analysis-Toolkit/gaitanalysis/controlid.pyc in solve(self, sparse_a, gain_omission_matrix)
    749         x, variance, covariance = self.least_squares(A, b)
    750 
--> 751         deconstructed_solution = self.deconstruct_solution(x, covariance)
    752 
    753         gain_matrices = deconstructed_solution[0]

/home/moorepants/src/Gait-Analysis-Toolkit/gaitanalysis/controlid.pyc in deconstruct_solution(self, x, covariance)
    299         control_vectors_variance = np.zeros((self.n, self.q))
    300 
--> 301         parameter_variance = np.diag(covariance)
    302 
    303         for i in range(self.n):

/home/moorepants/envs/walk/local/lib/python2.7/site-packages/numpy/lib/twodim_base.pyc in diag(v, k)
    287         return v.diagonal(k)
    288     else:
--> 289         raise ValueError("Input must be 1- or 2-d.")
    290 
    291 def diagflat(v, k=0):

ValueError: Input must be 1- or 2-d.