title: Issues using the scipy.sparse.linalg linear system solvers
body: <p>I've got linear system to solve which consists of large, sparse matrices.</p>
  
  <p>I've been using the <code>scipy.sparse</code> library, and its <code>linalg</code> sub-library to do this, but I can't get some of the linear solvers to work.</p>
  
  <p>Here is a working example which reproduces the issue for me:</p>
  
  <pre><code>from numpy.random import random
  from scipy.sparse import csc_matrix
  from scipy.sparse.linalg import spsolve, minres
  
  N = 10
  A = csc_matrix( random(size = (N,N)) )
  A = (A.T).dot(A) # force the matrix to be symmetric, as required by minres
  x = csc_matrix( random(size = (N,1)) ) # create a solution vector
  b = A.dot(x) # create the RHS vector
  
  # verify shapes and types are correct
  print('A', A.shape, type(A))
  print('x', x.shape, type(x))
  print('b', b.shape, type(b))
  
  # spsolve function works fine
  sol1 = spsolve(A, b)
  
  # other solvers throw a incompatible dimensions ValueError
  sol2 = minres(A, b)
  </code></pre>
  
  <p>Running this produces the following error</p>
  
  <pre><code>    raise ValueError('A and b have incompatible dimensions')
  ValueError: A and b have incompatible dimensions
  </code></pre>
  
  <p>for the call to <code>minres</code>, even though the dimensions clearly <em>are</em> compatible. Other solvers in <code>scipy.sparse.linalg</code>, such as <code>cg</code>, <code>lsqr</code> and <code>gmres</code> all throw an identical error.</p>
  
  <p>This is being run on python 3.6.1 with SciPy 0.19.</p>
  
  <p>Anyone have any idea what's going on here?</p>
  
  <p>Thanks!</p>