def fullrank(X, r=None):
 if (r is None):
  r = rank(X)
 (V, D, U) = L.svd(X, full_matrices=0)
 order = np.argsort(D)
 order = order[::(-1)]
 value = []
 for i in range(r):
  value.append(V[:, order[i]])
 return np.asarray(np.transpose(value)).astype(np.float64)

def fullrank ( X , r = None ) : if ( r is None ) : r = rank ( X ) ( V , D , U ) = L . svd ( X , full_matrices = 0 ) order = np . argsort ( D ) order = order [ : : ( - 1 ) ] value = [ ] for i in range ( r ) : value . append ( V [ : , order [ i ] ] ) return np . asarray ( np . transpose ( value ) ) . astype ( np . float64 )
return a matrix whose column span is the same as x .