@@ -108,7 +108,7 @@ def place(A, B, p):
108108 raise ControlDimension (err_str )
109109
110110 # Convert desired poles to numpy array
111- placed_eigs = np .array ( p )
111+ placed_eigs = np .atleast_1d ( np . squeeze ( np . asarray ( p )) )
112112
113113 result = place_poles (A_mat , B_mat , placed_eigs , method = 'YT' )
114114 K = result .gain_matrix
@@ -184,7 +184,7 @@ def place_varga(A, B, p, dtime=False, alpha=None):
184184
185185 # Compute the system eigenvalues and convert poles to numpy array
186186 system_eigs = np .linalg .eig (A_mat )[0 ]
187- placed_eigs = np .array ( p )
187+ placed_eigs = np .atleast_1d ( np . squeeze ( np . asarray ( p )) )
188188
189189 # Need a character parameter for SB01BD
190190 if dtime :
@@ -231,7 +231,7 @@ def lqe(A, G, C, QN, RN, NN=None):
231231 .. math::
232232 x = Ax + Bu + Gw
233233 y = Cx + Du + v
234-
234+
235235 with unbiased process noise w and measurement noise v with covariances
236236
237237 .. math:: E{ww'} = QN, E{vv'} = RN, E{wv'} = NN
@@ -264,12 +264,12 @@ def lqe(A, G, C, QN, RN, NN=None):
264264 A P + P A^T - (P C^T + G N) R^-1 (C P + N^T G^T) + G Q G^T = 0
265265 E: 1D array
266266 Eigenvalues of estimator poles eig(A - L C)
267-
267+
268268
269269 Examples
270270 --------
271- >>> K , P, E = lqe(A, G, C, QN, RN)
272- >>> K , P, E = lqe(A, G, C, QN, RN, NN)
271+ >>> L , P, E = lqe(A, G, C, QN, RN)
272+ >>> L , P, E = lqe(A, G, C, QN, RN, NN)
273273
274274 See Also
275275 --------
@@ -381,7 +381,7 @@ def lqr(*args, **keywords):
381381 See Also
382382 --------
383383 lqe
384-
384+
385385 """
386386
387387 # Make sure that SLICOT is installed
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