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Commitebd73c1

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fixes in canonical and canonical_test that were assuming numpy.matrix
1 parenteda91ca commitebd73c1

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2 files changed

+25
-29
lines changed

2 files changed

+25
-29
lines changed

‎control/canonical.py

Lines changed: 13 additions & 17 deletions
Original file line numberDiff line numberDiff line change
@@ -6,7 +6,8 @@
66
from .statespimportStateSpace
77
from .statefbkimportctrb,obsv
88

9-
fromnumpyimportzeros,shape,poly,iscomplex,hstack,dot,transpose
9+
fromnumpyimportzeros,zeros_like,shape,poly,iscomplex,vstack,hstack,dot, \
10+
transpose,empty
1011
fromnumpy.linalgimportsolve,matrix_rank,eig
1112

1213
__all__= ['canonical_form','reachable_form','observable_form','modal_form',
@@ -70,9 +71,9 @@ def reachable_form(xsys):
7071
zsys=StateSpace(xsys)
7172

7273
# Generate the system matrices for the desired canonical form
73-
zsys.B=zeros(shape(xsys.B))
74+
zsys.B=zeros_like(xsys.B)
7475
zsys.B[0,0]=1.0
75-
zsys.A=zeros(shape(xsys.A))
76+
zsys.A=zeros_like(xsys.A)
7677
Apoly=poly(xsys.A)# characteristic polynomial
7778
foriinrange(0,xsys.states):
7879
zsys.A[0,i]=-Apoly[i+1]/Apoly[0]
@@ -124,9 +125,9 @@ def observable_form(xsys):
124125
zsys=StateSpace(xsys)
125126

126127
# Generate the system matrices for the desired canonical form
127-
zsys.C=zeros(shape(xsys.C))
128+
zsys.C=zeros_like(xsys.C)
128129
zsys.C[0,0]=1
129-
zsys.A=zeros(shape(xsys.A))
130+
zsys.A=zeros_like(xsys.A)
130131
Apoly=poly(xsys.A)# characteristic polynomial
131132
foriinrange(0,xsys.states):
132133
zsys.A[i,0]=-Apoly[i+1]/Apoly[0]
@@ -144,7 +145,7 @@ def observable_form(xsys):
144145
raiseValueError("Transformation matrix singular to working precision.")
145146

146147
# Finally, compute the output matrix
147-
zsys.B=Tzx*xsys.B
148+
zsys.B=Tzx.dot(xsys.B)
148149

149150
returnzsys,Tzx
150151

@@ -174,9 +175,9 @@ def modal_form(xsys):
174175
# Calculate eigenvalues and matrix of eigenvectors Tzx,
175176
eigval,eigvec=eig(xsys.A)
176177

177-
# Eigenvalues andaccording eigenvectors are not sorted,
178+
# Eigenvalues andcorresponding eigenvectors are not sorted,
178179
# thus modal transformation is ambiguous
179-
#Sorting eigenvalues andrespectivevectorsby largest to smallest eigenvalue
180+
#Sort eigenvalues and vectorsfrom largest to smallest eigenvalue
180181
idx=eigval.argsort()[::-1]
181182
eigval=eigval[idx]
182183
eigvec=eigvec[:,idx]
@@ -189,23 +190,18 @@ def modal_form(xsys):
189190

190191
# Keep track of complex conjugates (need only one)
191192
lst_conjugates= []
192-
Tzx=None
193+
Tzx=empty((0,xsys.A.shape[0]))# empty zero-height row matrix
193194
forval,vecinzip(eigval,eigvec.T):
194195
ifiscomplex(val):
195196
ifvalnotinlst_conjugates:
196197
lst_conjugates.append(val.conjugate())
197-
ifTzxisnotNone:
198-
Tzx=hstack((Tzx,hstack((vec.real.T,vec.imag.T))))
199-
else:
200-
Tzx=hstack((vec.real.T,vec.imag.T))
198+
Tzx=vstack((Tzx,vec.real,vec.imag))
201199
else:
202200
# if conjugate has already been seen, skip this eigenvalue
203201
lst_conjugates.remove(val)
204202
else:
205-
ifTzxisnotNone:
206-
Tzx=hstack((Tzx,vec.real.T))
207-
else:
208-
Tzx=vec.real.T
203+
Tzx=vstack((Tzx,vec.real))
204+
Tzx=Tzx.T
209205

210206
# Generate the system matrices for the desired canonical form
211207
zsys.A=solve(Tzx,xsys.A).dot(Tzx)

‎control/tests/canonical_test.py

Lines changed: 12 additions & 12 deletions
Original file line numberDiff line numberDiff line change
@@ -22,13 +22,13 @@ def test_reachable_form(self):
2222
D_true=42.0
2323

2424
# Perform a coordinate transform with a random invertible matrix
25-
T_true=np.matrix([[-0.27144004,-0.39933167,0.75634684,0.44135471],
25+
T_true=np.array([[-0.27144004,-0.39933167,0.75634684,0.44135471],
2626
[-0.74855725,-0.39136285,-0.18142339,-0.50356997],
2727
[-0.40688007,0.81416369,0.38002113,-0.16483334],
2828
[-0.44769516,0.15654653,-0.50060858,0.72419146]])
29-
A=np.linalg.solve(T_true,A_true)*T_true
29+
A=np.linalg.solve(T_true,A_true).dot(T_true)
3030
B=np.linalg.solve(T_true,B_true)
31-
C=C_true*T_true
31+
C=C_true.dot(T_true)
3232
D=D_true
3333

3434
# Create a state space system and convert it to the reachable canonical form
@@ -69,11 +69,11 @@ def test_modal_form(self):
6969
D_true=42.0
7070

7171
# Perform a coordinate transform with a random invertible matrix
72-
T_true=np.matrix([[-0.27144004,-0.39933167,0.75634684,0.44135471],
72+
T_true=np.array([[-0.27144004,-0.39933167,0.75634684,0.44135471],
7373
[-0.74855725,-0.39136285,-0.18142339,-0.50356997],
7474
[-0.40688007,0.81416369,0.38002113,-0.16483334],
7575
[-0.44769516,0.15654653,-0.50060858,0.72419146]])
76-
A=np.linalg.solve(T_true,A_true)*T_true
76+
A=np.linalg.solve(T_true,A_true).dot(T_true)
7777
B=np.linalg.solve(T_true,B_true)
7878
C=C_true*T_true
7979
D=D_true
@@ -98,9 +98,9 @@ def test_modal_form(self):
9898
C_true=np.array([[1,0,0,1]])
9999
D_true=np.array([[0]])
100100

101-
A=np.linalg.solve(T_true,A_true)*T_true
101+
A=np.linalg.solve(T_true,A_true).dot(T_true)
102102
B=np.linalg.solve(T_true,B_true)
103-
C=C_true*T_true
103+
C=C_true.dot(T_true)
104104
D=D_true
105105

106106
# Create state space system and convert to modal canonical form
@@ -132,9 +132,9 @@ def test_modal_form(self):
132132
C_true=np.array([[0,1,0,1]])
133133
D_true=np.array([[0]])
134134

135-
A=np.linalg.solve(T_true,A_true)*T_true
135+
A=np.linalg.solve(T_true,A_true).dot(T_true)
136136
B=np.linalg.solve(T_true,B_true)
137-
C=C_true*T_true
137+
C=C_true.dot(T_true)
138138
D=D_true
139139

140140
# Create state space system and convert to modal canonical form
@@ -173,13 +173,13 @@ def test_observable_form(self):
173173
D_true=42.0
174174

175175
# Perform a coordinate transform with a random invertible matrix
176-
T_true=np.matrix([[-0.27144004,-0.39933167,0.75634684,0.44135471],
176+
T_true=np.array([[-0.27144004,-0.39933167,0.75634684,0.44135471],
177177
[-0.74855725,-0.39136285,-0.18142339,-0.50356997],
178178
[-0.40688007,0.81416369,0.38002113,-0.16483334],
179179
[-0.44769516,0.15654653,-0.50060858,0.72419146]])
180-
A=np.linalg.solve(T_true,A_true)*T_true
180+
A=np.linalg.solve(T_true,A_true).dot(T_true)
181181
B=np.linalg.solve(T_true,B_true)
182-
C=C_true*T_true
182+
C=C_true.dot(T_true)
183183
D=D_true
184184

185185
# Create a state space system and convert it to the observable canonical form

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