ab09nd iwork expression fix

slycot/src/analysis.pyf

@@ -315,7 +315,7 @@ subroutine ab09nd(dico,job,equil,ordsel,n,m,p,nr,alpha,a,lda,b,ldb,c,ldc,d,ldd,n
     double precision intent(out),dimension(n),depend(n) :: hsv
     double precision :: tol1 =0.0
     double precision :: tol2 =0.0
-    integer intent(hide,cache),dimension(max(m,p)) :: iwork
+    integer intent(hide,cache),dimension(max(1,2*n)) :: iwork
     double precision intent(hide,cache),dimension(ldwork) :: dwork
     integer optional :: ldwork = max(1,n*(2*n+max(n,max(m,p))+5)+n*(n+1)/2)
     integer intent(out) :: iwarn

slycot/tests/test_ab09nd.py

@@ -0,0 +1,93 @@
+# ab09nd - model order reduction
+
+import numpy as np
+from slycot import ab09nd
+
+# SLICOT reference test; see SLICOT-Reference/examples/AB09ND.dat, AB09ND.res, TAB09ND.f
+def test_slicot_ref():
+    n = 7
+    m = 2
+    p = 3
+    nr = None # Slycot uses None for ordsel = 'A'
+    alpha = -0.6
+    tol1 = 1e-1
+    tol2 = 1e-14
+    dico = 'C'
+    job = 'N'
+    equil = 'N'
+
+    a = np.array([[-0.04165, 0.0000, 4.9200, -4.9200, 0.0000, 0.0000, 0.0000],
+                  [-5.2100, -12.500, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000],
+                  [0.0000, 3.3300, -3.3300, 0.0000, 0.0000, 0.0000, 0.0000],
+                  [0.5450, 0.0000, 0.0000, 0.0000, -0.5450, 0.0000, 0.0000],
+                  [0.0000, 0.0000, 0.0000, 4.9200, -0.04165, 0.0000, 4.9200],
+                  [0.0000, 0.0000, 0.0000, 0.0000, -5.2100, -12.500, 0.0000],
+                  [0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 3.3300, -3.3300]])
+
+    b = np.array([[0.0000, 0.0000],
+                  [12.500, 0.0000],
+                  [0.0000, 0.0000],
+                  [0.0000, 0.0000],
+                  [0.0000, 0.0000],
+                  [0.0000, 12.500],
+                  [0.0000, 0.0000]])
+
+    c = np.array([[1.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000],
+                  [0.0000, 0.0000, 0.0000, 1.0000, 0.0000, 0.0000, 0.0000],
+                  [0.0000, 0.0000, 0.0000, 0.0000, 1.0000, 0.0000, 0.0000]])
+
+    d = np.zeros((3,2))
+
+    nr, ar, br, cr, dr, ns, hsv = \
+            ab09nd(dico, job, equil, n, m, p, a, b, c, d, alpha, nr, tol1, tol2)
+
+    # reference values
+    ref_nr = 5
+    ref_hsv = np.array([1.9178, 0.8621, 0.7666, 0.0336, 0.0246])
+    ref_ar = np.array([[-0.5181, -1.1084,  0.0000,  0.0000,  0.0000],
+                       [ 8.8157, -0.5181,  0.0000,  0.0000,  0.0000],
+                       [ 0.0000,  0.0000,  0.5847,  0.0000,  1.9230],
+                       [ 0.0000,  0.0000,  0.0000, -1.6606,  0.0000],
+                       [ 0.0000,  0.0000, -4.3823,  0.0000, -3.2922]])
+
+    ref_br = np.array([[-1.2837,  1.2837],
+                       [-0.7522,  0.7522],
+                       [-0.6379, -0.6379],
+                       [ 2.0656, -2.0656],
+                       [-3.9315, -3.9315]])
+
+    ref_cr = np.array([[-0.1380, -0.6445, -0.6416, -0.6293, 0.2526],
+                       [ 0.6246,  0.0196,  0.0000,  0.4107, 0.0000],
+                       [ 0.1380,  0.6445, -0.6416,  0.6293, 0.2526]])
+
+    ref_dr = np.array([[ 0.0582, -0.0090],
+                       [ 0.0015, -0.0015],
+                       [-0.0090,  0.0582]])
+
+    assert nr == ref_nr
+
+    np.testing.assert_array_almost_equal(hsv[:nr], ref_hsv, decimal=4)
+    np.testing.assert_array_almost_equal(ar, ref_ar, decimal=4)
+    np.testing.assert_array_almost_equal(br, ref_br, decimal=4)
+    np.testing.assert_array_almost_equal(cr, ref_cr, decimal=4)
+    np.testing.assert_array_almost_equal(dr, ref_dr, decimal=4)
+
+
+# gh-242 regression test
+# iwork was incorrectly sized
+def test_gh242_regression():
+    n = 67
+    m = 1
+    p = 1
+
+    a = -np.eye(n)
+    b = np.zeros((n, m))
+    c = np.zeros((p, n))
+    d = np.array([[42.24]])
+
+    nr, ar, br, cr, dr, ns, hsv = \
+        ab09nd(dico='C', job='B', equil='S', n=a.shape[0],
+               m=b.shape[1], p=c.shape[0], A=a, B=b, C=c, D=d)
+
+    assert nr == 0
+    np.testing.assert_equal(d, dr)