/[escript]/trunk/finley/test/python/run_simplesolve.py
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Revision 1703 - (show annotations)
Thu Aug 14 05:34:25 2008 UTC (10 years, 10 months ago) by artak
File MIME type: text/x-python
File size: 18575 byte(s)
TFQMR solver is added to PASO solver. It is not parallelised yet.
1 #
2 # $Id$
3 #
4 #######################################################
5 #
6 # Copyright 2003-2007 by ACceSS MNRF
7 # Copyright 2007 by University of Queensland
8 #
9 # http://esscc.uq.edu.au
10 # Primary Business: Queensland, Australia
11 # Licensed under the Open Software License version 3.0
12 # http://www.opensource.org/licenses/osl-3.0.php
13 #
14 #######################################################
15 #
16
17 """
18 Test suite for the linearPDE and pdetools test on finley
19
20 @remark:
21
22 @var __author__: name of author
23 @var __licence__: licence agreement
24 @var __url__: url entry point on documentation
25 @var __version__: version
26 @var __date__: date of the version
27 """
28
29 __copyright__=""" Copyright (c) 2006 by ACcESS MNRF
30 http://www.access.edu.au
31 Primary Business: Queensland, Australia"""
32 __license__="""Licensed under the Open Software License version 3.0
33 http://www.opensource.org/licenses/osl-3.0.php"""
34 __author__="Lutz Gross, l.gross@uq.edu.au"
35 __url__="http://www.iservo.edu.au/esys/escript"
36 __version__="$Revision: 859 $"
37 __date__="$Date: 2006-09-26 12:19:18 +1000 (Tue, 26 Sep 2006) $"
38
39 import unittest, sys
40
41 from esys.escript import *
42 from esys.finley import Rectangle,Brick
43 from esys.escript.linearPDEs import LinearPDE
44 OPTIMIZE=False
45 SOLVER_VERBOSE=False
46 # setNumberOfThreads(2)
47
48 try:
49 FINLEY_TEST_DATA=os.environ['FINLEY_TEST_DATA']
50 except KeyError:
51 FINLEY_TEST_DATA='.'
52
53 FINLEY_TEST_MESH_PATH=FINLEY_TEST_DATA+"/data_meshes/"
54
55 # number of elements in the spatial directions
56 NE0=8
57 NE1=10
58 NE2=12
59
60 NE0=12
61 NE1=12
62 NE2=8
63
64 SOLVER_TOL=1.e-8
65 REL_TOL=1.e-6
66
67 FAC_DIAG=1.
68 FAC_OFFDIAG=-0.4
69
70
71 class SimpleSolve_Rectangle_Order1_SinglePDE_Paso_BICGSTAB_Jacobi(unittest.TestCase):
72 def test_solve(self):
73 # Tell about how many MPI CPUs and OpenMP threads
74 printParallelThreadCounts()
75 domain=Rectangle(NE0,NE1,1, optimize=OPTIMIZE)
76 x=Solution(domain).getX()
77 # --- set exact solution ----
78 u_ex=Scalar(0,Solution(domain))
79 u_ex=1.+2.*x[0]+3.*x[1]
80 # --- set exact gradient -----------
81 g_ex=Data(0.,(2,),Solution(domain))
82 g_ex[0]=2.
83 g_ex[1]=3.
84 # -------- test gradient --------------------------------
85 g=grad(u_ex)
86 self.failUnless(Lsup(g_ex-g)<REL_TOL*Lsup(g_ex))
87 # -------- set-up PDE -----------------------------------
88 pde=LinearPDE(domain,numEquations=1)
89 mask=whereZero(x[0])
90 pde.setValue(r=u_ex,q=mask)
91 pde.setValue(A=kronecker(2),y=inner(g_ex,domain.getNormal()))
92 # -------- get the solution ---------------------------
93 pde.setTolerance(SOLVER_TOL)
94 pde.setSolverMethod(pde.BICGSTAB,pde.JACOBI)
95 pde.setSolverPackage(pde.PASO)
96 u=pde.getSolution(verbose=SOLVER_VERBOSE)
97 # -------- test the solution ---------------------------
98 error=Lsup(u-u_ex)/Lsup(u_ex)
99 self.failUnless(error<REL_TOL*Lsup(u_ex), "solution error %s is too big."%error)
100 class SimpleSolve_Rectangle_Order1_SinglePDE_Paso_PCG_Jacobi(unittest.TestCase):
101 def test_solve(self):
102 domain=Rectangle(NE0,NE1,1, optimize=OPTIMIZE)
103 x=Solution(domain).getX()
104 # --- set exact solution ----
105 u_ex=Scalar(0,Solution(domain))
106 u_ex=1.+2.*x[0]+3.*x[1]
107 # --- set exact gradient -----------
108 g_ex=Data(0.,(2,),Solution(domain))
109 g_ex[0]=2.
110 g_ex[1]=3.
111 # -------- test gradient --------------------------------
112 g=grad(u_ex)
113 self.failUnless(Lsup(g_ex-g)<REL_TOL*Lsup(g_ex))
114 # -------- set-up PDE -----------------------------------
115 pde=LinearPDE(domain,numEquations=1)
116 mask=whereZero(x[0])
117 pde.setValue(r=u_ex,q=mask)
118 pde.setValue(A=kronecker(2),y=inner(g_ex,domain.getNormal()))
119 # -------- get the solution ---------------------------
120 pde.setTolerance(SOLVER_TOL)
121 pde.setSolverMethod(pde.PCG,pde.JACOBI)
122 pde.setSolverPackage(pde.PASO)
123 u=pde.getSolution(verbose=SOLVER_VERBOSE)
124 # -------- test the solution ---------------------------
125 error=Lsup(u-u_ex)/Lsup(u_ex)
126 self.failUnless(error<REL_TOL*Lsup(u_ex), "solution error %s is too big."%error)
127 class SimpleSolve_Rectangle_Order1_SystemPDE_Paso_PCG_Jacobi(unittest.TestCase):
128 def test_solve(self):
129 domain=Rectangle(NE0,NE1,1,optimize=OPTIMIZE)
130 x=Solution(domain).getX()
131 # --- set exact solution ----
132 u_ex=Vector(0,Solution(domain))
133 u_ex[0]=1.+2.*x[0]+3.*x[1]
134 u_ex[1]=-1.+3.*x[0]+2.*x[1]
135 # --- set exact gradient -----------
136 g_ex=Data(0.,(2,2),Solution(domain))
137 g_ex[0,0]=2.
138 g_ex[0,1]=3.
139 g_ex[1,0]=3.
140 g_ex[1,1]=2.
141 # -------- test gradient --------------------------------
142 self.failUnless(Lsup(g_ex-grad(u_ex))<REL_TOL*Lsup(g_ex))
143 # -------- set-up PDE -----------------------------------
144 pde=LinearPDE(domain,numEquations=2)
145 mask=whereZero(x[0])
146 pde.setValue(r=u_ex,q=mask*numarray.ones(2,))
147 A=Tensor4(0,Function(domain))
148 A[0,:,0,:]=kronecker(2)
149 A[1,:,1,:]=kronecker(2)
150 Y=Vector(0.,Function(domain))
151 Y[0]=u_ex[0]*FAC_DIAG+u_ex[1]*FAC_OFFDIAG
152 Y[1]=u_ex[1]*FAC_DIAG+u_ex[0]*FAC_OFFDIAG
153 pde.setValue(A=A,
154 D=kronecker(2)*(FAC_DIAG-FAC_OFFDIAG)+numarray.ones((2,2))*FAC_OFFDIAG,
155 Y=Y,
156 y=matrixmult(g_ex,domain.getNormal()))
157 # -------- get the solution ---------------------------
158 pde.setTolerance(SOLVER_TOL)
159 pde.setSolverMethod(pde.PCG,pde.JACOBI)
160 pde.setSolverPackage(pde.PASO)
161 u=pde.getSolution(verbose=SOLVER_VERBOSE)
162 # -------- test the solution ---------------------------
163 error=Lsup(u-u_ex)/Lsup(u_ex)
164 self.failUnless(error<REL_TOL*Lsup(u_ex), "solution error %s is too big."%error)
165 class SimpleSolve_Rectangle_Order2_SinglePDE_Paso_PCG_Jacobi(unittest.TestCase):
166 def test_solve(self):
167 domain=Rectangle(NE0,NE1,2,l0=1.,l1=1,optimize=OPTIMIZE)
168 x=Solution(domain).getX()
169 # --- set exact solution ----
170 u_ex=1.+2.*x[0]+3.*x[1]+4.*x[0]**2+5.*x[1]*x[0]+6.*x[1]**2
171 # --- set exact gradient -----------
172 g_ex=Data(0.,(2,),Solution(domain))
173 g_ex[0]=2.+8.*x[0]+5.*x[1]
174 g_ex[1]=3.+5.*x[0]+12.*x[1]
175 # -------- test gradient --------------------------------
176 self.failUnless(Lsup(g_ex-grad(u_ex))<REL_TOL*Lsup(g_ex))
177 # -------- set-up PDE -----------------------------------
178 pde=LinearPDE(domain,numEquations=1)
179 mask=whereZero(x[0])
180 pde.setValue(r=u_ex,q=mask)
181 pde.setValue(A=kronecker(2),y=inner(g_ex,domain.getNormal()),Y=-20.)
182 # -------- get the solution ---------------------------
183 pde.setTolerance(SOLVER_TOL)
184 pde.setSolverMethod(pde.PCG,pde.JACOBI)
185 pde.setSolverPackage(pde.PASO)
186 u=pde.getSolution(verbose=SOLVER_VERBOSE)
187 # -------- test the solution ---------------------------
188 error=Lsup(u-u_ex)/Lsup(u_ex)
189 self.failUnless(error<REL_TOL*Lsup(u_ex), "solution error %s is too big."%error)
190 class SimpleSolve_Rectangle_Order2_SystemPDE_Paso_PCG_Jacobi(unittest.TestCase):
191 def test_solve(self):
192 domain=Rectangle(NE0,NE1,2,optimize=OPTIMIZE)
193 x=Solution(domain).getX()
194 # --- set exact solution ----
195 u_ex=Vector(0,Solution(domain))
196 u_ex[0]=1.+2.*x[0]+3.*x[1]+4.*x[0]**2+5.*x[1]*x[0]+6.*x[1]**2
197 u_ex[1]=-1.+4.*x[0]+2.*x[1]+1.*x[0]**2+6.*x[1]*x[0]+4.*x[1]**2
198 # --- set exact gradient -----------
199 g_ex=Data(0.,(2,2),Solution(domain))
200 g_ex[0,0]=2.+8.*x[0]+5.*x[1]
201 g_ex[0,1]=3.+5.*x[0]+12.*x[1]
202 g_ex[1,0]=4.+2.*x[0]+6.*x[1]
203 g_ex[1,1]=2.+6.*x[0]+8.*x[1]
204 # -------- test gradient --------------------------------
205 self.failUnless(Lsup(g_ex-grad(u_ex))<REL_TOL*Lsup(g_ex))
206 # -------- set-up PDE -----------------------------------
207 pde=LinearPDE(domain,numEquations=2)
208 mask=whereZero(x[0])
209 pde.setValue(r=u_ex,q=mask*numarray.ones(2,))
210 A=Tensor4(0,Function(domain))
211 A[0,:,0,:]=kronecker(2)
212 A[1,:,1,:]=kronecker(2)
213 Y=Vector(0.,Function(domain))
214 Y[0]=u_ex[0]*FAC_DIAG+u_ex[1]*FAC_OFFDIAG
215 Y[1]=u_ex[1]*FAC_DIAG+u_ex[0]*FAC_OFFDIAG
216 pde.setValue(A=A,
217 D=kronecker(2)*(FAC_DIAG-FAC_OFFDIAG)+numarray.ones((2,2))*FAC_OFFDIAG,
218 Y=Y-[20.,10.],
219 y=matrixmult(g_ex,domain.getNormal()))
220 # -------- get the solution ---------------------------
221 pde.setTolerance(SOLVER_TOL)
222 pde.setSolverMethod(pde.PCG,pde.JACOBI)
223 pde.setSolverPackage(pde.PASO)
224 u=pde.getSolution(verbose=SOLVER_VERBOSE)
225 # -------- test the solution ---------------------------
226 error=Lsup(u-u_ex)/Lsup(u_ex)
227 self.failUnless(error<REL_TOL*Lsup(u_ex), "solution error %s is too big."%error)
228 class SimpleSolve_Brick_Order1_SinglePDE_Paso_PCG_Jacobi(unittest.TestCase):
229 def test_solve(self):
230 domain=Brick(NE0,NE1,NE2,1,optimize=OPTIMIZE)
231 x=Solution(domain).getX()
232 u_ex=1.+2.*x[0]+3.*x[1]+4.*x[2]
233 # --- set exact gradient -----------
234 g_ex=Data(0.,(3,),Solution(domain))
235 g_ex[0]=2.
236 g_ex[1]=3.
237 g_ex[2]=4.
238 # -------- test gradient --------------------------------
239 self.failUnless(Lsup(g_ex-grad(u_ex))<REL_TOL*Lsup(g_ex))
240 # -------- set-up PDE -----------------------------------
241 pde=LinearPDE(domain,numEquations=1)
242 mask=whereZero(x[0])
243 pde.setValue(r=u_ex,q=mask)
244 pde.setValue(A=kronecker(3),y=inner(g_ex,domain.getNormal()))
245 # -------- get the solution ---------------------------
246 pde.setTolerance(SOLVER_TOL)
247 pde.setSolverMethod(pde.PCG,pde.JACOBI)
248 pde.setSolverPackage(pde.PASO)
249 u=pde.getSolution(verbose=SOLVER_VERBOSE)
250 # -------- test the solution ---------------------------
251 error=Lsup(u-u_ex)/Lsup(u_ex)
252 self.failUnless(error<REL_TOL*Lsup(u_ex), "solution error %s is too big."%error)
253 class SimpleSolve_Brick_Order1_SystemPDE_Paso_PCG_Jacobi(unittest.TestCase):
254 def test_solve(self):
255 domain=Brick(NE0,NE1,NE2,1,optimize=OPTIMIZE)
256 x=Solution(domain).getX()
257 # --- set exact solution ----
258 u_ex=Vector(0,Solution(domain))
259 u_ex[0]=1.+2.*x[0]+3.*x[1]+4.*x[2]
260 u_ex[1]=-1.+4.*x[0]+1.*x[1]-2.*x[2]
261 u_ex[2]=5.+8.*x[0]+4.*x[1]+5.*x[2]
262 # --- set exact gradient -----------
263 g_ex=Data(0.,(3,3),Solution(domain))
264 g_ex[0,0]=2.
265 g_ex[0,1]=3.
266 g_ex[0,2]=4.
267 g_ex[1,0]=4.
268 g_ex[1,1]=1.
269 g_ex[1,2]=-2.
270 g_ex[2,0]=8.
271 g_ex[2,1]=4.
272 g_ex[2,2]=5.
273 # -------- test gradient --------------------------------
274 self.failUnless(Lsup(g_ex-grad(u_ex))<REL_TOL*Lsup(g_ex))
275 # -------- set-up PDE -----------------------------------
276 pde=LinearPDE(domain,numEquations=3)
277 mask=whereZero(x[0])
278 pde.setValue(r=u_ex,q=mask*numarray.ones(3,))
279 A=Tensor4(0,Function(domain))
280 A[0,:,0,:]=kronecker(3)
281 A[1,:,1,:]=kronecker(3)
282 A[2,:,2,:]=kronecker(3)
283 Y=Vector(0.,Function(domain))
284 Y[0]=u_ex[0]*FAC_DIAG+u_ex[2]*FAC_OFFDIAG+u_ex[1]*FAC_OFFDIAG
285 Y[1]=u_ex[1]*FAC_DIAG+u_ex[0]*FAC_OFFDIAG+u_ex[2]*FAC_OFFDIAG
286 Y[2]=u_ex[2]*FAC_DIAG+u_ex[1]*FAC_OFFDIAG+u_ex[0]*FAC_OFFDIAG
287 pde.setValue(A=A,
288 D=kronecker(3)*(FAC_DIAG-FAC_OFFDIAG)+numarray.ones((3,3))*FAC_OFFDIAG,
289 Y=Y,
290 y=matrixmult(g_ex,domain.getNormal()))
291 # -------- get the solution ---------------------------
292 pde.setTolerance(SOLVER_TOL)
293 pde.setSolverMethod(pde.PCG,pde.JACOBI)
294 pde.setSolverPackage(pde.PASO)
295 u=pde.getSolution(verbose=SOLVER_VERBOSE)
296 # -------- test the solution ---------------------------
297 error=Lsup(u-u_ex)/Lsup(u_ex)
298 self.failUnless(error<REL_TOL*Lsup(u_ex), "solution error %s is too big."%error)
299 class SimpleSolve_Brick_Order2_SinglePDE_Paso_PCG_Jacobi(unittest.TestCase):
300 def test_solve(self):
301 domain=Brick(NE0,NE1,NE2,2,optimize=OPTIMIZE)
302 x=Solution(domain).getX()
303 # --- set exact solution ----
304 u_ex=1.+2.*x[0]+3.*x[1]+4.*x[2]+6.*x[0]*x[1]+7.*x[1]*x[2]+8.*x[2]*x[0]+9.*x[0]**2+10.*x[1]**2+11.*x[2]**2
305 # --- set exact gradient -----------
306 g_ex=Data(0.,(3,),Solution(domain))
307 g_ex[0]=2.+6.*x[1]+8.*x[2]+18.*x[0]
308 g_ex[1]=3.+6.*x[0]+7.*x[2]+20.*x[1]
309 g_ex[2]=4.+7.*x[1]+8.*x[0]+22.*x[2]
310 # -------- test gradient --------------------------------
311 self.failUnless(Lsup(g_ex-grad(u_ex))<REL_TOL*Lsup(g_ex))
312 # -------- set-up PDE -----------------------------------
313 pde=LinearPDE(domain,numEquations=1)
314 mask=whereZero(x[0])
315 pde.setValue(r=u_ex,q=mask)
316 pde.setValue(A=kronecker(3),y=inner(g_ex,domain.getNormal()),Y=-60.)
317 # -------- get the solution ---------------------------
318 pde.setTolerance(SOLVER_TOL)
319 pde.setSolverMethod(pde.PCG,pde.JACOBI)
320 pde.setSolverPackage(pde.PASO)
321 u=pde.getSolution(verbose=SOLVER_VERBOSE)
322 # -------- test the solution ---------------------------
323 error=Lsup(u-u_ex)/Lsup(u_ex)
324 self.failUnless(error<REL_TOL*Lsup(u_ex), "solution error %s is too big."%error)
325 class SimpleSolve_Brick_Order2_SystemPDE_Paso_PCG_Jacobi(unittest.TestCase):
326 def test_solve(self):
327 domain=Brick(NE0,NE1,NE2,2,optimize=OPTIMIZE)
328 x=Solution(domain).getX()
329 # --- set exact solution ----
330 u_ex=Vector(0,Solution(domain))
331 u_ex[0]=1.+2.*x[0]+3.*x[1]+4.*x[2]+6.*x[0]*x[1]+7.*x[1]*x[2]+8.*x[2]*x[0]+9.*x[0]**2+10.*x[1]**2+11.*x[2]**2
332 u_ex[1]=2.+4.*x[0]+1.*x[1]-6.*x[2]+3.*x[0]*x[1]+2.*x[1]*x[2]-8.*x[2]*x[0]-2.*x[0]**2+7.*x[1]**2+5.*x[2]**2
333 u_ex[2]=-2.+7.*x[0]+9.*x[1]+2*x[2]-6.*x[0]*x[1]+8.*x[1]*x[2]+2.*x[2]*x[0]+2.*x[0]**2+8.*x[1]**2+1.*x[2]**2
334 # --- set exact gradient -----------
335 g_ex=Data(0.,(3,3),Solution(domain))
336 g_ex[0,0]=2.+6.*x[1]+8.*x[2]+18.*x[0]
337 g_ex[0,1]=3.+6.*x[0]+7.*x[2]+20.*x[1]
338 g_ex[0,2]=4.+7.*x[1]+8.*x[0]+22.*x[2]
339 g_ex[1,0]=4.+3.*x[1]-8.*x[2]-4.*x[0]
340 g_ex[1,1]=1+3.*x[0]+2.*x[2]+14.*x[1]
341 g_ex[1,2]=-6.+2.*x[1]-8.*x[0]+10.*x[2]
342 g_ex[2,0]=7.-6.*x[1]+2.*x[2]+4.*x[0]
343 g_ex[2,1]=9.-6.*x[0]+8.*x[2]+16.*x[1]
344 g_ex[2,2]=2+8.*x[1]+2.*x[0]+2.*x[2]
345 # -------- test gradient --------------------------------
346 self.failUnless(Lsup(g_ex-grad(u_ex))<REL_TOL*Lsup(g_ex))
347 # -------- set-up PDE -----------------------------------
348 pde=LinearPDE(domain,numEquations=3)
349 mask=whereZero(x[0])
350 pde.setValue(r=u_ex,q=mask*numarray.ones(3,))
351 Y=Vector(0.,Function(domain))
352 Y[0]=u_ex[0]*FAC_DIAG+u_ex[2]*FAC_OFFDIAG+u_ex[1]*FAC_OFFDIAG
353 Y[1]=u_ex[1]*FAC_DIAG+u_ex[0]*FAC_OFFDIAG+u_ex[2]*FAC_OFFDIAG
354 Y[2]=u_ex[2]*FAC_DIAG+u_ex[1]*FAC_OFFDIAG+u_ex[0]*FAC_OFFDIAG
355 A=Tensor4(0,Function(domain))
356 A[0,:,0,:]=kronecker(3)
357 A[1,:,1,:]=kronecker(3)
358 A[2,:,2,:]=kronecker(3)
359 pde.setValue(A=A,
360 D=kronecker(3)*(FAC_DIAG-FAC_OFFDIAG)+numarray.ones((3,3))*FAC_OFFDIAG,
361 Y=Y-numarray.array([60.,20.,22.]),
362 y=matrixmult(g_ex,domain.getNormal()))
363 # -------- get the solution ---------------------------
364 pde.setTolerance(SOLVER_TOL)
365 pde.setSolverMethod(pde.PCG,pde.JACOBI)
366 pde.setSolverPackage(pde.PASO)
367 u=pde.getSolution(verbose=SOLVER_VERBOSE)
368 # -------- test the solution ---------------------------
369 error=Lsup(u-u_ex)/Lsup(u_ex)
370 self.failUnless(error<REL_TOL*Lsup(u_ex), "solution error %s is too big."%error)
371
372 class SimpleSolve_Rectangle_Order1_SinglePDE_Paso_TFQMR_Jacobi(unittest.TestCase):
373 def test_solve(self):
374 domain=Rectangle(NE0,NE1,1, optimize=OPTIMIZE)
375 x=Solution(domain).getX()
376 # --- set exact solution ----
377 u_ex=Scalar(0,Solution(domain))
378 u_ex=1.+2.*x[0]+3.*x[1]
379 # --- set exact gradient -----------
380 g_ex=Data(0.,(2,),Solution(domain))
381 g_ex[0]=2.
382 g_ex[1]=3.
383 # -------- test gradient --------------------------------
384 g=grad(u_ex)
385 self.failUnless(Lsup(g_ex-g)<REL_TOL*Lsup(g_ex))
386 # -------- set-up PDE -----------------------------------
387 pde=LinearPDE(domain,numEquations=1)
388 mask=whereZero(x[0])
389 pde.setValue(r=u_ex,q=mask)
390 pde.setValue(A=kronecker(2),y=inner(g_ex,domain.getNormal()))
391 # -------- get the solution ---------------------------
392 pde.setTolerance(SOLVER_TOL)
393 pde.setSolverMethod(pde.TFQMR,pde.JACOBI)
394 pde.setSolverPackage(pde.PASO)
395 u=pde.getSolution(verbose=SOLVER_VERBOSE)
396 # -------- test the solution ---------------------------
397 error=Lsup(u-u_ex)/Lsup(u_ex)
398 self.failUnless(error<REL_TOL*Lsup(u_ex), "solution error %s is too big."%error)
399
400 if __name__ == '__main__':
401 suite = unittest.TestSuite()
402 suite.addTest(unittest.makeSuite(SimpleSolve_Rectangle_Order1_SinglePDE_Paso_BICGSTAB_Jacobi))
403 suite.addTest(unittest.makeSuite(SimpleSolve_Rectangle_Order1_SinglePDE_Paso_PCG_Jacobi))
404 suite.addTest(unittest.makeSuite(SimpleSolve_Rectangle_Order1_SystemPDE_Paso_PCG_Jacobi))
405 suite.addTest(unittest.makeSuite(SimpleSolve_Rectangle_Order2_SinglePDE_Paso_PCG_Jacobi))
406 suite.addTest(unittest.makeSuite(SimpleSolve_Rectangle_Order2_SystemPDE_Paso_PCG_Jacobi))
407 suite.addTest(unittest.makeSuite(SimpleSolve_Brick_Order1_SinglePDE_Paso_PCG_Jacobi))
408 suite.addTest(unittest.makeSuite(SimpleSolve_Brick_Order1_SystemPDE_Paso_PCG_Jacobi))
409 suite.addTest(unittest.makeSuite(SimpleSolve_Brick_Order2_SinglePDE_Paso_PCG_Jacobi))
410 suite.addTest(unittest.makeSuite(SimpleSolve_Brick_Order2_SystemPDE_Paso_PCG_Jacobi))
411 suite.addTest(unittest.makeSuite(SimpleSolve_Rectangle_Order1_SinglePDE_Paso_TFQMR_Jacobi))
412
413 s=unittest.TextTestRunner(verbosity=2).run(suite)
414 if not s.wasSuccessful(): sys.exit(1)

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