examples: small corrections/changes in order to reduce CI time

examples/seismic/tti/operators.py

@@ -530,6 +530,7 @@ def JacobianOperator(model, geometry, space_order=4,
                      **kwargs):
     """
     Construct a Linearized Born operator in a TTI media.
+
     Parameters
     ----------
     model : Model
@@ -590,6 +591,7 @@ def JacobianAdjOperator(model, geometry, space_order=4,
                         save=True, **kwargs):
     """
     Construct a linearized JacobianAdjoint modeling Operator in a TTI media.
+
     Parameters
     ----------
     model : Model

examples/seismic/tti/tti_example.py

@@ -7,7 +7,7 @@
 from examples.seismic.tti import AnisotropicWaveSolver
 
 
-def tti_setup(shape=(50, 50, 50), spacing=(20.0, 20.0, 20.0), tn=500.0,
+def tti_setup(shape=(50, 50, 50), spacing=(20.0, 20.0, 20.0), tn=250.0,
               kernel='centered', space_order=4, nbl=10, preset='layers-tti',
               **kwargs):
 
@@ -21,7 +21,7 @@ def tti_setup(shape=(50, 50, 50), spacing=(20.0, 20.0, 20.0), tn=500.0,
     return AnisotropicWaveSolver(model, geometry, space_order=space_order, **kwargs)
 
 
-def run(shape=(50, 50, 50), spacing=(20.0, 20.0, 20.0), tn=500.0,
+def run(shape=(50, 50, 50), spacing=(20.0, 20.0, 20.0), tn=250.0,
         autotune=False, time_order=2, space_order=4, nbl=10,
         kernel='centered', full_run=False, **kwargs):
 

examples/seismic/tti/wavesolver.py

@@ -222,6 +222,7 @@ def jacobian(self, dm, src=None, rec=None, u0=None, v0=None, du=None, dv=None,
         """
         Linearized Born modelling function that creates the necessary
         data objects for running an adjoint modelling operator.
+
         Parameters
         ----------
         src : SparseTimeFunction or array_like, optional
@@ -285,6 +286,7 @@ def jacobian_adjoint(self, rec, u0, v0, du=None, dv=None, dm=None, vp=None,
         Gradient modelling function for computing the adjoint of the
         Linearized Born modelling function, ie. the action of the
         Jacobian adjoint on an input data.
+
         Parameters
         ----------
         rec : SparseTimeFunction

tests/test_adjoint.py

@@ -109,11 +109,11 @@ def test_adjoint_F(self, mkey, shape, kernel, space_order, setup_func):
         ('layers', (40, 50, 30), 'OT2', 8, acoustic_setup),
         ('layers', (40, 50, 30), 'OT2', 4, acoustic_setup),
         # 2D TTI tests with varying space orders
-        ('layers-tti', (30, 35), 'centered', 8, tti_setup),
-        ('layers-tti', (30, 35), 'centered', 4, tti_setup),
+        ('layers-tti', (20, 25), 'centered', 8, tti_setup),
+        ('layers-tti', (20, 25), 'centered', 4, tti_setup),
         # 3D TTI tests with varying space orders
-        ('layers-tti', (30, 35, 40), 'centered', 8, tti_setup),
-        ('layers-tti', (30, 35, 40), 'centered', 4, tti_setup),
+        ('layers-tti', (20, 25, 30), 'centered', 8, tti_setup),
+        ('layers-tti', (20, 25, 30), 'centered', 4, tti_setup),
     ])
     def test_adjoint_J(self, mkey, shape, kernel, space_order, setup_func):
         """

tests/test_gradient.py

@@ -144,10 +144,10 @@ def test_gradient_equivalence(self, shape, kernel, space_order, preset, nbl, dty
         (np.float32, 4, 'OT2', (70, 80), False, setup),
         (np.float64, 4, 'OT2', (70, 80), True, setup),
         (np.float64, 4, 'OT2', (70, 80), False, setup),
-        (np.float32, 4, 'centered', (70, 80), True, tti_setup),
-        (np.float32, 4, 'centered', (70, 80), False, tti_setup),
-        (np.float64, 4, 'centered', (70, 80), True, tti_setup),
-        (np.float64, 4, 'centered', (70, 80), False, tti_setup),
+        (np.float32, 4, 'centered', (50, 60), True, tti_setup),
+        (np.float32, 4, 'centered', (50, 60), False, tti_setup),
+        (np.float64, 4, 'centered', (50, 60), True, tti_setup),
+        (np.float64, 4, 'centered', (50, 60), False, tti_setup),
     ])
     def test_gradientFWI(self, dtype, space_order, kernel, shape, ckp, setup_func):
         """
@@ -167,7 +167,7 @@ def test_gradientFWI(self, dtype, space_order, kernel, shape, ckp, setup_func):
         """
         spacing = tuple(10. for _ in shape)
         wave = setup_func(shape=shape, spacing=spacing, dtype=dtype,
-                          kernel=kernel, space_order=space_order, nbl=40)
+                          kernel=kernel, tn=400.0, space_order=space_order, nbl=40)
 
         vel0 = Function(name='vel0', grid=wave.model.grid, space_order=space_order)
         smooth(vel0, wave.model.vp)