Implement tests

.github/workflows/linux.yml

@@ -63,7 +63,7 @@ jobs:
           - python-version: "3.12"
             name: full
             os: ubuntu
-            conda: "numba scipy xarray tqdm h5py discretize matplotlib"
+            conda: "numba scipy xarray tqdm h5py discretize matplotlib pygimli"
 
     env:
       # Used for coveralls flag
@@ -105,7 +105,7 @@ jobs:
           conda config --show-sources
           conda config --show
           conda info -a
-          conda install ${{ matrix.case.conda }} pytest pytest-cov pytest-console-scripts coveralls flake8 setuptools-scm
+          conda install -c conda-forge -c gimli ${{ matrix.case.conda }} pytest pytest-cov pytest-console-scripts coveralls flake8 setuptools-scm
 
       - name: Conda list
         shell: bash -l {0}

emg3d/inversion/pygimli.py

@@ -94,10 +94,10 @@ def __init__(self, simulation, markers=None, pgthreads=2):
 
         # Set markers.
         if markers is not None:
-            mesh.setCellMarkers(markers.ravel('F'))
             self.markers = markers
         else:
-            self.markers = np.zeros(simulation.model.size, dtype=int)
+            self.markers = np.arange(simulation.model.size, dtype=int)
+        mesh.setCellMarkers(self.markers.ravel('F'))
         # Store original props; required if a region is set to ``background``.
         self._model = simulation.model.property_x.copy()
         # Store volumes; required if a region is set to ``single``.
@@ -118,7 +118,7 @@ def __init__(self, simulation, markers=None, pgthreads=2):
         self.setJacobian(self.J)
 
     def response(self, model):
-        """Create synthetic data for provided model."""
+        """Create synthetic data for provided pyGIMLi model."""
 
         # Clean emg3d-simulation, so things are recomputed
         self.simulation.clean('computed')

tests/test_pygimli.py

@@ -1,7 +1,7 @@
-# import os
 import pytest
+import logging
 import numpy as np
-# from numpy.testing import assert_allclose
+from numpy.testing import assert_allclose
 
 import emg3d
 from emg3d.inversion import pygimli as ipygimli
@@ -16,90 +16,177 @@
     import discretize
 except ImportError:
     discretize = None
-try:
-    import h5py
-except ImportError:
-    h5py = False
 try:
     import pygimli
 except ImportError:
-    pygimli = False
+    pygimli = None
+
+
+LOGGER = logging.getLogger(__name__)
 
 
 @pytest.mark.skipif(xarray is None, reason="xarray not installed.")
-@pytest.mark.skipif(pygimli is None, reason="pygimli not installed.")
 class TestPygimli():
 
-    survey = emg3d.surveys.Survey(
-        sources=emg3d.TxElectricDipole((0, 0, -250, 0, 0)),
-        receivers=emg3d.RxElectricPoint((0, 0, -1250, 0, 0)),
-        frequencies=1.0,
-        noise_floor=1e-17,
-        relative_error=0.05,
-    )
-
-    hx = np.ones(3)*500.0
-    grid = emg3d.TensorMesh([hx, hx, hx], [-750, -750, -1500])
-
-    model_start = emg3d.Model(grid, 1.0, mapping='Conductivity')
-    model_true = emg3d.Model(grid, 1.0, mapping='Conductivity')
-    model_true.property_x[1, 1, 1] = 1/1000
-
-    # Create an emg3d Simulation instance
-    sim = emg3d.simulations.Simulation(
-        survey=survey.copy(),
-        model=model_true,
-        gridding='both',
-        max_workers=1,
-        gridding_opts={'center_on_edge': False},
-        receiver_interpolation='linear',
-        solver_opts={'tol_gradient': 1e-3},
-        tqdm_opts=False,
-    )
-    sim.compute(observed=True)
-    sim.clean('computed')
-
-    sim.model = model_start
-
-    sim.compute()
-    sim.survey.data['start'] = sim.survey.data.synthetic
-    sim.clean('computed')
-
-    sim.tol_gradient = 1e-2  # Reduce further
-    model_start = sim.model.copy()
-    grid = model_true.grid
-
-    markers = np.zeros(model_start.shape, dtype=int)
-    markers[1, 1, 1] = 1
-
-    # Without regions
-    fop = ipygimli.Kernel(simulation=sim, pgthreads=1)
-
-    INV = ipygimli.Inversion(fop=fop)
-    INV.inv.setCGLSTolerance(10)
-    INV.inv.setMaxCGLSIter(30)
-
-    errmodel = INV.run(maxIter=2, lam=0.10)
-
-    markers = np.zeros(model_start.shape, dtype=int)
-    markers[1, 1, 1] = 1
-    markers[0, :, :] = 2
-    markers[2, :, :] = 3
-
-    # With regions
-    fop = ipygimli.Kernel(simulation=sim, markers=markers, pgthreads=1)
-
-    INV = ipygimli.Inversion(fop=fop)
-    INV.inv.setCGLSTolerance(10)
-    INV.inv.setMaxCGLSIter(30)
-
-    INV.fop.setRegionProperties(1, limits=(0.0001, 2), startModel=1.0)
-    INV.fop.setRegionProperties(0, background=True)
-    INV.fop.setRegionProperties(2, fix=True, startModel=1)
-    INV.fop.setRegionProperties(
-            3, single=True, limits=(0.99999, 1.00001), startModel=1.0)
-
-    errmodel = INV.run(maxIter=2, lam=1)
+    if xarray is not None:
+        # Create data
+        survey = emg3d.surveys.Survey(
+            sources=emg3d.TxElectricDipole((0, 0, -250, 0, 0)),
+            receivers=emg3d.RxElectricPoint((0, 0, -1250, 0, 0)),
+            frequencies=1.0,
+            noise_floor=1e-17,
+            relative_error=0.05,
+        )
+
+        hx = np.ones(3)*500.0
+        grid = emg3d.TensorMesh([hx, hx, hx], [-750, -750, -1500])
+
+        model_start = emg3d.Model(grid, 1.0, mapping='Conductivity')
+        model_true = emg3d.Model(grid, 1.0, mapping='Conductivity')
+        model_true.property_x[1, 1, 1] = 1/1000
+
+        # Create an emg3d Simulation instance
+        sim = emg3d.simulations.Simulation(
+            survey=survey.copy(),
+            model=model_true,
+            gridding='both',
+            max_workers=1,
+            gridding_opts={'center_on_edge': False},
+            receiver_interpolation='linear',
+            solver_opts={'tol_gradient': 1e-2},
+            tqdm_opts=False,
+        )
+        sim.compute(observed=True)
+        synthetic = sim.survey.data.synthetic.copy()
+        sim.clean('computed')
+
+        sim.model = model_start
+
+        sim.compute()
+        sim.survey.data['start'] = sim.survey.data.synthetic
+        sim.clean('computed')
+
+        markers = np.zeros(sim.model.shape, dtype=int)
+        markers[1, 1, 1] = 1
+        markers[0, :, :] = 2
+        markers[2, :, :] = 3
+
+        def set_regions(self, fop):
+            fop.setRegionProperties(1, limits=(0.0001, 2), startModel=1.0)
+            fop.setRegionProperties(0, background=True)
+            fop.setRegionProperties(2, fix=True, startModel=1)
+            fop.setRegionProperties(
+                    3, single=True, limits=(0.99999, 1.00001), startModel=1.0)
+
+    @pytest.mark.skipif(pygimli is None, reason="pygimli not installed.")
+    def test_Kernel_errors(self):
+
+        sim = self.sim.copy()
+        sim.model = emg3d.Model(sim.model.grid, mapping='Resistivity')
+        with pytest.raises(NotImplementedError, match='for Resistivity'):
+            _ = ipygimli.Kernel(simulation=sim)
+
+        sim.model = emg3d.Model(sim.model.grid, 1, 2)
+        with pytest.raises(NotImplementedError, match='for HTI'):
+            _ = ipygimli.Kernel(simulation=sim)
+
+    @pytest.mark.skipif(pygimli is None, reason="pygimli not installed.")
+    def test_Kernel_markers(self):
+
+        # No regions
+        sim = self.sim.copy()
+        fop = ipygimli.Kernel(simulation=sim)
+        assert_allclose(fop.markers, np.arange(sim.model.size, dtype=int))
+        assert fop.fullmodel is True
+
+        # Regions
+        fop = ipygimli.Kernel(simulation=sim, markers=self.markers)
+        self.set_regions(fop)
+        assert_allclose(fop.markers, self.markers)
+        assert fop.fullmodel is False
+
+    @pytest.mark.skipif(pygimli is None, reason="pygimli not installed.")
+    def test_Kernel_conversions(self):
+        sim = self.sim.copy()
+        fop1 = ipygimli.Kernel(simulation=sim)
+        fop2 = ipygimli.Kernel(simulation=sim, markers=self.markers)
+        self.set_regions(fop2)
+
+        for fop in [fop1, fop2]:
+
+            assert_allclose(
+                fop.model2emg3d(fop.createStartModel()),
+                sim.model.property_x
+            )
+
+            assert_allclose(
+                sim.data.observed,
+                fop.data2emg3d(fop.data2gimli(sim.data.observed.data))
+            )
+
+            assert_allclose(
+                sim.model.property_x,
+                fop.model2emg3d(fop.model2gimli(sim.model.property_x))
+            )
+            data = sim.survey.standard_deviation.data
+            assert fop.data2gimli(data).dtype == np.float64
+
+    @pytest.mark.skipif(pygimli is None, reason="pygimli not installed.")
+    def test_Kernel_response(self):
+        sim = self.sim.copy()
+        sim.model = self.model_true
+        fop = ipygimli.Kernel(simulation=sim)
+        assert_allclose(
+            fop.data2emg3d(fop.response(fop.createStartModel())),
+            self.synthetic.data
+        )
+
+    @pytest.mark.skipif(pygimli is None, reason="pygimli not installed.")
+    @pytest.mark.skipif(discretize is None, reason="discretize not installed.")
+    def test_Inversion_noregions(self, caplog):
+        # Mainly "runtest"
+        sim = self.sim.copy()
+
+        fop = ipygimli.Kernel(simulation=sim, pgthreads=1)
+
+        INV = ipygimli.Inversion(fop=fop)
+        INV.inv.setCGLSTolerance(10)
+        INV.inv.setMaxCGLSIter(30)
+
+        _ = INV.run(maxIter=2, lam=0.1)
+
+        assert 'pyGIMLi(emg3d)' in caplog.text
+        assert 'Created startmodel from forward operator: 27' in caplog.text
+        assert 'λ = 0.1' in caplog.text
+
+        assert INV.inv.chi2() < 1
+
+    @pytest.mark.skipif(pygimli is None, reason="pygimli not installed.")
+    @pytest.mark.skipif(discretize is None, reason="discretize not installed.")
+    def test_Inversion_regions(self, caplog):
+        # Mainly "runtest"
+        sim = self.sim.copy()
+
+        fop = ipygimli.Kernel(
+                simulation=sim, markers=self.markers, pgthreads=1)
+
+        INV = ipygimli.Inversion(fop=fop)
+        INV.inv.setCGLSTolerance(10)
+        INV.inv.setMaxCGLSIter(30)
+
+        INV.fop.setRegionProperties(1, limits=(0.0001, 2), startModel=1.0)
+        INV.fop.setRegionProperties(0, background=True)
+        INV.fop.setRegionProperties(2, fix=True, startModel=1)
+        INV.fop.setRegionProperties(
+                3, single=True, limits=(0.99999, 1.00001), startModel=1.0)
+
+        _ = INV.run(maxIter=2, lam=1)
+
+        assert 'pyGIMLi(emg3d)' in caplog.text
+        assert 'Created startmodel from region infos: 2' in caplog.text
+        assert 'λ = 1.0' in caplog.text
+
+        assert INV.inv.chi2() < 1
 
 
 def test_all_dir():

tests/test_utils.py

@@ -34,7 +34,7 @@ def test_Report(capsys):
     # We just ensure the shown packages do not change (core and optional).
     out1 = utils.Report()
     out2 = scooby.Report(
-            core=['numpy', 'scipy', 'numba', 'emg3d'],
+            core=['numpy', 'scipy', 'numba', 'emg3d', 'empymod'],
             optional=['empymod', 'xarray', 'discretize', 'h5py',
                       'matplotlib', 'tqdm', 'IPython'],
             ncol=4)