Start tests

tests/test_pygimli.py

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+# import os
+import pytest
+import numpy as np
+# from numpy.testing import assert_allclose
+
+import emg3d
+from emg3d.inversion import pygimli as ipygimli
+
+
+# Soft dependencies
+try:
+    import xarray
+except ImportError:
+    xarray = None
+try:
+    import discretize
+except ImportError:
+    discretize = None
+try:
+    import h5py
+except ImportError:
+    h5py = False
+try:
+    import pygimli
+except ImportError:
+    pygimli = False
+
+
+@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)
+
+
+def test_all_dir():
+    assert set(ipygimli.__all__) == set(dir(ipygimli))