Test and fix for tensors in marching cubes when Pytorch

.gitignore

@@ -182,3 +182,4 @@ examples/tutorials/z_other_tutorials/json_io/multiple_series_faults_computed.jso
 examples/tutorials/z_other_tutorials/json_io/combination_model.json
 examples/tutorials/z_other_tutorials/json_io/combination_model_computed.json
 /test/temp/
+test/test_modules/run_test.py

gempy/modules/mesh_extranction/marching_cubes.py

@@ -1,3 +1,4 @@
+import os
 import numpy as np
 from typing import Optional
 from skimage import measure
@@ -72,6 +73,14 @@ def extract_mesh_for_element(structural_element: StructuralElement,
     mask : np.ndarray, optional
         Optional mask to restrict the mesh extraction to specific regions.
     """
+    if type(scalar_field).__module__ == 'torch':
+        import torch
+        scalar_field = torch.to_numpy(scalar_field)
+    if type(mask).__module__ == "torch":
+        import torch
+        mask = torch.to_numpy(mask)
+
+
     # Extract mesh using marching cubes
     verts, faces, _, _ = measure.marching_cubes(
         volume=scalar_field.reshape(regular_grid.resolution),

test/test_modules/test_marching_cubes_pytorch.py

@@ -0,0 +1,64 @@
+""" 
+Copied from "test_marching_cubes.py" to test the pytorch implementation of marching cubes with minor adjustments 
+"""
+
+import os
+
+os.environ["DEFAULT_BACKEND"] = "PYTORCH" 
+
+import numpy as np
+from gempy_engine.core.data.raw_arrays_solution import RawArraysSolution
+
+import gempy as gp
+from gempy.core.data.enumerators import ExampleModel
+from gempy.core.data.grid_modules import RegularGrid
+from gempy.modules.mesh_extranction import marching_cubes
+from gempy.optional_dependencies import require_gempy_viewer
+
+PLOT = True
+
+
+def test_marching_cubes_implementation():
+    assert os.environ["DEFAULT_BACKEND"] == "PYTORCH"
+    model = gp.generate_example_model(ExampleModel.COMBINATION, compute_model=False)
+
+    # Change the grid to only be the dense grid
+    dense_grid: RegularGrid = RegularGrid(
+        extent=model.grid.extent,
+        resolution=np.array([40, 20, 20])
+    )
+
+    model.grid.dense_grid = dense_grid
+    gp.set_active_grid(
+        grid=model.grid,
+        grid_type=[model.grid.GridTypes.DENSE],
+        reset=True
+    )
+    model.interpolation_options = gp.data.InterpolationOptions.init_dense_grid_options()
+    gp.compute_model(model)
+
+    # Assert
+    assert model.solutions.block_solution_type == RawArraysSolution.BlockSolutionType.DENSE_GRID
+    assert model.solutions.dc_meshes is None
+    arrays = model.solutions.raw_arrays  # * arrays is equivalent to gempy v2 solutions
+
+    # assert arrays.scalar_field_matrix.shape == (3, 8_000)  # * 3 surfaces, 8000 points
+
+    marching_cubes.set_meshes_with_marching_cubes(model)
+
+    # Assert
+    assert model.solutions.block_solution_type == RawArraysSolution.BlockSolutionType.DENSE_GRID
+    assert model.solutions.dc_meshes is  None
+    assert model.structural_frame.structural_groups[0].elements[0].vertices.shape == (600, 3)
+    assert model.structural_frame.structural_groups[1].elements[0].vertices.shape == (860, 3)
+    assert model.structural_frame.structural_groups[2].elements[0].vertices.shape == (1_256, 3)
+    assert model.structural_frame.structural_groups[2].elements[1].vertices.shape == (1_680, 3)
+
+    if PLOT:
+        gpv = require_gempy_viewer()
+        gtv: gpv.GemPyToVista = gpv.plot_3d(
+            model=model,
+            show_data=True,
+            image=True,
+            show=True
+        )