Describe the bug
When I use the pytorch backend in release 2025.2.1a2, gempy fails if a surface is only constrained by one contact point. Here is the traceback:
To Reproduce
import gempy as gp
import numpy as np
geo_model = gp.create_geomodel(
project_name='Model1',
extent=[0, 780, -200, 200, -582, 0],
resolution=(50, 50, 50),
# refinement=4, # We will use octrees
structural_frame=gp.data.StructuralFrame.initialize_default_structure()
)
gp.add_surface_points(
geo_model=geo_model,
x=[225],
y=[0],
z=[-95],
elements_names=['surface1']
)
gp.add_orientations(
geo_model=geo_model,
x=[350],
y=[0],
z=[-120],
elements_names=['surface1'],
pole_vector=[np.array([0, 0, 1])]
)
element = gp.data.StructuralElement(
name='surface2',
color='#FFA833', # color=next(geo_model.structural_frame.color_generator),
surface_points=gp.data.SurfacePointsTable.from_arrays(
x=np.array([460]),
y=np.array([0]),
z=np.array([-280]),
names='surface2'
),
orientations=gp.data.OrientationsTable.initialize_empty()
)
geo_model.structural_frame.structural_groups[0].append_element(element)
gp.compute_model(geo_model, engine_config=gp.data.GemPyEngineConfig(backend=gp.data.AvailableBackends.PYTORCH, use_gpu=False))
Expected behavior
I expect that as long as another layer has two surface points, as in the example I provided, the interpolation should be well defined and result in no errors. This is documented on the website:
Desktop (please complete the following information):
I'm on windows using:
gempy:
gempy-engine:
Additional context
There is no issue if I set the backend to 'numpy'.
Describe the bug
When I use the pytorch backend in release 2025.2.1a2, gempy fails if a surface is only constrained by one contact point. Here is the traceback:
To Reproduce
Expected behavior
I expect that as long as another layer has two surface points, as in the example I provided, the interpolation should be well defined and result in no errors. This is documented on the website:
Desktop (please complete the following information):
I'm on windows using:
gempy:
gempy-engine:
Additional context
There is no issue if I set the backend to 'numpy'.