Export 3D-Model as XZY file

[Sebadita]

Hi everyone!

How can I export an interpolated mesh surface as XZY. file? I have created a model, which consist only of a 3D surface, and i want to use in other software.

[yangjiandendi]

Hi Sebadita,

firstly, you have to export your gempy model as VTK format:

p.surface_poly['rock1'].save('rock1.vtk') # Save the vtk file for formation 1
p.surface_poly['rock2'].save('rock2.vtk') # Save the vtk file for formation 2
p.orientations_mesh.save('orientations.vtk') # Save the vtk file for the orientations
p.surface_points_mesh.save('surface_points.vtk') # Save the vtk file for the surface points
box = p.regular_grid_actor.GetMapper().GetInput() # Get the vtk file for the regular grid
box.save('box.vtk')

then, you can get the vertices of mesh surface in VTK like this:

import vtk
import pandas as pd`
def generate_normals(polydata):
    normal_generator = vtk.vtkPolyDataNormals()
    normal_generator.SetInputData(polydata)
    normal_generator.ComputePointNormalsOn()
    normal_generator.ComputeCellNormalsOff()
    normal_generator.Update()
    return normal_generator.GetOutput()

def get_vertices_and_normals(mesh):

    surface_mesh = mesh.extract_surface()
    polydata = surface_mesh

    # Generate normals if not present
    polydata_with_normals = generate_normals(polydata)

    # Get points (vertices)
    points = polydata_with_normals.GetPoints()
    vertices = []
    for i in range(points.GetNumberOfPoints()):
        vertices.append(points.GetPoint(i))

    # Get normals
    normals_array = polydata_with_normals.GetPointData().GetNormals()
    normals = []
    for i in range(normals_array.GetNumberOfTuples()):
        normals.append(normals_array.GetTuple(i))

    return vertices, normals

def save_to_excel(vertices, normals, vertices_file, normals_file):
    # Create DataFrames
    vertices_df = pd.DataFrame(vertices, columns=['X', 'Y', 'Z'])
    normals_df = pd.DataFrame(normals, columns=['x', 'y', 'z'])

    # Save to Excel files
    vertices_df.to_excel(vertices_file, index=False)
    normals_df.to_excel(normals_file, index=False)

# mesh = pv.read("../data/model.vtp")
mesh = p.surface_poly['rock1']
vertices, normals = get_vertices_and_normals(mesh)
vertices_df = pd.DataFrame(vertices, columns=['X', 'Y', 'Z'])
normals_df = pd.DataFrame(normals, columns=['x', 'y', 'z'])
# Save to Excel files
vertices_file = "rock1_vertices.xlsx"
normals_file = "rock1_norms.xlsx"
save_to_excel(vertices, normals, vertices_file, normals_file)

finally you can convert pandas dataframe to an XYZ file:

# Convert the DataFrame to an XYZ file
def dataframe_to_xyz(df, filename):
    with open(filename, 'w') as f:
        for index, row in df.iterrows():
            f.write(f"{row['X']} {row['Y']} {row['Z']}\n")

# Specify the filename
filename = "output.xyz"

# Call the function to write the DataFrame to an XYZ file
dataframe_to_xyz(vertices_df, filename)

[AlexanderJuestel]

@Sebadita this issue relates to #898

please also see this code that should allow you to export the meshes. surfaces_poly is the dict where the mesh is stored. You can access the mesh with surfaces_poly['Layer1'][0]. The XYZ coordinates of the vertices can be accessed with surfaces_poly['Layer1'][0].points. This will return irregularly spaced points. Do you need regular-spaced points like for a raster?

Here the code to export the meshes with their true XYZ coordinates

# List of Surfaces
surfaces = ['Layer1', 'Layer2']

# Getting a list of all surfaces
list_surfaces = list(geo_model.structural_frame.element_name_id_map.keys())

# Getting indices of provided surfaces
list_indices = [list_surfaces.index(surface) for surface in surfaces]

# Creating empty dict to store data
surfaces_poly = {}

for index in list_indices:

    # Extracting vertices
    vertices = geo_model.input_transform.apply_inverse(geo_model.solutions.raw_arrays.vertices[index])

    # Extracting faces
    faces = np.insert(geo_model.solutions.raw_arrays.edges[index], 0, 3, axis=1).ravel()

    # Creating PolyData from vertices and faces
    surf = pv.PolyData(vertices, faces)

    # Appending depth to PolyData
    surf['Depth [m]'] = geo_model.input_transform.apply_inverse(geo_model.solutions.raw_arrays.vertices[index])[:, 2]

    # Storing mesh, depth values and color values in dict
    surfaces_poly[list_surfaces[index]] = [surf, geo_model.structural_frame.elements_colors[index]]

[javoha]

Answered. Please feel free to reopen if you have additional questions.