Load Project

Load and visualize an OMF project file

# sphinx_gallery_thumbnail_number = 3
import pyvista as pv
import omfvista

Load the project into an pyvista.MultiBlock dataset

project = omfvista.load_project('../assets/test_file.omf')


MultiBlock (0x7f57a3d7bd60)
  N Blocks:     9
  X Bounds:     443941.105, 447059.611
  Y Bounds:     491941.536, 495059.859
  Z Bounds:     2330.000, 3555.942

Once the data is loaded as a pyvista.MultiBlock dataset from omfvista, then that object can be directly used for interactive 3D visualization from pyvista:

load project

Or an interactive scene can be created and manipulated to create a compelling figure directly in a Jupyter notebook. First, grab the elements from the project:

# Grab a few elements of interest and plot em up!
vol = project['Block Model']
assay = project['wolfpass_WP_assay']
topo = project['Topography']
dacite = project['Dacite']

p = pv.Plotter()
p.add_mesh(topo, opacity=0.5)
load project

Then apply a filtering tool from pyvista to the volumetric data:

# Threshold the volumetric data
thresh_vol = vol.threshold([1.09, 4.20])


UnstructuredGrid (0x7f57a3d57100)
  N Cells:      92525
  N Points:     107807
  X Bounds:     4.447e+05, 4.457e+05
  Y Bounds:     4.929e+05, 4.942e+05
  Z Bounds:     2.330e+03, 3.110e+03
  N Arrays:     1

Then you can put it all in one environment!

# Create a plotting window
p = pv.Plotter()
# Add the bounds axis

# Add our datasets
p.add_mesh(topo, opacity=0.5)
p.add_mesh(dacite, color='orange', opacity=0.6,)
p.add_mesh(thresh_vol, cmap='coolwarm', clim=vol.get_data_range())

# Add the assay logs: use a tube filter that varius the radius by an attribute
p.add_mesh(assay.tube(radius=3), cmap='viridis')

load project

Total running time of the script: ( 0 minutes 17.076 seconds)

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