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Spatial Data Declustering in Python
![Declustering is a common technique used in mineral resource estimation to account for spatial patterns in the data. This crucial step helps to improve the accuracy and reliability of the estimate and provides a more robust basis for decision-making..](/assets/spatial-data-declustering.8bafbe06_Z2kICAK.jpg)
import geolime as geo
drillholes = geo.read_file(
"rocklea_dh.geo"
)
drillholes.plot_2d(
attribute="Fe",
agg_method="mean"
)
geo.moving_window_declus(
obj=drillholes,
obj_attribute="Fe",
declus_attribute="Fe_declus_weight_mw",
diam_x=500,
diamy=500,
geometry='BALL'
)
geo.cell_declustering(
obj=drillholes,
obj_attribute="Fe",
declus_attribute="Fe_declus_weight_cd",
size_x=500,
size_y=500,
nb_off=25
)
geo.bar(
[
{"objects": dh, "property": "Fe"},
{
"objects": drillholes,
"property": "Fe",
"weights": "Fe_declus_weight_mw"
},
{
"objects": drillholes,
"property": "Fe",
"weights": "Fe_declus_weight_cd"
},
],
nbins=30
)
geo.plot_2d(
[
{
"objects": drillholes,
"property": "Fe_declus_weight_mw",
"size": "Fe_declus_weight_mw"
"title": "Moving Window Declustering"
},
{
"objects": drillholes,
"property": "Fe_declus_weight_cd",
"size": "Fe_declus_weight_cd"
"title": "Cell Declustering"
},
],
yaxis_shared=True,
colorscale_name="Weight Value"
)