Drillholes Operations

cell_declustering(obj, obj_region, obj_attribute, size_x, size_y, size_z, nb_off)

Compute declustered weights by Cell Declustering algorithm from C. Deutsch.

Parameters:

Name	Type	Description	Default
obj	GeoRefObject	Object to decluster in x, y, z.	required
obj_region	str	Object region or condition to apply declustering.	required
obj_attribute	str	Object attribute to apply declustering.	required
size_x	int	Cell size in x direction.	required
size_y	int	Cell size in y direction.	required
size_z	int	Cell size in z direction.	required
nb_off	int	Number of offsets.	required

Returns:

Type	Description
np.ndarray	Declustered weights $w_i$ of each data point $i$.

moving_window_declus(obj, obj_region, obj_attribute, diam_x, diam_y, diam_z, geometry)

Compute declustered weights by Moving Window algorithm.

Parameters:

Name	Type	Description	Default
obj	GeoRefObject	Object to decluster in x, y, z.	required
obj_region	str	Object region or condition to apply declustering.	required
obj_attribute	str	Object attribute to apply declustering.	required
diam_x	int	Ellipsoid diameter in x direction.	required
diam_y	int	Ellipsoid diameter in y direction.	required
diam_z	int	Ellipsoid diameter in z direction.	required
geometry	DeclusteringGeometry	Geometry to be used for the window. BALL -> which_in_ball PARALLELEPIPED -> __which_in_parallelepiped	required

Returns:

Type	Description
np.ndarray	declustered weights $w_i$ of each data point $i$.

Note

• counts the number $n_i$ of samples inside a moving window centered on point $i$.
• weight $w_i$ is $\frac{m_v}{n_i}$ where $m_v$ is the mean of all the $n_i$.

compositing(drillholes, attribute_list, composit_len=2.0, minimum_composit_len=0.0, residual_len=2.0, ref_z_value=None, method=DesurveyingMethod.TANGENTIAL, dip_convention=DipDownward.NEGATIVE)

Regularize drillholes into composites of same lengths.

Compositing regularizes data spacing along a drillhole from top to bottom. Composite with coverage length shorter than minimum composite length will have a nan composit grade value. Compositing might return longer drillhole than original. The residual composite is therefore longer or shorter than the composite length. If the last sample is shorter than the residual length it will be added to the previous composite, having a longer one in the Attribute.TO. If the last sample is longer than the residual length it will be considered as a separate composite, having a shorter one in the Attribute.TO. with the previous one. A reference value can be set in order to adjust the first composite at a certain elevation or its modulo regarding compositing length. This parameter enables to have same spatial limits for Drillholes and estimation grid used later on. Regularization is done by sum product average (sum of the grade time the length divided by the total length) In debug mode, original information used for the sum product average are given.

Parameters:

Name	Type	Description	Default
drillholes	Drillholes	GeoLime Drillholes object.	required
attribute_list	List[str]	List of grade names to be composited.	required
composit_len	float	Lenght of new composits. Defaults to 2.	2.0
minimum_composit_len	float	Minimum length of coverage in order to be used. Defaults to 0.	0.0
residual_len	float	Minimum residual length setting if residual is added to last one. Defaults to 0.	2.0
ref_z_value	Optional[float]	Elevation value to clip beginning of composit. Defaults to None.	None
method	DesurveyingMethod	Desurveying method.	DesurveyingMethod.TANGENTIAL
dip_convention	DipDownward	Convention of dip downward angle sign.	DipDownward.NEGATIVE

Returns:

Type	Description
Drillholes	Composited Drillholes.

find_duplicate(drillholes, max_distance=1.0)

Seek for the duplicates in drillhole - only in (x,y).

Add a new column with an id corresponding to a duplicated group.

Parameters:

Name	Type	Description	Default
drillholes	Drillholes	GeoLime Drillholes object.	required
max_distance	Optional[float]	Maximum radius for search. Defaults to 1.	1.0

Returns:

Type	Description
np.ndarray	Numpy array containing an id corresponding to a duplicated group for each point (x,y).

SurfaceSequenceEstimator

Object for creating surfaces from a drillhole based on a lithological sequence.

Attributes:

Name	Type	Description
method	SurfaceEstimationMethdo	Interpolation variable used.
interpolator	DrillholesInterpolationMethod	Mathematical interpolator used.

domain_sequence: DrillholesInterpolationMethod property

Return drillholes domain sequence.

interpolator: DrillholesInterpolationMethod property

Return drillholes interpolation method used.

method: SurfaceEstimationMethod property

Return estimation method used.

build_constraints(data, domain_col, domain_sequence)

Build constraints matrix based on drillholes data. Specify minimum and maximum value for each domain for drillholes.

Parameters:

Name	Type	Description	Default
data	Drillholes	Drillholes Object.	required
domain_col	str	Property name of the lithological domain.	required
domain_sequence	List[str]	Sequence of lithological domain from top to bottom.	required

surface_creation(grid_surf, interpolator, kwargs)

Create surfaces from filled constraints matrix and a gridded surface with topographic attribute (elavation data).

Parameters:

Name	Type	Description	Default
grid_surf	GriddedSurface	GriddedSurface used to compute elevation.	required
interpolator	Union[ExternalSurfaceInterpolationMethod, GeolimeSurfaceInterpolationMethod]	Interpolation Method used to compute on GriddedSurface.	required
**kwargs		Extra arguments used by interpolation method.	{}

ClosestPointValue

Bases: SurfaceSequenceEstimator

Deterministic method for creating surfaces from drillholes and constraints matrix.

compute_thickness(domain)

Compute thickness of a domain based on elevation data.

Parameters:

Name	Type	Description	Default
domain	str	Domain to compute thicness.	required

Returns:

Type	Description
pd.DataFrame	Updated constraints matrix.

determine_topography()

Determine fist lithological domain as topography. Needed for interpolation initialization.

Returns:

Type	Description
pd.DataFrame	Updated constraints matrix.

Note

Future version might envisage add of topographic data.

fill_constraints()

Fill constraints matrix with a naive interpolation on unknown data and constraint out of bound points with previously computed constraints.

fill_missing_constraint(domain)

Interpolate unknown data on a domain conditioned with known data.

Parameters:

Name	Type	Description	Default
domain	str	Domain to compute thicness.	required

Raises:

Type	Description
NotImplementedError	If given method is not implemented.
ValueError	If constraints has less than 3 points.

Returns:

Type	Description
pd.DataFrame	Updated constraints matrix.

fix_constraint_simple(domain)

Update matrix constraints by checking value and threshold.

Parameters:

Name	Type	Description	Default
domain	str	Domain to compute thicness.	required

Returns:

Type	Description
pd.DataFrame	Updated constraints matrix.

thickness_to_elevation(domain)

Convert thickness elevation to elevation information.

Parameters:

Name	Type	Description	Default
domain	str	Domain to compute thicness.	required

Returns:

Type	Description
pd.DataFrame	Updated constraints matrix.

update_constraints(domain)

Update constraints using information from above and below units.

Parameters:

Name	Type	Description	Default
domain	str	Domain to compute thicness.	required

Returns:

Type	Description
pd.DataFrame	Updated constraints matrix.

Note

Future version might envisage add of topographic data.

update_elevation_threshold_below(domain)

Update elevation thresholds of below unit.

Parameters:

Name	Type	Description	Default
domain	str	Domain to compute thicness.	required

Returns:

Type	Description
pd.DataFrame	Updated constraints matrix.