geolime.geostats

Classes:

ABCMeta(name, bases, namespace, **kwargs)

Metaclass for defining Abstract Base Classes (ABCs).

Anamorphosis(data, data_min, data_max, …)

Covariance(dim, angles, 0.0, 0.0], scales, …)

CovarianceElem(dim, angles, scales, …)

Enum(value)

Generic enumeration.

Exponential(dim, angles, scales, convention)

Gaussian(dim, angles, scales, convention)

Grid(metadata, convention)

GridPatternGenerator(grid, discr)

MinMaxPointsNeighborhood(dim, angles, …)

Neighborhood()

Nugget(dim, angles, scales, convention)

PatternGenerator()

Spherical(dim, angles, scales, convention)

product

product(*iterables, repeat=1) –> product object

Data:

Callable

Callable type; Callable[[int], str] is a function of (int) -> str.

Dict

The central part of internal API.

List

The central part of internal API.

Functions:

abstractmethod(funcobj)

A decorator indicating abstract methods.

angle_between_vectors(v1, v2)

Compute the angle between two vectors using the dot product

anisotropic_distance([a])

Anisotropic distance between two points according to the anisotropy matrix a.

arg_sort_near_points(p, x[, distance])

Function to compute the indexes indicating the order in which the rows of X are close to p according to the distance distance (from small distance to large distance)

average_kriging(xcoords, xdat, targets, cov, var)

Ordinary / Simple kriging algorithm (punctual).

block_kriging(xcoords, xdat, points, cov, neigh)

Block kriging function.

block_kriging_nodes(xcoords, xdat, point, …)

Punctual kriging function for a specific block node

ce(kriging, stdev, anam)

Conditional expectation

change_of_support(anam, cov_raw, …[, nlag])

Compute the change of support coefficient

compute_weights(xcoords, targets, cov)

Compute kriging weights according to a covariance model

compute_weights_idw(dist, power)

Compute IDW weights

covariance(values, indices)

Compute the covariance given an array of values for a set of pairs

cvv(cov[, pattern_generator, lag, method])

Applies a covariance model to a given grid for variance calculus

direct_block_simu_init(target_grid, xcoords, …)

Initialize conditional simulation against observed values (in Gaussian space).

direct_block_simulations_on_a_set(…[, …])

Applies Simple Kriging on conditional simulations

directional_vector(dimension, …[, deg])

Compute directional vector from angles

discrete_gaussian_kriging(target_grid, …)

Apply discrete gaussian kriging on a grid.

discrete_gaussian_kriging_block(point, …)

Apply discrete gaussian kriging on a grid block

discrete_gaussian_kriging_by_index(points, …)

Apply discrete gaussian kriging on a set of grid indices.

discrete_gaussian_weights(target_node, …)

Compute Discrete Gaussian Kriging weights

distance_matrix(x1, x2[, distance])

Computes the distance matrix of two sets of points in the Euclidean space according to a distance.

euclidian_distance(x, y)

Compute the Euclidean distance between two points.

evaluate_hermite_expansion(x[, coeff])

Evaluate at x a function determined by its coefficients in the Hermite expansion.

evaluate_hermite_expansion_for_metal(val, …)

Evaluate germite expansion for metal

evaluate_hermite_expansion_for_metal_memsafe_variable(…)

evaluate_hermite_expansion_memsafe(x[, coeff])

Evaluate at x a function determined by its coefficients in the Hermite expansion.

evaluate_hermite_expansion_memsafe_variable(x, …)

Evaluate at x a function determined by its coefficients in the Hermite expansion.

fill_cov(param, cov)

Append additional information to covariance element (angles and scales)

gauss_score(z[, weights])

Function to obtain the (standard) Gaussian scores of a sample.

gaussian_anamorphosis(z[, yzmin, yzmax, …])

Function to obtain a Gaussian anamorphose model for a sample.

generate_lags(lag, plag, nlags)

Generate lags array to be used with variogram

group_data(target_grid, xcoords, xdata)

Create a dataset from point mean in common blocks

hermite_coefficients_anamorphosis(n, z[, …])

Function to obtain the Hermite coefficients of a Gaussian anamorphose model function.

hermite_coefficients_piecewise_linear(n, x, y)

Computes the Hermite coefficients of a piece-wise linear function continuous in an interval, with a desired extension outside the interval.

hermite_polynomials(x, n)

Function to compute the Hermite polynomials up to order n.

idw(points, coords, values[, power])

Inverse Distance Weighting algorithm.

in_angle(vdir, atol)

Return a function that checks for an index vector if it belongs to an angular range.

in_range(target, atol)

Check if target angle lies within a range of angles (defined by an angle tolerance)

in_slice(trend, plunge, vdir[, width, height])

Return a function that check whether a vector (cartesian coordinates) lies within a slice (defined by a width and a height in meters)

in_which_block(x, grid)

Return indexes of block containing point

init_params(cov, vario[, constraints, …])

Initialize parameters for variogram model fitting

inverse_anamorphosis_from_obs(z[, yzmin, …])

Function to obtain the (pseudo-)inverse of a Gaussian anamorphose model for a sample date.

inverse_anamorphosis_theoretical(z, anam[, …])

Compute theoretical inverse anamorphosis for a single value.

inverse_var_function(var, anam[, nlag])

Compute inverse variance

metal(kriging, stdev, anam, cutoff)

Conditional expectation for metal

model_fit(variograms[, cov, constraints, …])

Fit a variogram model from an experimental semivariogram

model_regularize(variogram, model, …[, …])

Semi-variogram regularization from a covariance model.

norm(x[, ord, axis, keepdims])

Matrix or vector norm.

normalize(a, center)

(Adapted from Apach Commons normalizeAngle, MathUtils sources) Normalize an angle in a 2pi; wide interval around a center value.

ore(kriging, stdev, anam, cutoff)

Conditional expectation for ore

ore_metal(zcut, anam)

Apply non Conditional Expectation given hermite coefficients anamorphosis and a cut-off value

pairwise(coords)

Computes pairwise distances

plane_to_dir(azimuth, dip, pitch[, deg])

Convert plane angles to line angles.

residual(p, vario, cov, nlags)

Residuals to be minimized for model fitting

rot_z(alpha[, deg, clockwise])

Rotation againt the Z axis

rot_zyx(angles[, deg, clockwise])

Example of a convention (RGeoStats)

rotational_angles(angles)

Compute the angles in radians necessary for matrix rotation operation from geographic azimuth, dip and pitch angles defined in degrees

select_index_from_slice(idx, f)

Compare vectors from a set of indices

select_indices(coords, pwdist, lag, tol, …)

Check whether a set of points (linked to their distances) match the input restricted boundaries.

select_indices_from_angle(idx, f)

Compare vectors from a set of indices

select_indices_from_lag(pwdist, lag, tol)

Check whether a set of distances lie within a lag-range.

semivariance(values, indices[, weights])

Compute the semivariance given an array of values for a set of pairs

simu_grid(Zs, grid[, ind])

Evaluate simulations on an input grid.

simu_grid_init(cov, grid[, nbsimus, nbands, …])

This function will initialize Turning Band method for computing unconditional simulations from a covariance structure.

simu_grid_init_elem(covelem, sill, grid[, …])

Initialize Turning Band method on an atomic covariance element

simu_points(Zs, coords)

Applies unconditional simulations on input coordinates (evaluated as distances).

spherical_3d_random_function_tb(scale, sill, …)

Prepares one simulation with the Turning Band method.

spherical_3d_random_functions_tb(scale, …)

Compute random function with the Turning Band method.

uc(zcut, kriging_gauss_panel, anamblock, r, s)

Apply Uniform Conditoning on a Panel according to a cut off value.

uc_on_grid(anam, panel_grid, data_coords, …)

Apply Uniform Conditioning on a Panel Grid

uc_prepare(anam, panel_center, data_coords, …)

Prepare Uniform Conditioning on a panel by computing panel Kriging and Panel-Point support coefficient

variogram(coords, values, lags, tol, …[, …])

Given boundary input arguments (lag and its associated tolerance, angular reference and its associated tolerance), compute the variogram for a set of points (value associated with cartesian coordinates for a specific point)

which_in_ball(x[, p, r, distance])

Function to return the indexes of the points which are in a (closed) ball in the Euclidean space.

which_in_parallelepiped(x[, p, r, distance])

Function to return the indexes of the points which are in a (closed) parallelepiped in the Euclidean space.

which_nearest_in_ball(x[, p, r, distance, …])

Function to obtain the N closest points of a set of points to the # center of a ball which are on that ball.