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)

MaxPerCategoryNeighborhood(dim, angles, …)

MinMaxPointsNeighborhood(dim, angles, …)

Neighborhood()

Nugget(dim, angles, scales, convention)

PatternGenerator()

Spherical(dim, angles, scales, convention)

product

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

threadpool_limits([limits, user_api])

Change the maximal number of threads that can be used in thread pools.

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)

filter_with_scales(x[, p, scales])

Function to return the indexes of the points which are in a sphere in the Euclidean space.

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, scales])

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

which_nearest_in_ball_with_max_per_category(x)

Function to obtain the N closest points of a set of points to the center of a ball which are on that ball with a maximum per category.