API Reference¶
This reference is generated from the docstrings in the source code via
sphinx.ext.autosummary / sphinx.ext.autodoc. Each entry below links
to a page with the full signature, parameter descriptions, and (for
classes) a summary of public methods and attributes. Private helpers
(names prefixed with _) are intentionally not part of this reference.
Main package¶
Importing geossm re-exports the main classes and functions from
its submodules (geossm.covmodel, geossm.datasets,
geossm.ssm, geossm.stmodel, plus geossm.data_preparation
and geossm.utils) at the top level, e.g. geossm.LRStateSpaceModel
is the same object as geossm.stmodel.LRStateSpaceModel. The sections
below document each name once, grouped by the submodule it is defined in;
geossm.__version__ holds the installed package version.
Models¶
State-space model¶
The full-rank linear-Gaussian state-space model: Kalman filtering, smoothing, simulation, and prediction.
A linear-Gaussian state-space model with Kalman filtering, smoothing and simulation capabilities. |
|
Container for state-space model estimation results (filter and/or smoother outputs), with convenience methods for residuals, error metrics, confidence intervals, diagnostics and a printable summary. |
Low-rank state-space model¶
geossm’s flagship model for large spatial domains: a state-space model whose latent spatial field is represented through a low-rank, SPDE-based covariance basis (see Covariance below).
Low-Rank State-Space Model (LRSSM) for large-scale spatio-temporal data. |
|
Results of fitting a |
|
A single named model parameter, with its value, fixed/free status, and (once available) standard error. |
|
The full set of parameters estimated by |
|
Stopping-rule and logging options for |
Covariance¶
Finite-element (SPDE) approximation of the Matérn covariance, and the mesh builders used to discretize the spatial domain it is defined on.
The SPDE approximation of the Matérn covariance model. |
|
Low-level finite-element engine behind spdeAppoxCov. |
|
Build a 2D triangular (gmsh/pygmsh) mesh around a set of observed locations, in the spirit of R-INLA's |
|
Build a 2D triangular mesh whose interior vertices are a density- matched subset of points, rather than free vertices placed by a smooth size field (as buildMesh2d does). |
|
Simplified front door to buildMesh2d_density's density-matched mesh: picks a landmark-placement method instead of juggling snap_to_points/relax_iters directly, and leaves every other knob (min_edge, offset, cutoff, tol, max_iter) at buildMesh2d_density's own defaults, which are self-tuning (derived from lowrank, the interest domain, and max_edge) and rarely need hand-adjustment. |
|
Build a regular (structured) 2D triangular mesh: a lattice of nx by ny vertices spanning the bounding box of domain (or the convex hull of points if domain is not given), extended by offset. |
Spatial data preparation¶
Turning a geopandas.GeoDataFrame plus a model formula into the
design matrices consumed by the models above, and the datasets bundled
with the package.
Container for the response and covariate design matrices of a spatio-temporal dataset, organized on an [N x T] (site x time) grid, together with the spatial/temporal/formula metadata needed to interpret and reproduce them. |
|
Turn a spatio-temporal |
|
Check whether a collection of timestamps is regularly spaced. |
Load one of the example datasets bundled with geossm. |
|
List available example datasets bundled with the package. |
Utilities¶
General-purpose helpers shared across the package.
Stack 3D arrays into a single 3D block-diagonal array. |
|
Append a run log (observation grid, model, and hardware info) to a text file. |
|
Build a human-readable summary of the current machine's hardware. |
|
Stateful helper that hands out fresh JAX PRNG keys on demand. |