API reference

OceanDataset

OceanDataset(dataset)

OceanDataset combines a xarray.Dataset with other objects used by OceanSpy (e.g., xgcm.Grid).

Import

OceanDataset.shift_averages([averageList])	Shift average variables to time_midp.
OceanDataset.manipulate_coords([fillna, ...])	Manipulate coordinates to make them compatible with OceanSpy.

Attributes

OceanDataset.name	Name of the OceanDataset.
OceanDataset.description	Description of the OceanDataset.
OceanDataset.dataset	xarray.Dataset: A multi-dimensional, in memory, array database.
OceanDataset.grid	xgcm.Grid: A collection of axes, which is a group of coordinates that all lie along the same physical dimension but describe different positions relative to a grid cell.
OceanDataset.parameters	A dictionary defining model parameters that are used by OceanSpy.
OceanDataset.aliases	A dictionary to connect custom variable names to OceanSpy reference names.
OceanDataset.grid_coords	Grid coordinates used by xgcm.Grid.
OceanDataset.grid_periodic	List of xgcm.Grid axes that are periodic.
OceanDataset.projection	Cartopy projection of the OceanDataset.

Set

OceanDataset.set_name(name[, overwrite])	Set name of the OceanDataset.
OceanDataset.set_description(description[, ...])	Set description of the OceanDataset.
OceanDataset.set_parameters(parameters)	Set model parameters used by OceanSpy.
OceanDataset.set_aliases(aliases[, overwrite])	Set aliases to connect custom variables names to OceanSpy reference names.
OceanDataset.set_grid_coords(grid_coords[, ...])	Set grid coordinates used by xgcm.Grid.
OceanDataset.set_grid_periodic(grid_periodic)	Set grid axes that will be treated as periodic by xgcm.Grid.
OceanDataset.set_projection(projection, **kwargs)	Set Cartopy projection of the OceanDataset.

Methods

OceanDataset.merge_into_oceandataset(obj[, ...])	Merge a Dataset or DataArray into the OceanDataset.
OceanDataset.to_netcdf(path, **kwargs)	Write contents to a netCDF file.
OceanDataset.to_zarr(path, **kwargs)	Write contents to a zarr group.
OceanDataset.create_tree([grid_pos])	Create a scipy.spatial.cKDTree for quick nearest-neighbor lookup.

Shortcuts

OceanDataset.subsample	Access oceanspy.subsample functions.
OceanDataset.compute	Access oceanspy.compute functions, and merge the computed Dataset into the OceanDataset.
OceanDataset.plot	Access oceanspy.plot functions.
OceanDataset.animate	Access oceanspy.animate functions.

Opening

open_oceandataset

Open OceanDataset objects.

open_oceandataset.from_netcdf(path, **kwargs)	Load an OceanDataset from a netcdf file.
open_oceandataset.from_zarr(path, **kwargs)	Load an OceanDataset from a Zarr store.
open_oceandataset.from_catalog(name[, ...])	Import oceandataset using a yaml catalog.

Subsampling

subsample

Subsample OceanDataset objects.

Functions

subsample.cutout(od[, varList, YRange, ...])	Cutout the original dataset in space and time preserving the original grid structure.
subsample.mooring_array(od, Ymoor, Xmoor[, ...])	Extract a mooring array section following the grid.
subsample.survey_stations(od, Ysurv, Xsurv)	Extract survey stations.
subsample.particle_properties(od, times, ...)	Extract Eulerian properties of particles using nearest-neighbor interpolation.

Computing

compute

Create new variables using OceanDataset objects.

Smart-name

Computed variables are dynamically named. Names depend on input and operation.

compute.gradient(od[, varNameList, ...])	Compute gradient along specified axes, returning all terms (not summed).
compute.divergence(od[, iName, jName, ...])	Compute divergence of a vector field.
compute.curl(od[, iName, jName, kName, aliased])	Compute curl of a vector field.
compute.laplacian(od[, varNameList, ...])	Compute laplacian along specified axis
compute.integral(od[, varNameList, ...])	Compute integrals along specified axes (simple discretization).
compute.weighted_mean(od[, varNameList, ...])	Compute weighted means using volumes, surfaces, or distances.

Fixed-name

Computed variables have a hard-coded name.

compute.potential_density_anomaly(od)	Compute potential density anomaly.
compute.Brunt_Vaisala_frequency(od)	Compute Brunt-Väisälä Frequency.
compute.velocity_magnitude(od)	Compute velocity magnitude.
compute.horizontal_velocity_magnitude(od)	Compute magnitude of horizontal velocity.
compute.vertical_relative_vorticity(od)	Compute vertical component of relative vorticity.
compute.relative_vorticity(od)	Compute relative vorticity.
compute.kinetic_energy(od)	Compute kinetic energy.
compute.eddy_kinetic_energy(od)	Compute eddy kinetic energy.
compute.horizontal_divergence_velocity(od)	Compute horizontal divergence of the velocity field.
compute.shear_strain(od)	Compute shear component of strain.
compute.normal_strain(od)	Compute normal component of strain.
compute.Okubo_Weiss_parameter(od)	Compute Okubo-Weiss parameter.
compute.Ertel_potential_vorticity(od[, full])	Compute Ertel Potential Vorticity.
compute.mooring_volume_transport(od)	Compute horizontal volume flux through a mooring array section (in/outflow).
compute.heat_budget(od)	Compute terms to close heat budget as explained by [R6f0e4d5c55c6-Pie17].
compute.salt_budget(od)	Compute terms to close salt budget as explained by [R8275cee51d73-Pie17].
compute.geographical_aligned_velocities(od)	Compute zonal and meridional velocities from U and V on orthogonal curvilinear grid.
compute.survey_aligned_velocities(od)	Compute horizontal velocities orthogonal and tangential to a survey.
compute.missing_horizontal_spacing(od)	Compute missing horizontal spacing.

Plotting

plot	Plot using OceanDataset objects.

Functions

plot.TS_diagram(od[, Tlim, Slim, dens, ...])	Plot temperature-salinity diagram.
plot.time_series(od, varName[, meanAxes, ...])	Plot time series.
plot.horizontal_section(od, varName[, ...])	Plot horizontal section.
plot.vertical_section(od, varName[, ...])	Plot vertical section.

Animating

animate

Animate using oceanspy plot functions.

Functions

animate.TS_diagram(od[, display, ...])	Animate TS diagrams.
animate.horizontal_section(od[, display, ...])	Animate horizontal section plots.
animate.vertical_section(od[, display, ...])	Animate vertical section plots.

Utilities

utils

OceanSpy utilities that don't need OceanDataset objects.

Functions

utils.spherical2cartesian(Y, X[, R])	Convert spherical coordinates to cartesian.
utils.great_circle_path(lat1, lon1, lat2, lon2)	Generate a great circle trajectory specifying the distance resolution.
utils.cartesian_path(x1, y1, x2, y2[, delta])	Generate a trajectory specifying the distance resolution.
utils.densjmd95(s, t, p)	Density of Sea Water using Jackett and McDougall 1995 (JAOT 12) polynomial (modified UNESCO polynomial) [R5a812deaf4b9-JaMc95].
utils.densmdjwf(s, t, p)	Density of Sea Water using McDougall et al. 2003 (JAOT 20) polynomial (Gibbs Potential) [Re2d133f292dd-McJa03].
utils.Coriolis_parameter(Y[, omega])	Compute Coriolis parameter (both vertical and horizontal components).

LLC-transformation

llc_rearrange

OceanSpy functionality that transforms a dataset with LLC geometry characterized by 13 faces (or tiles), into one with simple geometry.

Class

llc_rearrange.LLCtransformation(ds[, ...])

A class containing the transformation types of LLCgrids.