The ocean module provides an interface to fetching, loading and interpolating ocean variables.

class kadlu.geospatial.ocean.Ocean(*, south=44.25, west=-64.5, north=44.7, east=-63.33, bottom=5000, top=0, start=datetime.datetime(2015, 3, 1, 0, 0), end=datetime.datetime(2015, 3, 1, 12, 0), **loadvars)[source]

Bases: object

class for handling ocean data requests

data will be loaded using the given data sources and boundaries from arguments. an interpolation for each variable will be computed in parallel

data will be averaged over time frames for interpolation. for finer temporal resolution, define smaller time boundaries

any of the below load_args may also accept a callback function instead of a string or array value if you wish to write your own data loading function. the boundary arguments supplied here will be passed to the callable, i.e. north, south, west, east, top, bottom, start, end

callables or array arguments must be ordered by [val, lat, lon] for 2D data, or [val, lat, lon, depth] for 3D data

north, south:

latitude boundaries (float)

west, east:

longitude boundaries (float)

top, bottom:

depth range in metres (float) only applies to salinity and temperature

start, end:

time range for data load query (datetime) if multiple times exist within range, they will be averaged before computing interpolation


keyword args supplied as ‘load_{v}’ where v is either an integer, float, array of [val, lat, lon[, time[, depth]]], or string source as described by the source_map

interps: dict

Dictionary of data interpolators

origin: tuple(float, float)

Latitude and longitude coordinates of the centre point of the geographic bounding box. This point serves as the origin of the planar x-y coordinate system.

boundaries: dict

Bounding box for the ocean volume in space and time

bathymetry_deriv(lat, lon, axis, grid=False)[source]
bathymetry_deriv_xy(x, y, axis, grid=False)[source]
precip_type(lat, lon, epoch, grid=False)[source]
precip_type_xy(x, y, epoch, grid=False)[source]
kadlu.geospatial.ocean.worker(interpfcn, reshapefcn, cols, var, q)[source]

compute interpolation in parallel worker process


callback function for interpolation


callback function for reshaping row data into matrix format for interpolation


data as returned from load function


variable type. used as key in Ocean().interps dictionary


shared queue object to pass interpolation back to parent