opendrift.readers.basereader.structured

Attributes

logger

Classes

StructuredReader

A structured reader. Data is gridded on a regular grid. Used by e.g.:

Module Contents

opendrift.readers.basereader.structured.logger

class opendrift.readers.basereader.structured.StructuredReader

Bases: opendrift.readers.basereader.variables.Variables

A structured reader. Data is gridded on a regular grid. Used by e.g.: opendrift.readers.reader_netCDF_CF_generic.Reader.

Attributes:

projected: is True if fakeproj.fakeproj is used because of missing projection information. The data points are assumed to be approximately equidistant on the surface (i.e. in meters).

clipped: pixels to to remove along boundary (e.g. in case of bad data).

See also

opendrift.readers

clipped = 0

x = None

y = None

interpolation = 'linearNDFast'

convolve = None

save_interpolator = None

interpolator_filename = None

__lonlat2xy_parallel__ = None

__disable_parallel__ = False

var_block_before

var_block_after

abstract get_variables(variables, time=None, x=None, y=None, z=None)

Obtain a _block_ of values of the requested variables at all positions (x, y, z) closest to given time. These will be stored in opendrift.readers.interpolation.structured.ReaderBlock and accessed from there.

Arguments:

variables: list of variables.

time: datetime or None, time at which data are requested.

x, y: float or ndarrays; coordinates of requested points.

z: float or ndarray; vertical position (in meters, positive up)

Returns:

Dictionary

keywords: variables (string) values: 2D ndarray bounding x and y.

prepare(extent, start_time, end_time, max_speed)

Prepare reader for given simulation coverage in time and space.

set_convolution_kernel(convolve)

Set a convolution kernel or kernel size (of array of ones) used by get_variables on read variables.

__convolve_block__(env)

Convolve arrays with a kernel, if reader.convolve is set

lon_range()

_get_variables_interpolated_(variables, profiles, profiles_depth, time, reader_x, reader_y, z)

This method _must_ be implemented by every reader. Usually by subclassing one of the reader types (e.g. structured.StructuredReader).

Arguments are in _native projection_ of reader.

__check_env_arrays__(env)

For the StructuredReader the variables are checked before entered into the ReaderBlock interpolator. This methods makes the second check a no-op.

See also

variables.Variables.__check_env_arrays__().

xy2lonlat(x, y)

Calculate x,y in own projection from given lon,lat (scalars/arrays).

lonlat2xy(lon, lat)

Calculate lon,lat from given x,y (scalars/arrays) in own projection.

pixel_size()

get_ocean_depth_area_volume(lonmin, lonmax, latmin, latmax)

Get depth, area and volume of ocean basin within given coordinates

_coverage_unit_()

_bbox_(x, y)

Find bounding box on grid containing points (x, y)

_make_projected_grid_(lon, lat, eq_eps=0.1)

Make the projected grid in cases where lon and lat are present as 2D variables, but not x and y and assert that it is approximately equidistant.

Args:

eq_eps: tolerance for equidistance checks.

__validate_projected_grid__(eq_eps=0.1)

Validate that the projected grid is approximately equidistant.

Args:

eq_eps: tolerance for equidistance checks.

Raises:

AssertionError if not equidistant within eq_eps.

_slice_variable_(var, indxTime=None, indy=None, indx=None, indz=None, indrealization=None)

Slice variable depending on number of dimensions available.

Args:

All arguments can be slice objects or index.

Returns:

var sliced using the slices or indexes necessary to use depending on number of dimensions available.

Raises:

Unsupported number of dimensions (outside 2..5) raises an exception.