"""
Function to download the GSHHG Earth Mask dataset from the GMT data server, and load as
:class:`xarray.DataArray`.
The grids are available in various resolutions.
"""
from collections.abc import Sequence
from typing import Literal
import xarray as xr
from pygmt.datasets.load_remote_dataset import _load_remote_dataset
__doctest_skip__ = ["load_earth_mask"]
[docs]
def load_earth_mask(
resolution: Literal[
"01d",
"30m",
"20m",
"15m",
"10m",
"06m",
"05m",
"04m",
"03m",
"02m",
"01m",
"30s",
"15s",
] = "01d",
region: Sequence[float] | str | None = None,
registration: Literal["gridline", "pixel"] = "gridline",
) -> xr.DataArray:
r"""
Load the GSHHG Earth mask dataset in various resolutions.
.. figure:: https://www.generic-mapping-tools.org/remote-datasets/_images/GMT_earth_mask.jpg
:width: 80 %
:align: center
GSHHG Earth mask dataset.
The grids are downloaded to a user data directory
(usually ``~/.gmt/server/earth/earth_mask/``) the first time you invoke
this function. Afterwards, it will load the grid from the data directory.
So you'll need an internet connection the first time around.
These grids can also be accessed by passing in the file name
**@earth_mask**\_\ *res*\[_\ *reg*] to any grid processing function or
plotting method. *res* is the grid resolution (see below), and *reg* is
the grid registration type (**p** for pixel registration or **g** for
gridline registration).
Refer to :gmt-datasets:`earth-mask.html` for more details about available
datasets, including version information and references.
Parameters
----------
resolution
The grid resolution. The suffix ``d``, ``m``, and ``s`` stand for arc-degrees,
arc-minutes, and arc-seconds.
region
The subregion of the grid to load, in the form of a sequence [*xmin*, *xmax*,
*ymin*, *ymax*] or an ISO country code.
registration
Grid registration type. Either ``"pixel"`` for pixel registration or
``"gridline"`` for gridline registration.
Returns
-------
grid
The Earth mask grid. Coordinates are latitude and
longitude in degrees. The node values in the mask grids are all in
the 0-4 range and reflect different surface types:
- 0: Oceanic areas beyond the shoreline
- 1: Land areas inside the shoreline
- 2: Lakes inside the land areas
- 3: Islands in lakes in the land areas
- 4: Smaller lakes in islands that are found within lakes
inside the land area
Note
----
The registration and coordinate system type of the returned
:class:`xarray.DataArray` grid can be accessed via the GMT accessors
(i.e., ``grid.gmt.registration`` and ``grid.gmt.gtype`` respectively).
However, these properties may be lost after specific grid operations (such
as slicing) and will need to be manually set before passing the grid to any
PyGMT data processing or plotting functions. Refer to
:class:`pygmt.GMTDataArrayAccessor` for detailed explanations and
workarounds.
Examples
--------
>>> from pygmt.datasets import load_earth_mask
>>> # load the default grid (gridline-registered 1 arc-degree grid)
>>> grid = load_earth_mask()
>>> # location (120°E, 50°N) is in land area (1)
>>> grid.sel(lon=120, lat=50).values
array(1, dtype=int8)
>>> # location (170°E, 50°N) is in oceanic area (0)
>>> grid.sel(lon=170, lat=50).values
array(0, dtype=int8)
"""
grid = _load_remote_dataset(
name="earth_mask",
prefix="earth_mask",
resolution=resolution,
region=region,
registration=registration,
)
# `return grid.astype("int8")` doesn't work because grid encoding is lost.
# See https://github.com/GenericMappingTools/pygmt/issues/2629.
grid.data = grid.data.astype("int8")
return grid