Source code for pygmt.xarray.backend

"""
An xarray backend for reading raster grid/image files using the 'gmt' engine.
"""

from typing import Literal

import xarray as xr
from pygmt._typing import PathLike
from pygmt.clib import Session
from pygmt.exceptions import GMTInvalidInput
from pygmt.helpers import build_arg_list
from pygmt.src.which import which
from xarray.backends import BackendEntrypoint


[docs] class GMTBackendEntrypoint(BackendEntrypoint): """ Xarray backend to read raster grid/image files using 'gmt' engine. Internally, GMT uses the netCDF C library to read netCDF files, and GDAL for GeoTIFF and other raster formats. See :gmt-docs:`reference/features.html#grid-file-format` for more details about supported formats. This GMT engine can also read :gmt-docs:`GMT remote datasets <datasets/remote-data.html>` (file names starting with an `@`) directly, and pre-loads :class:`pygmt.GMTDataArrayAccessor` properties (in the '.gmt' accessor) for easy access to GMT-specific metadata and features. When using :py:func:`xarray.open_dataarray` or :py:func:`xarray.load_dataarray` with ``engine="gmt"``, the ``raster_kind`` parameter is required and can be either: - ``"grid"``: for reading single-band raster grids - ``"image"``: for reading multi-band raster images Examples -------- Read a single-band netCDF file using ``raster_kind="grid"`` >>> import pygmt >>> import xarray as xr >>> >>> da_grid = xr.open_dataarray( ... "@static_earth_relief.nc", engine="gmt", raster_kind="grid" ... ) >>> da_grid # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS <xarray.DataArray 'z' (lat: 14, lon: 8)>... [112 values with dtype=float32] Coordinates: * lat (lat) float64... -23.5 -22.5 -21.5 -20.5 ... -12.5 -11.5 -10.5 * lon (lon) float64... -54.5 -53.5 -52.5 -51.5 -50.5 -49.5 -48.5 -47.5 Attributes:... Conventions: CF-1.7 title: Produced by grdcut history: grdcut @earth_relief_01d_p -R-55/-47/-24/-10 -Gstatic_eart... description: Reduced by Gaussian Cartesian filtering (111.2 km fullwidt... actual_range: [190. 981.] long_name: elevation (m) Read a multi-band GeoTIFF file using ``raster_kind="image"`` >>> da_image = xr.open_dataarray( ... "@earth_night_01d", engine="gmt", raster_kind="image" ... ) >>> da_image # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS <xarray.DataArray 'z' (band: 3, y: 180, x: 360)>... [194400 values with dtype=uint8] Coordinates: * y (y) float64... 89.5 88.5 87.5 86.5 ... -86.5 -87.5 -88.5 -89.5 * x (x) float64... -179.5 -178.5 -177.5 -176.5 ... 177.5 178.5 179.5 * band (band) uint8... 1 2 3 Attributes:... long_name: z """ description = "Open raster (.grd, .nc or .tif) files in Xarray via GMT." open_dataset_parameters = ("filename_or_obj", "raster_kind") url = "https://pygmt.org/dev/api/generated/pygmt.GMTBackendEntrypoint.html"
[docs] def open_dataset( # type: ignore[override] self, filename_or_obj: PathLike, *, drop_variables=None, # noqa: ARG002 raster_kind: Literal["grid", "image"], # other backend specific keyword arguments # `chunks` and `cache` DO NOT go here, they are handled by xarray ) -> xr.Dataset: """ Backend open_dataset method used by Xarray in :py:func:`~xarray.open_dataset`. Parameters ---------- filename_or_obj File path to a netCDF (.nc), GeoTIFF (.tif) or other grid/image file format that can be read by GMT via the netCDF or GDAL C libraries. See also :gmt-docs:`reference/features.html#grid-file-format`. raster_kind Whether to read the file as a "grid" (single-band) or "image" (multi-band). """ if raster_kind not in {"grid", "image"}: msg = f"Invalid raster kind: '{raster_kind}'. Valid values are 'grid' or 'image'." raise GMTInvalidInput(msg) with Session() as lib: with lib.virtualfile_out(kind=raster_kind) as voutfile: kwdict = {"T": {"grid": "g", "image": "i"}[raster_kind]} lib.call_module( module="read", args=[filename_or_obj, voutfile, *build_arg_list(kwdict)], ) raster: xr.DataArray = lib.virtualfile_to_raster( vfname=voutfile, kind=raster_kind ) # Add "source" encoding source = which(fname=filename_or_obj) raster.encoding["source"] = ( source[0] if isinstance(source, list) else source ) _ = raster.gmt # Load GMTDataArray accessor information return raster.to_dataset()