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Add function to load Blue Marble dataset (#2235)
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Function to load the `@earth_day_` NASA Blue Marble mosaic RGB images stored as GeoTIFF files.

---------

Co-authored-by: Wei Ji <23487320+weiji14@users.noreply.github.com>
Co-authored-by: Dongdong Tian <seisman.info@gmail.com>
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3 people committed Sep 30, 2024
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1 change: 1 addition & 0 deletions doc/api/index.rst
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Expand Up @@ -218,6 +218,7 @@ and store them in GMT's user data directory.
:toctree: generated

datasets.list_sample_data
datasets.load_blue_marble
datasets.load_earth_age
datasets.load_earth_free_air_anomaly
datasets.load_earth_geoid
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1 change: 1 addition & 0 deletions pygmt/datasets/__init__.py
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"""

from pygmt.datasets.earth_age import load_earth_age
from pygmt.datasets.earth_day import load_blue_marble
from pygmt.datasets.earth_free_air_anomaly import load_earth_free_air_anomaly
from pygmt.datasets.earth_geoid import load_earth_geoid
from pygmt.datasets.earth_magnetic_anomaly import load_earth_magnetic_anomaly
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97 changes: 97 additions & 0 deletions pygmt/datasets/earth_day.py
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"""
Function to download the NASA Blue Marble image datasets from the GMT data server, and
load as :class:`xarray.DataArray`.
The images 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_blue_marble"]


def load_blue_marble(
resolution: Literal[
"01d",
"30m",
"20m",
"15m",
"10m",
"06m",
"05m",
"04m",
"03m",
"02m",
"01m",
"30s",
] = "01d",
region: Sequence[float] | str | None = None,
) -> xr.DataArray:
r"""
Load NASA Blue Marble images in various resolutions.
.. figure:: https://www.generic-mapping-tools.org/remote-datasets/_images/GMT_earth_daynight.jpg
:width: 80%
:align: center
Earth day/night dataset.
The images are downloaded to a user data directory (usually
``~/.gmt/server/earth/earth_day/``) the first time you invoke this function.
Afterwards, it will load the image from the data directory. So you'll need an
internet connection the first time around.
These images can also be accessed by passing in the file name
**@earth_day**\_\ *res* to any image processing function or plotting method. *res*
is the image resolution (see below).
Refer to :gmt-datasets:`earth-daynight.html` for more details about available
datasets, including version information and references.
Parameters
----------
resolution
The image resolution. The suffix ``d``, ``m``, and ``s`` stand for arc-degree,
arc-minute, and arc-second.
region
The subregion of the image to load, in the form of a sequence [*xmin*, *xmax*,
*ymin*, *ymax*].
Returns
-------
image
The NASA Blue Marble image. Coordinates are latitude and longitude in degrees.
Note
----
The registration and coordinate system type of the returned
:class:`xarray.DataArray` image can be accessed via the GMT accessors (i.e.,
``image.gmt.registration`` and ``image.gmt.gtype`` respectively). However, these
properties may be lost after specific image operations (such as slicing) and will
need to be manually set before passing the image to any PyGMT data processing or
plotting functions. Refer to :class:`pygmt.GMTDataArrayAccessor` for detailed
explanations and workarounds.
Examples
--------
>>> from pygmt.datasets import load_blue_marble
>>> # load the default image (pixel-registered 1 arc-degree image)
>>> image = load_blue_marble()
"""
image = _load_remote_dataset(
name="earth_day",
prefix="earth_day",
resolution=resolution,
region=region,
registration="pixel",
)
# If rioxarray is installed, set the coordinate reference system
if hasattr(image, "rio"):
image = image.rio.write_crs(input_crs="OGC:CRS84")
return image
30 changes: 26 additions & 4 deletions pygmt/datasets/load_remote_dataset.py
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Expand Up @@ -78,6 +78,25 @@ class GMTRemoteDataset(NamedTuple):
"01m": Resolution("01m", registrations=["gridline"], tiled=True),
},
),
"earth_day": GMTRemoteDataset(
description="NASA Day Images",
units=None,
extra_attributes={"long_name": "blue_marble", "horizontal_datum": "WGS84"},
resolutions={
"01d": Resolution("01d", registrations=["pixel"]),
"30m": Resolution("30m", registrations=["pixel"]),
"20m": Resolution("20m", registrations=["pixel"]),
"15m": Resolution("15m", registrations=["pixel"]),
"10m": Resolution("10m", registrations=["pixel"]),
"06m": Resolution("06m", registrations=["pixel"]),
"05m": Resolution("05m", registrations=["pixel"]),
"04m": Resolution("04m", registrations=["pixel"]),
"03m": Resolution("03m", registrations=["pixel"]),
"02m": Resolution("02m", registrations=["pixel"]),
"01m": Resolution("01m", registrations=["pixel"]),
"30s": Resolution("30s", registrations=["pixel"]),
},
),
"earth_faa": GMTRemoteDataset(
description="IGPP Earth free-air anomaly",
units="mGal",
Expand Down Expand Up @@ -409,15 +428,18 @@ def _load_remote_dataset(
f"'region' is required for {dataset.description} resolution '{resolution}'."
)

# Currently, only grids are supported. Will support images in the future.
kwdict = {"T": "g", "R": region} # region can be None
kind = "image" if name in {"earth_day"} else "grid"
kwdict = {
"R": region, # region can be None
"T": "i" if kind == "image" else "g",
}
with Session() as lib:
with lib.virtualfile_out(kind="grid") as voutgrd:
with lib.virtualfile_out(kind=kind) as voutgrd:
lib.call_module(
module="read",
args=[fname, voutgrd, *build_arg_list(kwdict)],
)
grid = lib.virtualfile_to_raster(outgrid=None, vfname=voutgrd)
grid = lib.virtualfile_to_raster(kind=kind, outgrid=None, vfname=voutgrd)

# Full path to the grid if not tiled grids.
source = which(fname, download="a") if not resinfo.tiled else None
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41 changes: 41 additions & 0 deletions pygmt/tests/test_datasets_earth_day.py
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"""
Test basic functionality for loading Blue Marble datasets.
"""

import numpy as np
import numpy.testing as npt
from pygmt.datasets import load_blue_marble


def test_blue_marble_01d():
"""
Test some properties of the Blue Marble 01d data.
"""
data = load_blue_marble(resolution="01d")
assert data.name == "z"
assert data.long_name == "blue_marble"
assert data.attrs["horizontal_datum"] == "WGS84"
assert data.attrs["description"] == "NASA Day Images"
assert data.shape == (3, 180, 360)
assert data.dtype == "uint8"
assert data.gmt.registration == 1
assert data.gmt.gtype == 1
npt.assert_allclose(data.y, np.arange(89.5, -90.5, -1))
npt.assert_allclose(data.x, np.arange(-179.5, 180.5, 1))
npt.assert_allclose(data.min(), 10, atol=1)
npt.assert_allclose(data.max(), 255, atol=1)


def test_blue_marble_01d_with_region():
"""
Test loading low-resolution Blue Marble with 'region'.
"""
data = load_blue_marble(resolution="01d", region=[-10, 10, -5, 5])
assert data.shape == (3, 10, 20)
assert data.dtype == "uint8"
assert data.gmt.registration == 1
assert data.gmt.gtype == 1
npt.assert_allclose(data.y, np.arange(4.5, -5.5, -1))
npt.assert_allclose(data.x, np.arange(-9.5, 10.5, 1))
npt.assert_allclose(data.min(), 10, atol=1)
npt.assert_allclose(data.max(), 77, atol=1)
12 changes: 5 additions & 7 deletions pygmt/tests/test_grdimage_image.py
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Expand Up @@ -3,7 +3,8 @@
"""

import pytest
from pygmt import Figure, which
from pygmt import Figure
from pygmt.datasets import load_blue_marble

rioxarray = pytest.importorskip("rioxarray")

Expand All @@ -14,12 +15,9 @@ def fixture_xr_image():
Load the image data from Blue Marble as an xarray.DataArray with shape {"band": 3,
"y": 180, "x": 360}.
"""
geotiff = which(fname="@earth_day_01d_p", download="c")
with rioxarray.open_rasterio(filename=geotiff) as rda:
if len(rda.band) == 3:
xr_image = rda.load()
assert xr_image.sizes == {"band": 3, "y": 180, "x": 360}
return xr_image
xr_image = load_blue_marble(resolution="01d")
assert xr_image.sizes == {"band": 3, "y": 180, "x": 360}
return xr_image


@pytest.mark.mpl_image_compare
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