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Add function to load Blue Marble dataset #2235
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""" | ||
Function to download the NASA Blue Marble image datasets from the GMT data server, and | ||
load as :class:`xarray.DataArray`. | ||
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The images are available in various resolutions. | ||
""" | ||
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from collections.abc import Sequence | ||
from typing import Literal | ||
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import xarray as xr | ||
from pygmt.datasets.load_remote_dataset import _load_remote_dataset | ||
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__doctest_skip__ = ["load_blue_marble"] | ||
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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. | ||
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.. figure:: https://www.generic-mapping-tools.org/remote-datasets/_images/GMT_earth_daynight.jpg | ||
:width: 80% | ||
:align: center | ||
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Earth day/night dataset. | ||
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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. | ||
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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). | ||
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Refer to :gmt-datasets:`earth-daynight.html` for more details about available | ||
datasets, including version information and references. | ||
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Parameters | ||
---------- | ||
resolution | ||
The image resolution. The suffix ``d``, ``m``, and ``s`` stand for arc-degree, | ||
arc-minute, and arc-second. | ||
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region | ||
The subregion of the image to load, in the form of a sequence [*xmin*, *xmax*, | ||
*ymin*, *ymax*]. | ||
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Returns | ||
------- | ||
image | ||
The NASA Blue Marble image. Coordinates are latitude and longitude in degrees. | ||
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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. | ||
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Examples | ||
-------- | ||
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>>> 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 |
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""" | ||
Test basic functionality for loading Blue Marble datasets. | ||
""" | ||
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import numpy as np | ||
import numpy.testing as npt | ||
from pygmt.datasets import load_blue_marble | ||
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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) | ||
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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) |
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""" | ||||
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import pytest | ||||
from pygmt import Figure, which | ||||
from pygmt import Figure | ||||
from pygmt.datasets import load_blue_marble | ||||
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rioxarray = pytest.importorskip("rioxarray") | ||||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Can this line be removed?
Suggested change
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Not yet, because we are still using |
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@@ -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 | ||||
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@pytest.mark.mpl_image_compare | ||||
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In
GMT_IMAGE.to_dataarray()
, perhaps we should parse theheader->ProjRefPROJ4
and set the correct CRS to the 3-band xarray.DataArray. If done, then we probably don't need to set the CRS here.There was a problem hiding this comment.
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Yeah, I was thinking of parsing the projection information from the header when you mentioned this
ProjRefPROJ4
field at #3128 (comment). But ideally we'll need to handle PROJ4/WKT/EPSG:pygmt/pygmt/datatypes/header.py
Lines 138 to 143 in f97c3a4
Something to consider for a separate PR, because we might need to use
pyproj
for this.