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Remote datasets: Add "load_earth_mean_dynamic_topography" to load "CN…
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…ES Earth Mean Dynamic Topography" dataset (#3718)

Co-authored-by: Dongdong Tian <[email protected]>
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yvonnefroehlich and seisman authored Dec 26, 2024
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1 change: 1 addition & 0 deletions doc/api/index.rst
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datasets.load_earth_geoid
datasets.load_earth_magnetic_anomaly
datasets.load_earth_mask
datasets.load_earth_mean_dynamic_topography
datasets.load_earth_relief
datasets.load_earth_vertical_gravity_gradient
datasets.load_mars_relief
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3 changes: 3 additions & 0 deletions pygmt/datasets/__init__.py
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from pygmt.datasets.earth_geoid import load_earth_geoid
from pygmt.datasets.earth_magnetic_anomaly import load_earth_magnetic_anomaly
from pygmt.datasets.earth_mask import load_earth_mask
from pygmt.datasets.earth_mean_dynamic_topography import (
load_earth_mean_dynamic_topography,
)
from pygmt.datasets.earth_night import load_black_marble
from pygmt.datasets.earth_relief import load_earth_relief
from pygmt.datasets.earth_vertical_gravity_gradient import (
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103 changes: 103 additions & 0 deletions pygmt/datasets/earth_mean_dynamic_topography.py
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"""
Function to download the CNES Earth mean dynamic topography 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_mean_dynamic_topography"]


def load_earth_mean_dynamic_topography(
resolution: Literal["01d", "30m", "20m", "15m", "10m", "07m"] = "01d",
region: Sequence[float] | str | None = None,
registration: Literal["gridline", "pixel"] = "gridline",
) -> xr.DataArray:
r"""
Load the CNES Earth mean dynamic topography dataset in various resolutions.
.. figure:: https://www.generic-mapping-tools.org/remote-datasets/_images/GMT_earth_mdt.jpg
:width: 80 %
:align: center
CNES Earth mean dynamic topography dataset.
The grids are downloaded to a user data directory (usually
``~/.gmt/server/earth/earth_mdt/``) 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_mdt**\_\ *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).
The default color palette table (CPT) for this dataset is *@earth_mdt.cpt*. It's
implicitly used when passing in the file name of the dataset to any grid plotting
method if no CPT is explicitly specified. When the dataset is loaded and plotted
as an :class:`xarray.DataArray` object, the default CPT is ignored, and GMT's
default CPT (*turbo*) is used. To use the dataset-specific CPT, you need to
explicitly set ``cmap="@earth_mdt.cpt"``.
Refer to :gmt-datasets:`earth-mdt.html` for more details about available datasets,
including version information and references.
Parameters
----------
resolution
The grid resolution. The suffix ``d`` and ``m`` stand for arc-degrees and
arc-minutes. Note that ``"07m"`` refers to a resolution of 7.5 arc-minutes.
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 CNES Earth mean dynamic topography grid. Coordinates are latitude and
longitude in degrees. Values are in meters.
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_mean_dynamic_topography
>>> # load the default grid (gridline-registered 1 arc-degree grid)
>>> grid = load_earth_mean_dynamic_topography()
>>> # load the 30 arc-minutes grid with "gridline" registration
>>> grid = load_earth_mean_dynamic_topography(
resolution="30m", registration="gridline"
...)
>>> # load high-resolution (5 arc-minutes) grid for a specific region
>>> grid = load_earth_mean_dynamic_topography(
... resolution="05m",
... region=[120, 160, 30, 60],
... registration="gridline",
... )
"""
grid = _load_remote_dataset(
name="earth_mdt",
prefix="earth_mdt",
resolution=resolution,
region=region,
registration=registration,
)
return grid
13 changes: 13 additions & 0 deletions pygmt/datasets/load_remote_dataset.py
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Expand Up @@ -246,6 +246,19 @@ class GMTRemoteDataset(NamedTuple):
"30s": Resolution("30s", registrations=["pixel"]),
},
),
"earth_mdt": GMTRemoteDataset(
description="CNES Earth mean dynamic topography",
units="meters",
extra_attributes={"horizontal_datum": "WGS84"},
resolutions={
"01d": Resolution("01d"),
"30m": Resolution("30m"),
"20m": Resolution("20m"),
"15m": Resolution("15m"),
"10m": Resolution("10m"),
"07m": Resolution("07m", registrations=["gridline"]),
},
),
"earth_vgg": GMTRemoteDataset(
description="IGPP Earth vertical gravity gradient",
units="Eotvos",
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2 changes: 2 additions & 0 deletions pygmt/helpers/caching.py
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Expand Up @@ -23,6 +23,8 @@ def cache_data():
"@earth_mag_01d_g",
"@earth_mag4km_01d_g",
"@earth_mask_01d_g",
"@earth_mdt_01d_g",
"@earth_mdt_07m_g",
"@earth_night_01d",
"@earth_relief_01d_g",
"@earth_relief_01d_p",
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53 changes: 53 additions & 0 deletions pygmt/tests/test_datasets_mean_dynamic_topography.py
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"""
Test basic functionality for loading Earth mean dynamic topography datasets.
"""

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


def test_earth_mdt_01d():
"""
Test some properties of the Earth mean dynamic topography 01d data.
"""
data = load_earth_mean_dynamic_topography(resolution="01d")
assert data.name == "z"
assert data.attrs["description"] == "CNES Earth mean dynamic topography"
assert data.attrs["units"] == "meters"
assert data.attrs["horizontal_datum"] == "WGS84"
assert data.shape == (181, 361)
assert data.gmt.registration == 0
npt.assert_allclose(data.lat, np.arange(-90, 91, 1))
npt.assert_allclose(data.lon, np.arange(-180, 181, 1))
npt.assert_allclose(data.min(), -1.4668, atol=0.0001)
npt.assert_allclose(data.max(), 1.7151, atol=0.0001)


def test_earth_mdt_01d_with_region():
"""
Test loading low-resolution Earth mean dynamic topography with "region".
"""
data = load_earth_mean_dynamic_topography(resolution="01d", region=[-10, 10, -5, 5])
assert data.shape == (11, 21)
assert data.gmt.registration == 0
npt.assert_allclose(data.lat, np.arange(-5, 6, 1))
npt.assert_allclose(data.lon, np.arange(-10, 11, 1))
npt.assert_allclose(data.min(), 0.346, atol=0.0001)
npt.assert_allclose(data.max(), 0.4839, atol=0.0001)


def test_earth_mdt_07m_default_registration():
"""
Test that the grid returned by default for the 7 arc-minutes resolution has a
"gridline" registration.
"""
data = load_earth_mean_dynamic_topography(resolution="07m", region=[-10, -9, 3, 5])
assert data.shape == (17, 9)
assert data.gmt.registration == 0
assert data.coords["lat"].data.min() == 3.0
assert data.coords["lat"].data.max() == 5.0
assert data.coords["lon"].data.min() == -10.0
assert data.coords["lon"].data.max() == -9.0
npt.assert_allclose(data.min(), 0.4138, atol=0.0001)
npt.assert_allclose(data.max(), 0.4302, atol=0.0001)

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