Add load_static_earth_relief function for internal testing

pygmt/datasets/samples.py

@@ -4,6 +4,7 @@
 import warnings
 
 import pandas as pd
+import xarray as xr
 from pygmt.exceptions import GMTInvalidInput
 from pygmt.src import which
 
@@ -30,6 +31,7 @@ def list_sample_data():
         "mars_shape": "Table of topographic signature of the hemispheric dichotomy of "
         " Mars from Smith and Zuber (1996)",
         "ocean_ridge_points": "Table of ocean ridge points for the entire world",
+        "static_earth_relief": "Sample grid used for testing",
         "usgs_quakes": "Table of global earthquakes from the USGS",
     }
     return names
@@ -70,6 +72,7 @@ def load_sample_data(name):
         "japan_quakes": load_japan_quakes,
         "mars_shape": load_mars_shape,
         "ocean_ridge_points": load_ocean_ridge_points,
+        "static_earth_relief": _load_static_earth_relief,
         "usgs_quakes": load_usgs_quakes,
     }
 
@@ -343,3 +346,17 @@ def load_mars_shape(**kwargs):
         fname, sep="\t", header=None, names=["longitude", "latitude", "radius(m)"]
     )
     return data
+
+
+def _load_static_earth_relief(**kwargs):
+    """
+    Load the static_earth_relief file for internal testing.
+
+    Returns
+    -------
+    data : xarray.DataArray
+        A grid of Earth relief for internal tests.
+    """
+    fname = which("@static_earth_relief.nc", download="c")
+    data = xr.open_dataarray(fname)
+    return data

pygmt/tests/test_datasets_samples.py

@@ -1,8 +1,10 @@
 """
 Test basic functionality for loading sample datasets.
 """
+import numpy.testing as npt
 import pandas as pd
 import pytest
+import xarray as xr
 from pygmt.datasets import (
     load_fractures_compilation,
     load_hotspots,
@@ -145,3 +147,17 @@ def test_hotspots():
         "place_name",
     ]
     assert isinstance(data, pd.DataFrame)
+
+
+def test_load_static_earth_relief():
+    """
+    Check that @static_earth_relief.nc loads without errors.
+    """
+    data = load_sample_data("static_earth_relief")
+    assert data.dims == ("lat", "lon")
+    assert data.shape == (14, 8)
+    assert data.min() == 190
+    assert data.max() == 981
+    assert data.median() == 467
+    npt.assert_allclose(data.mean(), 490.87946)
+    assert isinstance(data, xr.DataArray)