Refactor pygmt.surface tests

pygmt/helpers/testing.py

@@ -172,6 +172,7 @@ def download_test_data():
         "@EGM96_to_36.txt",
         "@MaunaLoa_CO2.txt",
         "@Table_5_11.txt",
+        "@Table_5_11_mean.xyz",
         "@fractures_06.txt",
         "@hotspots.txt",
         "@ridge.txt",

pygmt/tests/test_surface.py

@@ -3,118 +3,167 @@
 """
 import os
 
+import pandas as pd
 import pytest
 import xarray as xr
 from pygmt import surface, which
-from pygmt.datasets import load_sample_bathymetry
 from pygmt.exceptions import GMTInvalidInput
-from pygmt.helpers import data_kind
+from pygmt.helpers import GMTTempFile, data_kind
 
-TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), "data")
-TEMP_GRID = os.path.join(TEST_DATA_DIR, "tmp_grid.nc")
 
+@pytest.fixture(scope="module", name="data")
+def fixture_data():
+    """
+    Load Table 5.11 in Davis: Statistics and Data Analysis in Geology.
+    """
+    fname = which("@Table_5_11_mean.xyz", download="c")
+    return pd.read_csv(
+        fname, sep=r"\s+", header=None, names=["x", "y", "z"], skiprows=1
+    )
+
+
+@pytest.fixture(scope="module", name="region")
+def fixture_region():
+    """
+    Define the region.
+    """
+    return [0, 4, 0, 8]
 
-@pytest.fixture(scope="module", name="ship_data")
-def fixture_ship_data():
+
+@pytest.fixture(scope="module", name="spacing")
+def fixture_spacing():
     """
-    Load the data from the sample bathymetry dataset.
+    Define the spacing.
     """
-    return load_sample_bathymetry()
+    return "1"
 
 
-def test_surface_input_file():
+@pytest.fixture(scope="module", name="expected_grid")
+def fixture_grid_result():
+    """
+    Load the expected grdcut grid result.
+    """
+    return xr.DataArray(
+        data=[
+            [962.2361, 909.526, 872.2578, 876.5983, 950.573],
+            [944.369, 905.8253, 872.1614, 901.8583, 943.6854],
+            [911.0599, 865.305, 845.5058, 855.7317, 867.1638],
+            [878.5973, 851.71, 814.6884, 812.1127, 819.9591],
+            [842.0522, 815.2896, 788.2292, 777.0031, 785.6345],
+            [854.2515, 813.3035, 781, 742.3641, 735.6497],
+            [882.972, 818.4636, 773.611, 718.7798, 685.4824],
+            [897.4532, 822.9642, 756.4472, 687.594, 626.2299],
+            [910.2932, 823.3307, 737.9952, 651.4994, 565.9981],
+        ],
+        coords=dict(
+            y=[0, 1, 2, 3, 4, 5, 6, 7, 8],
+            x=[0, 1, 2, 3, 4],
+        ),
+        dims=[
+            "y",
+            "x",
+        ],
+    )
+
+
+def check_values(grid, expected_grid):
+    """
+    Check the attributes and values of the DataArray returned by surface.
+    """
+    assert isinstance(grid, xr.DataArray)
+    assert grid.gmt.registration == 0  # Gridline registration
+    assert grid.gmt.gtype == 0  # Cartesian type
+    xr.testing.assert_allclose(a=grid, b=expected_grid)
+
+
+def test_surface_input_file(region, spacing, expected_grid):
     """
     Run surface by passing in a filename.
     """
-    fname = which("@tut_ship.xyz", download="c")
-    output = surface(data=fname, spacing="5m", region=[245, 255, 20, 30])
-    assert isinstance(output, xr.DataArray)
-    assert output.gmt.registration == 0  # Gridline registration
-    assert output.gmt.gtype == 0  # Cartesian type
+    output = surface(
+        data="@Table_5_11_mean.xyz",
+        spacing=spacing,
+        region=region,
+        verbose="e",  # Suppress warnings for IEEE 754 rounding
+    )
+    check_values(output, expected_grid)
 
 
-def test_surface_input_data_array(ship_data):
+def test_surface_input_data_array(data, region, spacing, expected_grid):
     """
     Run surface by passing in a numpy array into data.
     """
-    data = ship_data.values  # convert pandas.DataFrame to numpy.ndarray
-    output = surface(data=data, spacing="5m", region=[245, 255, 20, 30])
-    assert isinstance(output, xr.DataArray)
+    data = data.values  # convert pandas.DataFrame to numpy.ndarray
+    output = surface(
+        data=data,
+        spacing=spacing,
+        region=region,
+        verbose="e",  # Suppress warnings for IEEE 754 rounding
+    )
+    check_values(output, expected_grid)
 
 
-def test_surface_input_xyz(ship_data):
+def test_surface_input_xyz(data, region, spacing, expected_grid):
     """
     Run surface by passing in x, y, z numpy.ndarrays individually.
     """
     output = surface(
-        x=ship_data.longitude,
-        y=ship_data.latitude,
-        z=ship_data.bathymetry,
-        spacing="5m",
-        region=[245, 255, 20, 30],
+        x=data.x,
+        y=data.y,
+        z=data.z,
+        spacing=spacing,
+        region=region,
+        verbose="e",  # Suppress warnings for IEEE 754 rounding
     )
-    assert isinstance(output, xr.DataArray)
+    check_values(output, expected_grid)
 
 
-def test_surface_wrong_kind_of_input(ship_data):
+def test_surface_wrong_kind_of_input(data, region, spacing):
     """
     Run surface using grid input that is not file/matrix/vectors.
     """
-    data = ship_data.bathymetry.to_xarray()  # convert pandas.Series to xarray.DataArray
+    data = data.z.to_xarray()  # convert pandas.Series to xarray.DataArray
     assert data_kind(data) == "grid"
     with pytest.raises(GMTInvalidInput):
-        surface(data=data, spacing="5m", region=[245, 255, 20, 30])
+        surface(data=data, spacing=spacing, region=region)
 
 
-def test_surface_with_outgrid_param(ship_data):
+def test_surface_with_outgrid_param(data, region, spacing, expected_grid):
     """
     Run surface with the -Goutputfile.nc parameter.
     """
-    data = ship_data.values  # convert pandas.DataFrame to numpy.ndarray
-    try:
+    data = data.values  # convert pandas.DataFrame to numpy.ndarray
+    with GMTTempFile(suffix=".nc") as tmpfile:
         output = surface(
-            data=data, spacing="5m", region=[245, 255, 20, 30], outgrid=TEMP_GRID
+            data=data,
+            spacing=spacing,
+            region=region,
+            outgrid=tmpfile.name,
+            verbose="e",  # Suppress warnings for IEEE 754 rounding
         )
         assert output is None  # check that output is None since outgrid is set
-        assert os.path.exists(path=TEMP_GRID)  # check that outgrid exists at path
-        with xr.open_dataarray(TEMP_GRID) as grid:
-            assert isinstance(grid, xr.DataArray)  # ensure netcdf grid loads ok
-    finally:
-        os.remove(path=TEMP_GRID)
+        assert os.path.exists(path=tmpfile.name)  # check that outgrid exists at path
+        with xr.open_dataarray(tmpfile.name) as grid:
+            check_values(grid, expected_grid)
 
 
-def test_surface_deprecate_outfile_to_outgrid(ship_data):
+def test_surface_deprecate_outfile_to_outgrid(data, region, spacing, expected_grid):
     """
     Make sure that the old parameter "outfile" is supported and it reports a
     warning.
     """
     with pytest.warns(expected_warning=FutureWarning) as record:
-        data = ship_data.values  # convert pandas.DataFrame to numpy.ndarray
-        try:
+        data = data.values  # convert pandas.DataFrame to numpy.ndarray
+        with GMTTempFile(suffix=".nc") as tmpfile:
             output = surface(
-                data=data, spacing="5m", region=[245, 255, 20, 30], outfile=TEMP_GRID
+                data=data,
+                spacing=spacing,
+                region=region,
+                outfile=tmpfile.name,
+                verbose="e",  # Suppress warnings for IEEE 754 rounding
             )
             assert output is None  # check that output is None since outfile is set
-            assert os.path.exists(path=TEMP_GRID)  # check that file exists at path
-
-            with xr.open_dataarray(TEMP_GRID) as grid:
-                assert isinstance(grid, xr.DataArray)  # ensure netcdf grid loads ok
-        finally:
-            os.remove(path=TEMP_GRID)
+            assert os.path.exists(path=tmpfile.name)  # check that file exists at path
+            with xr.open_dataarray(tmpfile.name) as grid:
+                check_values(grid, expected_grid)
         assert len(record) == 1  # check that only one warning was raised
-
-
-def test_surface_short_aliases(ship_data):
-    """
-    Run surface using short aliases -I for spacing, -R for region, -G for
-    outgrid.
-    """
-    data = ship_data.values  # convert pandas.DataFrame to numpy.ndarray
-    try:
-        output = surface(data=data, I="5m", R=[245, 255, 20, 30], G=TEMP_GRID)
-        assert output is None  # check that output is None since outgrid is set
-        assert os.path.exists(path=TEMP_GRID)  # check that outgrid exists at path
-        with xr.open_dataarray(TEMP_GRID) as grid:
-            assert isinstance(grid, xr.DataArray)  # ensure netcdf grid loads ok
-    finally:
-        os.remove(path=TEMP_GRID)