Merge two tests using pytest parametrize

Check that numpy.array and xarray.Dataset inputs work.

pygmt/tests/test_nearneighbor.py

@@ -3,6 +3,7 @@
 """
 import os
 
+import numpy as np
 import numpy.testing as npt
 import pytest
 import xarray as xr
@@ -20,32 +21,18 @@ def fixture_ship_data():
  return load_sample_bathymetry()
 
 
-def test_nearneighbor_input_file():
+@pytest.mark.parametrize("array_func", [np.array, xr.Dataset])
+def test_nearneighbor_input_data(array_func, ship_data):
  """
- Run nearneighbor by passing in a filename.
+ Run nearneighbor by passing in a numpy.array or xarray.Dataset.
  """
- output = nearneighbor(
- data="@tut_ship.xyz",
- spacing="5m",
- region=[245, 255, 20, 30],
- search_radius="10m",
- )
- assert isinstance(output, xr.DataArray)
- assert output.gmt.registration == 0 # Gridline registration
- assert output.gmt.gtype == 0 # Cartesian type
- assert output.shape == (121, 121)
- npt.assert_allclose(output.mean(), -2378.2385)
-
-
-def test_nearneighbor_input_numpy_array(ship_data):
- """
- Run nearneighbor by passing in a numpy array into data.
- """
- data = ship_data.values # convert pandas.DataFrame to numpy.ndarray
+ data = array_func(ship_data)
  output = nearneighbor(
  data=data, spacing="5m", region=[245, 255, 20, 30], search_radius="10m"
  )
  assert isinstance(output, xr.DataArray)
+ assert output.gmt.registration == 0 # Gridline registration
+ assert output.gmt.gtype == 1 # Geographic type
  assert output.shape == (121, 121)
  npt.assert_allclose(output.mean(), -2378.2385)