def fixture_tracks():
"""
Load track data from the sample bathymetry file.
"""
dataframe = load_sample_bathymetry()
dataframe.columns = ["x", "y", "z"] # longitude, latitude, bathymetry
return [dataframe.query(expr="z > -20")] # reduce size of dataset
def test_surface_input_data_array():
"""
Run surface by passing in a numpy array into data
"""
ship_data = load_sample_bathymetry()
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)
return output
def test_blockmean_wrong_kind_of_input_table_grid():
"""
Run blockmean using table input that is not a pandas.DataFrame or file but
a grid.
"""
dataframe = load_sample_bathymetry()
invalid_table = dataframe.bathymetry.to_xarray()
assert data_kind(invalid_table) == "grid"
with pytest.raises(GMTInvalidInput):
blockmean(table=invalid_table, spacing="5m", region=[245, 255, 20, 30])
def test_blockmean_wrong_kind_of_input_table_matrix():
"""
Run blockmean using table input that is not a pandas.DataFrame but still a
matrix.
"""
dataframe = load_sample_bathymetry()
invalid_table = dataframe.values
assert data_kind(invalid_table) == "matrix"
with pytest.raises(GMTInvalidInput):
blockmean(table=invalid_table, spacing="5m", region=[245, 255, 20, 30])
def test_surface_wrong_kind_of_input():
"""
Run surface using grid input that is not file/matrix/vectors
"""
ship_data = load_sample_bathymetry()
data = ship_data.bathymetry.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])
def test_sample_bathymetry():
"Check that the @tut_ship.xyz dataset loads without errors"
data = load_sample_bathymetry()
assert data.shape == (82970, 3)
summary = data.describe()
assert summary.loc["min", "longitude"] == 245.0
assert summary.loc["max", "longitude"] == 254.705
assert summary.loc["min", "latitude"] == 20.0
assert summary.loc["max", "latitude"] == 29.99131
assert summary.loc["min", "bathymetry"] == -7708.0
assert summary.loc["max", "bathymetry"] == -9.0
def test_surface_input_xy_no_z():
"""
Run surface by passing in x and y, but no z
"""
ship_data = load_sample_bathymetry()
with pytest.raises(GMTInvalidInput):
surface(
x=ship_data.longitude,
y=ship_data.latitude,
spacing="5m",
region=[245, 255, 20, 30],
)
def test_blockmedian_input_dataframe():
"""
Run blockmedian by passing in a pandas.DataFrame as input
"""
dataframe = load_sample_bathymetry()
output = blockmedian(table=dataframe, spacing="5m", region=[245, 255, 20, 30])
assert isinstance(output, pd.DataFrame)
assert all(dataframe.columns == output.columns)
assert output.shape == (5849, 3)
npt.assert_allclose(output.iloc[0], [245.88819, 29.97895, -385.0])
return output
def test_surface_input_xyz():
"""
Run surface by passing in x, y, z numpy.ndarrays individually
"""
ship_data = load_sample_bathymetry()
output = surface(
x=ship_data.longitude,
y=ship_data.latitude,
z=ship_data.bathymetry,
spacing="5m",
region=[245, 255, 20, 30],
)
assert isinstance(output, xr.DataArray)
return output
def test_sample_bathymetry():
"""
Check that the @tut_ship.xyz dataset loads without errors.
"""
with pytest.warns(expected_warning=FutureWarning) as record:
data = load_sample_bathymetry()
assert len(record) == 1
assert data.shape == (82970, 3)
summary = data.describe()
assert summary.loc["min", "longitude"] == 245.0
assert summary.loc["max", "longitude"] == 254.705
assert summary.loc["min", "latitude"] == 20.0
assert summary.loc["max", "latitude"] == 29.99131
assert summary.loc["min", "bathymetry"] == -7708.0
assert summary.loc["max", "bathymetry"] == -9.0
def test_surface_short_aliases():
"""
Run surface using short aliases -I for spacing, -R for region, -G for
outfile
"""
ship_data = load_sample_bathymetry()
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 outfile is set
assert os.path.exists(
path=TEMP_GRID) # check that outfile 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)
return output
def test_surface_with_outfile_param():
"""
Run surface with the -Goutputfile.nc parameter
"""
ship_data = load_sample_bathymetry()
data = ship_data.values # convert pandas.DataFrame to numpy.ndarray
try:
output = surface(data=data,
spacing="5m",
region=[245, 255, 20, 30],
outfile=TEMP_GRID)
assert output is None # check that output is None since outfile is set
assert os.path.exists(
path=TEMP_GRID) # check that outfile 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)
return output
def fixture_ship_data():
"""
Load the data from the sample bathymetry dataset.
"""
return load_sample_bathymetry()
def fixture_dataframe():
"""
Load the grid data from the sample earth_relief file.
"""
return load_sample_bathymetry()
def fixture_dataframe():
"""
Load the table data from the sample bathymetry dataset.
"""
return load_sample_bathymetry()
