def test_grdgradient_fails(grid):
"""
Check that grdgradient fails correctly when neither of azimuth, direction
or radiance is given.
"""
with pytest.raises(GMTInvalidInput):
grdgradient(grid=grid)
def test_grdgradient_fails(grid):
"""
Check that grdgradient fails correctly.
Check that grdgradient fails correctly when `tiles` is specified but
normalize is not.
"""
with pytest.raises(GMTInvalidInput):
grdgradient(grid=grid) # fails without required arguments
with pytest.raises(GMTInvalidInput):
# fails when tiles is specified but not normalize
grdgradient(grid=grid, azimuth=10, direction="c", tiles="c")
def test_grdgradient_no_outgrid(grid, expected_grid):
"""
Test the azimuth and direction parameters for grdgradient with no set
outgrid.
"""
result = grdgradient(grid=grid, azimuth=10, region=[-53, -49, -20, -17])
# check information of the output grid
assert isinstance(result, xr.DataArray)
assert result.gmt.gtype == 1 # Geographic grid
assert result.gmt.registration == 1 # Pixel registration
# check information of the output grid
xr.testing.assert_allclose(a=result, b=expected_grid)
def test_grdgradient_no_outgrid(grid):
"""
Test the azimuth and direction parameters for grdgradient with no set
outgrid.
"""
temp_grid = grdgradient(grid=grid, azimuth=10, direction="c")
assert temp_grid.dims == ("lat", "lon")
assert temp_grid.gmt.gtype == 1 # Geographic grid
assert temp_grid.gmt.registration == 1 # Pixel registration
npt.assert_allclose(temp_grid.min(), -0.0045060496)
npt.assert_allclose(temp_grid.max(), 0.0575332976)
npt.assert_allclose(temp_grid.median(), 0.0004889865522272885)
npt.assert_allclose(temp_grid.mean(), 0.0028633063193410635)
def test_grdgradient_outgrid(grid, expected_grid):
"""
Test the azimuth and direction parameters for grdgradient with a set
outgrid.
"""
with GMTTempFile(suffix=".nc") as tmpfile:
result = grdgradient(grid=grid,
outgrid=tmpfile.name,
azimuth=10,
region=[-53, -49, -20, -17])
assert result is None # return value is None
assert os.path.exists(path=tmpfile.name) # check that outgrid exists
temp_grid = load_dataarray(tmpfile.name)
xr.testing.assert_allclose(a=temp_grid, b=expected_grid)
def test_grdgradient_no_outgrid(grid, expected_grid):
"""
Test the azimuth and direction parameters for grdgradient with no set
outgrid.
This is a regression test for
https://github.com/GenericMappingTools/pygmt/issues/1807.
"""
result = grdgradient(grid=grid,
azimuth=10,
region=[-53, -49, -20, -17],
outgrid=None)
# check information of the output grid
assert isinstance(result, xr.DataArray)
assert result.gmt.gtype == 1 # Geographic grid
assert result.gmt.registration == 1 # Pixel registration
# check information of the output grid
xr.testing.assert_allclose(a=result, b=expected_grid)
def test_grdgradient_outgrid(grid):
"""
Test the azimuth and direction parameters for grdgradient with a set
outgrid.
"""
with GMTTempFile(suffix=".nc") as tmpfile:
result = grdgradient(grid=grid,
outgrid=tmpfile.name,
azimuth=10,
direction="c")
assert result is None # return value is None
assert os.path.exists(path=tmpfile.name) # check that outgrid exists
result = (grdinfo(grid=tmpfile.name, force_scan="a",
per_column="n").strip().split())
npt.assert_allclose(float(result[4]), -0.0045060496) # min
npt.assert_allclose(float(result[5]), 0.0575332976) # max
# Check spherically weighted statistics below
npt.assert_allclose(float(result[10]), 0.000384754501283) # median
npt.assert_allclose(float(result[12]), 0.00285958005568) # mean
the respective gradient and returns it as an :class:`xarray.DataArray` object.
We will use the ``radiance`` parameter in order to set the illumination source
direction and altitude.
"""
import pygmt
# Define region of interest around Yosemite valley
region = [-119.825, -119.4, 37.6, 37.825]
# Load sample grid (3 arc second global relief) in target area
grid = pygmt.datasets.load_earth_relief(resolution="03s", region=region)
# calculate the reflection of a light source projecting from west to east
# (azimuth of 270 degrees) and at a latitude of 30 degrees from the horizon
dgrid = pygmt.grdgradient(grid=grid, radiance=[270, 30])
fig = pygmt.Figure()
# define figure configuration
pygmt.config(FORMAT_GEO_MAP="ddd.x", MAP_FRAME_TYPE="plain")
# --------------- plotting the original Data Elevation Model -----------
pygmt.makecpt(cmap="gray", series=[200, 4000, 10])
fig.grdimage(
grid=grid,
projection="M12c",
frame=['WSrt+t"Original Data Elevation Model"', "xa0.1", "ya0.1"],
cmap=True,
)
