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Set dims to longitude, latitude if projection passed #328

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Set dims to longitude, latitude if projection passed #328

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e670482
Set dims to longitude, latitude if projection passed
santisoler Jul 19, 2021
9a8f73d
Check if projection is not None instead of True
santisoler Jul 21, 2021
49d9782
Run test function with a dummy projection
santisoler Jul 21, 2021
5c88a74
Merge branch 'master' into dims-on-projection
santisoler Aug 30, 2021
91b2889
Merge branch '2.0-dev' into dims-on-projection
santisoler Nov 3, 2021
7e65800
Make projection argument in _get_dims optional
santisoler Nov 3, 2021
fcc4e1c
Call _get_dims with projection as a kwarg
santisoler Nov 3, 2021
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13 changes: 9 additions & 4 deletions verde/base/base_classes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -215,6 +215,9 @@ class BaseGridder(BaseEstimator):
# (pd.DataFrame, xr.Dataset, etc)
dims = ("northing", "easting")

# The default dimension names for generated outputs if projection is passed
unproj_dims = ("latitude", "longitude")

# The default name for any extra coordinates given to methods below
# through the `extra_coords` keyword argument. Coordinates are
# included in the outputs (pandas.DataFrame or xarray.Dataset)
Expand Down Expand Up @@ -482,7 +485,7 @@ def grid(
self.predict(project_coordinates(coordinates, projection))
)
# Get names for dims, data and any extra coordinates
dims = self._get_dims(dims)
dims = self._get_dims(dims, projection=projection)
data_names = self._get_data_names(data, data_names)
extra_coords_names = self._get_extra_coords_names(coordinates)
# Create xarray.Dataset
Expand Down Expand Up @@ -563,7 +566,7 @@ def scatter(
The interpolated values on a random set of points.

"""
dims = self._get_dims(dims)
dims = self._get_dims(dims, projection=projection)
region = get_instance_region(self, region)
coordinates = scatter_points(region, size, random_state=random_state, **kwargs)
if projection is None:
Expand Down Expand Up @@ -669,7 +672,7 @@ def profile(
The interpolated values along the profile.

"""
dims = self._get_dims(dims)
dims = self._get_dims(dims, projection=projection)
# Project the input points to generate the profile in Cartesian
# coordinates (the distance calculation doesn't make sense in
# geographic coordinates since we don't do actual distances on a
Expand All @@ -694,12 +697,14 @@ def profile(
columns.extend(zip(data_names, data))
return pd.DataFrame(dict(columns), columns=[c[0] for c in columns])

def _get_dims(self, dims):
def _get_dims(self, dims, projection=None):
"""
Get default dimension names.
"""
if dims is not None:
return dims
if projection is not None:
return self.unproj_dims
return self.dims

def _get_extra_coords_names(self, coordinates):
Expand Down
45 changes: 31 additions & 14 deletions verde/tests/test_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,11 +39,28 @@ def test_check_coordinates():

def test_get_dims():
"Tests that get_dims returns the expected results"
# Define a dummy projection function
def proj(lon, lat, inverse=False):
return None

gridder = BaseGridder()
assert gridder._get_dims(dims=None) == ("northing", "easting")
assert gridder._get_dims(dims=("john", "paul")) == ("john", "paul")
assert gridder._get_dims(dims=None, projection=None) == ("northing", "easting")
assert gridder._get_dims(dims=("john", "paul"), projection=None) == ("john", "paul")
gridder.dims = ("latitude", "longitude")
assert gridder._get_dims(dims=None) == ("latitude", "longitude")
assert gridder._get_dims(dims=None, projection=None) == ("latitude", "longitude")
# Test with a projection
gridder = BaseGridder()
assert gridder._get_dims(dims=None, projection=proj) == ("latitude", "longitude")
assert gridder._get_dims(dims=("john", "paul"), projection=proj) == (
"john",
"paul",
)
gridder.unproj_dims = ("latitude_1", "longitude_1")
assert gridder._get_dims(dims=None, projection=proj) == (
"latitude_1",
"longitude_1",
)


def test_get_data_names():
Expand Down Expand Up @@ -214,14 +231,14 @@ def proj(lon, lat, inverse=False):
# Check the scatter
scat = grd.scatter(region, 1000, random_state=0, projection=proj)
npt.assert_allclose(scat.scalars, data)
npt.assert_allclose(scat.easting, coordinates[0])
npt.assert_allclose(scat.northing, coordinates[1])
npt.assert_allclose(scat.longitude, coordinates[0])
npt.assert_allclose(scat.latitude, coordinates[1])

# Check the grid
grid = grd.grid(region=region, shape=shape, projection=proj)
npt.assert_allclose(grid.scalars.values, data_true)
npt.assert_allclose(grid.easting.values, coordinates_true[0][0, :])
npt.assert_allclose(grid.northing.values, coordinates_true[1][:, 0])
npt.assert_allclose(grid.longitude.values, coordinates_true[0][0, :])
npt.assert_allclose(grid.latitude.values, coordinates_true[1][:, 0])

# Check the profile
prof = grd.profile(
Expand All @@ -230,8 +247,8 @@ def proj(lon, lat, inverse=False):
npt.assert_allclose(prof.scalars, data_true[-1, :])
# Coordinates should still be evenly spaced since the projection is a
# multiplication.
npt.assert_allclose(prof.easting, coordinates_true[0][0, :])
npt.assert_allclose(prof.northing, coordinates_true[1][-1, :])
npt.assert_allclose(prof.longitude, coordinates_true[0][0, :])
npt.assert_allclose(prof.latitude, coordinates_true[1][-1, :])
# Distance should still be in the projected coordinates. If the projection
# is from geographic, we shouldn't be returning distances in degrees but in
# projected meters. The distances will be evenly spaced in unprojected
Expand Down Expand Up @@ -339,14 +356,14 @@ def proj(lon, lat, inverse=False):
region, 1000, random_state=0, projection=proj, extra_coords=(13, 17)
)
npt.assert_allclose(scat.scalars, data)
npt.assert_allclose(scat.easting, coordinates[0])
npt.assert_allclose(scat.northing, coordinates[1])
npt.assert_allclose(scat.longitude, coordinates[0])
npt.assert_allclose(scat.latitude, coordinates[1])

# Check the grid
grid = grd.grid(region=region, shape=shape, projection=proj, extra_coords=(13, 17))
npt.assert_allclose(grid.scalars.values, data_true)
npt.assert_allclose(grid.easting.values, coordinates_true[0][0, :])
npt.assert_allclose(grid.northing.values, coordinates_true[1][:, 0])
npt.assert_allclose(grid.longitude.values, coordinates_true[0][0, :])
npt.assert_allclose(grid.latitude.values, coordinates_true[1][:, 0])

# Check the profile
prof = grd.profile(
Expand All @@ -359,8 +376,8 @@ def proj(lon, lat, inverse=False):
npt.assert_allclose(prof.scalars, data_true[-1, :])
# Coordinates should still be evenly spaced since the projection is a
# multiplication.
npt.assert_allclose(prof.easting, coordinates_true[0][0, :])
npt.assert_allclose(prof.northing, coordinates_true[1][-1, :])
npt.assert_allclose(prof.longitude, coordinates_true[0][0, :])
npt.assert_allclose(prof.latitude, coordinates_true[1][-1, :])
# Distance should still be in the projected coordinates. If the projection
# is from geographic, we shouldn't be returning distances in degrees but in
# projected meters. The distances will be evenly spaced in unprojected
Expand Down