def test_interpolation_tables_agree_anywhere_for_dbarclays_data():
# load data and initialize interpolator
path = path_to_assets + '/BathyData_Mariana_500kmx500km.mat'
bathy, lat, lon = load_data_from_file(path,
lat_name='latgrat',
lon_name='longrat',
val_name='mat',
lon_axis=0)
ip = Interpolator2D(bathy, lat, lon)
# --- at origo ---
lat_c = ip.origin[0]
lon_c = ip.origin[1]
z_ll = ip.interp(lat=lat_c, lon=lon_c) # interpolate using lat-lon
z_ll = float(z_ll)
z_xy = ip.interp_xy(x=0, y=0) # interpolate using x-y
z_xy = float(z_xy)
assert z_ll == pytest.approx(z_xy, rel=1E-3) or z_ll == pytest.approx(
z_xy, abs=0.1)
# --- at shifted origo ---
bathy, lat, lon = load_data_from_file(path,
lat_name='latgrat',
lon_name='longrat',
val_name='mat',
lon_axis=0)
ip = Interpolator2D(bathy, lat, lon, origin=(9., 140.))
lat_c = ip.origin[0]
lon_c = ip.origin[1]
z_ll = ip.interp(lat=lat_c, lon=lon_c) # interpolate using lat-lon
z_ll = float(z_ll)
z_xy = ip.interp_xy(x=0, y=0) # interpolate using x-y
z_xy = float(z_xy)
assert z_ll == pytest.approx(z_xy, rel=1E-3) or z_ll == pytest.approx(
z_xy, abs=0.1)
def test_interpolation_tables_agree_anywhere():
# load data and initialize interpolator
path = path_to_assets + '/bornholm.mat'
bathy, lat, lon = load_data_from_file(path)
ip = Interpolator2D(bathy, lat, lon)
# --- at origo ---
lat_c, lon_c = center_point(lat, lon)
#lat_c = ip.origin.latitude
#lon_c = ip.origin.longitude
z_ll = ip.interp(lat=lat_c, lon=lon_c) # interpolate using lat-lon
z_ll = float(z_ll)
z_xy = ip.interp_xy(x=0, y=0) # interpolate using x-y
z_xy = float(z_xy)
assert z_ll == pytest.approx(z_xy, rel=1e-3) or z_xy == pytest.approx(
z_ll, abs=0.1)
# --- 0.1 degrees north of origo ---
lat = lat_c + 0.1
lon = lon_c
x, y = LLtoXY(lat=lat, lon=lon, lat_ref=lat_c, lon_ref=lon_c)
z_ll = ip.interp(lat=lat, lon=lon)
z_ll = float(z_ll)
z_xy = ip.interp_xy(x=x, y=y)
z_xy = float(z_xy)
assert z_ll == pytest.approx(z_xy, rel=1e-3) or z_xy == pytest.approx(
z_ll, abs=0.1)
# --- 0.08 degrees south of origo ---
lat = lat_c - 0.08
lon = lon_c
x, y = LLtoXY(lat=lat, lon=lon, lat_ref=lat_c, lon_ref=lon_c)
z_ll = ip.interp(lat=lat, lon=lon)
z_ll = float(z_ll)
z_xy = ip.interp_xy(x=x, y=y)
z_xy = float(z_xy)
assert z_ll == pytest.approx(z_xy, rel=1e-3) or z_xy == pytest.approx(
z_ll, abs=0.1)
# --- at shifted origo ---
bathy, lat, lon = load_data_from_file(path)
ip = Interpolator2D(bathy, lat, lon, origin=(55.30, 15.10))
lat_c = ip.origin[0]
lon_c = ip.origin[1]
z_ll = ip.interp(lat=lat_c, lon=lon_c) # interpolate using lat-lon
z_ll = float(z_ll)
z_xy = ip.interp_xy(x=0, y=0) # interpolate using x-y
z_xy = float(z_xy)
assert z_ll == pytest.approx(z_xy, rel=1e-3) or z_xy == pytest.approx(
z_ll, abs=0.1)
def test_interpolation_tables_agree_on_ll_grid_for_dbarclays_data():
# load data and initialize interpolator
path = path_to_assets + '/BathyData_Mariana_500kmx500km.mat'
bathy, lat, lon = load_data_from_file(path,
lat_name='latgrat',
lon_name='longrat',
val_name='mat',
lon_axis=0)
ip = Interpolator2D(bathy, lat, lon)
# lat fixed
ilat = int(len(ip.lat_nodes) / 2)
lat = ip.lat_nodes[ilat]
for lon in ip.lon_nodes:
bll = ip.interp(lat=lat, lon=lon)
x, y = LLtoXY(lat=lat,
lon=lon,
lat_ref=ip.origin[0],
lon_ref=ip.origin[1])
bxy = ip.interp_xy(x=x, y=y)
assert bxy == pytest.approx(bll, rel=1e-3) or bxy == pytest.approx(
bll, abs=0.1)
# lon fixed
ilon = int(len(ip.lon_nodes) / 2)
lon = ip.lon_nodes[ilon]
for lat in ip.lat_nodes:
bll = ip.interp(lat=lat, lon=lon)
x, y = LLtoXY(lat=lat,
lon=lon,
lat_ref=ip.origin[0],
lon_ref=ip.origin[1])
bxy = ip.interp_xy(x=x, y=y)
assert bxy == pytest.approx(bll, rel=1e-3) or bxy == pytest.approx(
bll, abs=0.1)
def test_interpolation_tables_agree_on_latlon_grid():
# load data and initialize interpolator
path = path_to_assets + '/bornholm.mat'
bathy, lat, lon = load_data_from_file(path)
ip = Interpolator2D(bathy, lat, lon)
# lat fixed
ilat = int(len(ip.lat_nodes) / 2)
lat = ip.lat_nodes[ilat]
for lon in ip.lon_nodes:
bll = ip.interp(lat=lat, lon=lon)
#x, y = LLtoXY(lat=lat, lon=lon, lat_ref=ip.origin.latitude, lon_ref=ip.origin.longitude)
x, y = LLtoXY(lat=lat,
lon=lon,
lat_ref=ip.origin[0],
lon_ref=ip.origin[1])
bxy = ip.interp_xy(x=x, y=y)
assert bxy == pytest.approx(bll, rel=1e-3) or bxy == pytest.approx(
bll, abs=0.1)
# lon fixed
ilon = int(len(ip.lon_nodes) / 2)
lon = ip.lon_nodes[ilon]
for lat in ip.lat_nodes:
bll = ip.interp(lat=lat, lon=lon)
x, y = LLtoXY(lat=lat,
lon=lon,
lat_ref=ip.origin[0],
lon_ref=ip.origin[1])
bxy = ip.interp_xy(x=x, y=y)
assert bxy == pytest.approx(bll, rel=1e-3) or bxy == pytest.approx(
bll, abs=0.1)
def test_interpolation_grids_are_what_they_should_be():
# load data and initialize interpolator
path = path_to_assets + '/bornholm.mat'
bathy, lat, lon = load_data_from_file(path)
ip = Interpolator2D(bathy, lat, lon)
lat_c = 0.5 * (lat[0] + lat[-1])
lon_c = 0.5 * (lon[0] + lon[-1])
assert lat_c, lon_c == center_point(lat, lon)
def test_mariana_trench_is_in_correct_location():
# load data and initialize interpolator
path = path_to_assets + '/BathyData_Mariana_500kmx500km.mat'
bathy, lat, lon = load_data_from_file(path,
lat_name='latgrat',
lon_name='longrat',
val_name='mat',
lon_axis=0)
ip = Interpolator2D(bathy, lat, lon)
d = ip.interp(lat=11.3733, lon=142.5917)
assert d < -10770
d = ip.interp(lat=12.0, lon=142.4)
assert d > -3000
d = ip.interp(lat=11.4, lon=143.1)
assert d < -9000
def test_interpolate_bathymetry_using_latlon_coordinates():
# load bathy data
path = path_to_assets + '/bornholm.mat'
bathy, lat, lon = load_data_from_file(path)
# initialize interpolator
ip = Interpolator2D(bathy, lat, lon)
# interpolate at a single point on the grid
z = ip.interp(lat=lat[0], lon=lon[0])
z = int(z)
assert z == bathy[0, 0]
# interpolate at a single point between two grid points
x = (lat[1] + lat[2]) / 2
z = ip.interp(lat=x, lon=lon[0])
z = float(z)
zmin = min(bathy[1, 0], bathy[2, 0])
zmax = max(bathy[1, 0], bathy[2, 0])
assert z >= zmin
assert z <= zmax
# interpolate at two points
x1 = (lat[1] + lat[2]) / 2
x2 = (lat[2] + lat[3]) / 2
z = ip.interp(lat=[x1, x2], lon=lon[0])
zmin = min(bathy[1, 0], bathy[2, 0])
zmax = max(bathy[1, 0], bathy[2, 0])
assert z[0] >= zmin
assert z[0] <= zmax
zmin = min(bathy[2, 0], bathy[3, 0])
zmax = max(bathy[2, 0], bathy[3, 0])
assert z[1] >= zmin
assert z[1] <= zmax
# interpolate with grid = True/False
x1 = (lat[1] + lat[2]) / 2
x2 = (lat[2] + lat[3]) / 2
y1 = (lon[1] + lon[2]) / 2
y2 = (lon[2] + lon[3]) / 2
z = ip.interp(lat=[x1, x2], lon=[y1, y2], grid=False)
assert np.ndim(z) == 1
assert z.shape[0] == 2
z = ip.interp(lat=[x1, x2], lon=[y1, y2], grid=True)
assert np.ndim(z) == 2
assert z.shape[0] == 2
assert z.shape[1] == 2
def test_can_interpolate_multiple_points_in_xx():
# load data and initialize interpolator
path = path_to_assets + '/bornholm.mat'
bathy, lat, lon = load_data_from_file(path)
ip = Interpolator2D(bathy, lat, lon)
# --- 4 x coordinates ---
xs = [0, 1000, -2000, 300]
# --- 4 y coordinates ---
ys = [0, 1500, 800, -120]
# interpolate
depths = ip.interp_xy(x=xs, y=ys)
zi = list()
for x, y in zip(xs, ys):
zi.append(ip.interp_xy(x=x, y=y))
for z, d in zip(zi, depths):
assert z == pytest.approx(d, rel=1e-3)
def test_can_interpolate_multiple_points_in_ll():
# load data and initialize interpolator
path = path_to_assets + '/bornholm.mat'
bathy, lat, lon = load_data_from_file(path)
ip = Interpolator2D(bathy, lat, lon)
# coordinates of origin
lat_c = ip.origin[0]
lon_c = ip.origin[1]
# --- 4 latitudes ---
lats = [lat_c, lat_c + 0.1, lat_c - 0.2, lat_c + 0.03]
# --- 4 longitudes ---
lons = [lon_c, lon_c + 0.15, lon_c - 0.08, lon_c - 0.12]
# interpolate
depths = ip.interp(lat=lats, lon=lons)
zi = list()
for lat, lon in zip(lats, lons):
zi.append(ip.interp(lat=lat, lon=lon))
for z, d in zip(zi, depths):
assert z == pytest.approx(d, rel=1e-3)