def test_remove_repeat_coordinates(test_coords):
r"""Test remove repeat coordinates function."""
x, y = test_coords
x[0] = 8.523
x[-1] = 8.523
y[0] = 24.123
y[-1] = 24.123
z = np.array(list(range(-10, 10, 2)))
x_, y_, z_ = remove_repeat_coordinates(x, y, z)
truthx = np.array([8.523, 67, 79, 10, 52, 53, 98, 34, 15])
truthy = np.array([24.123, 87, 48, 94, 98, 66, 14, 24, 60])
truthz = np.array([-10, -8, -6, -4, -2, 0, 2, 4, 6])
assert_array_almost_equal(truthx, x_)
assert_array_almost_equal(truthy, y_)
assert_array_almost_equal(truthz, z_)
return lon, lat, value
from_proj = ccrs.Geodetic()
to_proj = ccrs.AlbersEqualArea(central_longitude=-97.0000,
central_latitude=38.0000)
levels = list(range(-20, 20, 1))
cmap = plt.get_cmap('magma')
norm = BoundaryNorm(levels, ncolors=cmap.N, clip=True)
x, y, temp = station_test_data('air_temperature', from_proj, to_proj)
x, y, temp = remove_nan_observations(x, y, temp)
x, y, temp = remove_repeat_coordinates(x, y, temp)
###########################################
# Scipy.interpolate linear
# ------------------------
gx, gy, img = interpolate_to_grid(x, y, temp, interp_type='linear', hres=75000)
img = np.ma.masked_where(np.isnan(img), img)
fig, view = basic_map(to_proj)
mmb = view.pcolormesh(gx, gy, img, cmap=cmap, norm=norm)
fig.colorbar(mmb, shrink=.4, pad=0, boundaries=levels)
###########################################
# Natural neighbor interpolation (MetPy implementation)
# -----------------------------------------------------
# `Reference <https://github.com/Unidata/MetPy/files/138653/cwp-657.pdf>`_
gx, gy, img = interpolate_to_grid(x,
return None
return lon, lat, value
from_proj = ccrs.Geodetic()
to_proj = ccrs.AlbersEqualArea(central_longitude=-97.0000, central_latitude=38.0000)
levels = list(range(-20, 20, 1))
cmap = plt.get_cmap('magma')
norm = BoundaryNorm(levels, ncolors=cmap.N, clip=True)
x, y, temp = station_test_data('air_temperature', from_proj, to_proj)
x, y, temp = remove_nan_observations(x, y, temp)
x, y, temp = remove_repeat_coordinates(x, y, temp)
###########################################
# Scipy.interpolate linear
# ------------------------
gx, gy, img = interpolate_to_grid(x, y, temp, interp_type='linear', hres=75000)
img = np.ma.masked_where(np.isnan(img), img)
fig, view = basic_map(to_proj)
mmb = view.pcolormesh(gx, gy, img, cmap=cmap, norm=norm)
fig.colorbar(mmb, shrink=.4, pad=0, boundaries=levels)
###########################################
# Natural neighbor interpolation (MetPy implementation)
# -----------------------------------------------------
# `Reference <https://github.com/Unidata/MetPy/files/138653/cwp-657.pdf>`_
gx, gy, img = interpolate_to_grid(x, y, temp, interp_type='natural_neighbor', hres=75000)