def test_data_fits():
"""Tests the is_correct_grid() function"""
# Should get False returned if the number of points is incorrect
test_grid = Geogrid('1deg-global')
bad_y = test_grid.num_y - 1
bad_x = test_grid.num_x - 1
test_array = np.random.rand(bad_y, bad_x)
assert test_grid.data_fits(test_array) == False
# Should get True returned if the number of points is correct
test_grid = Geogrid('1deg-global')
test_array = np.random.rand(test_grid.num_y, test_grid.num_x)
assert test_grid.data_fits(test_array) == True
# Should raise a GridError if the data isn't a NumPy array
test_grid = Geogrid('1deg-global')
with raises(GeogridError):
test_grid.data_fits(1)
def test_interpolation():
"""Test that interpolation can be done between all grids"""
# Create fake data for every grid
fake_data = {}
for gridname in list_builtin_geogrids():
grid = Geogrid(gridname)
fake_data[gridname] = np.random.rand(grid.num_y,
grid.num_x).astype('float16')
# Loop over every possible combination of grids
for gridname1 in list_builtin_geogrids():
for gridname2 in list_builtin_geogrids():
# Create 2 Grid objects
grid1 = Geogrid(gridname1)
grid2 = Geogrid(gridname2)
interpolate(fake_data[gridname1], grid1, grid2)
# Make sure a 1-d input results in a 1-d output
grid1 = Geogrid(list_builtin_geogrids()[0])
grid2 = Geogrid(list_builtin_geogrids()[1])
data1 = np.random.rand(grid1.num_y * grid1.num_x)
data2 = interpolate(data1, grid1, grid2)
assert data1.ndim == data2.ndim
# Make sure a 2-d input results in a 2-d output
grid1 = Geogrid(list_builtin_geogrids()[0])
grid2 = Geogrid(list_builtin_geogrids()[1])
data1 = np.random.rand(grid1.num_y, grid1.num_x)
data2 = interpolate(data1, grid1, grid2)
assert data1.ndim == data2.ndim
def test_smooth():
"""Test the function that smooths an array of spatial data"""
# Make sure when passing in a MaskedArray, a MaskedArray is returned
test_array = np.ma.masked_array(np.random.rand(2, 2))
returned_array = fill_outside_mask_borders(test_array)
mask = returned_array.mask
# Make sure when passing in a non-MaskedArray, a non-MaskedArray is returned
test_array = np.random.rand(2, 2)
returned_array = fill_outside_mask_borders(test_array)
with raises(AttributeError):
returned_array.mask
# Make sure a GridError is raised if the grid doesn't match the data
test_grid = Geogrid(list_builtin_geogrids()[-1])
test_array = np.random.rand(5, 5)
with raises(GeogridError):
smooth(test_array, test_grid)
# Make sure the dimensions of the data don't change when smoothed
test_grid = Geogrid(list_builtin_geogrids()[-1])
test_array = np.random.rand(test_grid.num_y, test_grid.num_x)
smoothed_array = smooth(test_array, test_grid)
assert test_array.shape == smoothed_array.shape
def test_latlon_to_gridpoint():
"""Tests the latlon_to_gridpoint() function"""
# gridpoint of latlon pair (0, 0) should be 90 for a 1deg-global Geogrid
grid = Geogrid('1deg-global')
assert set(grid.latlon_to_1d_index((0, 0))) == {90}
# gridpoint should be [-1] if the latlon pair isn't found on the Geogrid
grid = Geogrid('2deg-conus')
assert set(grid.latlon_to_1d_index((0, 0))) == {-1}
def test_create_geogrid():
"""Ensure the Geogrid object can be created"""
for builtin_geogrid in list_builtin_geogrids():
Geogrid(builtin_geogrid)
def test_print_returns_something(capfd):
"""Ensure the print_info() functions returns a non-empty string"""
for builtin_geogrid in list_builtin_geogrids():
print(Geogrid(builtin_geogrid))
out, err = capfd.readouterr()
assert out
def test_create_custom_geogrid():
"""Ensure a custom Grid object can be created"""
Geogrid(ll_corner=(0, 0), ur_corner=(90, 90), res=1)
def test_exception_raised_for_no_grid_name():
"""Ensure an exception is raised for an unsupported units"""
with raises(GeogridError):
Geogrid()