def test_calculate(testdata):
ds = twinotter.load_flight(testdata["flight_data_path"])
theta = twinotter.derive.calculate("air_potential_temperature", ds)
# This number is correct for the testdata using r004
assert np.isclose(theta[0], 298.76865)
def test_calculate_equivalent(testdata, variable, function, arguments):
# Check that "calculate" returns an equivalent variable to calling the specific
# function Currently only setup for "first-order" functions. i.e. functions that
# calculate a new variable using only variables that are already in the basic
# MASIN dataset
ds = twinotter.load_flight(testdata["flight_data_path"])
result1 = twinotter.derive.calculate(variable, ds)
result2 = function(*[ds[arg] for arg in arguments])
result1 = _filter_nans(result1)
result2 = _filter_nans(result2)
assert (result1 == result2).all()
def test_load_flight(testdata, load_from, revision):
ds = twinotter.load_flight(flight_data_path=testdata[load_from],
revision=revision)
# Check that the dataset still contains the right number of variables
assert len(ds) == 58
# Check that the time period of the dataset is the same
assert len(ds.Time == 9928)
# Check that there are no NaNs left in the dataset
# Awkward syntax because xarray.DataArray.any returns an array
# Numpy now has it's own bool type so we have to use "==" rather than "is"
# Using pd.isnull because np.isnan doesn't work on object arrays
# - https://stackoverflow.com/a/36001191/8270394
assert pd.isnull(ds.Time.values).any() == False
return
def main(flight_data_path, alt_max=100.0):
ds = twinotter.load_flight(flight_data_path)
da_alt = ds.ALT_OXTS
da_lat = ds.LAT_OXTS
da_lon = ds.LON_OXTS
da_lw_up = ds.LW_UP_C
fig, axes = plt.subplots(
subplot_kw=dict(projection=ccrs.PlateCarree()), nrows=2,
figsize=(10, 12), sharey=True,
)
def _bootstrap(ax):
ax.coastlines(resolution='10m')
twinotter.external.eurec4a.add_halo_circle(ax=ax)
gl = ax.gridlines(draw_labels=True)
gl.top_labels = False
gl.right_labels = False
ax = axes[0]
_bootstrap(ax)
sc = ax.scatter(da_lon, da_lat, c=da_lw_up.where(da_alt < alt_max, np.nan))
cb = fig.colorbar(sc, ax=ax)
cb.set_label(xr.plot.utils.label_from_attrs(da_lw_up))
ax = axes[1]
_bootstrap(ax)
sc = ax.scatter(da_lon, da_lat, c=da_alt.where(da_alt < alt_max, np.nan))
cb = fig.colorbar(sc, ax=ax)
cb.set_label(xr.plot.utils.label_from_attrs(da_alt))
plt.tight_layout()
date = ds.Time.isel(Time=0).dt.strftime("%d/%m/%Y").item()
plt.suptitle(f"Flight {ds.flight_number} - {date} - below {alt_max}m")
return fig, ds
def test_calculate_nonsense(testdata):
ds = twinotter.load_flight(testdata["flight_data_path"])
with pytest.raises(ValueError):
twinotter.derive.calculate("nonsense", ds)
def test_extract_segments(testdata):
ds = twinotter.load_flight(flight_data_path=testdata["flight_data_path"])
flight_segments = twinotter.load_segments(testdata["flight_segments_file"])
ds_segs = twinotter.extract_segments(ds, flight_segments, "level")
assert len(ds_segs.Time) == 5684
def test_load_flight_empty_fails(testdata_empty):
with pytest.raises(FileNotFoundError):
twinotter.load_flight(
flight_data_path=testdata_empty["flight_data_path"])
return