def test_load_wind_uv():
# gulf st lawrence
#south = 46
#north = 52
#west = -70
#east = -56
result = kadlu.load(source='wwiii', var='wind_uv', south=south-1, west=west-1, north=north, east=east, start=start, end=end)
print(result)
def test_wwiii_load_wind_u():
try:
#wave, lat, lon, time = Wwiii().load_wind_uv(south=south, west=west, north=north, east=east, start=start, end=end)
result = kadlu.load(source='wwiii', var='wind_u', south=south, west=west, north=north, east=east, start=start, end=end)
except AssertionError as err:
logging.info(f'CAUGHT EXCEPTION: {str(err)}')
except Exception as err:
raise err
def test_era5_load_wind():
ns_offset = 1
ew_offset = 1
uval, lat, lon, epoch = kadlu.load(source='era5',
var='wind_u',
start=datetime(2016, 3, 9),
end=datetime(2016, 3, 11),
south=44.5541333 - ns_offset,
west=-64.17682 - ew_offset,
north=44.5541333 + ns_offset,
east=-64.17682 + ew_offset,
top=0,
bottom=0)
vval, lat, lon, epoch = kadlu.load(source='era5',
var='wind_v',
start=datetime(2016, 3, 9),
end=datetime(2016, 3, 11),
south=44.5541333 - ns_offset,
west=-64.17682 - ew_offset,
north=44.5541333 + ns_offset,
east=-64.17682 + ew_offset,
top=0,
bottom=0)
uvval, lat, lon, epoch = kadlu.load(source='era5',
var='wind_uv',
start=datetime(2016, 3, 9),
end=datetime(2016, 3, 11),
south=44.5541333 - ns_offset,
west=-64.17682 - ew_offset,
north=44.5541333 + ns_offset,
east=-64.17682 + ew_offset,
top=0,
bottom=0)
def add_kadlu_env_data(bounds, sources, detection_df):
"""
Fetches the requested environmental data for the given region & time. The data is interpolated
across space (2D or 3D) and time before being merged into a new version of detection_df.
:param bounds: Dictionary containing the boundaries (space & time) which will be used to fetch
data from kadlu. Must include `north`, `south`, `east`, `west`, `start`, `end`,
`top`, and `bottom`.
:type bounds: dict
:param sources: Dictionary containing a variable -> source mapping.
:type sources: dict.
:param detection_df: Dataframe containing detection data.
:type detection_df: pandas.DataFrame
:return: - **detection_df_env** (`pandas.DataFrame`) - A copy of detection_df where interpolated
environment data has been added.
- **kadlu_result** (`numpy.array`) - The raw result from kadlu (not interpolated)
"""
detection_df_copy = copy.copy(detection_df)
axes_to_interpolate = [detection_df_copy['Receiver.lat'],
detection_df_copy['Receiver.lon'],
[d.timestamp() for d in detection_df_copy['datetime']],
detection_df_copy['Receiver.depth']]
for load_func, source in sources.items():
col_name = '_'.join(load_func.split('_')[1:])
kadlu_result = kadlu.load(source=source, var=col_name, **bounds)
interpolations = interpolate(kadlu_result, axes_to_interpolate)
detection_df_copy[col_name] = interpolations
# TODO: kadlu_result is currently only the last result. Should probably be a list of results
return detection_df_copy, kadlu_result
def test_wwiii_load_waveperiod():
#wave, lat, lon, time = Wwiii().load_waveperiod(south=south, west=west, north=north, east=east, start=start, end=end)
result = kadlu.load(source='wwiii', var='waveperiod', south=south, west=west, north=north, east=east, start=start, end=end)