def test_alternative_region(self, tmp_path):
# make the dataset
(tmp_path / "raw/chirps/global").mkdir(parents=True)
data_path = tmp_path / "raw/chirps/global/testy_test.nc"
dataset = self._make_chirps_dataset(size=(100, 100))
dataset.to_netcdf(path=data_path)
ethiopia = get_ethiopia()
# regrid the datasets
regrid_dataset, _, _ = _make_dataset(
size=(20, 20),
latmin=ethiopia.latmin,
latmax=ethiopia.latmax,
lonmin=ethiopia.lonmin,
lonmax=ethiopia.lonmax,
)
regrid_path = tmp_path / "regridder.nc"
regrid_dataset.to_netcdf(regrid_path)
# build the Preprocessor object and subset with a different subset_str
processor = CHIRPSPreprocessor(tmp_path)
processor.preprocess(subset_str="ethiopia",
regrid=regrid_path,
parallel=False)
expected_out_path = tmp_path / "interim/chirps_preprocessed/data_ethiopia.nc"
assert (expected_out_path.exists(
)), f"Expected processed file to be saved to {expected_out_path}"
def process_precip_2018():
data_path = get_data_path()
regrid_path = data_path / "interim/VCI_preprocessed/data_kenya.nc"
assert regrid_path.exists(), f"{regrid_path} not available"
processor = CHIRPSPreprocessor(data_path)
processor.preprocess(subset_str="kenya", regrid=regrid_path, parallel=False)
def test_get_filenames(tmp_path):
(tmp_path / "raw" / "chirps").mkdir(parents=True)
test_file = tmp_path / "raw/chirps/testy_test.nc"
test_file.touch()
processor = CHIRPSPreprocessor(tmp_path)
files = processor.get_filepaths()
assert files[0] == test_file, f"Expected {test_file} to be retrieved"
def process_precip_2018(subset_str: str = "kenya"):
data_path = get_data_path()
regrid_path = (
data_path /
f"interim/reanalysis-era5-land_preprocessed/data_{subset_str}.nc")
assert regrid_path.exists(), f"{regrid_path} not available"
processor = CHIRPSPreprocessor(data_path)
processor.preprocess(subset_str=subset_str,
regrid=regrid_path,
parallel=False)
def test_preprocess(self, tmp_path):
(tmp_path / "raw/chirps/global").mkdir(parents=True)
data_path = tmp_path / "raw/chirps/global/testy_test.nc"
dataset = self._make_chirps_dataset(size=(100, 100))
dataset.to_netcdf(path=data_path)
kenya = get_kenya()
regrid_dataset, _, _ = _make_dataset(
size=(20, 20),
latmin=kenya.latmin,
latmax=kenya.latmax,
lonmin=kenya.lonmin,
lonmax=kenya.lonmax,
)
regrid_path = tmp_path / "regridder.nc"
regrid_dataset.to_netcdf(regrid_path)
processor = CHIRPSPreprocessor(tmp_path)
processor.preprocess(subset_str="kenya",
regrid=regrid_path,
parallel=False)
expected_out_path = tmp_path / "interim/chirps_preprocessed/data_kenya.nc"
assert (expected_out_path.exists(
)), f"Expected processed file to be saved to {expected_out_path}"
# check the subsetting happened correctly
out_data = xr.open_dataset(expected_out_path)
expected_dims = ["lat", "lon", "time"]
assert len(list(out_data.dims)) == len(expected_dims)
for dim in expected_dims:
assert dim in list(
out_data.dims
), f"Expected {dim} to be in the processed dataset dims"
lons = out_data.lon.values
assert (lons.min() >= kenya.lonmin) and (
lons.max() <= kenya.lonmax), "Longitudes not correctly subset"
lats = out_data.lat.values
assert (lats.min() >= kenya.latmin) and (
lats.max() <= kenya.latmax), "Latitudes not correctly subset"
assert out_data.VHI.values.shape[1:] == (20, 20)
assert (not processor.interim.exists()
), f"Interim chirps folder should have been deleted"
def test_make_filename():
test_file = "testy_test.nc"
expected_output = "testy_test_kenya.nc"
filename = CHIRPSPreprocessor.create_filename(test_file, "kenya")
assert (filename == expected_output
), f"Expected output to be {expected_output}, got {filename}"
def test_directories_created(tmp_path):
v = CHIRPSPreprocessor(tmp_path)
assert (
tmp_path / v.preprocessed_folder / "chirps_preprocessed"
).exists(), (
"Should have created a directory tmp_path/interim/chirps_preprocessed"
)
assert (tmp_path / v.preprocessed_folder / "chirps_interim").exists(
), "Should have created a directory tmp_path/interim/chirps_interim"
def preprocess_data(data_path):
# preprocess VHI
print("** Preprocessing VHI **")
processor = VHIPreprocessor(data_path)
processor.preprocess(
subset_str="kenya",
regrid=regrid_path,
n_parallel_processes=1,
resample_time="M",
upsampling=False,
)
regrid_path = data_path / "interim" / "vhi_preprocessed" / "vhi_kenya.nc"
# preprocess CHIRPS Rainfall
print("** Preprocessing CHIRPS Precipitation **")
processor = CHIRPSPreprocessor(data_path)
processor.preprocess(subset_str="kenya",
regrid=regrid_path,
n_parallel_processes=1)
# preprocess GLEAM evaporation
print("** Preprocessing GLEAM Evaporation **")
processor = GLEAMPreprocessor(data_path)
processor.preprocess(subset_str="kenya",
regrid=regrid_path,
resample_time="M",
upsampling=False)
# preprocess SRTM Topography
print("** Preprocessing SRTM Topography **")
processor = SRTMPreprocessor(data_path)
processor.preprocess(subset_str="kenya", regrid=regrid_path)
# preprocess ESA CCI Landcover
print("** Preprocessing ESA CCI Landcover **")
processor = ESACCIPreprocessor(data_path)
processor.preprocess(subset_str="kenya",
regrid=regrid_path,
resample_time="M",
upsampling=False)
# ml_drought_dir = Path('/users/tommylees/github/ml_drought/data')
ds = xr.open_dataset(data_dir / 'topo.nc')
# ds['nlon'] = ds.latitude
# ds['nlat'] = ds.longitude
# ds = ds.rename({'nlon': 'lon', 'nlat': 'lat'})
# topo = ds.elevation
# topo.to_netcdf(data_dir / 'topo_clean.nc')
regrid_path = data_dir / 'temp/temp_doy.nc'
# regrid_path = data_dir / 'precip/precip_africa.nc'
assert regrid_path.exists()
print("Reading in topo data for regridding")
processor = CHIRPSPreprocessor()
ds = xr.open_dataset(out_dir / 'topo.nc')
regrid_da = processor.load_reference_grid(regrid_path)
print("Chop Africa")
# AFRICA bounding box
lonmin = -31.6
lonmax = 51.8
latmin = -35.8
latmax = 37.2
inverse_lat = inverse_lon = False
# processor.chop_roi(
# ds=ds,
# subset_str='africa',
