def _load_meta(filename, ftype, **kwargs):
if ftype == 'netcdf':
return load_netcdf_meta(filename)
elif ftype == 'hdf5':
return load_hdf5_meta(filename)
elif ftype == 'hdf4':
return load_hdf4_meta(filename)
elif ftype == 'tif':
return load_dir_of_tifs_meta(filename, **kwargs)
elif ftype == 'hdf':
try:
return load_hdf4_meta(filename, **kwargs)
except Exception as e:
logger.info('NOTE: guessed HDF4 type. Failed: {}. \nTrying HDF5'.format(repr(e)))
return load_hdf5_meta(filename, **kwargs)
def test_load_subdataset():
import gdal
f = HDF5_FILES[0]
_, layer_specs = get_layer_specs(f)
data_file = gdal.Open(f)
meta = load_hdf5_meta(f)
data_array = load_subdataset(data_file.GetSubDatasets()[0][0],
meta['layer_meta'][0], layer_specs[0])
assert data_array.data is not None
def test_load_subdataset():
f = HDF5_FILES[0]
_ , band_specs = get_band_specs(f)
data_file = gdal.Open(f)
meta = load_hdf5_meta(f)
data_array = load_subdataset(data_file.GetSubDatasets()[0][0],
meta['band_meta'][0],
band_specs[0])
assert 'canvas' in data_array.attrs.keys()
assert data_array.data is not None
def test_reader_kwargs():
sub_dataset_names, band_specs = get_band_specs(HDF5_FILES[0])
band_specs_kwargs = []
for b in band_specs:
b = attr.asdict(b)
b['buf_xsize'], b['buf_ysize'] = 200, 300
band_specs_kwargs.append(BandSpec(**b))
meta = load_hdf5_meta(HDF5_FILES[0])
es = load_hdf5_array(HDF5_FILES[0], meta, band_specs_kwargs)
for b in es.band_order:
assert getattr(es, b).values.shape == (300, 200)
def test_read_array(filename):
sub_dataset_names, band_specs = get_band_specs(filename)
meta = load_hdf5_meta(filename)
es = load_hdf5_array(filename, meta, band_specs)
assert len(es.data_vars) == len(sub_dataset_names)
for band in es.data_vars:
sample = getattr(es, band)
assert sample.y.size == 1800
assert sample.x.size == 3600
assert len(es.data_vars) == len(band_specs)
assertions_on_band_metadata(sample.attrs)
def test_reader_kwargs():
sub_dataset_names, layer_specs = get_layer_specs(HDF5_FILES[0])
layer_specs_kwargs = []
for b in layer_specs:
b = b.get_params()
b['buf_xsize'], b['buf_ysize'] = 200, 300
layer_specs_kwargs.append(LayerSpec(**b))
meta = load_hdf5_meta(HDF5_FILES[0])
dset = load_hdf5_array(HDF5_FILES[0], meta, layer_specs_kwargs)
for b in dset.layer_order:
assert getattr(dset, b).values.shape == (300, 200)
def test_read_array(filename):
sub_dataset_names, layer_specs = get_layer_specs(filename)
meta = load_hdf5_meta(filename)
dset = load_hdf5_array(filename, meta, layer_specs)
assert len(dset.data_vars) == len(sub_dataset_names)
for layer in dset.data_vars:
sample = getattr(dset, layer)
assert sample.y.size == 1800
assert sample.x.size == 3600
assert len(dset.data_vars) == len(layer_specs)
assertions_on_layer_metadata(sample.attrs)
def test_read_meta(hdf):
meta = load_hdf5_meta(hdf)
assertions_on_metadata(meta)
