def load_hdf5_array(datafile, meta, band_specs):
'''Return an ElmStore where each subdataset is a DataArray
Parameters:
:datafile: filename
:meta: meta from earthio.load_hdf5_meta
:band_specs: list of earthio.BandSpec objects,
defaulting to reading all subdatasets
as bands
Returns:
:es: An ElmStore
'''
logger.debug('load_hdf5_array: {}'.format(datafile))
f = gdal.Open(datafile, GA_ReadOnly)
sds = meta['sub_datasets']
band_metas = meta['band_meta']
band_order_info = []
for band_idx, (band_meta, sd) in enumerate(zip(band_metas, sds)):
if band_specs:
for idx, bs in enumerate(band_specs):
if match_meta(band_meta, bs):
band_order_info.append((idx, band_meta, sd, bs))
break
else:
band_order_info.append(
(band_idx, band_meta, sd, 'band_{}'.format(band_idx)))
if band_specs and len(band_order_info) != len(band_specs):
raise ValueError(
'Number of bands matching band_specs {} was not equal '
'to the number of band_specs {}'.format(len(band_order_info),
len(band_specs)))
band_order_info.sort(key=lambda x: x[0])
elm_store_data = OrderedDict()
band_order = []
for _, band_meta, sd, band_spec in band_order_info:
if isinstance(band_spec, BandSpec):
name = band_spec.name
reader_kwargs = {
k: getattr(band_spec, k)
for k in READ_ARRAY_KWARGS if getattr(band_spec, k)
}
else:
reader_kwargs = {}
name = band_spec
reader_kwargs = window_to_gdal_read_kwargs(**reader_kwargs)
attrs = copy.deepcopy(meta)
attrs.update(copy.deepcopy(band_meta))
elm_store_data[name] = load_subdataset(sd[0], attrs, band_spec,
**reader_kwargs)
band_order.append(name)
attrs = copy.deepcopy(attrs)
attrs['band_order'] = band_order
gc.collect()
return ElmStore(elm_store_data, attrs=attrs)
def load_hdf4_array(datafile, meta, layer_specs=None):
'''Return an xr.Dataset where each subdataset is a xr.DataArray
Parameters:
:datafile: filename
:meta: meta from earthio.load_hdf4_meta
:layer_specs: list of earthio.LayerSpec objects,
defaulting to reading all subdatasets
as layers
Returns:
:Elmstore: Elmstore of teh hdf4 data
'''
import gdal
from gdalconst import GA_ReadOnly
from earthio.metadata_selection import match_meta
logger.debug('load_hdf4_array: {}'.format(datafile))
f = gdal.Open(datafile, GA_ReadOnly)
sds = meta['sub_datasets']
layer_metas = meta['layer_meta']
layer_order_info = []
if layer_specs:
for layer_meta, s in zip(layer_metas, sds):
#layer_meta['name'] = s[0]
for idx, layer_spec in enumerate(layer_specs):
if match_meta(layer_meta, layer_spec):
layer_order_info.append((idx, layer_meta, s, layer_spec))
break
layer_order_info.sort(key=lambda x: x[0])
if len(layer_order_info) != len(layer_specs):
raise ValueError('No matching layers with '
'layer_specs {} (meta = {})'.format(
layer_specs, layer_meta))
else:
layer_order_info = [(idx, layer_meta, s, 'layer_{}'.format(idx))
for idx, (layer_meta,
s) in enumerate(zip(layer_metas, sds))]
native_dims = ('y', 'x')
elm_store_data = OrderedDict()
layer_order = []
for _, layer_meta, s, layer_spec in layer_order_info:
attrs = copy.deepcopy(meta)
attrs.update(copy.deepcopy(layer_meta))
if isinstance(layer_spec, LayerSpec):
name = layer_spec.name
reader_kwargs = {
k: getattr(layer_spec, k)
for k in READ_ARRAY_KWARGS if getattr(layer_spec, k)
}
geo_transform = take_geo_transform_from_meta(layer_spec, **attrs)
else:
reader_kwargs = {}
name = layer_spec
geo_transform = None
reader_kwargs = window_to_gdal_read_kwargs(**reader_kwargs)
handle = gdal.Open(s[0], GA_ReadOnly)
layer_meta.update(reader_kwargs)
np_arr = handle.ReadAsArray(**reader_kwargs)
out = _np_arr_to_coords_dims(np_arr,
layer_spec,
reader_kwargs,
geo_transform=geo_transform,
layer_meta=layer_meta,
handle=handle)
np_arr, coords, dims, attrs2 = out
attrs.update(attrs2)
elm_store_data[name] = xr.DataArray(np_arr,
coords=coords,
dims=dims,
attrs=attrs)
layer_order.append(name)
del handle
attrs = copy.deepcopy(attrs)
attrs['layer_order'] = layer_order
gc.collect()
return xr.Dataset(elm_store_data, attrs=attrs)
def load_hdf4_array(datafile, meta, band_specs=None):
'''Return an ElmStore where each subdataset is a DataArray
Parameters:
:datafile: filename
:meta: meta from earthio.load_hdf4_meta
:band_specs: list of earthio.BandSpec objects,
defaulting to reading all subdatasets
as bands
Returns:
:Elmstore: Elmstore of teh hdf4 data
'''
from earthio import ElmStore
from earthio.metadata_selection import match_meta
logger.debug('load_hdf4_array: {}'.format(datafile))
f = gdal.Open(datafile, GA_ReadOnly)
sds = meta['sub_datasets']
band_metas = meta['band_meta']
band_order_info = []
if band_specs:
for band_meta, s in zip(band_metas, sds):
for idx, band_spec in enumerate(band_specs):
if match_meta(band_meta, band_spec):
band_order_info.append((idx, band_meta, s, band_spec))
break
band_order_info.sort(key=lambda x: x[0])
if not len(band_order_info):
raise ValueError('No matching bands with '
'band_specs {}'.format(band_specs))
else:
band_order_info = [(idx, band_meta, s, 'band_{}'.format(idx))
for idx, (band_meta,
s) in enumerate(zip(band_metas, sds))]
native_dims = ('y', 'x')
elm_store_data = OrderedDict()
band_order = []
for _, band_meta, s, band_spec in band_order_info:
attrs = copy.deepcopy(meta)
attrs.update(copy.deepcopy(band_meta))
if isinstance(band_spec, BandSpec):
name = band_spec.name
reader_kwargs = {
k: getattr(band_spec, k)
for k in READ_ARRAY_KWARGS if getattr(band_spec, k)
}
geo_transform = take_geo_transform_from_meta(band_spec, **attrs)
else:
reader_kwargs = {}
name = band_spec
geo_transform = None
reader_kwargs = window_to_gdal_read_kwargs(**reader_kwargs)
dat0 = gdal.Open(s[0], GA_ReadOnly)
band_meta.update(reader_kwargs)
raster = raster_as_2d(dat0.ReadAsArray(**reader_kwargs))
if geo_transform is None:
geo_transform = dat0.GetGeoTransform()
attrs['geo_transform'] = geo_transform
if hasattr(band_spec, 'store_coords_order'):
if band_spec.stored_coords_order[0] == 'y':
rows, cols = raster.shape
else:
rows, cols = raster.T.shape
else:
rows, cols = raster.shape
coord_x, coord_y = geotransform_to_coords(cols, rows, geo_transform)
canvas = Canvas(geo_transform=geo_transform,
buf_xsize=cols,
buf_ysize=rows,
dims=native_dims,
ravel_order='C',
bounds=geotransform_to_bounds(cols, rows,
geo_transform))
attrs['canvas'] = canvas
elm_store_data[name] = xr.DataArray(raster,
coords=[('y', coord_y),
('x', coord_x)],
dims=native_dims,
attrs=attrs)
band_order.append(name)
del dat0
attrs = copy.deepcopy(attrs)
attrs['band_order'] = band_order
gc.collect()
return ElmStore(elm_store_data, attrs=attrs)
def load_hdf5_array(datafile, meta, layer_specs):
'''Return an xr.Dataset where each subdataset is a xr.DataArray
Parameters:
:datafile: filename
:meta: meta from earthio.load_hdf5_meta
:layer_specs: list of earthio.LayerSpec objects,
defaulting to reading all subdatasets
as layers
Returns:
:dset: An xr.Dataset
'''
import gdal
from gdalconst import GA_ReadOnly
logger.debug('load_hdf5_array: {}'.format(datafile))
f = gdal.Open(datafile, GA_ReadOnly)
sds = meta['sub_datasets']
layer_metas = meta['layer_meta']
layer_order_info = []
for layer_idx, (layer_meta, sd) in enumerate(zip(layer_metas, sds)):
if layer_specs:
for idx, bs in enumerate(layer_specs):
if match_meta(layer_meta, bs):
layer_order_info.append((idx, layer_meta, sd, bs))
break
else:
layer_order_info.append(
(layer_idx, layer_meta, sd, 'layer_{}'.format(layer_idx)))
if layer_specs and len(layer_order_info) != len(layer_specs):
raise ValueError(
'Number of layers matching layer_specs {} was not equal '
'to the number of layer_specs {}'.format(len(layer_order_info),
len(layer_specs)))
layer_order_info.sort(key=lambda x: x[0])
elm_store_data = OrderedDict()
layer_order = []
for _, layer_meta, sd, layer_spec in layer_order_info:
if isinstance(layer_spec, LayerSpec):
name = layer_spec.name
reader_kwargs = {
k: getattr(layer_spec, k)
for k in READ_ARRAY_KWARGS if getattr(layer_spec, k)
}
else:
reader_kwargs = {}
name = layer_spec
reader_kwargs = window_to_gdal_read_kwargs(**reader_kwargs)
attrs = copy.deepcopy(meta)
attrs.update(copy.deepcopy(layer_meta))
elm_store_data[name] = load_subdataset(sd[0], attrs, layer_spec,
**reader_kwargs)
layer_order.append(name)
attrs = copy.deepcopy(attrs)
attrs['layer_order'] = layer_order
gc.collect()
return xr.Dataset(elm_store_data, attrs=attrs)