def test_dtypes():
assert Dtype('Float32').gdalint == 6
assert Dtype(6).gdalstr == 'Float32'
assert Dtype('uint32').gdalstr == 'UInt32'
with pytest.raises(ValueError):
Dtype('foobar')
with pytest.raises(ValueError):
Dtype(999)
with pytest.raises(TypeError):
Dtype(None)
def __init__(self, filename, units='DN'):
if isinstance(filename, list):
combined = sum([Dataset(x, units) for x in filename])
self.__init__(combined)
elif isinstance(filename, Dataset):
for attr, value in vars(filename).items():
setattr(self, attr, value)
elif isinstance(filename, str):
# map pyroSAR sensor identifiers to platform and instrument codes
sensor_lookup = {
'ASAR': ('ENVISAT', 'ASAR'),
'ERS1': ('ERS-1', 'SAR'),
'ERS2': ('ERS-2', 'SAR'),
'PSR1': ('ALOS-1', 'PALSAR'),
'PSR2': ('ALOS-2', 'PALSAR-2'),
'S1A': ('SENTINEL-1', 'C-SAR'),
'S1B': ('SENTINEL-1', 'C-SAR'),
'TSX1': ('TERRASAR-X_1', 'SAR'),
'TDX1': ('TANDEM-X_1', 'SAR')
}
# extract basic metadata attributes from the filename and register them to the object
meta = parse_datasetname(filename)
if meta is None:
raise ValueError(
'could not identify dataset: {}'.format(filename))
for key, val in meta.items():
setattr(self, key, val)
# define acquisition start and end time; Currently both are set to the acquisition start time,
# which is contained in the filename
# Time will only be correct if the full scene was processed, start and end time of s subset will
# differ. Thus, accurately setting both is not seen as too relevant.
self.from_dt = strftime('%Y-%m-%dT%H:%M:%S',
strptime(self.start, '%Y%m%dT%H%M%S'))
self.to_dt = strftime('%Y-%m-%dT%H:%M:%S',
strptime(self.start, '%Y%m%dT%H%M%S'))
# match the sensor ID from the filename to a platform and instrument
if self.sensor not in sensor_lookup.keys():
raise ValueError('unknown sensor: {}'.format(self.sensor))
self.platform, self.instrument = sensor_lookup[self.sensor]
# extract general geo metadata from the GTiff information
with Raster(filename) as ras:
self.dtype = Dtype(ras.dtype).numpystr
self.nodata = ras.nodata
self.format = ras.format
self.xres, self.yres = ras.res
self.crs = 'EPSG:{}'.format(ras.epsg)
self.is_projected = ras.projcs is not None
self.extent = self.__extent_convert(ras.geo, 'x', 'y')
# reproject the raster bounding box to EPSG 4326 and store its extent
with ras.bbox() as bbox:
bbox.reproject(4326)
self.extent_4326 = self.__extent_convert(
bbox.extent, 'lon', 'lat')
# create dictionary for resolution metadata depending on CRS characteristics
resolution_keys = ('x',
'y') if self.is_projected else ('longitude',
'latitude')
self.resolution = dict(zip(resolution_keys,
(self.xres, self.yres)))
# check whether the data type is supported
pattern = '(?:(?:u|)int(?:8|16|32|64)|float(?:32|64))'
if not re.search(pattern, self.dtype):
raise ValueError('unsupported data type {}'.format(self.dtype))
# determine the dataset units
if isinstance(units, str):
units = units
elif isinstance(units, dict):
try:
units = units[self.polarization]
except KeyError:
raise KeyError(
"parameter 'units' does not contain key '{}'".format(
self.polarization))
else:
raise TypeError(
"parameter 'units' must be of type str or dict")
# create the measurement entry from collected metadata;
# this is intended for easy access by class Product
self.measurements = {
self.polarization: {
'dtype': self.dtype,
'name': self.polarization,
'nodata': self.nodata,
'filename': filename,
'units': units
}
}
else:
raise TypeError('filename must be of type str, list or Dataset')