def __getitem__(self, key):
if np.isscalar(key) and resolve_scalar_dtype(key) == 'int64':
orig_key = key
if key < 0:
# Interpret negative key as offset from end of array
key += self.size
if (key >= 0 and key < self.size):
cmd = "segmentedIndex"
args = " {} {} {} {} {}".format('intIndex', self.objtype,
self.offsets.name,
self.bytes.name, key)
repMsg = generic_msg(cmd=cmd, args=args)
_, value = repMsg.split(maxsplit=1)
return parse_single_value(value)
else:
raise IndexError("[int] {} is out of bounds with size {}".\
format(orig_key,self.size))
elif isinstance(key, slice):
(start, stop, stride) = key.indices(self.size)
self.logger.debug('start: {}; stop: {}; stride: {}'.format(
start, stop, stride))
cmd = "segmentedIndex"
args = " {} {} {} {} {} {} {}".format('sliceIndex', self.objtype,
self.offsets.name,
self.bytes.name, start, stop,
stride)
repMsg = generic_msg(cmd=cmd, args=args)
offsets, values = repMsg.split('+')
return Strings(offsets, values)
elif isinstance(key, pdarray):
kind, _ = translate_np_dtype(key.dtype)
if kind not in ("bool", "int"):
raise TypeError("unsupported pdarray index type {}".format(
key.dtype))
if kind == "bool" and self.size != key.size:
raise ValueError("size mismatch {} {}".format(
self.size, key.size))
cmd = "segmentedIndex"
args = "{} {} {} {} {}".format('pdarrayIndex', self.objtype,
self.offsets.name, self.bytes.name,
key.name)
repMsg = generic_msg(cmd, args)
offsets, values = repMsg.split('+')
return Strings(offsets, values)
else:
raise TypeError("unsupported pdarray index type {}".format(
key.__class__.__name__))
def __getitem__(self, key):
if np.isscalar(key) and resolve_scalar_dtype(key) == 'int64':
if (key >= 0 and key < self.size):
msg = "segmentedIndex {} {} {} {} {}".format(
'intIndex', self.objtype, self.offsets.name,
self.bytes.name, key)
repMsg = generic_msg(msg)
fields = repMsg.split()
# value = fields[2]
return parse_single_value(' '.join(fields[1:]))
else:
raise IndexError(
"[int] {} is out of bounds with size {}".format(
key, self.size))
elif isinstance(key, slice):
(start, stop, stride) = key.indices(self.size)
if verbose: print(start, stop, stride)
msg = "segmentedIndex {} {} {} {} {} {} {}".format(
'sliceIndex', self.objtype, self.offsets.name, self.bytes.name,
start, stop, stride)
repMsg = generic_msg(msg)
offsets, values = repMsg.split('+')
return Strings(offsets, values)
elif isinstance(key, pdarray):
kind, itemsize = translate_np_dtype(key.dtype)
if kind not in ("bool", "int"):
raise TypeError("unsupported pdarray index type {}".format(
key.dtype))
if kind == "bool" and self.size != key.size:
raise ValueError("size mismatch {} {}".format(
self.size, key.size))
msg = "segmentedIndex {} {} {} {} {}".format(
'pdarrayIndex', self.objtype, self.offsets.name,
self.bytes.name, key.name)
repMsg = generic_msg(msg)
offsets, values = repMsg.split('+')
return Strings(offsets, values)
else:
raise TypeError("unsupported pdarray index type {}".format(
type(key)))