def split(self, t: ty.Union[int, None], allow_early_split=False):
"""Return (chunk_left, chunk_right) split at time t.
:param t: Time at which to split the data.
All data in the left chunk will have their (exclusive) end <= t,
all data in the right chunk will have (inclusive) start >=t.
:param allow_early_split:
If False, raise CannotSplit if the requirements above cannot be met.
If True, split at the closest possible time before t.
"""
t = max(min(t, self.end), self.start)
if t == self.end:
data1, data2 = self.data, self.data[:0]
elif t == self.start:
data1, data2 = self.data[:0], self.data
else:
data1, data2, t = split_array(data=self.data,
t=t,
allow_early_split=allow_early_split)
common_kwargs = dict(run_id=self.run_id,
dtype=self.dtype,
data_type=self.data_type,
data_kind=self.data_kind,
target_size_mb=self.target_size_mb)
c1 = strax.Chunk(start=self.start,
end=max(self.start, t),
data=data1,
**common_kwargs)
c2 = strax.Chunk(start=max(self.start, t),
end=max(t, self.end),
data=data2,
**common_kwargs)
return c1, c2
def _read_and_format_chunk(self, *, backend_key, dtype, metadata,
chunk_info, time_range,
chunk_construction_kwargs) -> strax.Chunk:
if chunk_info['n'] == 0:
# No data, no need to load
data = np.empty(0, dtype=dtype)
else:
data = self._read_chunk(backend_key,
chunk_info=chunk_info,
dtype=dtype,
compressor=metadata['compressor'])
result = strax.Chunk(start=chunk_info['start'],
end=chunk_info['end'],
run_id=chunk_info['run_id'],
data=data,
**chunk_construction_kwargs)
if time_range:
if result.start < time_range[0]:
_, result = result.split(t=time_range[0],
allow_early_split=True)
if result.end > time_range[1]:
try:
result, _ = result.split(t=time_range[1],
allow_early_split=False)
except strax.CannotSplit:
pass
return result
def chunk(self, *, start, end, data, data_type=None, run_id=None):
if data_type is None:
if self.multi_output:
raise ValueError("Must give data_type when making chunks from "
"a multi-output plugin")
data_type = self.provides[0]
if run_id is None:
run_id = self.run_id
return strax.Chunk(start=start,
end=end,
run_id=run_id,
data_kind=self.data_kind_for(data_type),
data_type=data_type,
dtype=self.dtype_for(data_type),
data=data,
target_size_mb=self.chunk_target_size_mb)
