def map_reduce_partitions(self, map_func_nb=None, map_args=None,
reduce_func_nb=None, reduce_args=None):
"""See `vectorbt.signals.nb.map_reduce_partitions_nb`.
## Example
Get average length of each partition in `sig`:
```python-repl
>>> distance_map_nb = njit(lambda from_i, to_i, col: to_i - from_i)
>>> mean_reduce_nb = njit(lambda col, a: np.nanmean(a))
>>> sig.vbt.signals.map_reduce_partitions(
... map_func_nb=distance_map_nb,
... reduce_func_nb=mean_reduce_nb)
a 1.0
b 1.0
c 3.0
dtype: float64
```
"""
checks.assert_not_none(map_func_nb)
checks.assert_not_none(reduce_func_nb)
checks.assert_numba_func(map_func_nb)
checks.assert_numba_func(reduce_func_nb)
if map_args is None:
map_args = ()
if reduce_args is None:
reduce_args = ()
result = nb.map_reduce_partitions_nb(
self.to_2d_array(),
map_func_nb, map_args,
reduce_func_nb, reduce_args
)
return self.wrapper.wrap_reduced(result)
def map_reduce_partitions(
self,
map_func_nb: tp.Optional[tp.SignalMapFunc] = None,
map_args: tp.Optional[tp.Args] = None,
reduce_func_nb: tp.Optional[tp.SignalReduceFunc] = None,
reduce_args: tp.Optional[tp.Args] = None,
wrap_kwargs: tp.KwargsLike = None) -> tp.MaybeSeries:
"""See `vectorbt.signals.nb.map_reduce_partitions_nb`.
## Example
Get average length of each partition in `sig`:
```python-repl
>>> distance_map_nb = njit(lambda from_i, to_i, col: to_i - from_i)
>>> mean_reduce_nb = njit(lambda col, a: np.nanmean(a))
>>> sig.vbt.signals.map_reduce_partitions(
... map_func_nb=distance_map_nb,
... reduce_func_nb=mean_reduce_nb)
a 1.0
b 1.0
c 3.0
dtype: float64
```
"""
checks.assert_not_none(map_func_nb)
checks.assert_not_none(reduce_func_nb)
checks.assert_numba_func(map_func_nb)
checks.assert_numba_func(reduce_func_nb)
if map_args is None:
map_args = ()
if reduce_args is None:
reduce_args = ()
result = nb.map_reduce_partitions_nb(self.to_2d_array(), map_func_nb,
map_args, reduce_func_nb,
reduce_args)
wrap_kwargs = merge_dicts(dict(name_or_index='map_reduce_partitions'),
wrap_kwargs)
return self.wrapper.wrap_reduced(result, **wrap_kwargs)
