Splitting

systematica.generic.splitting

default_splitter_kwargs

default_splitter_kwargs(
    splitter: str,
    **kwargs,
) ‑> Dict[str, Any]

Generate default keyword arguments for the specified splitter type.

Parameters:

Name	Type	Default	Description
splitter	str	--	The type of splitter.
kwargs	tp.Kwargs	--	Arbitrary keyword arguments, will be filtered based on the splitter type.

Raises:

Type	Description
ValueError	If the splitter type is unsupported.

Returns:

Type	Description
tp.Kwargs	A dictionary containing the necessary keyword arguments for the splitter.

CustomSplitter

CustomSplitter(
    wrapper: vectorbtpro.base.wrapping.ArrayWrapper,
    index: pandas.core.indexes.base.Index,
    splits_arr: numpy.ndarray,
    **kwargs,
)

Custom splitter.

Ancestors

• vectorbtpro.generic.splitting.base.Splitter
• vectorbtpro.generic.analyzable.Analyzable
• vectorbtpro.base.wrapping.Wrapping
• vectorbtpro.utils.config.Configured
• vectorbtpro.utils.config.HasSettings
• vectorbtpro.utils.caching.Cacheable
• vectorbtpro.utils.checks.Comparable
• vectorbtpro.utils.pickling.Pickleable
• vectorbtpro.utils.formatting.Prettified
• vectorbtpro.utils.chaining.Chainable
• vectorbtpro.base.wrapping.HasWrapper
• vectorbtpro.base.indexing.ExtPandasIndexer
• vectorbtpro.base.indexing.PandasIndexer
• vectorbtpro.base.indexing.IndexingBase
• vectorbtpro.utils.params.ItemParamable
• vectorbtpro.utils.params.Itemable
• vectorbtpro.utils.params.Paramable
• vectorbtpro.base.indexes.IndexApplier
• vectorbtpro.utils.attr_.AttrResolverMixin
• vectorbtpro.generic.stats_builder.StatsBuilderMixin
• vectorbtpro.generic.plots_builder.PlotsBuilderMixin
• vectorbtpro.utils.base.Base

Static methods

from_custom_rolling

from_custom_rolling(
    index: pandas.core.indexes.base.Index,
    length: int,
    offset: int = 0,
    offset_anchor: str = 'prev_end',
    offset_anchor_set: int = 0,
    offset_space: str = 'prev',
    backwards: bool | str = False,
    split: int = None,
    split_range_kwargs: Dict[str, Any] = None,
    range_bounds_kwargs: Dict[str, Any] = None,
    template_context: Dict[str, Any] = None,
    freq: str = None,
    **kwargs,
) ‑> ~SplitterT

Create a custom Splitter instance from a rolling range of fixed length.

Superset Splitter.from_rolling by adding the first (if backwards is sorted) or last remaining split. Creates a rolling sequence of slices based on the provided index. The first slice uses a length defined by length, and each subsequent slice begins after an offset from the previous slice’s right boundary.

Uses Splitter.from_splits to generate an array of splits and corresponding labels, and then construct the Splitter instance. See Splitter.from_rolling for further informations.

Parameters:

Name	Type	Default	Description
index	tp.IndexLike	--	The index to use for the splits. Must be a datetime-like index.
length	int	--	The length of each rolling slice. Can be an int, Float, or timedelta.
offset	int	0	The offset to apply to the start of each slice after the first one. Can be an integer, float, or timedelta.
offset_anchor	str	prev_end	The anchor point for the offset. Can be prev_end or start.
offset_anchor_set	int	0	The index of the anchor point to use for the offset. If None, uses the last anchor point.
offset_space	str	prev	The space in which the offset is applied. Can be prev or all.
backwards	bool	False	If True, the rolling slices are created in reverse order. If ‘sorted’, the first slice is sorted in reverse order. If False, the rolling slices are created in forward order.
split	tp.SplitLike	None	If provided, the rolling slices will be split further according to this parameter. Can be a single split or a list of splits.
split_range_kwargs	tp.KwargsLike	None	Additional keyword arguments to pass to the split_range method.
range_bounds_kwargs	tp.KwargsLike	None	Additional keyword arguments to pass to the get_range_bounds method.
template_context	tp.KwargsLike	None	Context for template rendering, if applicable.
freq	tp.FrequencyLike	None	Frequency of the index. If None, it will be inferred from the index.
kwargs	tp.Kwargs	--	Additional keyword arguments to pass to the Splitter.from_splits method.

Raises:

Type	Description
ValueError	If backwards is a string that is not sorted.
ValueError	If the length is negative when backwards is True.

Returns:

Type	Description
SplitterT	An instance of Splitter containing the rolling slices and their labels.

from_custom_expanding

from_custom_expanding(
    index: pandas.core.indexes.base.Index,
    min_length: int,
    offset: int,
    split: int = None,
    split_range_kwargs: Dict[str, Any] = None,
    range_bounds_kwargs: Dict[str, Any] = None,
    template_context: Dict[str, Any] = None,
    freq: str = None,
    **kwargs,
) ‑> ~SplitterT

Create a Splitter instance from an expanding range.

Creates an expanding sequence of slices based on the provided index. The first slice uses a minimum length defined by min_length, and each subsequent slice begins after an offset from the previous slice’s right boundary.

Uses Splitter.from_expanding by adding the last remaining split. See Splitter.from_expanding for further informations.

Parameters:

Name	Type	Default	Description
index	tp.IndexLike	--	The index to use for the splits. Must be a datetime-like index.
min_length	int	--	The minimum length of each expanding slice. Can be an int, float, or timedelta.
offset	int	--	The offset to apply to the start of each slice after the first one. Can be an int, Float, or timedelta.
split	tp.SplitLike	None	If provided, the expanding slices will be split further according to this parameter. Can be a single split or a list of splits.
split_range_kwargs	tp.KwargsLike	None	Additional keyword arguments to pass to the split_range method.
range_bounds_kwargs	tp.KwargsLike	None	Additional keyword arguments to pass to the get_range_bounds method.
template_context	tp.KwargsLike	None	Context for template rendering, if applicable.
freq	tp.FrequencyLike	None	Frequency of the index. If None, it will be inferred from the index.
kwargs	tp.Kwargs	--	Additional keyword arguments to pass to the Splitter.from_splits method.

Raises:

Type	Description
ValueError	If the min_length is negative.
ValueError	If the offset is negative.
ValueError	If the split is not a valid split type.

Returns:

Type	Description
SplitterT	An instance of Splitter containing the expanding slices and their labels.