Source code for static_frame.core.node_fill_value

from __future__ import annotations

import numpy as np
import typing_extensions as tp

from static_frame.core.node_selector import Interface
from static_frame.core.node_selector import InterfaceBatch
from static_frame.core.node_selector import InterGetItemLocReduces
from static_frame.core.util import KEY_MULTIPLE_TYPES
from static_frame.core.util import NULL_SLICE
from static_frame.core.util import OPERATORS
from static_frame.core.util import TCallableAny
from static_frame.core.util import TLabel
from static_frame.core.util import TLocSelector
from static_frame.core.util import TLocSelectorCompound

if tp.TYPE_CHECKING:
    from static_frame.core.batch import Batch  # pragma: no cover
    from static_frame.core.frame import Frame  # pragma: no cover
    from static_frame.core.index_base import IndexBase  # pragma: no cover
    from static_frame.core.node_selector import TFrameOrSeries  # pragma: no cover
    from static_frame.core.node_transpose import InterfaceBatchTranspose  # pragma: no cover
    from static_frame.core.node_transpose import InterfaceTranspose  # pragma: no cover
    from static_frame.core.series import Series  # pragma: no cover
    from static_frame.core.type_blocks import TypeBlocks  # pylint: disable=W0611 #pragma: no cover

    TSeriesAny = Series[tp.Any, tp.Any] #pragma: no cover
    TFrameAny = Frame[tp.Any, tp.Any, tp.Unpack[tp.Tuple[tp.Any, ...]]] # type: ignore[type-arg] #pragma: no cover

TVContainer_co = tp.TypeVar('TVContainer_co',
        'Frame[tp.Any, tp.Any, tp.Unpack[tp.Tuple[tp.Any, ...]]]', # type: ignore[type-arg]
        'Series[tp.Any, tp.Any]',
        covariant=True,
        )
INTERFACE_FILL_VALUE = (
        'loc',
        '__getitem__',
        'via_T',
        '__add__',
        '__sub__',
        '__mul__',
        # '__matmul__',
        '__truediv__',
        '__floordiv__',
        '__mod__',
        '__pow__',
        '__lshift__',
        '__rshift__',
        '__and__',
        '__xor__',
        '__or__',
        '__lt__',
        '__le__',
        '__eq__',
        '__ne__',
        '__gt__',
        '__ge__',
        '__radd__',
        '__rsub__',
        '__rmul__',
        # '__rmatmul__',
        '__rtruediv__',
        '__rfloordiv__',
        )


class InterfaceFillValue(Interface, tp.Generic[TVContainer_co]):

    __slots__ = (
            '_container',
            '_fill_value',
            '_axis',
            )

    _INTERFACE = INTERFACE_FILL_VALUE

    def __init__(self,
            container: TVContainer_co,
            *,
            fill_value: tp.Any = np.nan,
            axis: int = 0,
            ) -> None:
        self._container: TVContainer_co = container
        self._fill_value = fill_value
        self._axis = axis

    #---------------------------------------------------------------------------
    @property
    def via_T(self) -> InterfaceTranspose[TFrameAny]:
        '''
        Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.
        '''
        from static_frame.core.frame import Frame
        from static_frame.core.node_transpose import InterfaceTranspose
        if not isinstance(self._container, Frame):
            raise NotImplementedError('via_T functionality only available on Frame')
        return InterfaceTranspose(
                container=self._container,
                fill_value=self._fill_value,
                )

    #---------------------------------------------------------------------------
    @staticmethod
    def _extract_key_attrs(
            key: TLocSelector,
            index: 'IndexBase',
            ) -> tp.Tuple[TLocSelector, bool, bool]:
        from static_frame.core.container_util import key_from_container_key

        key = key_from_container_key(index, key, expand_iloc=True)
        key_is_multiple = isinstance(key, KEY_MULTIPLE_TYPES)

        if key.__class__ is slice:
            key_is_null_slice = key == NULL_SLICE
            key = index._extract_loc(key) #type: ignore
        else:
            key_is_null_slice = False

        return key, key_is_multiple, key_is_null_slice

    def _extract_loc1d(self,
            key: TLocSelector = NULL_SLICE,
            ) -> TSeriesAny:
        '''This is only called if container is 1D
        '''
        from static_frame.core.container_util import get_col_fill_value_factory

        key, is_multiple, is_null_slice = self._extract_key_attrs(
                key,
                self._container._index,
                )
        fill_value = self._fill_value
        container = self._container

        if is_multiple:
            return container.reindex(key if not is_null_slice else None, #type: ignore
                    fill_value=fill_value,
                    )
        # if a single value, return it or the fill value
        fv = get_col_fill_value_factory(fill_value, None)(0, container.dtype) #type: ignore
        return container.get(key, fv) #type: ignore

    def _extract_loc2d(self,
            row_key: TLocSelector = NULL_SLICE,
            column_key: TLocSelector = NULL_SLICE,
            ) -> tp.Union[TFrameAny, TSeriesAny]:
        '''
        NOTE: keys are loc keys; None is interpreted as selector, not a NULL_SLICE
        '''
        from static_frame.core.container_util import get_col_fill_value_factory
        from static_frame.core.series import Series

        fill_value = self._fill_value
        container = self._container # always a Frame

        row_key, row_is_multiple, row_is_null_slice = self._extract_key_attrs(
                row_key,
                container._index,
                )
        column_key, column_is_multiple, column_is_null_slice = self._extract_key_attrs(
                column_key,
                container._columns, #type: ignore
                )

        if row_is_multiple and column_is_multiple:
            # cannot reindex if loc keys are elements
            return container.reindex( # type: ignore
                    index=row_key if not row_is_null_slice else None, # type: ignore
                    columns=column_key if not column_is_null_slice else None, # type: ignore
                    fill_value=fill_value,
                    )
        elif not row_is_multiple and not column_is_multiple: # selecting an element
            try:
                return container.loc[row_key, column_key] # type: ignore
            except KeyError:
                fv = get_col_fill_value_factory(fill_value, None)(0, None)
                return fv #type: ignore
        elif not row_is_multiple:
            # row is an element, return Series indexed by columns
            if row_key in container._index: #type: ignore
                s = container.loc[row_key]
                return s.reindex(column_key, fill_value=fill_value) #type: ignore

            fv = get_col_fill_value_factory(fill_value, None)(0, None)
            return Series.from_element(fv,
                    index=column_key, # type: ignore
                    name=row_key, # type: ignore
                    )
        # columns is an element, return Series indexed by index
        if column_key in container._columns: #type: ignore
            s = container[column_key]
            return s.reindex(row_key, fill_value=fill_value) #type: ignore

        fv = get_col_fill_value_factory(fill_value, None)(0, None)
        return Series.from_element(fv,
                index=row_key, # type: ignore
                name=column_key, # type: ignore
                )

    def _extract_loc2d_compound(self, key: TLocSelectorCompound) -> TFrameOrSeries:
        if isinstance(key, tuple):
            row_key, column_key = key # pyright: ignore
        else:
            row_key = key
            column_key = NULL_SLICE
        return self._extract_loc2d(row_key, column_key)

    #---------------------------------------------------------------------------
    @property
    def loc(self) -> InterGetItemLocReduces[TFrameOrSeries, tp.Any]:
        '''Label-based selection where labels not specified will define a new container containing those labels filled with the fill value.
        '''
        if self._container._NDIM == 1:
            return InterGetItemLocReduces(self._extract_loc1d)
        return InterGetItemLocReduces(self._extract_loc2d_compound)

[docs] def __getitem__(self, key: TLocSelector) -> TFrameOrSeries: '''Label-based selection where labels not specified will define a new container containing those labels filled with the fill value. ''' if self._container._NDIM == 1: return self._extract_loc1d(key) return self._extract_loc2d(NULL_SLICE, key)
#---------------------------------------------------------------------------
[docs] def __add__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__add__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __sub__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__sub__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __mul__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__mul__'], other=other, axis=self._axis, fill_value=self._fill_value, )
# def __matmul__(self, other: tp.Any) -> tp.Any: # return self._container._ufunc_binary_operator( # operator=OPERATORS['__matmul__'], # other=other, # axis=self._axis, # fill_value=self._fill_value, # )
[docs] def __truediv__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__truediv__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __floordiv__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__floordiv__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __mod__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__mod__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __pow__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__pow__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __lshift__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__lshift__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __rshift__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__rshift__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __and__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__and__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __xor__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__xor__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __or__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__or__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __lt__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__lt__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __le__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__le__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __eq__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__eq__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __ne__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__ne__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __gt__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__gt__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __ge__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__ge__'], other=other, axis=self._axis, fill_value=self._fill_value, )
#---------------------------------------------------------------------------
[docs] def __radd__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__radd__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __rsub__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__rsub__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __rmul__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__rmul__'], other=other, axis=self._axis, fill_value=self._fill_value, )
# def __rmatmul__(self, other: tp.Any) -> tp.Any: # return self._container._ufunc_binary_operator( # operator=OPERATORS['__rmatmul__'], # other=other, # axis=self._axis, # fill_value=self._fill_value, # )
[docs] def __rtruediv__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__rtruediv__'], other=other, axis=self._axis, fill_value=self._fill_value, )
[docs] def __rfloordiv__(self, other: tp.Any) -> tp.Any: return self._container._ufunc_binary_operator( operator=OPERATORS['__rfloordiv__'], other=other, axis=self._axis, fill_value=self._fill_value, )
#--------------------------------------------------------------------------- class InterfaceFillValueGO(InterfaceFillValue[TVContainer_co]): # only type is FrameGO __slots__ = () _INTERFACE = InterfaceFillValue._INTERFACE + ( #type: ignore '__setitem__', ) def __setitem__(self, key: TLabel, value: tp.Any, ) -> None: self._container.__setitem__(key, value, self._fill_value) #type: ignore #--------------------------------------------------------------------------- class InterfaceBatchFillValue(InterfaceBatch): '''Alternate string interface specialized for the :obj:`Batch`. ''' _INTERFACE = INTERFACE_FILL_VALUE __slots__ = ( '_batch_apply', '_fill_value', '_axis', ) def __init__(self, batch_apply: tp.Callable[[TCallableAny], 'Batch'], fill_value: object = np.nan, axis: int = 0, ) -> None: self._batch_apply = batch_apply self._fill_value = fill_value self._axis = axis #--------------------------------------------------------------------------- @property def via_T(self) -> 'InterfaceBatchTranspose': ''' Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise. ''' from static_frame.core.node_transpose import InterfaceBatchTranspose return InterfaceBatchTranspose( batch_apply=self._batch_apply, fill_value=self._fill_value, ) #--------------------------------------------------------------------------- @property def loc(self) -> InterGetItemLocReduces[Batch, tp.Any]: '''Label-based selection where labels not specified will define a new container containing those labels filled with the fill value. ''' def func(key: TLocSelector) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).loc[key] ) return InterGetItemLocReduces(func) def __getitem__(self, key: TLocSelector) -> 'Batch': '''Label-based selection where labels not specified will define a new container containing those labels filled with the fill value. ''' return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__getitem__(key) ) #--------------------------------------------------------------------------- def __add__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__add__(other) ) def __sub__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__sub__(other) ) def __mul__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__mul__(other) ) # def __matmul__(self, other: tp.Any) -> 'Batch': def __truediv__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__truediv__(other) ) def __floordiv__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__floordiv__(other) ) def __mod__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__mod__(other) ) def __pow__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__pow__(other) ) def __lshift__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__lshift__(other) ) def __rshift__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__rshift__(other) ) def __and__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__and__(other) ) def __xor__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__xor__(other) ) def __or__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__or__(other) ) def __lt__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__lt__(other) ) def __le__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__le__(other) ) def __eq__(self, other: tp.Any) -> 'Batch': #type: ignore return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__eq__(other) ) def __ne__(self, other: tp.Any) -> 'Batch': #type: ignore return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__ne__(other) ) def __gt__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__gt__(other) ) def __ge__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__ge__(other) ) #--------------------------------------------------------------------------- def __radd__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__radd__(other) ) def __rsub__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__rsub__(other) ) def __rmul__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__rmul__(other) ) # def __rmatmul__(self, other: tp.Any) -> 'Batch': def __rtruediv__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__rtruediv__(other) ) def __rfloordiv__(self, other: tp.Any) -> 'Batch': return self._batch_apply( lambda c: InterfaceFillValue(c, fill_value=self._fill_value, axis=self._axis).__rfloordiv__(other) )