from flojoy import OrderedPair, flojoy, Matrix, Scalar
import numpy as np
from collections import namedtuple
from typing import Literal

import scipy.stats


@flojoy
def TRIM1(
    default: OrderedPair | Matrix,
    proportiontocut: float = 0.1,
    tail: str = "right",
    axis: int = 0,
) -> OrderedPair | Matrix | Scalar:
    """The TRIM1 node is based on a numpy or scipy function.

    The description of that function is as follows:

        Slice off a proportion from ONE end of the passed array distribution.

        If 'proportiontocut' = 0.1, slices off 'leftmost' or 'rightmost' 10% of scores.
        The lowest or highest values are trimmed (depending on the tail).
        Slice off less if proportion results in a non-integer slice index (i.e. conservatively slices off 'proportiontocut').

    Parameters
    ----------
    a : array_like
        Input array.
    proportiontocut : float
        Fraction to cut off of 'left' or 'right' of distribution.
    tail : {'left', 'right'}, optional
        Defaults to 'right'.
    axis : int or None, optional
        Axis along which to trim data.
        Default is 0.
        If None, compute over the whole array 'a'.

    Returns
    -------
    DataContainer
        type 'ordered pair', 'scalar', or 'matrix'
    """

    result = scipy.stats.trim1(
        a=default.y,
        proportiontocut=proportiontocut,
        tail=tail,
        axis=axis,
    )

    if isinstance(result, np.ndarray):
        result = OrderedPair(x=default.x, y=result)
    else:
        assert isinstance(
            result, np.number | float | int
        ), f"Expected np.number, float or int for result, got {type(result)}"
        result = Scalar(c=float(result))

    return result

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