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use itertools::Itertools;
use crate::arrays::Array;
use crate::traits::{
    errors::ArrayError,
    manipulate::{
        ArrayManipulate,
        axis::ArrayAxis,
    },
    meta::ArrayMeta,
    create::ArrayCreate,
    types::numeric::Numeric,
};
use crate::traits::validators::{
    validate_compare::ValidateEqual,
    validate_unique::ValidateUnique,
};

impl <N: Numeric> ArrayAxis<N> for Array<N> {

    fn transpose(&self, axes: Option<Vec<isize>>) -> Result<Self, ArrayError> {

        fn transpose_recursive<N: Numeric>(
            input: &[N], input_shape: &[usize],
            output: &mut [N], output_shape: &[usize],
            current_indices: &mut [usize], current_dim: usize,
            axes: &Option<Vec<usize>>) {
            if current_dim < input_shape.len() - 1 {
                (0 .. input_shape[current_dim]).for_each(|i| {
                    current_indices[current_dim] = i;
                    transpose_recursive(input, input_shape, output, output_shape, current_indices, current_dim + 1, axes);
                });
            } else {
                (0 .. input_shape[current_dim]).for_each(|i| {
                    current_indices[current_dim] = i;
                    let input_index = input_shape.iter().enumerate().fold(0, |acc, (dim, size)| { acc * size + current_indices[dim] });
                    let output_indices = match axes {
                        Some(ref axes) => axes.iter().map(|&ax| current_indices[ax]).collect::<Vec<usize>>(),
                        None => current_indices.iter().rev().cloned().collect::<Vec<usize>>(),
                    };
                    let output_index = output_shape.iter().enumerate().fold(0, |acc, (dim, size)| { acc * size + output_indices[dim] });
                    output[output_index] = input[input_index];
                });
            }
        }

        let self_ndim = self.ndim()?;
        let axes = axes.map(|axes| axes.iter()
            .map(|i| Self::normalize_axis(*i, self_ndim))
            .collect::<Vec<usize>>());
        let mut new_elements = vec![N::ZERO; self.elements.len()];
        let new_shape: Vec<usize> = match axes.clone() {
            Some(axes) => axes.into_iter().map(|ax| self.shape[ax]).collect(),
            None => self.shape.clone().into_iter().rev().collect(),
        };

        transpose_recursive(
            &self.elements, &self.shape,
            &mut new_elements, &new_shape,
            &mut vec![0; self.shape.len()], 0,
            &axes
        );

        Self::new(new_elements, new_shape)
    }

    fn moveaxis(&self, source: Vec<isize>, destination: Vec<isize>) -> Result<Self, ArrayError> {
        source.is_unique()?;
        source.len().is_equal(&destination.len())?;
        let self_ndim = self.ndim()?;
        let source = source.iter().map(|i| Self::normalize_axis(*i, self_ndim)).collect::<Vec<usize>>();
        let destination = destination.iter().map(|i| Self::normalize_axis(*i, self_ndim)).collect::<Vec<usize>>();
        source.is_unique()?;
        destination.is_unique()?;

        let mut order = (0 .. self.ndim()?)
            .filter(|f| !source.contains(f))
            .collect::<Vec<usize>>();

        destination.into_iter()
            .zip(source.into_iter())
            .sorted()
            .for_each(|(d, s)| order.insert(d.min(order.len()), s));

        let order = order.iter().map(|i| *i as isize).collect();
        self.transpose(Some(order))
    }

    fn rollaxis(&self, axis: isize, start: Option<isize>) -> Result<Self, ArrayError> {
        let axis = Self::normalize_axis(axis, self.ndim()?);
        let start = if let Some(start) = start { Self::normalize_axis(start, self.ndim()?) } else { 0 };

        let mut new_axes = (0 .. self.ndim()?).collect::<Vec<usize>>();
        let axis_to_move = new_axes.remove(axis);
        new_axes.insert(start, axis_to_move);

        self.transpose(Some(new_axes.iter().map(|&i| i as isize).collect()))
    }

    fn swapaxes(&self, axis_1: isize, axis_2: isize) -> Result<Self, ArrayError> {
        let axis_1 = Self::normalize_axis(axis_1, self.ndim()?);
        let axis_2 = Self::normalize_axis(axis_2, self.ndim()?);

        let mut new_axes = (0 .. self.ndim()?).collect::<Vec<usize>>();
        new_axes.swap(axis_1, axis_2);

        self.transpose(Some(new_axes.iter().map(|&i| i as isize).collect()))
    }

    fn expand_dims(&self, axes: Vec<isize>) -> Result<Self, ArrayError> {
        let self_ndim = self.ndim()?;
        let axes = axes.iter()
            .map(|&i| Self::normalize_axis(i, self_ndim + axes.len()))
            .sorted()
            .collect::<Vec<usize>>();
        let mut new_shape = self.get_shape()?;

        for item in axes { new_shape.insert(item, 1) }
        self.reshape(new_shape)
    }

    fn squeeze(&self, axes: Option<Vec<isize>>) -> Result<Self, ArrayError> {
        let self_ndim = self.ndim()?;
        if let Some(axes) = axes {
            let axes = axes.iter()
                .map(|&i| Self::normalize_axis(i, self_ndim))
                .sorted()
                .rev()
                .collect::<Vec<usize>>();
            let mut new_shape = self.get_shape()?;

            if axes.iter().any(|a| new_shape[*a] != 1) {
                Err(ArrayError::SqueezeShapeOfAxisMustBeOne)
            } else {
                for item in axes { new_shape.remove(item); }
                self.reshape(new_shape)
            }
        }
        else {
            self.reshape(self.get_shape()?.into_iter().filter(|&i| i != 1).collect())
        }
    }
}

impl <N: Numeric> ArrayAxis<N> for Result<Array<N>, ArrayError> {

    fn transpose(&self, axes: Option<Vec<isize>>) -> Result<Array<N>, ArrayError> {
        self.clone()?.transpose(axes)
    }

    fn moveaxis(&self, source: Vec<isize>, destination: Vec<isize>) -> Result<Array<N>, ArrayError> {
        self.clone()?.moveaxis(source, destination)
    }

    fn rollaxis(&self, axis: isize, start: Option<isize>) -> Result<Array<N>, ArrayError> {
        self.clone()?.rollaxis(axis, start)
    }

    fn swapaxes(&self, axis: isize, start: isize) -> Result<Array<N>, ArrayError> {
        self.clone()?.swapaxes(axis, start)
    }

    fn expand_dims(&self, axes: Vec<isize>) -> Result<Array<N>, ArrayError> {
        self.clone()?.expand_dims(axes)
    }

    fn squeeze(&self, axes: Option<Vec<isize>>) -> Result<Array<N>, ArrayError> {
        self.clone()?.squeeze(axes)
    }
}