cellular_raza-building-blocks 0.1.4

// Imports from this crate
use cellular_raza_concepts::*;

#[cfg(feature = "pyo3")]
use pyo3::prelude::*;

// Imports from std and core
use core::cmp::{max, min};
use std::usize;

// Imports from other crates
use itertools::Itertools;
use nalgebra::SVector;

use serde::{ser::SerializeStruct, Deserialize, Deserializer, Serialize};

/// Helper function to calculate the decomposition of a large number N into n as evenly-sizedchunks
/// chunks as possible
/// Examples:
/// N   n   decomp
/// 10  3    1 *  4  +  3 *  3
/// 13  4    1 *  5  +  3 *  4
/// 100 13   4 * 13  +  4 * 12
/// 225 16   1 * 15  + 15 * 14
/// 225 17   4 * 14  + 13 * 13
pub(super) fn get_decomp_res(n_voxel: usize, n_regions: usize) -> Option<(usize, usize, usize)> {
    // We calculate how many times we need to drain how many voxels
    // Example:
    //      n_voxels    = 59
    //      n_regions   = 6
    //      average_len = (59 / 8).ceil() = (9.833 ...).ceil() = 10
    //
    // try to solve this equation:
    //      n_voxels = average_len * n + (average_len-1) * m
    //      where n,m are whole positive numbers
    //
    // We start with    n = n_regions = 6
    // and with         m = min(0, n_voxel - average_len.pow(2)) = min(0, 59 - 6^2) = 23
    let mut average_len: i64 = (n_voxel as f64 / n_regions as f64).ceil() as i64;

    let residue = |n: i64, m: i64, avg: i64| n_voxel as i64 - avg * n - (avg - 1) * m;

    let mut n = n_regions as i64;
    let mut m = 0;

    for _ in 0..n_regions {
        let r = residue(n, m, average_len);
        if r == 0 {
            return Some((n as usize, m as usize, average_len as usize));
        } else if r > 0 {
            if n == n_regions as i64 {
                // Start from the beginning again but with different value for average length
                average_len += 1;
                n = n_regions as i64;
                m = 0;
            } else {
                n += 1;
                m -= 1;
            }
        // Residue is negative. This means we have subtracted too much and we just decrease n and
        // increase m
        } else {
            n -= 1;
            m += 1;
        }
    }
    None
}

/// A generic Domain with a cuboid layout.
///
/// This struct can be used to define custom domains on top of its behaviour.
#[derive(Clone, Debug)]
pub struct CartesianCuboid<F, const D: usize> {
    min: SVector<F, D>,
    max: SVector<F, D>,
    dx: SVector<F, D>,
    n_voxels: SVector<usize, D>,
    /// Seed from which all random numbers will be initially drawn
    pub rng_seed: u64,
}

impl<F, const D: usize> CartesianCuboid<F, D>
where
    F: Clone,
{
    /// Get the minimum point which defines the simulation domain
    pub fn get_min(&self) -> SVector<F, D> {
        self.min.clone()
    }

    /// Get the maximum point which defines the simulation domain
    pub fn get_max(&self) -> SVector<F, D> {
        self.max.clone()
    }

    /// Get the discretization used to generate voxels
    pub fn get_dx(&self) -> SVector<F, D> {
        self.dx.clone()
    }

    /// Get the number of voxels in each dimension of the domain
    pub fn get_n_voxels(&self) -> SVector<usize, D> {
        self.n_voxels.clone()
    }
}

impl<C, Ci, F, const D: usize> Domain<C, CartesianSubDomain<F, D>, Ci> for CartesianCuboid<F, D>
where
    C: Position<nalgebra::SVector<F, D>>,
    F: 'static
        + num::Float
        + Copy
        + core::fmt::Debug
        + num::FromPrimitive
        + num::ToPrimitive
        + core::ops::SubAssign
        + core::ops::Div<Output = F>
        + core::ops::DivAssign,
    Ci: IntoIterator<Item = C>,
{
    type SubDomainIndex = usize;
    type VoxelIndex = [usize; D];

    fn decompose(
        self,
        n_subdomains: core::num::NonZeroUsize,
        cells: Ci,
    ) -> Result<DecomposedDomain<Self::SubDomainIndex, CartesianSubDomain<F, D>, C>, DecomposeError>
    {
        #[derive(Clone, Domain)]
        struct MyIntermdiatedomain<F, const D: usize>
        where
            F: 'static
                + num::Float
                + Copy
                + core::fmt::Debug
                + num::FromPrimitive
                + num::ToPrimitive
                + core::ops::SubAssign
                + core::ops::Div<Output = F>
                + core::ops::DivAssign,
        {
            #[DomainRngSeed]
            #[DomainCreateSubDomains]
            #[SortCells]
            domain: CartesianCuboid<F, D>,
        }
        let my_intermediate_domain = MyIntermdiatedomain { domain: self };
        my_intermediate_domain.decompose(n_subdomains, cells)
    }
}

impl<F, const D: usize> CartesianCuboid<F, D>
where
    F: 'static + num::Float + Copy + core::fmt::Debug + num::FromPrimitive + num::ToPrimitive,
{
    fn check_min_max(min: &[F; D], max: &[F; D]) -> Result<(), BoundaryError>
    where
        F: core::fmt::Debug,
    {
        for i in 0..D {
            if min[i] >= max[i] {
                return Err(BoundaryError(format!(
                    "Min {:?} must be smaller than Max {:?} for domain boundaries!",
                    min, max
                )));
            }
        }
        Ok(())
    }

    /// Builds a new [CartesianCuboid] from given boundaries and maximum interaction ranges of the
    /// containing cells.
    ///
    /// ```
    /// # use cellular_raza_building_blocks::CartesianCuboid;
    /// let min = [2.0, 3.0, 1.0];
    /// let max = [10.0, 10.0, 20.0];
    /// let interaction_range = 2.0;
    /// let domain = CartesianCuboid::from_boundaries_and_interaction_range(
    ///     min,
    ///     max,
    ///     interaction_range
    /// )?;
    ///
    /// assert_eq!(domain.get_n_voxels()[0], 4);
    /// assert_eq!(domain.get_n_voxels()[1], 3);
    /// assert_eq!(domain.get_n_voxels()[2], 9);
    /// # Ok::<(), Box<dyn std::error::Error>>(())
    /// ```
    pub fn from_boundaries_and_interaction_range(
        min: impl Into<[F; D]>,
        max: impl Into<[F; D]>,
        interaction_range: F,
    ) -> Result<Self, BoundaryError> {
        // Perform conversions
        let min: [F; D] = min.into();
        let max: [F; D] = max.into();

        // Check that the specified min and max are actually smaller / larger
        Self::check_min_max(&min, &max)?;

        // Calculate the number of voxels from given interaction ranges
        let mut n_voxels = [0; D];
        let mut dx = [F::zero(); D];
        for i in 0..D {
            let n = ((max[i] - min[i]) / interaction_range).floor();
            // This conversion should hopefully never fail.
            n_voxels[i] = n.to_usize().ok_or(BoundaryError(
                cellular_raza_concepts::format_error_message!(
                    format!(
                        "Cannot convert float {:?} of type {} to usize",
                        n,
                        std::any::type_name::<F>()
                    ),
                    "conversion error during domain setup"
                ),
            ))?;
            dx[i] = (max[i] - min[i]) / n;
        }

        Ok(Self {
            min: min.into(),
            max: max.into(),
            dx: dx.into(),
            n_voxels: n_voxels.into(),
            rng_seed: 0,
        })
    }

    /// Builds a new [CartesianCuboid] from given boundaries and the number of voxels per dimension
    /// specified.
    pub fn from_boundaries_and_n_voxels(
        min: impl Into<[F; D]>,
        max: impl Into<[F; D]>,
        n_voxels: impl Into<[usize; D]>,
    ) -> Result<Self, BoundaryError> {
        let min: [F; D] = min.into();
        let max: [F; D] = max.into();
        let n_voxels: [usize; D] = n_voxels.into();
        Self::check_min_max(&min, &max)?;
        let mut dx: SVector<F, D> = [F::zero(); D].into();
        for i in 0..D {
            let n = F::from_usize(n_voxels[i]).ok_or(BoundaryError(
                cellular_raza_concepts::format_error_message!(
                    "conversion error during domain setup",
                    format!(
                        "Cannot convert usize {} to float of type {}",
                        n_voxels[i],
                        std::any::type_name::<F>()
                    )
                ),
            ))?;
            dx[i] = (max[i] - min[i]) / n;
        }
        Ok(Self {
            min: min.into(),
            max: max.into(),
            dx,
            n_voxels: n_voxels.into(),
            rng_seed: 0,
        })
    }
}

impl<F, const D: usize> CartesianCuboid<F, D> {
    fn get_all_voxel_indices(&self) -> impl IntoIterator<Item = [usize; D]> {
        use itertools::*;
        (0..D)
            .map(|i| 0..self.n_voxels[i])
            .multi_cartesian_product()
            .map(|x| {
                let mut index = [0; D];
                for j in 0..D {
                    index[j] = x[j];
                }
                index
            })
    }

    /// Get the total amount of indices in this domain
    fn get_n_indices(&self) -> usize {
        let mut res = 1;
        for i in 0..D {
            res *= self.n_voxels[i];
        }
        res
    }
}

mod test_domain_setup {
    #[test]
    fn from_boundaries_and_interaction_range() {
        use crate::CartesianCuboid;
        let min = [0.0; 2];
        let max = [2.0; 2];
        let interaction_range = 1.0;
        let _ = CartesianCuboid::from_boundaries_and_interaction_range(min, max, interaction_range)
            .unwrap();
        // TODO add actual test case here
    }

    #[test]
    fn from_boundaries_and_n_voxels() {
        use crate::CartesianCuboid;
        let min = [-100.0f32; 55];
        let max = [43000.0f32; 55];
        let n_voxels = [22; 55];
        let _ = CartesianCuboid::from_boundaries_and_n_voxels(min, max, n_voxels).unwrap();
        // TODO add actual test case here
    }
}

impl<F, const D: usize> CartesianCuboid<F, D>
where
    F: 'static
        + num::Float
        + Copy
        + core::fmt::Debug
        + num::FromPrimitive
        + num::ToPrimitive
        + core::ops::SubAssign
        + core::ops::Div<Output = F>
        + core::ops::DivAssign,
{
    /// Obtains the voxel index given a regular vector
    ///
    /// This function can be used in derivatives of this type.
    pub fn get_voxel_index_of_raw(&self, pos: &SVector<F, D>) -> Result<[usize; D], BoundaryError> {
        Self::check_min_max(&self.min.into(), &(*pos).into())?;
        let n_vox = (pos - self.min).component_div(&self.dx);
        let mut res = [0usize; D];
        for i in 0..D {
            res[i] = n_vox[i].to_usize().ok_or(BoundaryError(
                cellular_raza_concepts::format_error_message!(
                    "conversion error during domain setup",
                    format!(
                        "Cannot convert float {:?} of type {} to usize",
                        n_vox[i],
                        std::any::type_name::<F>()
                    )
                ),
            ))?;
        }
        Ok(res.into())
    }
}

impl<C, F, const D: usize> SortCells<C> for CartesianCuboid<F, D>
where
    F: 'static
        + num::Float
        + Copy
        + core::fmt::Debug
        + num::FromPrimitive
        + num::ToPrimitive
        + core::ops::SubAssign
        + core::ops::Div<Output = F>
        + core::ops::DivAssign,
    C: Position<SVector<F, D>>,
{
    type VoxelIndex = [usize; D];

    fn get_voxel_index_of(&self, cell: &C) -> Result<Self::VoxelIndex, BoundaryError> {
        let pos = cell.pos();
        self.get_voxel_index_of_raw(&pos)
    }
}

impl<C, F, const D: usize> SortCells<C> for CartesianSubDomain<F, D>
where
    C: Position<nalgebra::SVector<F, D>>,
    F: 'static + num::Float + core::fmt::Debug + core::ops::SubAssign + core::ops::DivAssign,
{
    type VoxelIndex = [usize; D];

    fn get_voxel_index_of(&self, cell: &C) -> Result<Self::VoxelIndex, BoundaryError> {
        let pos = cell.pos();
        self.get_index_of(pos)
    }
}

impl<F, const D: usize> DomainRngSeed for CartesianCuboid<F, D> {
    fn get_rng_seed(&self) -> u64 {
        self.rng_seed
    }
}

#[test]
fn generate_subdomains() {
    use DomainCreateSubDomains;
    let min = [0.0; 3];
    let max = [100.0; 3];
    let interaction_range = 20.0;
    let domain =
        CartesianCuboid::from_boundaries_and_interaction_range(min, max, interaction_range)
            .unwrap();
    let sub_domains = domain
        .create_subdomains(4.try_into().unwrap())
        .unwrap()
        .into_iter()
        .collect::<Vec<_>>();
    assert_eq!(sub_domains.len(), 4);
    assert_eq!(
        sub_domains
            .iter()
            .map(|(_, _, voxels)| voxels.len())
            .sum::<usize>(),
        5usize.pow(3)
    );
}

/// Subdomain corresponding to the [CartesianCuboid] struct.
#[derive(Clone, Debug, PartialEq)]
pub struct CartesianSubDomain<F, const D: usize> {
    min: SVector<F, D>,
    max: SVector<F, D>,
    dx: SVector<F, D>,
    voxels: Vec<[usize; D]>,
    domain_min: SVector<F, D>,
    domain_max: SVector<F, D>,
    domain_n_voxels: SVector<usize, D>,
}

#[derive(Deserialize)]
#[serde(rename(serialize = "CartesianSubDomain", deserialize = "CartesianSubDomain",))]
struct __CartesianSubDomainSerde<F: 'static + Clone + core::fmt::Debug + PartialEq, const D: usize>
{
    min: SVector<F, D>,
    max: SVector<F, D>,
    dx: SVector<F, D>,
    voxels: Vec<SVector<usize, D>>,
    domain_min: SVector<F, D>,
    domain_max: SVector<F, D>,
    domain_n_voxels: SVector<usize, D>,
}

impl<F, const D: usize> From<__CartesianSubDomainSerde<F, D>> for CartesianSubDomain<F, D>
where
    F: 'static + Clone + core::fmt::Debug + PartialEq,
{
    fn from(s: __CartesianSubDomainSerde<F, D>) -> Self {
        CartesianSubDomain {
            min: s.min,
            max: s.max,
            dx: s.dx,
            voxels: s
                .voxels
                .into_iter()
                .map(|vox| <[usize; D]>::from(vox))
                .collect(),
            domain_min: s.domain_min,
            domain_max: s.domain_max,
            domain_n_voxels: s.domain_n_voxels,
        }
    }
}

impl<F, const D: usize> Serialize for CartesianSubDomain<F, D>
where
    F: nalgebra::Scalar + Serialize,
{
    fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
    where
        S: serde::Serializer,
    {
        let mut state = serializer.serialize_struct("CartesianSubDomain", 7)?;
        state.serialize_field("min", &self.min)?;
        state.serialize_field("max", &self.max)?;
        state.serialize_field("dx", &self.dx)?;
        let voxels = self
            .voxels
            .iter()
            .map(|ind| ind.clone().into_iter().collect::<Vec<_>>())
            .collect::<Vec<_>>();
        state.serialize_field("voxels", &voxels)?;
        state.serialize_field("domain_min", &self.domain_min)?;
        state.serialize_field("domain_max", &self.domain_max)?;
        state.serialize_field("domain_n_voxels", &self.domain_n_voxels)?;
        state.end()
    }
}

impl<'de, F, const D: usize> Deserialize<'de> for CartesianSubDomain<F, D>
where
    F: nalgebra::Scalar + for<'a> Deserialize<'a>,
{
    fn deserialize<De>(deserializer: De) -> Result<Self, De::Error>
    where
        De: Deserializer<'de>,
    {
        let s = __CartesianSubDomainSerde::deserialize(deserializer)?;
        let subdomain = s.into();
        Ok(subdomain)
    }
}

#[test]
fn serialize_cartesiansubdomain() {
    let subdomain = CartesianSubDomain {
        min: [-30.0, 10.0].into(),
        max: [55.33, 11.0].into(),
        dx: [1.0, 0.01].into(),
        voxels: vec![[1, 2], [3, 4], [5, 6]],
        domain_min: [-30.0, 10.0].into(),
        domain_max: [55.33, 22.38].into(),
        domain_n_voxels: [1, 2].into(),
    };
    // TODO finish this test
    use serde_test::{assert_de_tokens, assert_ser_tokens, Token};
    let tokens = [
        Token::Struct {
            name: "CartesianSubDomain",
            len: 7,
        },
        // subdomain.min
        Token::Str("min"),
        Token::Tuple { len: 2 },
        Token::F64(subdomain.min[0]),
        Token::F64(subdomain.min[1]),
        Token::TupleEnd,
        // subdomain.max
        Token::Str("max"),
        Token::Tuple { len: 2 },
        Token::F64(subdomain.max[0]),
        Token::F64(subdomain.max[1]),
        Token::TupleEnd,
        // subdomain.dx
        Token::Str("dx"),
        Token::Tuple { len: 2 },
        Token::F64(subdomain.dx[0]),
        Token::F64(subdomain.dx[1]),
        Token::TupleEnd,
        // subdomain.voxels
        Token::Str("voxels"),
        Token::Seq { len: Some(3) },
        Token::Seq { len: Some(2) },
        Token::U64(subdomain.voxels[0][0] as u64),
        Token::U64(subdomain.voxels[0][1] as u64),
        Token::SeqEnd,
        Token::Seq { len: Some(2) },
        Token::U64(subdomain.voxels[1][0] as u64),
        Token::U64(subdomain.voxels[1][1] as u64),
        Token::SeqEnd,
        Token::Seq { len: Some(2) },
        Token::U64(subdomain.voxels[2][0] as u64),
        Token::U64(subdomain.voxels[2][1] as u64),
        Token::SeqEnd,
        Token::SeqEnd,
        // domain.min
        Token::Str("domain_min"),
        Token::Tuple { len: 2 },
        Token::F64(subdomain.domain_min[0]),
        Token::F64(subdomain.domain_min[1]),
        Token::TupleEnd,
        // domain.max
        Token::Str("domain_max"),
        Token::Tuple { len: 2 },
        Token::F64(subdomain.domain_max[0]),
        Token::F64(subdomain.domain_max[1]),
        Token::TupleEnd,
        // domain.dx
        Token::Str("domain_n_voxels"),
        Token::Tuple { len: 2 },
        Token::U64(subdomain.domain_n_voxels[0] as u64),
        Token::U64(subdomain.domain_n_voxels[1] as u64),
        Token::TupleEnd,
        Token::StructEnd,
    ];
    assert_ser_tokens(&subdomain, &tokens);
    assert_de_tokens(&subdomain, &tokens);
}

impl<F, const D: usize> CartesianSubDomain<F, D>
where
    F: Clone,
{
    /// Get the minimum boundary of the subdomain.
    /// Note that not all voxels which could be in the space of the subdomain need to be in it.
    pub fn get_min(&self) -> SVector<F, D> {
        self.min.clone()
    }

    /// Get the maximum boundary of the subdomain.
    /// Note that not all voxels which could be in the space of the subdomain need to be in it.
    pub fn get_max(&self) -> SVector<F, D> {
        self.max.clone()
    }

    /// Get the discretization used to generate voxels
    pub fn get_dx(&self) -> SVector<F, D> {
        self.dx.clone()
    }

    /// Get all voxel indices which are currently in this subdomain
    pub fn get_voxels(&self) -> Vec<[usize; D]> {
        self.voxels.clone()
    }

    /// See [CartesianCuboid::get_min].
    pub fn get_domain_min(&self) -> SVector<F, D> {
        self.domain_min.clone()
    }

    /// See [CartesianCuboid::get_max].
    pub fn get_domain_max(&self) -> SVector<F, D> {
        self.domain_max.clone()
    }

    /// See [CartesianCuboid::get_n_voxels].
    pub fn get_domain_n_voxels(&self) -> SVector<usize, D> {
        self.domain_n_voxels.clone()
    }
}

impl<F, const D: usize> CartesianSubDomain<F, D> {
    /// Generic method to obtain the voxel index of any type that can be casted to an array.
    pub fn get_index_of<P>(&self, pos: P) -> Result<[usize; D], BoundaryError>
    where
        [F; D]: From<P>,
        F: 'static + num::Float + core::fmt::Debug + core::ops::SubAssign + core::ops::DivAssign,
    {
        let pos: [F; D] = pos.into();
        let mut res = [0usize; D];
        for i in 0..D {
            let n_vox = (pos[i] - self.domain_min[i]) / self.dx[i];
            res[i] = n_vox.to_usize().ok_or(BoundaryError(
                cellular_raza_concepts::format_error_message!(
                    "conversion error during domain setup",
                    format!(
                        "Cannot convert float {:?} of type {} to usize",
                        n_vox,
                        std::any::type_name::<F>()
                    )
                ),
            ))?;
        }
        Ok(res)
    }
}

impl<F, const D: usize> DomainCreateSubDomains<CartesianSubDomain<F, D>> for CartesianCuboid<F, D>
where
    F: 'static + num::Float + core::fmt::Debug + num::FromPrimitive,
{
    type SubDomainIndex = usize;
    type VoxelIndex = [usize; D];

    fn create_subdomains(
        &self,
        n_subdomains: core::num::NonZeroUsize,
    ) -> Result<
        impl IntoIterator<
            Item = (
                Self::SubDomainIndex,
                CartesianSubDomain<F, D>,
                Vec<Self::VoxelIndex>,
            ),
        >,
        DecomposeError,
    > {
        let indices = self.get_all_voxel_indices();
        let n_indices = self.get_n_indices();

        let (n, _m, average_len) = get_decomp_res(n_indices, n_subdomains.into()).ok_or(
            DecomposeError::Generic("Could not find a suiting decomposition".to_owned()),
        )?;

        // TODO Currently we are not splitting the voxels apart efficiently
        // These are subdomains which contain n voxels
        let switcher = n * average_len;
        let indices_grouped = indices.into_iter().enumerate().chunk_by(|(i, _)| {
            use num::Integer;
            if *i < switcher {
                i.div_rem(&average_len).0
            } else {
                (i - switcher).div_rem(&(average_len - 1).max(1)).0 + n
            }
        });
        let mut res = Vec::new();
        for (n_subdomain, indices) in indices_grouped.into_iter() {
            let mut min_vox = [usize::MAX; D];
            let mut max_vox = [0; D];
            let voxels = indices
                .into_iter()
                .map(|(_, index)| {
                    for i in 0..D {
                        min_vox[i] = min_vox[i].min(index[i]);
                        max_vox[i] = max_vox[i].max(index[i]);
                    }
                    index
                })
                .collect::<Vec<_>>();
            let mut min = [F::zero(); D];
            let mut max = [F::zero(); D];
            for i in 0..D {
                let n_vox_min = F::from_usize(min_vox[i]).ok_or(DecomposeError::Generic(
                    cellular_raza_concepts::format_error_message!(
                        "conversion error during domain setup",
                        format!(
                            "Cannot convert float {:?} of type {} to usize",
                            min_vox[i],
                            std::any::type_name::<F>()
                        )
                    ),
                ))?;
                let n_vox_max = F::from_usize(max_vox[i]).ok_or(DecomposeError::Generic(
                    cellular_raza_concepts::format_error_message!(
                        "conversion error during domain setup",
                        format!(
                            "Cannot convert float {:?} of type {} to usize",
                            max_vox[i],
                            std::any::type_name::<F>()
                        )
                    ),
                ))?;
                min[i] = self.min[i] + n_vox_min * self.dx[i];
                max[i] = self.min[i] + (n_vox_max + F::one()) * self.dx[i];
            }
            let subdomain = CartesianSubDomain {
                min: min.into(),
                max: max.into(),
                dx: self.dx.clone(),
                voxels: voxels.clone(),
                domain_min: self.min,
                domain_max: self.max,
                domain_n_voxels: self.n_voxels.clone(),
            };
            res.push((n_subdomain, subdomain, voxels));
        }
        Ok(res)
    }
}

impl<Coord, F, const D: usize> SubDomainMechanics<Coord, Coord> for CartesianSubDomain<F, D>
where
    Coord: Clone,
    [F; D]: From<Coord>,
    Coord: From<[F; D]>,
    Coord: std::fmt::Debug,
    F: num::Float,
{
    fn apply_boundary(&self, pos: &mut Coord, vel: &mut Coord) -> Result<(), BoundaryError> {
        let mut velocity: [F; D] = vel.clone().into();
        let mut position: [F; D] = pos.clone().into();

        // Define constant two
        let two = F::one() + F::one();

        // For each dimension
        for i in 0..D {
            // Check if the particle is below lower edge
            if position[i] < self.domain_min[i] {
                position[i] = two * self.domain_min[i] - position[i];
                velocity[i] = velocity[i].abs();
            }
            // Check if the particle is over the edge
            if position[i] > self.domain_max[i] {
                position[i] = two * self.domain_max[i] - position[i];
                velocity[i] = -velocity[i].abs();
            }
        }

        // If new position is still out of boundary return error
        for i in 0..D {
            if position[i] < self.domain_min[i] || position[i] > self.domain_max[i] {
                return Err(BoundaryError(format!(
                    "Particle is out of domain at position {:?}",
                    pos
                )));
            }
        }

        // Set the position and velocity
        *pos = position.into();
        *vel = velocity.into();
        Ok(())
    }
}

impl<F, const D: usize> SubDomain for CartesianSubDomain<F, D> {
    type VoxelIndex = [usize; D];

    fn get_all_indices(&self) -> Vec<Self::VoxelIndex> {
        self.voxels.clone()
    }

    fn get_neighbor_voxel_indices(&self, voxel_index: &Self::VoxelIndex) -> Vec<Self::VoxelIndex> {
        // Create the bounds for the following creation of all the voxel indices
        let mut bounds = [[0; 2]; D];
        for i in 0..D {
            bounds[i] = [
                (voxel_index[i] as i64 - 1).max(0) as usize,
                (voxel_index[i] + 2).min(self.domain_n_voxels[i]),
            ];
        }

        // Create voxel indices
        (0..D)
            .map(|i| (bounds[i][0]..bounds[i][1]))
            .multi_cartesian_product()
            .map(|ind_v| {
                let mut res = [0; D];
                for i in 0..D {
                    res[i] = ind_v[i];
                }
                res
            })
            .filter(|ind| ind != voxel_index)
            .collect()
    }
}

macro_rules! implement_cartesian_cuboid_domain {
    (
        $d: literal,
        $domain_name: ident,
        $subdomain_name: ident,
        $voxel_name: ident,
        $float_type: ty,
        $($k: expr),+
    ) => {
        #[derive(Clone, Debug, Deserialize, Serialize)]
        #[cfg_attr(feature = "pyo3", pyclass)]
        #[cfg_attr(feature = "pyo3", pyo3(get_all, set_all))]
        /// Cartesian cuboid in
        #[doc = concat!(" `", stringify!($d), "D`")]
        /// with float type
        #[doc = concat!(" `", stringify!($float_type), "`")]
        pub struct $domain_name {
            /// Lower boundary of domain
            pub min: [$float_type; $d],
            /// Upper boundary of domain
            pub max: [$float_type; $d],
            /// Number of voxels in domain along axes
            pub n_voxels: [i64; $d],
            /// Length of individual voxels in domain
            pub dx_voxels: [$float_type; $d],
            /// Initial seed from which to generate seeds for voxels
            pub rng_seed: u64,
        }

        impl $domain_name {
            fn check_min_max(min: [$float_type; $d], max: [$float_type; $d]) -> Result<(), CalcError> {
                for i in 0..$d {
                    match max[i] > min[i] {
                        false => Err(CalcError(format!(
                            "Min {:?} must be smaller than Max {:?} for domain boundaries!",
                            min,
                            max
                        ))),
                        true => Ok(()),
                    }?;
                }
                Ok(())
            }

            fn check_positive<F>(interaction_ranges: [F; $d]) -> Result<(), CalcError>
            where
                F: PartialOrd + num::Zero + core::fmt::Debug,
            {
                for i in 0..$d {
                    match interaction_ranges[i] > F::zero() {
                        false => Err(CalcError(format!("Interaction range must be positive and non-negative! Got value {:?}", interaction_ranges[i]))),
                        true => Ok(())
                    }?;
                }
                Ok(())
            }

            /// Construct the domain from given lower/upper boundaries and maximum
            /// length of interaction ranges along axes.
            pub fn from_boundaries_and_interaction_ranges(
                min: [$float_type; $d],
                max: [$float_type; $d],
                interaction_ranges: [$float_type; $d]
            ) -> Result<$domain_name, CalcError>
            {
                Self::check_min_max(min, max)?;
                Self::check_positive(interaction_ranges)?;
                let mut n_voxels = [0; $d];
                let mut dx_voxels = [0.0; $d];
                for i in 0..$d {
                    n_voxels[i] = ((max[i] - min[i]) / interaction_ranges[i] * 0.5).ceil() as i64;
                    dx_voxels[i] = (max[i]-min[i])/n_voxels[i] as $float_type;
                }
                Ok(Self {
                    min,
                    max,
                    n_voxels,
                    dx_voxels,
                    rng_seed: 0,
                })
            }

            /// Construct the domain from given lower/upper boundaries and
            /// number of voxels along axes.
            pub fn from_boundaries_and_n_voxels(
                min: [$float_type; $d],
                max: [$float_type; $d],
                n_vox: [usize; $d]
            ) -> Result<$domain_name, CalcError>
            {
                Self::check_min_max(min, max)?;
                Self::check_positive(n_vox)?;
                let mut dx_voxels = [0.0; $d];
                for i in 0..$d {
                    dx_voxels[i] = (max[i] - min[i]) / n_vox[i] as $float_type;
                }
                Ok(Self {
                    min,
                    max,
                    n_voxels: [$(n_vox[$k] as i64),+],
                    dx_voxels,
                    rng_seed: 0,
                })
            }

            fn get_voxel_index(
                &self,
                position: &nalgebra::SVector<$float_type, $d>,
            ) -> Result<[i64; $d], BoundaryError> {
                let mut percent: nalgebra::SVector<$float_type, $d> = self.max.into();
                percent -= nalgebra::SVector::<$float_type, $d>::from(self.min);
                percent = position.component_div(&percent);
                let vox = [$(
                    (percent[$k] * self.n_voxels[$k] as $float_type).floor() as i64,
                )+];

                // If the returned voxel is not positive and smaller than the maximum
                // number of voxel indices this function needs to return an error.
                if vox
                    .iter()
                    .enumerate()
                    .any(|(i, &p)| p<0 && self.n_voxels[i]<p) {
                        return Err(
                            BoundaryError(format!("Cell with position {:?} could not find index in domain with size min: {:?} max: {:?}", position, self.min, self.max))
                        );
                } else {
                    return Ok(vox);
                }
            }

            fn get_neighbor_voxel_indices(&self, index: &[i64; $d]) -> Vec<[i64; $d]> {
                // Create the bounds for the following creation of all the voxel indices
                let bounds: [[i64; 2]; $d] = [$(
                    [
                        max(index[$k] as i32 - 1, 0) as i64,
                        min(index[$k]+2, self.n_voxels[$k])
                    ]
                ),+];

                // Create voxel indices
                let v: Vec<[i64; $d]> = [$($k),+].iter()      // indices supplied in macro invocation
                    .map(|i| (bounds[*i][0]..bounds[*i][1]))    // ranges from bounds
                    .multi_cartesian_product()                  // all possible combinations
                    .map(|ind_v| [$(ind_v[$k]),+])              // multi_cartesian_product gives us vector elements. We map them to arrays.
                    .filter(|ind| ind!=index)                   // filter the elements such that the current index is not included.
                    .collect();                                 // collect into the correct type

                return v;
            }

            fn get_all_voxel_indices(&self) -> Vec<[i64; $d]> {
                [$($k),+]
                    .iter()                                     // indices supplied in macro invocation
                    .map(|i| (0..self.n_voxels[*i]))            // ranges from self.n_vox
                    .multi_cartesian_product()                  // all possible combinations
                    .map(|ind_v| [$(ind_v[$k]),+])              // multi_cartesian_product gives us vector elements. We map them to arrays.
                    .collect()
            }

        }

        #[doc ="Subdomain of ["]
        #[doc = stringify!($domain_name)]
        #[doc = "]"]
        ///
        /// The subdomain contains voxels
        #[derive(Clone, Debug, Deserialize, Serialize)]
        #[cfg_attr(feature = "pyo3", pyclass)]
        #[cfg_attr(feature = "pyo3", pyo3(get_all, set_all))]
        pub struct $subdomain_name {
            /// All voxels contained in this subdomain
            pub voxels: Vec<$voxel_name>,
            domain_min: [$float_type; $d],
            domain_max: [$float_type; $d],
            domain_n_voxels: [i64; $d],
            domain_voxel_sizes: [$float_type; $d],
        }

        #[derive(Clone, Debug, Deserialize, Serialize)]
        #[cfg_attr(feature = "pyo3", pyclass)]
        #[cfg_attr(feature = "pyo3", pyo3(get_all, set_all))]
        /// Voxel of the [
        #[doc = stringify!($subdomain_name)]
        /// ]
        pub struct $voxel_name {
            /// Lower boundary of the voxel
            pub min: [$float_type; $d],
            /// Upper boundary of the voxel
            pub max: [$float_type; $d],
            /// Index of the voxel
            pub ind: [i64; $d],
        }

        impl<C, I: IntoIterator<Item=C>> Domain<C, $subdomain_name, I> for $domain_name
        where
            // C: cellular_raza_concepts::Mechanics<nalgebra::SVector<$float_type, $d>, nalgebra::SVector<$float_type, $d>, nalgebra::SVector<$float_type, $d>, $float_type>,
            C: Position<SVector<$float_type, $d>>,
        {
            // TODO THINK VERY HARD ABOUT THESE TYPES! THEY MIGHT BE CHOSEN STUPIDLY!
            type SubDomainIndex = usize;
            type VoxelIndex = [i64; $d];

            /// Much more research must be done to effectively write this function.
            /// We should be using more sophisticated functionality based on common known facts for
            /// minimizing surface area and number of neighbors.
            /// For more information also see
            /// - [Wikipedia](https://en.wikipedia.org/wiki/Plateau%27s_laws)
            /// - [Math StackExchange](https://math.stackexchange.com/questions/3488409/dividing-a-square-into-n-equal-size-parts-with-minimal-fence)
            fn decompose(
                self,
                n_subdomains: core::num::NonZeroUsize,
                cells: I,
            ) -> Result<DecomposedDomain<
                Self::SubDomainIndex,
                $subdomain_name,
                C
            >, DecomposeError> {
                let mut indices = self.get_all_voxel_indices();

                let (n, m, average_len);
                match get_decomp_res(indices.len(), n_subdomains.into()) {
                    Some(res) => (n, m, average_len) = res,
                    None => return Err(
                        DecomposeError::Generic("Could not find a suiting decomposition".to_owned())
                    ),
                };

                // TODO optimize this!
                // Currently we are not splitting the voxels apart efficiently
                // These are subdomains which contain n voxels
                let mut ind_n: Vec<Vec<_>> = indices
                    .drain(0..(average_len*n) as usize)
                    .into_iter()
                    .chunks(average_len as usize)
                    .into_iter()
                    .map(|chunk| chunk.collect::<Vec<_>>())
                    .collect();

                // These are subdomains that contain m indices
                let mut ind_m: Vec<Vec<_>> = indices
                    .drain(..)
                    .into_iter()
                    .chunks((max(average_len-1, 1)) as usize)
                    .into_iter()
                    .map(|chunk| chunk.collect::<Vec<_>>())
                    .collect();

                // Combine them into one Vector
                ind_n.append(&mut ind_m);

                // We construct all Voxels which are grouped in their according subdomains
                // Then we construct the subdomain
                let mut index_subdomain_cells: std::collections::BTreeMap<
                    Self::SubDomainIndex,
                    (_, Vec<C>)
                > = ind_n
                    .clone()
                    .into_iter()
                    .enumerate()
                    .map(|(i, indices)| {
                        let voxels = indices
                            .into_iter()
                            .map(|ind| {
                                let min = [$(
                                    self.min[$k] + ind[$k] as $float_type*self.dx_voxels[$k]
                                ),+];
                                let max = [$(
                                    self.min[$k] + (1+ind[$k]) as $float_type*self.dx_voxels[$k]
                                ),+];

                                $voxel_name {
                                    min,
                                    max,
                                    ind,
                                }
                            }).collect::<Vec<_>>();
                            (i as Self::SubDomainIndex, ($subdomain_name {
                                voxels,
                                domain_min: self.min,
                                domain_max: self.max,
                                domain_n_voxels: self.n_voxels,
                                domain_voxel_sizes: self.dx_voxels,
                            }, Vec::<C>::new()))
                        }
                    ).collect();

                // Construct a map from voxel_index to subdomain_index
                let voxel_index_to_subdomain_index = ind_n
                    .clone()
                    .into_iter()
                    .enumerate()
                    .map(|(subdomain_index, voxel_indices)| voxel_indices
                        .into_iter()
                        .map(move |voxel_index| (voxel_index, subdomain_index))
                    )
                    .flatten()
                    .collect::<std::collections::BTreeMap<Self::VoxelIndex, Self::SubDomainIndex>>();

                // Sort the cells into the correct voxels
                cells
                    .into_iter()
                    .map(|cell| {
                        // Get the voxel index of the cell
                        let voxel_index = self.get_voxel_index(&cell.pos())?;
                        // Now get the subdomain index of the voxel
                        let subdomain_index = voxel_index_to_subdomain_index.get(&voxel_index).ok_or(
                            DecomposeError::IndexError(IndexError(
                                format!(
                                    "Could not cell with position {:?} in domain {:?}",
                                    cell.pos(),
                                    self
                                )
                            ))
                        )?;
                        // Then add the cell to the subdomains cells.
                        index_subdomain_cells.get_mut(&subdomain_index).ok_or(
                            DecomposeError::IndexError(IndexError(
                                format!(
                                    "Could not find subdomain index {:?} internally which should\
                                    have been there.",
                                    subdomain_index
                                )
                            ))
                        )?.1.push(cell);
                        Ok(())

                    }).collect::<Result<Vec<_>, DecomposeError>>()?;

                //
                let index_subdomain_cells: Vec<(Self::SubDomainIndex, _, _)> = index_subdomain_cells
                    .into_iter()
                    .map(|(index, (subdomain, cells))| (index, subdomain, cells))
                    .collect();

                let neighbor_map = ind_n
                    .into_iter()
                    .enumerate()
                    .map(|(subdomain_index, voxel_indices)| {
                        let neighbor_voxels = voxel_indices
                            .into_iter()
                            .map(|voxel_index| self.get_neighbor_voxel_indices(&voxel_index))
                            .flatten();
                        let neighbor_subdomains = neighbor_voxels
                            .map(|neighbor_voxel_index| voxel_index_to_subdomain_index
                                .get(&neighbor_voxel_index)
                                .and_then(|v| Some(v.clone()))
                                .ok_or(
                                    DecomposeError::IndexError(IndexError(format!(
                                        "Could not find neighboring voxel index {:?} internally\
                                        which should have been initialized.",
                                        neighbor_voxel_index))
                                )
                            ))
                            .collect::<Result<std::collections::BTreeSet<usize>, _>>()?;
                            /* .and_then(|neighbors| Ok(neighbors
                                .into_iter()
                                .unique()
                                .filter(|neighbor_index| *neighbor_index!=subdomain_index)
                                .collect::<std::collections::BTreeSet<_>>()))?;*/
                        Ok((subdomain_index, neighbor_subdomains))
                    })
                    .collect::<Result<_, DecomposeError>>()?;

                Ok(DecomposedDomain {
                    n_subdomains: (n+m).try_into().unwrap_or(1.try_into().unwrap()),
                    index_subdomain_cells,
                    neighbor_map,
                    rng_seed: self.rng_seed.clone(),
                })
            }
        }

        impl SubDomain for $subdomain_name
        // where
        //     C: cellular_raza_concepts::Mechanics<SVector<$float_type, $d>, SVector<$float_type, $d>, SVector<$float_type, $d>, $float_type>,
        {
            type VoxelIndex = [i64; $d];


            fn get_neighbor_voxel_indices(&self, index: &Self::VoxelIndex) -> Vec<Self::VoxelIndex> {
                // Create the bounds for the following creation of all the voxel indices
                let bounds: [[i64; 2]; $d] = [$(
                    [
                        max(index[$k] as i32 - 1, 0) as i64,
                        min(index[$k]+2, self.domain_n_voxels[$k])
                    ]
                ),+];

                // Create voxel indices
                let v: Vec<[i64; $d]> = [$($k),+].iter()      // indices supplied in macro invocation
                    .map(|i| (bounds[*i][0]..bounds[*i][1]))    // ranges from bounds
                    .multi_cartesian_product()                  // all possible combinations
                    .map(|ind_v| [$(ind_v[$k]),+])              // multi_cartesian_product gives us vector elements. We map them to arrays.
                    .filter(|ind| ind!=index)                   // filter the elements such that the current index is not included.
                    .collect();                                 // collect into the correct type

                return v;
            }

            fn get_all_indices(&self) -> Vec<Self::VoxelIndex> {
                self.voxels.iter().map(|vox| vox.ind.clone()).collect()
            }
        }

        impl<C> SortCells<C> for $subdomain_name
        where
            C: Position<SVector<$float_type, $d>>,
        {
            type VoxelIndex = [i64; $d];

            fn get_voxel_index_of(&self, cell: &C) -> Result<Self::VoxelIndex, BoundaryError> {
                let pos = cell.pos();
                let mut out = [0; $d];

                for i in 0..$d {
                    out[i] = ((pos[i] - self.domain_min[0]) / self.domain_voxel_sizes[i]) as i64;
                    out[i] = out[i].min(self.domain_n_voxels[i]-1).max(0);
                }
                Ok(out)
            }
        }

        impl SubDomainMechanics<
            SVector<$float_type, $d>,
            SVector<$float_type, $d>,
        > for $subdomain_name {
            fn apply_boundary(
                &self,
                pos: &mut SVector<$float_type, $d>,
                velocity: &mut SVector<$float_type, $d>
            ) -> Result<(), BoundaryError> {
                // For each dimension
                for i in 0..$d {
                    // Check if the particle is below lower edge
                    if pos[i] < self.domain_min[i] {
                        pos[i] = 2.0 * self.domain_min[i] - pos[i];
                        velocity[i] = velocity[i].abs();
                    }
                    // Check if the particle is over the edge
                    if pos[i] > self.domain_max[i] {
                        pos[i] = 2.0 * self.domain_max[i] - pos[i];
                        velocity[i] = - velocity[i].abs();
                    }
                }

                // If new position is still out of boundary return error
                for i in 0..$d {
                    if pos[i] < self.domain_min[i] || pos[i] > self.domain_max[i] {
                        return Err(BoundaryError(
                                format!("Particle is out of domain at position {:?}", pos)
                        ));
                    }
                }
                Ok(())
            }
        }
    }
}

implement_cartesian_cuboid_domain!(
    1,
    CartesianCuboid1New,
    CartesianSubDomain1,
    CartesianVoxel1,
    f64,
    0
);
implement_cartesian_cuboid_domain!(
    2,
    CartesianCuboid2New,
    CartesianSubDomain2,
    CartesianVoxel2,
    f64,
    0,
    1
);
implement_cartesian_cuboid_domain!(
    3,
    CartesianCuboid3New,
    CartesianSubDomain3,
    CartesianVoxel3,
    f64,
    0,
    1,
    2
);

implement_cartesian_cuboid_domain!(
    1,
    CartesianCuboid1NewF32,
    CartesianSubDomain1F32,
    CartesianVoxel1F32,
    f32,
    0
);
implement_cartesian_cuboid_domain!(
    2,
    CartesianCuboid2NewF32,
    CartesianSubDomain2F32,
    CartesianVoxel2F32,
    f32,
    0,
    1
);
implement_cartesian_cuboid_domain!(
    3,
    CartesianCuboid3NewF32,
    CartesianSubDomain3F32,
    CartesianVoxel3F32,
    f32,
    0,
    1,
    2
);

#[cfg(test)]
mod test {
    use super::get_decomp_res;
    use rayon::prelude::*;

    #[test]
    fn test_get_demomp_res() {
        #[cfg(debug_assertions)]
        let max = 500;
        #[cfg(not(debug_assertions))]
        let max = 5_000;

        (1..max)
            .into_par_iter()
            .map(|n_voxel| {
                #[cfg(debug_assertions)]
                let max_regions = 100;
                #[cfg(not(debug_assertions))]
                let max_regions = 1_000;
                for n_regions in 1..max_regions {
                    match get_decomp_res(n_voxel, n_regions) {
                        Some(res) => {
                            let (n, m, average_len) = res;
                            assert_eq!(n + m, n_regions);
                            assert_eq!(n * average_len + m * (average_len - 1), n_voxel);
                        }
                        None => panic!(
                            "No result for inputs n_voxel: {} n_regions: {}",
                            n_voxel, n_regions
                        ),
                    }
                }
            })
            .collect::<Vec<()>>();
    }
}