#[cfg(test)]
use crate::math::test::ErrorTensor;
use crate::math::{write_tensor_rank_0, Tensor, TensorRank0, TensorVec};
use std::{
fmt::{Display, Formatter, Result},
ops::{Add, AddAssign, Div, DivAssign, Index, IndexMut, Mul, MulAssign, Sub, SubAssign},
};
#[derive(Debug)]
pub struct Vector(Vec<TensorRank0>);
#[cfg(test)]
impl ErrorTensor for Vector {
fn error(
&self,
comparator: &Self,
tol_abs: &TensorRank0,
tol_rel: &TensorRank0,
) -> Option<usize> {
let error_count = self
.iter()
.zip(comparator.iter())
.map(|(entry, comparator_entry)| {
entry
.iter()
.zip(comparator_entry.iter())
.filter(|(&entry_i, &comparator_entry_i)| {
&(entry_i - comparator_entry_i).abs() >= tol_abs
&& &(entry_i / comparator_entry_i - 1.0).abs() >= tol_rel
})
.count()
})
.sum();
if error_count > 0 {
Some(error_count)
} else {
None
}
}
fn error_fd(&self, comparator: &Self, epsilon: &TensorRank0) -> Option<(bool, usize)> {
let error_count = self
.iter()
.zip(comparator.iter())
.map(|(entry, comparator_entry)| {
entry
.iter()
.zip(comparator_entry.iter())
.filter(|(&entry_i, &comparator_entry_i)| {
&(entry_i / comparator_entry_i - 1.0).abs() >= epsilon
&& (&entry_i.abs() >= epsilon || &comparator_entry_i.abs() >= epsilon)
})
.count()
})
.sum();
if error_count > 0 {
let auxillary = self
.iter()
.zip(comparator.iter())
.map(|(entry, comparator_entry)| {
entry
.iter()
.zip(comparator_entry.iter())
.filter(|(&entry_i, &comparator_entry_i)| {
&(entry_i / comparator_entry_i - 1.0).abs() >= epsilon
&& &(entry_i - comparator_entry_i).abs() >= epsilon
&& (&entry_i.abs() >= epsilon
|| &comparator_entry_i.abs() >= epsilon)
})
.count()
})
.sum::<usize>()
> 0;
Some((auxillary, error_count))
} else {
None
}
}
}
impl Display for Vector {
fn fmt(&self, f: &mut Formatter) -> Result {
write!(f, "\x1B[s")?;
write!(f, "[")?;
self.0.chunks(5).enumerate().try_for_each(|(i, chunk)| {
chunk
.iter()
.try_for_each(|entry| write_tensor_rank_0(f, entry))?;
if (i + 1) * 5 < self.len() {
writeln!(f, "\x1B[2D,")?;
write!(f, "\x1B[u")?;
write!(f, "\x1B[{}B ", i + 1)?;
}
Ok(())
})?;
write!(f, "\x1B[2D]")?;
Ok(())
}
}
impl PartialEq for Vector {
fn eq(&self, other: &Self) -> bool {
self.0 == other.0
}
}
impl FromIterator<TensorRank0> for Vector {
fn from_iter<Ii: IntoIterator<Item = TensorRank0>>(into_iterator: Ii) -> Self {
Self(Vec::from_iter(into_iterator))
}
}
impl Index<usize> for Vector {
type Output = TensorRank0;
fn index(&self, index: usize) -> &Self::Output {
&self.0[index]
}
}
impl IndexMut<usize> for Vector {
fn index_mut(&mut self, index: usize) -> &mut Self::Output {
&mut self.0[index]
}
}
impl Tensor for Vector {
type Item = TensorRank0;
fn copy(&self) -> Self {
self.iter().map(|entry| entry.copy()).collect()
}
fn iter(&self) -> impl Iterator<Item = &Self::Item> {
self.0.iter()
}
fn iter_mut(&mut self) -> impl Iterator<Item = &mut Self::Item> {
self.0.iter_mut()
}
}
impl<'a> TensorVec<'a> for Vector {
type Item = TensorRank0;
type Slice = &'a [TensorRank0];
fn is_empty(&self) -> bool {
self.0.is_empty()
}
fn len(&self) -> usize {
self.0.len()
}
fn new(slice: Self::Slice) -> Self {
slice.iter().copied().collect()
}
fn zero(len: usize) -> Self {
Self(vec![0.0; len])
}
}
impl Div<TensorRank0> for Vector {
type Output = Self;
fn div(mut self, tensor_rank_0: TensorRank0) -> Self::Output {
self /= &tensor_rank_0;
self
}
}
impl Div<&TensorRank0> for Vector {
type Output = Self;
fn div(mut self, tensor_rank_0: &TensorRank0) -> Self::Output {
self /= tensor_rank_0;
self
}
}
impl DivAssign<TensorRank0> for Vector {
fn div_assign(&mut self, tensor_rank_0: TensorRank0) {
self.iter_mut().for_each(|entry| *entry /= &tensor_rank_0);
}
}
impl DivAssign<&TensorRank0> for Vector {
fn div_assign(&mut self, tensor_rank_0: &TensorRank0) {
self.iter_mut().for_each(|entry| *entry /= tensor_rank_0);
}
}
impl Mul<TensorRank0> for Vector {
type Output = Self;
fn mul(mut self, tensor_rank_0: TensorRank0) -> Self::Output {
self *= &tensor_rank_0;
self
}
}
impl Mul<&TensorRank0> for Vector {
type Output = Self;
fn mul(mut self, tensor_rank_0: &TensorRank0) -> Self::Output {
self *= tensor_rank_0;
self
}
}
impl Mul<&TensorRank0> for &Vector {
type Output = Vector;
fn mul(self, tensor_rank_0: &TensorRank0) -> Self::Output {
self.iter().map(|self_i| self_i * tensor_rank_0).collect()
}
}
impl MulAssign<TensorRank0> for Vector {
fn mul_assign(&mut self, tensor_rank_0: TensorRank0) {
self.iter_mut().for_each(|entry| *entry *= &tensor_rank_0);
}
}
impl MulAssign<&TensorRank0> for Vector {
fn mul_assign(&mut self, tensor_rank_0: &TensorRank0) {
self.iter_mut().for_each(|entry| *entry *= tensor_rank_0);
}
}
impl Add for Vector {
type Output = Self;
fn add(mut self, vector: Self) -> Self::Output {
self += vector;
self
}
}
impl Add<&Self> for Vector {
type Output = Self;
fn add(mut self, vector: &Self) -> Self::Output {
self += vector;
self
}
}
impl AddAssign for Vector {
fn add_assign(&mut self, vector: Self) {
self.iter_mut()
.zip(vector.iter())
.for_each(|(self_entry, tensor_rank_1)| *self_entry += tensor_rank_1);
}
}
impl AddAssign<&Self> for Vector {
fn add_assign(&mut self, vector: &Self) {
self.iter_mut()
.zip(vector.iter())
.for_each(|(self_entry, tensor_rank_1)| *self_entry += tensor_rank_1);
}
}
impl Sub for Vector {
type Output = Self;
fn sub(mut self, vector: Self) -> Self::Output {
self -= vector;
self
}
}
impl Sub<&Self> for Vector {
type Output = Self;
fn sub(mut self, vector: &Self) -> Self::Output {
self -= vector;
self
}
}
impl SubAssign for Vector {
fn sub_assign(&mut self, vector: Self) {
self.iter_mut()
.zip(vector.iter())
.for_each(|(self_entry, tensor_rank_1)| *self_entry -= tensor_rank_1);
}
}
impl SubAssign<&Self> for Vector {
fn sub_assign(&mut self, vector: &Self) {
self.iter_mut()
.zip(vector.iter())
.for_each(|(self_entry, tensor_rank_1)| *self_entry -= tensor_rank_1);
}
}