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use multicore_support::{Chunk, Complexity};
use super::definitions::{
DataVector,
VecResult,
ErrorReason,
ScalarResult,
Statistics,
Scale,
Offset,
GenericVectorOperations,
RealVectorOperations};
use super::GenericDataVector;
use super::stats_impl::Stats;
use simd_extensions::{Simd, Reg32, Reg64};
macro_rules! add_real_impl {
($($data_type:ident, $reg:ident);*)
=>
{
$(
impl RealVectorOperations<$data_type> for GenericDataVector<$data_type>
{
type ComplexPartner = Self;
fn real_offset(self, offset: $data_type) -> VecResult<Self>
{
assert_real!(self);
self.simd_real_operation(|x, y| x.add_real(y), |x, y| x + y, offset, Complexity::Small)
}
fn real_scale(self, factor: $data_type) -> VecResult<Self>
{
self.simd_real_operation(|x, y| x.scale_real(y), |x, y| x * y, factor, Complexity::Small)
}
fn abs(self) -> VecResult<Self>
{
assert_real!(self);
self.simd_real_operation(|x, _arg| (x * x).sqrt(), |x, _arg| x.abs(), (), Complexity::Small)
}
fn to_complex(self) -> VecResult<Self>
{
assert_real!(self);
let result = self.zero_interleave(2);
match result {
Ok(mut vec) => {
vec.is_complex = true;
Ok(vec)
},
Err((r, mut vec)) => {
vec.is_complex = true;
Err((r, vec))
}
}
}
fn wrap(self, divisor: $data_type) -> VecResult<Self>
{
assert_real!(self);
self.pure_real_operation(|x, y| x % y, divisor, Complexity::Small)
}
fn unwrap(mut self, divisor: $data_type) -> VecResult<Self>
{
{
assert_real!(self);
let data_length = self.len();
let mut data = &mut self.data;
let mut i = 0;
let mut j = 1;
let half = divisor / 2.0;
while j < data_length {
let mut diff = data[j] - data[i];
if diff > half {
diff = diff % divisor;
diff -= divisor;
data[j] = data[i] + diff;
}
else if diff < -half {
diff = diff % divisor;
diff += divisor;
data[j] = data[i] + diff;
}
i += 1;
j += 1;
}
}
Ok(self)
}
fn real_dot_product(&self, factor: &Self) -> ScalarResult<$data_type>
{
if self.is_complex {
return Err(ErrorReason::VectorMustBeReal);
}
let data_length = self.len();
let scalar_length = data_length % $reg::len();
let vectorization_length = data_length - scalar_length;
let array = &self.data;
let other = &factor.data;
let chunks = Chunk::get_a_fold_b(
Complexity::Small, &self.multicore_settings,
&other, vectorization_length, $reg::len(),
&array, vectorization_length, $reg::len(),
|original, range, target| {
let mut i = 0;
let mut j = range.start;
let mut result = $reg::splat(0.0);
while i < target.len()
{
let vector1 = $reg::load(original, j);
let vector2 = $reg::load(target, i);
result = result + (vector2 * vector1);
i += $reg::len();
j += $reg::len();
}
result.sum_real()
});
let mut i = vectorization_length;
let mut sum = 0.0;
while i < data_length
{
sum += array[i] * other[i];
i += 1;
}
let chunk_sum: $data_type = chunks.iter().fold(0.0, |a, b| a + b);
Ok(chunk_sum + sum)
}
fn real_statistics(&self) -> Statistics<$data_type> {
let data_length = self.len();
let array = &self.data;
let chunks = Chunk::get_chunked_results(
Complexity::Small, &self.multicore_settings,
&array, data_length, 1, (),
|array, range, _arg| {
let mut stats = Statistics::empty();
let mut i = 0;
let mut j = range.start;
while i < array.len()
{
stats.add(array[i], j);
i += 1;
j += 1;
}
stats
});
Statistics::merge(&chunks)
}
fn real_statistics_splitted(&self, len: usize) -> Vec<Statistics<$data_type>> {
if len == 0 {
return Vec::new();
}
let data_length = self.len();
let array = &self.data;
let chunks = Chunk::get_chunked_results(
Complexity::Small, &self.multicore_settings,
&array, data_length, 1, len,
|array, range, len| {
let mut results = Statistics::empty_vec(len);
let mut i = 0;
let mut j = range.start;
while i < array.len() {
let stats = &mut results[i % len];
stats.add(array[i], j / len);
i += 1;
j += 1;
}
results
});
Statistics::merge_cols(&chunks)
}
}
impl Scale<$data_type> for GenericDataVector<$data_type> {
fn scale(self, offset: $data_type) -> VecResult<Self> {
self.real_scale(offset)
}
}
impl Offset<$data_type> for GenericDataVector<$data_type> {
fn offset(self, offset: $data_type) -> VecResult<Self> {
self.real_offset(offset)
}
}
)*
}
}
add_real_impl!(f32, Reg32; f64, Reg64);