polars_core/chunked_array/ops/rolling_window.rs
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use arrow::legacy::prelude::RollingFnParams;
#[cfg(feature = "serde")]
use serde::{Deserialize, Serialize};
#[derive(Clone, Debug)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
#[cfg_attr(feature = "rolling_window", derive(PartialEq))]
pub struct RollingOptionsFixedWindow {
/// The length of the window.
pub window_size: usize,
/// Amount of elements in the window that should be filled before computing a result.
pub min_periods: usize,
/// An optional slice with the same length as the window that will be multiplied
/// elementwise with the values in the window.
pub weights: Option<Vec<f64>>,
/// Set the labels at the center of the window.
pub center: bool,
/// Optional parameters for the rolling
#[cfg_attr(feature = "serde", serde(default))]
pub fn_params: Option<RollingFnParams>,
}
impl Default for RollingOptionsFixedWindow {
fn default() -> Self {
RollingOptionsFixedWindow {
window_size: 3,
min_periods: 1,
weights: None,
center: false,
fn_params: None,
}
}
}
#[cfg(feature = "rolling_window")]
mod inner_mod {
use std::ops::SubAssign;
use arrow::bitmap::utils::set_bit_unchecked;
use arrow::bitmap::MutableBitmap;
use arrow::legacy::trusted_len::TrustedLenPush;
use num_traits::pow::Pow;
use num_traits::{Float, Zero};
use polars_utils::float::IsFloat;
use crate::chunked_array::cast::CastOptions;
use crate::prelude::*;
/// utility
fn check_input(window_size: usize, min_periods: usize) -> PolarsResult<()> {
polars_ensure!(
min_periods <= window_size,
ComputeError: "`window_size`: {} should be >= `min_periods`: {}",
window_size, min_periods
);
Ok(())
}
/// utility
fn window_edges(idx: usize, len: usize, window_size: usize, center: bool) -> (usize, usize) {
let (start, end) = if center {
let right_window = (window_size + 1) / 2;
(
idx.saturating_sub(window_size - right_window),
len.min(idx + right_window),
)
} else {
(idx.saturating_sub(window_size - 1), idx + 1)
};
(start, end - start)
}
impl<T> ChunkRollApply for ChunkedArray<T>
where
T: PolarsNumericType,
Self: IntoSeries,
{
/// Apply a rolling custom function. This is pretty slow because of dynamic dispatch.
fn rolling_map(
&self,
f: &dyn Fn(&Series) -> Series,
mut options: RollingOptionsFixedWindow,
) -> PolarsResult<Series> {
check_input(options.window_size, options.min_periods)?;
let ca = self.rechunk();
if options.weights.is_some()
&& !matches!(self.dtype(), DataType::Float64 | DataType::Float32)
{
let s = self.cast_with_options(&DataType::Float64, CastOptions::NonStrict)?;
return s.rolling_map(f, options);
}
options.window_size = std::cmp::min(self.len(), options.window_size);
let len = self.len();
let arr = ca.downcast_iter().next().unwrap();
let mut ca = ChunkedArray::<T>::from_slice(PlSmallStr::EMPTY, &[T::Native::zero()]);
let ptr = ca.chunks[0].as_mut() as *mut dyn Array as *mut PrimitiveArray<T::Native>;
let mut series_container = ca.into_series();
let mut builder = PrimitiveChunkedBuilder::<T>::new(self.name().clone(), self.len());
if let Some(weights) = options.weights {
let weights_series =
Float64Chunked::new(PlSmallStr::from_static("weights"), &weights).into_series();
let weights_series = weights_series.cast(self.dtype()).unwrap();
for idx in 0..len {
let (start, size) = window_edges(idx, len, options.window_size, options.center);
if size < options.min_periods {
builder.append_null();
} else {
// SAFETY:
// we are in bounds
let arr_window = unsafe { arr.slice_typed_unchecked(start, size) };
// ensure we still meet window size criteria after removing null values
if size - arr_window.null_count() < options.min_periods {
builder.append_null();
continue;
}
// SAFETY.
// ptr is not dropped as we are in scope
// We are also the only owner of the contents of the Arc
// we do this to reduce heap allocs.
unsafe {
*ptr = arr_window;
}
// reset flags as we reuse this container
series_container.clear_flags();
// ensure the length is correct
series_container._get_inner_mut().compute_len();
let s = if size == options.window_size {
f(&series_container.multiply(&weights_series).unwrap())
} else {
let weights_cutoff: Series = match self.dtype() {
DataType::Float64 => weights_series
.f64()
.unwrap()
.into_iter()
.take(series_container.len())
.collect(),
_ => weights_series // Float32 case
.f32()
.unwrap()
.into_iter()
.take(series_container.len())
.collect(),
};
f(&series_container.multiply(&weights_cutoff).unwrap())
};
let out = self.unpack_series_matching_type(&s)?;
builder.append_option(out.get(0));
}
}
Ok(builder.finish().into_series())
} else {
for idx in 0..len {
let (start, size) = window_edges(idx, len, options.window_size, options.center);
if size < options.min_periods {
builder.append_null();
} else {
// SAFETY:
// we are in bounds
let arr_window = unsafe { arr.slice_typed_unchecked(start, size) };
// ensure we still meet window size criteria after removing null values
if size - arr_window.null_count() < options.min_periods {
builder.append_null();
continue;
}
// SAFETY.
// ptr is not dropped as we are in scope
// We are also the only owner of the contents of the Arc
// we do this to reduce heap allocs.
unsafe {
*ptr = arr_window;
}
// reset flags as we reuse this container
series_container.clear_flags();
// ensure the length is correct
series_container._get_inner_mut().compute_len();
let s = f(&series_container);
let out = self.unpack_series_matching_type(&s)?;
builder.append_option(out.get(0));
}
}
Ok(builder.finish().into_series())
}
}
}
impl<T> ChunkedArray<T>
where
ChunkedArray<T>: IntoSeries,
T: PolarsFloatType,
T::Native: Float + IsFloat + SubAssign + Pow<T::Native, Output = T::Native>,
{
/// Apply a rolling custom function. This is pretty slow because of dynamic dispatch.
pub fn rolling_map_float<F>(&self, window_size: usize, mut f: F) -> PolarsResult<Self>
where
F: FnMut(&mut ChunkedArray<T>) -> Option<T::Native>,
{
if window_size > self.len() {
return Ok(Self::full_null(self.name().clone(), self.len()));
}
let ca = self.rechunk();
let arr = ca.downcast_iter().next().unwrap();
// We create a temporary dummy ChunkedArray. This will be a
// container where we swap the window contents every iteration doing
// so will save a lot of heap allocations.
let mut heap_container =
ChunkedArray::<T>::from_slice(PlSmallStr::EMPTY, &[T::Native::zero()]);
let ptr = heap_container.chunks[0].as_mut() as *mut dyn Array
as *mut PrimitiveArray<T::Native>;
let mut validity = MutableBitmap::with_capacity(ca.len());
validity.extend_constant(window_size - 1, false);
validity.extend_constant(ca.len() - (window_size - 1), true);
let validity_slice = validity.as_mut_slice();
let mut values = Vec::with_capacity(ca.len());
values.extend(std::iter::repeat(T::Native::default()).take(window_size - 1));
for offset in 0..self.len() + 1 - window_size {
debug_assert!(offset + window_size <= arr.len());
let arr_window = unsafe { arr.slice_typed_unchecked(offset, window_size) };
// The lengths are cached, so we must update them.
heap_container.length = arr_window.len();
// SAFETY: ptr is not dropped as we are in scope. We are also the only
// owner of the contents of the Arc (we do this to reduce heap allocs).
unsafe {
*ptr = arr_window;
}
let out = f(&mut heap_container);
match out {
Some(v) => {
// SAFETY: we have pre-allocated.
unsafe { values.push_unchecked(v) }
},
None => {
// SAFETY: we allocated enough for both the `values` vec
// and the `validity_ptr`.
unsafe {
values.push_unchecked(T::Native::default());
set_bit_unchecked(validity_slice, offset + window_size - 1, false);
}
},
}
}
let arr = PrimitiveArray::new(
T::get_dtype().to_arrow(CompatLevel::newest()),
values.into(),
Some(validity.into()),
);
Ok(Self::with_chunk(self.name().clone(), arr))
}
}
}