1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
use std::hash::{Hash, Hasher};
use polars_compute::rolling::RollingFnParams;
#[cfg(feature = "serde")]
use serde::{Deserialize, Serialize};
#[derive(Clone, Debug)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
#[cfg_attr(feature = "dsl-schema", derive(schemars::JsonSchema))]
#[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(any(feature = "serde", feature = "dsl-schema"), serde(default))]
pub fn_params: Option<RollingFnParams>,
}
impl Hash for RollingOptionsFixedWindow {
fn hash<H: Hasher>(&self, state: &mut H) {
self.window_size.hash(state);
self.min_periods.hash(state);
self.center.hash(state);
self.weights.is_some().hash(state);
}
}
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 num_traits::Zero;
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.div_ceil(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: PolarsNumericType> ChunkRollApply for ChunkedArray<T> {
/// Apply a rolling custom function. This is pretty slow because of dynamic dispatch.
fn rolling_map(
&self,
f: &dyn Fn(&Series) -> PolarsResult<Series>,
mut options: RollingOptionsFixedWindow,
) -> PolarsResult<Series> {
check_input(options.window_size, options.min_periods)?;
let ca = self.rechunk();
if options.weights.is_some() && !self.dtype().is_float() {
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_as_array();
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 {
// Determine which side to slice weights from
let weights_cutoff: Series = match self.dtype() {
DataType::Float64 => {
let ws = weights_series.f64().unwrap();
if start == 0 {
ws.slice(
(ws.len() - series_container.len()) as i64,
series_container.len(),
)
.into_series()
} else {
ws.slice(0, series_container.len()).into_series()
}
},
_ => {
let ws = weights_series.f32().unwrap();
if start == 0 {
ws.slice(
(ws.len() - series_container.len()) as i64,
series_container.len(),
)
.into_series()
} else {
ws.slice(0, series_container.len()).into_series()
}
},
};
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())
}
}
}
}