19076069272

Committed 04 Nov 2025 04:42PM UTC coverage: 61.785% (-0.2%) from 61.976%

Build # 19076069272

Build Type

push

github

Committed by

vigna

Commit Message

Fixed doctests

Run Details

5143 of 8324 relevant lines covered (61.79%)

30278823.63 hits per line

Source File
Press 'n' to go to next uncovered line, 'b' for previous

53.06

/webgraph/src/utils/mod.rs

/*
 * SPDX-FileCopyrightText: 2023 Inria
 * SPDX-FileCopyrightText: 2023 Sebastiano Vigna
 *
 * SPDX-License-Identifier: Apache-2.0 OR LGPL-2.1-or-later
 */

//! Miscellaneous utilities.

use rand::Rng;
use std::path::PathBuf;

/// Creates a new random dir inside the given folder
pub fn temp_dir<P: AsRef<std::path::Path>>(base: P) -> anyhow::Result<PathBuf> {
    let mut base = base.as_ref().to_owned();
    const ALPHABET: &[u8] = b"0123456789abcdef";
    let mut rnd = rand::rng();
    let mut random_str = String::new();
    loop {
        random_str.clear();
        for _ in 0..16 {
            let idx = rnd.random_range(0..ALPHABET.len());
            random_str.push(ALPHABET[idx] as char);
        }
        base.push(&random_str);

        if !base.exists() {
            std::fs::create_dir(&base)?;
            return Ok(base);
        }
        base.pop();
    }
}

mod circular_buffer;
pub(crate) use circular_buffer::*;

mod mmap_helper;
pub use mmap_helper::*;

mod java_perm;
pub use java_perm::*;

mod granularity;
pub use granularity::*;

pub mod sort_pairs;
pub use sort_pairs::SortPairs;

pub mod par_sort_pairs;
pub use par_sort_pairs::ParSortPairs;

pub mod par_sort_iters;
pub use par_sort_iters::ParSortIters;

use crate::graphs::{
    arc_list_graph::Iter,
    bvgraph::{Decode, Encode},
};

/// A decoder that encodes the read values using the given encoder.
/// This is commonly used to change the codes of a graph without decoding and
/// re-encoding it but by changing the codes.
pub struct Converter<D: Decode, E: Encode> {
    pub decoder: D,
    pub encoder: E,
    pub offset: usize,
}

impl<D: Decode, E: Encode> Decode for Converter<D, E> {
    // TODO: implement correctly start_node/end_node
    #[inline(always)]
    fn read_outdegree(&mut self) -> u64 {
        let res = self.decoder.read_outdegree();
        self.offset += self.encoder.write_outdegree(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_reference_offset(&mut self) -> u64 {
        let res = self.decoder.read_reference_offset();
        self.offset += self.encoder.write_reference_offset(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_block_count(&mut self) -> u64 {
        let res = self.decoder.read_block_count();
        self.offset += self.encoder.write_block_count(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_block(&mut self) -> u64 {
        let res = self.decoder.read_block();
        self.offset += self.encoder.write_block(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_interval_count(&mut self) -> u64 {
        let res = self.decoder.read_interval_count();
        self.offset += self.encoder.write_interval_count(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_interval_start(&mut self) -> u64 {
        let res = self.decoder.read_interval_start();
        self.offset += self.encoder.write_interval_start(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_interval_len(&mut self) -> u64 {
        let res = self.decoder.read_interval_len();
        self.offset += self.encoder.write_interval_len(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_first_residual(&mut self) -> u64 {
        let res = self.decoder.read_first_residual();
        self.offset += self.encoder.write_first_residual(res).unwrap();
        res
    }
    #[inline(always)]
    fn read_residual(&mut self) -> u64 {
        let res = self.decoder.read_residual();
        self.offset += self.encoder.write_residual(res).unwrap();
        res
    }
}

/// An enum expressing the memory requirements for batched algorithms
/// such as [`SortPairs`], [`ParSortPairs`], and [`ParSortIters`].
///
/// This type implements [`Mul`](core::ops::Mul) and [`Div`](core::ops::Div) to
/// scale the memory usage requirements by a given factor, independently of the
/// variant.
#[derive(Clone, Copy, Debug)]
pub enum MemoryUsage {
    /// The target overall memory usage in bytes.
    ///
    /// This is the more user-friendly option. The actual number of elements
    /// can be computed using [`batch_size`](MemoryUsage::batch_size).
    MemorySize(usize),
    /// The number of elements used in all batches.
    ///
    /// This is a more low-level option that gives more control to the user, but
    /// the actual memory usage will depend on the size of labels (if any).
    BatchSize(usize),
}

/// Default implementation, returning half of the physical RAM.
impl Default for MemoryUsage {
    fn default() -> Self {
        Self::from_perc(50.0)
    }
}

impl core::fmt::Display for MemoryUsage {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        match self {
            MemoryUsage::MemorySize(size) => write!(f, "{} bytes", size),
            MemoryUsage::BatchSize(size) => write!(f, "{} elements", size),
        }
    }
}

impl core::ops::Mul<usize> for MemoryUsage {
    type Output = MemoryUsage;

    fn mul(self, rhs: usize) -> Self::Output {
        match self {
            MemoryUsage::MemorySize(size) => MemoryUsage::MemorySize(size * rhs),
            MemoryUsage::BatchSize(size) => MemoryUsage::BatchSize(size * rhs),
        }
    }
}

impl core::ops::Div<usize> for MemoryUsage {
    type Output = MemoryUsage;

    fn div(self, rhs: usize) -> Self::Output {
        match self {
            MemoryUsage::MemorySize(size) => MemoryUsage::MemorySize(size / rhs),
            MemoryUsage::BatchSize(size) => MemoryUsage::BatchSize(size / rhs),
        }
    }
}

impl MemoryUsage {
    /// Creates a new memory usage expressed as a percentage of the
    /// physical RAM.
    pub fn from_perc(perc: f64) -> Self {
        let system = sysinfo::System::new_with_specifics(
            sysinfo::RefreshKind::nothing()
                .with_memory(sysinfo::MemoryRefreshKind::nothing().with_ram()),
        );
        MemoryUsage::MemorySize(
            usize::try_from((system.total_memory() as f64 * perc / 100.0) as u64)
                .expect("System memory overflows usize"),
        )
    }

    /// Returns the batch size for elements of type `T`.
    ///
    /// If the [memory usage is expressed as a number of
    /// bytes](MemoryUsage::MemorySize), this method divides the number of bytes
    /// by the size of `T` to obtain the number of elements. Otherwise, [it just
    /// returns specified batch size](MemoryUsage::BatchSize).
    pub fn batch_size<T>(&self) -> usize {
        match &self {
            MemoryUsage::MemorySize(memory_size) => {
                let elem_size = std::mem::size_of::<T>();
                assert!(elem_size > 0, "Element size cannot be zero");
                memory_size / elem_size
            }
            MemoryUsage::BatchSize(batch_size) => *batch_size,
        }
    }
}

/// A structure holding partition iterators and their boundaries.
///
/// This type holds a list of iterators and a list of boundaries, one more
/// than the number of iterators. The implied semantics is that each iterator
/// returns (labelled) pairs of nodes, and that the first element of
/// each pair sits between the boundaries associated with the iterator.
///
/// This structures is returned by [`ParSortPairs`] and [`ParSortIters`] and can
/// easily be converted into lenders for use with
/// [`BvComp::parallel_iter`](crate::graphs::bvgraph::BvComp::parallel_iter)
/// using a convenient implementation of the [`From`] trait.
///
/// Note that it sufficient to write `let lenders: Vec<_> = split_iters.into()`
/// to perform the conversion. Type inference might not work properly if the
/// call is embedded in a larger expression, in which case an explicit type
/// annotation might be necessary.
pub struct SplitIters<I> {
    pub boundaries: Box<[usize]>,
    pub iters: Box<[I]>,
}

impl<I> SplitIters<I> {
    pub fn new(boundaries: Box<[usize]>, iters: Box<[I]>) -> Self {
        Self { boundaries, iters }
    }
}

impl<I> From<(Box<[usize]>, Box<[I]>)> for SplitIters<I> {
    fn from((boundaries, iters): (Box<[usize]>, Box<[I]>)) -> Self {
        Self::new(boundaries, iters)
    }
}

/// Conversion of a [`SplitIters`] of iterators on unlabeled pairs into a
/// sequence of pairs of starting points and associated lenders.
///
/// This is useful for converting the output of sorting utilities like
/// [`ParSortPairs`] or [`ParSortIters`] into a form suitable for
/// [`BvComp::parallel_iter`](crate::graphs::bvgraph::BvComp::parallel_iter)
/// when working with unlabeled graphs.
///
/// The pairs `(src, dst)` are automatically converted to labeled form with unit
/// labels, and the resulting lenders are wrapped with
/// [`LeftIterator`](crate::labels::proj::LeftIterator) to project out just the
/// successor nodes.
///
/// Note that it sufficient to write `let lenders: Vec<_> = split_iters.into()`
/// to perform the conversion. Type inference might not work properly if the
/// call is embedded in a larger expression, in which case an explicit type
/// annotation might be necessary.
impl<
        I: Iterator<Item = (usize, usize)> + Send + Sync,
        IT: IntoIterator<Item = (usize, usize), IntoIter = I>,
    > From<SplitIters<IT>>
    for Vec<
        crate::labels::proj::LeftIterator<
            Iter<(), std::iter::Map<I, fn((usize, usize)) -> ((usize, usize), ())>>,
        >,
    >
{
    fn from(split: SplitIters<IT>) -> Self {
        Box::into_iter(split.iters)
            .enumerate()
            .map(|(i, iter)| {
                let start_node = split.boundaries[i];
                let end_node = split.boundaries[i + 1];
                let num_partition_nodes = end_node - start_node;
                // Map pairs to labeled pairs with unit labels
                let map_fn: fn((usize, usize)) -> ((usize, usize), ()) = |pair| (pair, ());
                let labeled_iter = iter.into_iter().map(map_fn);
                let lender = Iter::try_new_from(num_partition_nodes, labeled_iter, start_node)
                    .expect("Iterator should start from the expected first node");
                // Wrap with LeftIterator to project out just the successor
                crate::labels::proj::LeftIterator(lender)
            })
            .collect()
    }
}

/// Conversion of a [`SplitIters`] of iterators on labelled pairs into a
/// sequences of pairs of starting points and associated lenders.
///
/// This is useful for converting the output of sorting utilities like
/// [`ParSortPairs`] or [`ParSortIters`] into a form suitable for
/// [`BvComp::parallel_iter`](crate::graphs::bvgraph::BvComp::parallel_iter).
///
/// Note that it sufficient to write `let lenders: Vec<_> = split_iters.into()`
/// to perform the conversion. Type inference might not work properly if the
/// call is embedded in a larger expression, in which case an explicit type
/// annotation might be necessary.
impl<
        L: Clone + Copy + 'static,
        I: Iterator<Item = ((usize, usize), L)> + Send + Sync,
        IT: IntoIterator<Item = ((usize, usize), L), IntoIter = I>,
    > From<SplitIters<IT>> for Vec<Iter<L, I>>
{
    fn from(split: SplitIters<IT>) -> Self {
        Box::into_iter(split.iters)
            .enumerate()
            .map(|(i, iter)| {
                let start_node = split.boundaries[i];
                let end_node = split.boundaries[i + 1];
                let num_partition_nodes = end_node - start_node;

                Iter::try_new_from(num_partition_nodes, iter.into_iter(), start_node)
                    .expect("Iterator should start from the expected first node")
            })
            .collect()
    }
}

1	/*
2	* SPDX-FileCopyrightText: 2023 Inria
3	* SPDX-FileCopyrightText: 2023 Sebastiano Vigna
4	*
5	* SPDX-License-Identifier: Apache-2.0 OR LGPL-2.1-or-later
6	*/
7
8	//! Miscellaneous utilities.
9
10	use rand::Rng;
11	use std::path::PathBuf;
12
13	/// Creates a new random dir inside the given folder
14	pub fn temp_dir<P: AsRef<std::path::Path>>(base: P) -> anyhow::Result<PathBuf> {	9✔
15	let mut base = base.as_ref().to_owned();	27✔
16	const ALPHABET: &[u8] = b"0123456789abcdef";
17	let mut rnd = rand::rng();	18✔
18	let mut random_str = String::new();	18✔
19	loop {	×
20	random_str.clear();	18✔
21	for _ in 0..16 {	297✔
22	let idx = rnd.random_range(0..ALPHABET.len());	720✔
23	random_str.push(ALPHABET[idx] as char);	432✔
24	}
25	base.push(&random_str);	27✔
26
27	if !base.exists() {	9✔
28	std::fs::create_dir(&base)?;	18✔
29	return Ok(base);	9✔
30	}
31	base.pop();	×
32	}
33	}
34
35	mod circular_buffer;
36	pub(crate) use circular_buffer::*;
37
38	mod mmap_helper;
39	pub use mmap_helper::*;
40
41	mod java_perm;
42	pub use java_perm::*;
43
44	mod granularity;
45	pub use granularity::*;
46
47	pub mod sort_pairs;
48	pub use sort_pairs::SortPairs;
49
50	pub mod par_sort_pairs;
51	pub use par_sort_pairs::ParSortPairs;
52
53	pub mod par_sort_iters;
54	pub use par_sort_iters::ParSortIters;
55
56	use crate::graphs::{
57	arc_list_graph::Iter,
58	bvgraph::{Decode, Encode},
59	};
60
61	/// A decoder that encodes the read values using the given encoder.
62	/// This is commonly used to change the codes of a graph without decoding and
63	/// re-encoding it but by changing the codes.
64	pub struct Converter<D: Decode, E: Encode> {
65	pub decoder: D,
66	pub encoder: E,
67	pub offset: usize,
68	}
69
70	impl<D: Decode, E: Encode> Decode for Converter<D, E> {
71	// TODO: implement correctly start_node/end_node
72	#[inline(always)]
73	fn read_outdegree(&mut self) -> u64 {	×
74	let res = self.decoder.read_outdegree();	×
75	self.offset += self.encoder.write_outdegree(res).unwrap();	×
76	res	×
77	}
78	#[inline(always)]
79	fn read_reference_offset(&mut self) -> u64 {	×
80	let res = self.decoder.read_reference_offset();	×
81	self.offset += self.encoder.write_reference_offset(res).unwrap();	×
82	res	×
83	}
84	#[inline(always)]
85	fn read_block_count(&mut self) -> u64 {	×
86	let res = self.decoder.read_block_count();	×
87	self.offset += self.encoder.write_block_count(res).unwrap();	×
88	res	×
89	}
90	#[inline(always)]
91	fn read_block(&mut self) -> u64 {	×
92	let res = self.decoder.read_block();	×
93	self.offset += self.encoder.write_block(res).unwrap();	×
94	res	×
95	}
96	#[inline(always)]
97	fn read_interval_count(&mut self) -> u64 {	×
98	let res = self.decoder.read_interval_count();	×
99	self.offset += self.encoder.write_interval_count(res).unwrap();	×
100	res	×
101	}
102	#[inline(always)]
103	fn read_interval_start(&mut self) -> u64 {	×
104	let res = self.decoder.read_interval_start();	×
105	self.offset += self.encoder.write_interval_start(res).unwrap();	×
106	res	×
107	}
108	#[inline(always)]
109	fn read_interval_len(&mut self) -> u64 {	×
110	let res = self.decoder.read_interval_len();	×
111	self.offset += self.encoder.write_interval_len(res).unwrap();	×
112	res	×
113	}
114	#[inline(always)]
115	fn read_first_residual(&mut self) -> u64 {	×
116	let res = self.decoder.read_first_residual();	×
117	self.offset += self.encoder.write_first_residual(res).unwrap();	×
118	res	×
119	}
120	#[inline(always)]
121	fn read_residual(&mut self) -> u64 {	×
122	let res = self.decoder.read_residual();	×
123	self.offset += self.encoder.write_residual(res).unwrap();	×
124	res	×
125	}
126	}
127
128	/// An enum expressing the memory requirements for batched algorithms
129	/// such as [`SortPairs`], [`ParSortPairs`], and [`ParSortIters`].
130	///
131	/// This type implements [`Mul`](core::ops::Mul) and [`Div`](core::ops::Div) to
132	/// scale the memory usage requirements by a given factor, independently of the
133	/// variant.
134	#[derive(Clone, Copy, Debug)]
135	pub enum MemoryUsage {
136	/// The target overall memory usage in bytes.
137	///
138	/// This is the more user-friendly option. The actual number of elements
139	/// can be computed using [`batch_size`](MemoryUsage::batch_size).
140	MemorySize(usize),
141	/// The number of elements used in all batches.
142	///
143	/// This is a more low-level option that gives more control to the user, but
144	/// the actual memory usage will depend on the size of labels (if any).
145	BatchSize(usize),
146	}
147
148	/// Default implementation, returning half of the physical RAM.
149	impl Default for MemoryUsage {
150	fn default() -> Self {	16✔
151	Self::from_perc(50.0)	16✔
152	}
153	}
154
155	impl core::fmt::Display for MemoryUsage {
156	fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {	4✔
157	match self {	4✔
158	MemoryUsage::MemorySize(size) => write!(f, "{} bytes", size),	16✔
159	MemoryUsage::BatchSize(size) => write!(f, "{} elements", size),	×
160	}
161	}
162	}
163
164	impl core::ops::Mul<usize> for MemoryUsage {
165	type Output = MemoryUsage;
166
167	fn mul(self, rhs: usize) -> Self::Output {	×
168	match self {	×
169	MemoryUsage::MemorySize(size) => MemoryUsage::MemorySize(size * rhs),	×
170	MemoryUsage::BatchSize(size) => MemoryUsage::BatchSize(size * rhs),	×
171	}
172	}
173	}
174
175	impl core::ops::Div<usize> for MemoryUsage {
176	type Output = MemoryUsage;
177
178	fn div(self, rhs: usize) -> Self::Output {	16✔
179	match self {	16✔
180	MemoryUsage::MemorySize(size) => MemoryUsage::MemorySize(size / rhs),	32✔
181	MemoryUsage::BatchSize(size) => MemoryUsage::BatchSize(size / rhs),	×
182	}
183	}
184	}
185
186	impl MemoryUsage {
187	/// Creates a new memory usage expressed as a percentage of the
188	/// physical RAM.
189	pub fn from_perc(perc: f64) -> Self {	24✔
190	let system = sysinfo::System::new_with_specifics(
191	sysinfo::RefreshKind::nothing()	24✔
192	.with_memory(sysinfo::MemoryRefreshKind::nothing().with_ram()),	72✔
193	);
194	MemoryUsage::MemorySize(
195	usize::try_from((system.total_memory() as f64 * perc / 100.0) as u64)	72✔
196	.expect("System memory overflows usize"),	24✔
197	)
198	}
199
200	/// Returns the batch size for elements of type `T`.
201	///
202	/// If the [memory usage is expressed as a number of
203	/// bytes](MemoryUsage::MemorySize), this method divides the number of bytes
204	/// by the size of `T` to obtain the number of elements. Otherwise, [it just
205	/// returns specified batch size](MemoryUsage::BatchSize).
206	pub fn batch_size<T>(&self) -> usize {	135✔
207	match &self {	135✔
208	MemoryUsage::MemorySize(memory_size) => {	35✔
209	let elem_size = std::mem::size_of::<T>();	70✔
210	assert!(elem_size > 0, "Element size cannot be zero");	70✔
211	memory_size / elem_size	35✔
212	}
213	MemoryUsage::BatchSize(batch_size) => *batch_size,	200✔
214	}
215	}
216	}
217
218	/// A structure holding partition iterators and their boundaries.
219	///
220	/// This type holds a list of iterators and a list of boundaries, one more
221	/// than the number of iterators. The implied semantics is that each iterator
222	/// returns (labelled) pairs of nodes, and that the first element of
223	/// each pair sits between the boundaries associated with the iterator.
224	///
225	/// This structures is returned by [`ParSortPairs`] and [`ParSortIters`] and can
226	/// easily be converted into lenders for use with
227	/// [`BvComp::parallel_iter`](crate::graphs::bvgraph::BvComp::parallel_iter)
228	/// using a convenient implementation of the [`From`] trait.
229	///
230	/// Note that it sufficient to write `let lenders: Vec<_> = split_iters.into()`
231	/// to perform the conversion. Type inference might not work properly if the
232	/// call is embedded in a larger expression, in which case an explicit type
233	/// annotation might be necessary.
234	pub struct SplitIters<I> {
235	pub boundaries: Box<[usize]>,
236	pub iters: Box<[I]>,
237	}
238
239	impl<I> SplitIters<I> {
240	pub fn new(boundaries: Box<[usize]>, iters: Box<[I]>) -> Self {	2✔
241	Self { boundaries, iters }
242	}
243	}
244
245	impl<I> From<(Box<[usize]>, Box<[I]>)> for SplitIters<I> {
246	fn from((boundaries, iters): (Box<[usize]>, Box<[I]>)) -> Self {	×
247	Self::new(boundaries, iters)	×
248	}
249	}
250
251	/// Conversion of a [`SplitIters`] of iterators on unlabeled pairs into a
252	/// sequence of pairs of starting points and associated lenders.
253	///
254	/// This is useful for converting the output of sorting utilities like
255	/// [`ParSortPairs`] or [`ParSortIters`] into a form suitable for
256	/// [`BvComp::parallel_iter`](crate::graphs::bvgraph::BvComp::parallel_iter)
257	/// when working with unlabeled graphs.
258	///
259	/// The pairs `(src, dst)` are automatically converted to labeled form with unit
260	/// labels, and the resulting lenders are wrapped with
261	/// [`LeftIterator`](crate::labels::proj::LeftIterator) to project out just the
262	/// successor nodes.
263	///
264	/// Note that it sufficient to write `let lenders: Vec<_> = split_iters.into()`
265	/// to perform the conversion. Type inference might not work properly if the
266	/// call is embedded in a larger expression, in which case an explicit type
267	/// annotation might be necessary.
268	impl<
269	I: Iterator<Item = (usize, usize)> + Send + Sync,
270	IT: IntoIterator<Item = (usize, usize), IntoIter = I>,
271	> From<SplitIters<IT>>
272	for Vec<
273	crate::labels::proj::LeftIterator<
274	Iter<(), std::iter::Map<I, fn((usize, usize)) -> ((usize, usize), ())>>,
275	>,
276	>
277	{
278	fn from(split: SplitIters<IT>) -> Self {	1✔
279	Box::into_iter(split.iters)	2✔
280	.enumerate()
281	.map(\|(i, iter)\| {	5✔
282	let start_node = split.boundaries[i];	8✔
283	let end_node = split.boundaries[i + 1];	8✔
284	let num_partition_nodes = end_node - start_node;	8✔
285	// Map pairs to labeled pairs with unit labels
286	let map_fn: fn((usize, usize)) -> ((usize, usize), ()) = \|pair\| (pair, ());	20✔
287	let labeled_iter = iter.into_iter().map(map_fn);	20✔
288	let lender = Iter::try_new_from(num_partition_nodes, labeled_iter, start_node)	20✔
289	.expect("Iterator should start from the expected first node");	8✔
290	// Wrap with LeftIterator to project out just the successor
291	crate::labels::proj::LeftIterator(lender)	4✔
292	})
293	.collect()
294	}
295	}
296
297	/// Conversion of a [`SplitIters`] of iterators on labelled pairs into a
298	/// sequences of pairs of starting points and associated lenders.
299	///
300	/// This is useful for converting the output of sorting utilities like
301	/// [`ParSortPairs`] or [`ParSortIters`] into a form suitable for
302	/// [`BvComp::parallel_iter`](crate::graphs::bvgraph::BvComp::parallel_iter).
303	///
304	/// Note that it sufficient to write `let lenders: Vec<_> = split_iters.into()`
305	/// to perform the conversion. Type inference might not work properly if the
306	/// call is embedded in a larger expression, in which case an explicit type
307	/// annotation might be necessary.
308	impl<
309	L: Clone + Copy + 'static,
310	I: Iterator<Item = ((usize, usize), L)> + Send + Sync,
311	IT: IntoIterator<Item = ((usize, usize), L), IntoIter = I>,
312	> From<SplitIters<IT>> for Vec<Iter<L, I>>
313	{
314	fn from(split: SplitIters<IT>) -> Self {	1✔
315	Box::into_iter(split.iters)	2✔
316	.enumerate()
317	.map(\|(i, iter)\| {	4✔
318	let start_node = split.boundaries[i];	6✔
319	let end_node = split.boundaries[i + 1];	6✔
320	let num_partition_nodes = end_node - start_node;	6✔
321
322	Iter::try_new_from(num_partition_nodes, iter.into_iter(), start_node)	15✔
323	.expect("Iterator should start from the expected first node")	6✔
324	})
325	.collect()
326	}
327	}

vigna / webgraph-rs / 19076069272

Source File Press 'n' to go to next uncovered line, 'b' for previous

Source File
Press 'n' to go to next uncovered line, 'b' for previous