[−][src]Struct plr::OptimalPLR
Performs an optimal piecewise linear regression (PLR) in an online fashion. This approach uses linear
time for each call to process
and potentially linear space. In practice,
the space used is generally a small fraction of the data. If constant space is required for your
applications, please see GreedyPLR
.
Each call to process
consumes a single point. Each time it is called,
process
returns either a Segment
representing
a piece of the final regression, or None
. If your stream of points terminates, you can call
finish
to flush the buffer and return the final segment.
Example
use plr::OptimalPLR; // first, generate some data points... let mut data = Vec::new(); for i in 0..1000 { let x = (i as f64) / 1000.0 * 7.0; let y = f64::sin(x); data.push((x, y)); } let mut plr = OptimalPLR::new(0.0005); // gamma = 0.0005, the maximum regression error let mut segments = Vec::new(); for (x, y) in data { // when `process` returns a segment, we should add it to our list if let Some(segment) = plr.process(x, y) { segments.push(segment); } } // because we have a finite amount of data, we flush the buffer and get the potential // last segment. if let Some(segment) = plr.finish() { segments.push(segment); } // the `segments` vector now contains all segments for this regression.
Methods
impl OptimalPLR
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pub fn new(gamma: f64) -> OptimalPLR
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Enables performing PLR using an optimal algorithm with a fixed gamma (maximum error).
Examples
To perform an optimal PLR with a maximum error of 0.05
:
use plr::OptimalPLR; let plr = OptimalPLR::new(0.05);
pub fn process(&mut self, x: f64, y: f64) -> Option<Segment>
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Processes a single point using the optimal PLR algorithm. This function returns
a new Segment
when the current segment cannot accommodate
the passed point, and returns None if the current segment could be (greedily) adjusted to
fit the point.
pub fn finish(self) -> Option<Segment>
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Terminates the PLR process, returning a final segment if required.
Auto Trait Implementations
impl Send for OptimalPLR
impl Sync for OptimalPLR
impl Unpin for OptimalPLR
impl UnwindSafe for OptimalPLR
impl RefUnwindSafe for OptimalPLR
Blanket Implementations
impl<T, U> Into<U> for T where
U: From<T>,
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U: From<T>,
impl<T> From<T> for T
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impl<T, U> TryFrom<U> for T where
U: Into<T>,
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U: Into<T>,
type Error = Infallible
The type returned in the event of a conversion error.
fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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impl<T, U> TryInto<U> for T where
U: TryFrom<T>,
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U: TryFrom<T>,
type Error = <U as TryFrom<T>>::Error
The type returned in the event of a conversion error.
fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>
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impl<T> Borrow<T> for T where
T: ?Sized,
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T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
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T: ?Sized,
fn borrow_mut(&mut self) -> &mut T
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impl<T> Any for T where
T: 'static + ?Sized,
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T: 'static + ?Sized,