pub type HistF64 = HistogramFloat<f64>;
Expand description
Histogram for binning f64
- alias for HistogramFloat<f64>
Aliased Type§
struct HistF64 { /* private fields */ }
Implementations
Source§impl<T> HistogramFloat<T>
impl<T> HistogramFloat<T>
Source§impl<T> HistogramFloat<T>
impl<T> HistogramFloat<T>
Sourcepub fn new(left: T, right: T, bins: usize) -> Result<Self, HistErrors>
pub fn new(left: T, right: T, bins: usize) -> Result<Self, HistErrors>
§Create a new Histogram
- right exclusive, left inclusive
- if you want
right
to behave (almost) the same as an inclusive border, consider usingnew(left, right + T::EPSILON, bins)
(make sure, that adding Epsilon actually changes the value!)
Sourcepub fn interval_length(&self) -> T
pub fn interval_length(&self) -> T
Returns the length of the interval
Sourcepub fn bin_iter(&self) -> impl Iterator<Item = &[T; 2]>
pub fn bin_iter(&self) -> impl Iterator<Item = &[T; 2]>
§Iterator over all the bins
In HistogramFloat a bin is defined by two values: The left border (inclusive) and the right border (exclusive)
Here you get an iterator which iterates over said borders. The Iterator returns a borrowed Array of length two, where the first value is the left (inclusive) border and the second value is the right (exclusive) border
§Example
use sampling::histogram::*;
let hist = HistogramFloat::<f32>::new(0.0, 1.0, 2).unwrap();
let mut iter = hist.bin_iter();
assert_eq!(iter.next(), Some(&[0.0, 0.5]));
assert_eq!(iter.next(), Some(&[0.5, 1.0]));
assert_eq!(iter.next(), None);
Sourcepub fn bin_hits_iter(&self) -> impl Iterator<Item = (&[T; 2], usize)>
pub fn bin_hits_iter(&self) -> impl Iterator<Item = (&[T; 2], usize)>
§Iterate over all bins
In HistogramFloat a bin is defined by two values: The left border (inclusive) and the right border (exclusive)
This Iterator iterates over these values as well as the corresponding hit count ( i.e., how often a bin was hit)
§Item of Iterator
(&[left_border, right_border], number_of_hits)
§Example
use sampling::histogram::*;
let mut hist = HistogramFloat::<f64>::new(0.0, 1.0, 2).unwrap();
hist.increment_quiet(0.5);
hist.increment_quiet(0.71253782387);
let mut iter = hist.bin_hits_iter();
assert_eq!(iter.next(), Some((&[0.0, 0.5], 0)));
assert_eq!(iter.next(), Some((&[0.5, 1.0], 2)));
assert_eq!(iter.next(), None);
Sourcepub fn increment<B: Borrow<T>>(&mut self, val: B) -> Result<usize, HistErrors>
pub fn increment<B: Borrow<T>>(&mut self, val: B) -> Result<usize, HistErrors>
§Increment hit count of bin
This will increment the hit count of the bin corresponding to the value val
.
If the bin was valid it will return the index of the corresponding bin
Sourcepub fn increment_quiet<B: Borrow<T>>(&mut self, val: B)
pub fn increment_quiet<B: Borrow<T>>(&mut self, val: B)
§Increment hit count
Increments the hit count of the bin corresponding to val
.
If no bin corresponding to val
exists, nothing happens
Trait Implementations
Source§impl<T: Clone> Clone for HistogramFloat<T>
impl<T: Clone> Clone for HistogramFloat<T>
Source§fn clone(&self) -> HistogramFloat<T>
fn clone(&self) -> HistogramFloat<T>
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read moreSource§impl<T: Debug> Debug for HistogramFloat<T>
impl<T: Debug> Debug for HistogramFloat<T>
Source§impl<'de, T> Deserialize<'de> for HistogramFloat<T>where
T: Deserialize<'de>,
impl<'de, T> Deserialize<'de> for HistogramFloat<T>where
T: Deserialize<'de>,
Source§fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where
__D: Deserializer<'de>,
fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where
__D: Deserializer<'de>,
Source§impl<T> From<AtomicHistogramFloat<T>> for HistogramFloat<T>
impl<T> From<AtomicHistogramFloat<T>> for HistogramFloat<T>
Source§fn from(other: AtomicHistogramFloat<T>) -> Self
fn from(other: AtomicHistogramFloat<T>) -> Self
Source§impl<T> Histogram for HistogramFloat<T>
impl<T> Histogram for HistogramFloat<T>
Source§fn increment_index_by(
&mut self,
index: usize,
count: usize,
) -> Result<(), HistErrors>
fn increment_index_by( &mut self, index: usize, count: usize, ) -> Result<(), HistErrors>
Source§fn increment_index(&mut self, index: usize) -> Result<(), HistErrors>
fn increment_index(&mut self, index: usize) -> Result<(), HistErrors>
Source§fn any_bin_zero(&self) -> bool
fn any_bin_zero(&self) -> bool
Source§impl<T> HistogramIntervalDistance<T> for HistogramFloat<T>
impl<T> HistogramIntervalDistance<T> for HistogramFloat<T>
Source§fn interval_distance_overlap<V: Borrow<T>>(
&self,
val: V,
overlap: NonZeroUsize,
) -> usize
fn interval_distance_overlap<V: Borrow<T>>( &self, val: V, overlap: NonZeroUsize, ) -> usize
Source§impl<T> HistogramVal<T> for HistogramFloat<T>
impl<T> HistogramVal<T> for HistogramFloat<T>
Source§fn bin_enum_iter(&self) -> Box<dyn Iterator<Item = Bin<T>> + '_>
fn bin_enum_iter(&self) -> Box<dyn Iterator<Item = Bin<T>> + '_>
§consider using self.bin_iter()
instead
- This gives you a dynamic iterator over all bins-
- For this type all bins are InclusiveExclusive -> Usage of
self.bin_iter
is more efficient
Source§fn count_val<V: Borrow<T>>(&mut self, val: V) -> Result<usize, HistErrors>
fn count_val<V: Borrow<T>>(&mut self, val: V) -> Result<usize, HistErrors>
Ok(index)
, if inside of hist, Err(_)
if val is invalidSource§fn distance<V: Borrow<T>>(&self, val: V) -> f64
fn distance<V: Borrow<T>>(&self, val: V) -> f64
Source§fn first_border(&self) -> T
fn first_border(&self) -> T
Source§fn last_border(&self) -> T
fn last_border(&self) -> T
Source§fn last_border_is_inclusive(&self) -> bool
fn last_border_is_inclusive(&self) -> bool
Source§fn not_inside<V: Borrow<T>>(&self, val: V) -> bool
fn not_inside<V: Borrow<T>>(&self, val: V) -> bool
is_inside