Small improvements to Histogram docs
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@ -23,7 +23,9 @@ macro_rules! define_histogram {
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/// A histogram with a number of bins known at compile time.
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#[derive(Debug, Clone)]
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pub struct $name {
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/// The ranges defining the bins of the histogram.
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range: [f64; LEN + 1],
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/// The bins of the histogram.
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bin: [u64; LEN],
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}
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10
src/lib.rs
10
src/lib.rs
@ -14,7 +14,7 @@
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//! Everything is calculated iteratively in a single pass using constant memory,
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//! so the sequence of numbers can be an iterator. The used algorithms try to
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//! avoid numerical instabilities.
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//!
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//!
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//! If you want [Serde](https://github.com/serde-rs/serde) support,
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//! include `"serde"` in your list of features.
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//!
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@ -45,6 +45,7 @@
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//! * Quantiles ([`Quantile`]).
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//! * Minimum ([`Min`]) and maximum ([`Max`]).
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//!
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//!
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//! ## Estimating several statistics at once
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//!
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//! The estimators are designed to have minimal state. The recommended way to
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@ -59,6 +60,12 @@
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//! only need to include the highest moment in your struct.
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//!
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//!
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//! ## Calculating histograms
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//!
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//! The [`define_histogram`] macro can be used to define a histogram struct that
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//! uses constant memory.
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//!
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//!
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//! [`Mean`]: ./struct.Mean.html
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//! [`MeanWithError`]: ./type.MeanWithError.html
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//! [`WeightedMean`]: ./struct.WeightedMean.html
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@ -70,6 +77,7 @@
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//! [`Min`]: ./struct.Min.html
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//! [`Max`]: ./struct.Max.html
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//! [`concatenate`]: ./macro.concatenate.html
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//! [`define_histogram`]: ./macro.define_histogram.html
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#![cfg_attr(feature = "cargo-clippy", allow(float_cmp))]
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@ -55,7 +55,7 @@ pub trait Histogram:
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/// Return an iterator over the bin variances.
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///
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/// This is more efficient than using `variance()` each bin.
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/// This is more efficient than calling `variance()` for each bin.
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#[inline]
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fn variances(&self) -> IterVariances<<&Self as IntoIterator>::IntoIter> {
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let sum: u64 = self.bins().iter().sum();
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