Small improvements to Histogram docs

src/histogram.rs

@@ -23,7 +23,9 @@ macro_rules! define_histogram {
         /// A histogram with a number of bins known at compile time.
         #[derive(Debug, Clone)]
         pub struct $name {
+            /// The ranges defining the bins of the histogram.
             range: [f64; LEN + 1],
+            /// The bins of the histogram.
             bin: [u64; LEN],
         }
 

src/lib.rs

@@ -45,6 +45,7 @@
 //! * Quantiles ([`Quantile`]).
 //! * Minimum ([`Min`]) and maximum ([`Max`]).
 //!
+//!
 //! ## Estimating several statistics at once
 //!
 //! The estimators are designed to have minimal state. The recommended way to
@@ -59,6 +60,12 @@
 //! only need to include the highest moment in your struct.
 //!
 //!
+//! ## Calculating histograms
+//!
+//! The [`define_histogram`] macro can be used to define a histogram struct that
+//! uses constant memory.
+//!
+//!
 //! [`Mean`]: ./struct.Mean.html
 //! [`MeanWithError`]: ./type.MeanWithError.html
 //! [`WeightedMean`]: ./struct.WeightedMean.html
@@ -70,6 +77,7 @@
 //! [`Min`]: ./struct.Min.html
 //! [`Max`]: ./struct.Max.html
 //! [`concatenate`]: ./macro.concatenate.html
+//! [`define_histogram`]: ./macro.define_histogram.html
 
 #![cfg_attr(feature = "cargo-clippy", allow(float_cmp))]
 

src/traits.rs

@@ -55,7 +55,7 @@ pub trait Histogram:
 
     /// Return an iterator over the bin variances.
     ///
-    /// This is more efficient than using `variance()` each bin.
+    /// This is more efficient than calling `variance()` for each bin.
     #[inline]
     fn variances(&self) -> IterVariances<<&Self as IntoIterator>::IntoIter> {
         let sum: u64 = self.bins().iter().sum();