auto merge of #19050 : japaric/rust/moar-dst, r=aturon
r? @aturon cc #16918
This commit is contained in:
commit
f637f1c5a2
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@ -62,12 +62,12 @@ impl RegClass {
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}
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}
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trait ClassList {
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trait ClassList for Sized? {
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fn is_pass_byval(&self) -> bool;
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fn is_ret_bysret(&self) -> bool;
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}
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impl<'a> ClassList for &'a [RegClass] {
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impl ClassList for [RegClass] {
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fn is_pass_byval(&self) -> bool {
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if self.len() == 0 { return false; }
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@ -12,11 +12,11 @@ use middle::trans::context::CrateContext;
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use middle::trans::type_::Type;
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use llvm::ValueRef;
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pub trait LlvmRepr {
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pub trait LlvmRepr for Sized? {
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fn llrepr(&self, ccx: &CrateContext) -> String;
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}
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impl<'a, T:LlvmRepr> LlvmRepr for &'a [T] {
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impl<T:LlvmRepr> LlvmRepr for [T] {
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fn llrepr(&self, ccx: &CrateContext) -> String {
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let reprs: Vec<String> = self.iter().map(|t| t.llrepr(ccx)).collect();
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format!("[{}]", reprs.connect(","))
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@ -37,7 +37,7 @@ use syntax::{ast, ast_util};
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use syntax::owned_slice::OwnedSlice;
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/// Produces a string suitable for debugging output.
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pub trait Repr {
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pub trait Repr for Sized? {
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fn repr(&self, tcx: &ctxt) -> String;
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}
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@ -578,9 +578,9 @@ impl Repr for () {
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}
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}
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impl<'a,T:Repr> Repr for &'a T {
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impl<'a, Sized? T:Repr> Repr for &'a T {
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fn repr(&self, tcx: &ctxt) -> String {
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(&**self).repr(tcx)
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Repr::repr(*self, tcx)
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}
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}
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@ -600,9 +600,9 @@ fn repr_vec<T:Repr>(tcx: &ctxt, v: &[T]) -> String {
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vec_map_to_string(v, |t| t.repr(tcx))
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}
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impl<'a, T:Repr> Repr for &'a [T] {
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impl<T:Repr> Repr for [T] {
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fn repr(&self, tcx: &ctxt) -> String {
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repr_vec(tcx, *self)
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repr_vec(tcx, self)
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}
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}
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@ -90,14 +90,14 @@ pub mod rt {
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*/
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// FIXME: Move this trait to pprust and get rid of *_to_str?
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pub trait ToSource {
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pub trait ToSource for Sized? {
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// Takes a thing and generates a string containing rust code for it.
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fn to_source(&self) -> String;
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}
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// FIXME (Issue #16472): This should go away after ToToken impls
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// are revised to go directly to token-trees.
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trait ToSourceWithHygiene : ToSource {
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trait ToSourceWithHygiene for Sized? : ToSource {
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// Takes a thing and generates a string containing rust code
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// for it, encoding Idents as special byte sequences to
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// maintain hygiene across serialization and deserialization.
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@ -150,15 +150,15 @@ pub mod rt {
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macro_rules! impl_to_source_slice(
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($t:ty, $sep:expr) => (
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impl<'a> ToSource for &'a [$t] {
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impl ToSource for [$t] {
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fn to_source(&self) -> String {
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slice_to_source($sep, *self)
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slice_to_source($sep, self)
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}
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}
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impl<'a> ToSourceWithHygiene for &'a [$t] {
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impl ToSourceWithHygiene for [$t] {
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fn to_source_with_hygiene(&self) -> String {
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slice_to_source_with_hygiene($sep, *self)
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slice_to_source_with_hygiene($sep, self)
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}
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}
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)
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@ -200,14 +200,14 @@ pub mod rt {
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}
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}
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impl<'a> ToSource for &'a str {
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impl ToSource for str {
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fn to_source(&self) -> String {
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let lit = dummy_spanned(ast::LitStr(
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token::intern_and_get_ident(*self), ast::CookedStr));
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token::intern_and_get_ident(self), ast::CookedStr));
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pprust::lit_to_string(&lit)
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}
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}
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impl<'a> ToSourceWithHygiene for &'a str {
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impl ToSourceWithHygiene for str {
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fn to_source_with_hygiene(&self) -> String {
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self.to_source()
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}
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@ -38,7 +38,7 @@ fn local_sort<T: Float>(v: &mut [T]) {
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}
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/// Trait that provides simple descriptive statistics on a univariate set of numeric samples.
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pub trait Stats <T: FloatMath + FromPrimitive>{
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pub trait Stats <T: FloatMath + FromPrimitive> for Sized? {
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/// Sum of the samples.
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///
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@ -47,24 +47,24 @@ pub trait Stats <T: FloatMath + FromPrimitive>{
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/// ["Adaptive Precision Floating-Point Arithmetic and Fast Robust Geometric Predicates"]
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/// (http://www.cs.cmu.edu/~quake-papers/robust-arithmetic.ps)
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/// *Discrete & Computational Geometry 18*, 3 (Oct 1997), 305-363, Shewchuk J.R.
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fn sum(self) -> T;
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fn sum(&self) -> T;
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/// Minimum value of the samples.
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fn min(self) -> T;
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fn min(&self) -> T;
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/// Maximum value of the samples.
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fn max(self) -> T;
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fn max(&self) -> T;
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/// Arithmetic mean (average) of the samples: sum divided by sample-count.
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///
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/// See: https://en.wikipedia.org/wiki/Arithmetic_mean
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fn mean(self) -> T;
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fn mean(&self) -> T;
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/// Median of the samples: value separating the lower half of the samples from the higher half.
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/// Equal to `self.percentile(50.0)`.
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///
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/// See: https://en.wikipedia.org/wiki/Median
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fn median(self) -> T;
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fn median(&self) -> T;
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/// Variance of the samples: bias-corrected mean of the squares of the differences of each
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/// sample from the sample mean. Note that this calculates the _sample variance_ rather than the
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@ -73,7 +73,7 @@ pub trait Stats <T: FloatMath + FromPrimitive>{
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/// than `n`.
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///
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/// See: https://en.wikipedia.org/wiki/Variance
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fn var(self) -> T;
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fn var(&self) -> T;
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/// Standard deviation: the square root of the sample variance.
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///
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@ -81,13 +81,13 @@ pub trait Stats <T: FloatMath + FromPrimitive>{
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/// `median_abs_dev` for unknown distributions.
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///
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/// See: https://en.wikipedia.org/wiki/Standard_deviation
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fn std_dev(self) -> T;
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fn std_dev(&self) -> T;
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/// Standard deviation as a percent of the mean value. See `std_dev` and `mean`.
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///
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/// Note: this is not a robust statistic for non-normal distributions. Prefer the
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/// `median_abs_dev_pct` for unknown distributions.
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fn std_dev_pct(self) -> T;
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fn std_dev_pct(&self) -> T;
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/// Scaled median of the absolute deviations of each sample from the sample median. This is a
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/// robust (distribution-agnostic) estimator of sample variability. Use this in preference to
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@ -96,10 +96,10 @@ pub trait Stats <T: FloatMath + FromPrimitive>{
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/// deviation.
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///
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/// See: http://en.wikipedia.org/wiki/Median_absolute_deviation
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fn median_abs_dev(self) -> T;
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fn median_abs_dev(&self) -> T;
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/// Median absolute deviation as a percent of the median. See `median_abs_dev` and `median`.
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fn median_abs_dev_pct(self) -> T;
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fn median_abs_dev_pct(&self) -> T;
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/// Percentile: the value below which `pct` percent of the values in `self` fall. For example,
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/// percentile(95.0) will return the value `v` such that 95% of the samples `s` in `self`
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@ -108,7 +108,7 @@ pub trait Stats <T: FloatMath + FromPrimitive>{
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/// Calculated by linear interpolation between closest ranks.
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///
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/// See: http://en.wikipedia.org/wiki/Percentile
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fn percentile(self, pct: T) -> T;
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fn percentile(&self, pct: T) -> T;
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/// Quartiles of the sample: three values that divide the sample into four equal groups, each
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/// with 1/4 of the data. The middle value is the median. See `median` and `percentile`. This
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@ -116,13 +116,13 @@ pub trait Stats <T: FloatMath + FromPrimitive>{
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/// is otherwise equivalent.
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///
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/// See also: https://en.wikipedia.org/wiki/Quartile
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fn quartiles(self) -> (T,T,T);
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fn quartiles(&self) -> (T,T,T);
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/// Inter-quartile range: the difference between the 25th percentile (1st quartile) and the 75th
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/// percentile (3rd quartile). See `quartiles`.
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///
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/// See also: https://en.wikipedia.org/wiki/Interquartile_range
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fn iqr(self) -> T;
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fn iqr(&self) -> T;
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}
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/// Extracted collection of all the summary statistics of a sample set.
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@ -163,9 +163,9 @@ impl<T: FloatMath + FromPrimitive> Summary<T> {
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}
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}
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impl<'a, T: FloatMath + FromPrimitive> Stats<T> for &'a [T] {
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impl<T: FloatMath + FromPrimitive> Stats<T> for [T] {
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// FIXME #11059 handle NaN, inf and overflow
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fn sum(self) -> T {
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fn sum(&self) -> T {
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let mut partials = vec![];
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for &mut x in self.iter() {
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@ -198,26 +198,26 @@ impl<'a, T: FloatMath + FromPrimitive> Stats<T> for &'a [T] {
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partials.iter().fold(zero, |p, q| p + *q)
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}
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fn min(self) -> T {
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fn min(&self) -> T {
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assert!(self.len() != 0);
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self.iter().fold(self[0], |p, q| p.min(*q))
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}
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fn max(self) -> T {
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fn max(&self) -> T {
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assert!(self.len() != 0);
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self.iter().fold(self[0], |p, q| p.max(*q))
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}
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fn mean(self) -> T {
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fn mean(&self) -> T {
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assert!(self.len() != 0);
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self.sum() / FromPrimitive::from_uint(self.len()).unwrap()
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}
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fn median(self) -> T {
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fn median(&self) -> T {
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self.percentile(FromPrimitive::from_uint(50).unwrap())
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}
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fn var(self) -> T {
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fn var(&self) -> T {
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if self.len() < 2 {
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Float::zero()
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} else {
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@ -235,16 +235,16 @@ impl<'a, T: FloatMath + FromPrimitive> Stats<T> for &'a [T] {
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}
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}
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fn std_dev(self) -> T {
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fn std_dev(&self) -> T {
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self.var().sqrt()
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}
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fn std_dev_pct(self) -> T {
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fn std_dev_pct(&self) -> T {
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let hundred = FromPrimitive::from_uint(100).unwrap();
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(self.std_dev() / self.mean()) * hundred
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}
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fn median_abs_dev(self) -> T {
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fn median_abs_dev(&self) -> T {
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let med = self.median();
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let abs_devs: Vec<T> = self.iter().map(|&v| (med - v).abs()).collect();
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// This constant is derived by smarter statistics brains than me, but it is
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@ -253,18 +253,18 @@ impl<'a, T: FloatMath + FromPrimitive> Stats<T> for &'a [T] {
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abs_devs.as_slice().median() * number
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}
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fn median_abs_dev_pct(self) -> T {
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fn median_abs_dev_pct(&self) -> T {
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let hundred = FromPrimitive::from_uint(100).unwrap();
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(self.median_abs_dev() / self.median()) * hundred
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}
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fn percentile(self, pct: T) -> T {
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fn percentile(&self, pct: T) -> T {
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let mut tmp = self.to_vec();
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local_sort(tmp.as_mut_slice());
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percentile_of_sorted(tmp.as_slice(), pct)
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}
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fn quartiles(self) -> (T,T,T) {
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fn quartiles(&self) -> (T,T,T) {
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let mut tmp = self.to_vec();
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local_sort(tmp.as_mut_slice());
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let first = FromPrimitive::from_uint(25).unwrap();
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@ -276,7 +276,7 @@ impl<'a, T: FloatMath + FromPrimitive> Stats<T> for &'a [T] {
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(a,b,c)
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}
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fn iqr(self) -> T {
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fn iqr(&self) -> T {
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let (a,_,c) = self.quartiles();
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c - a
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}
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