Implement various Clippy suggestions

Many lints were disabled due to low or nil utility, and a few suggestions
ignored in the interests of readability or correctness. Command:

~/.cargo/bin/cargo-clippy --features=log,nightly,serde-1 -- -A inline_always -A approx_constant -A unreadable_literal -A cast_lossless -A len_zero -A unit_arg -A many_single_char_names -A doc_markdown -A single_match -A transmute_int_to_float -A float_cmp -A identity_op -A too_many_arguments -A new_ret_no_self

Author: dhardy

benches/distributions.rs

@@ -43,7 +43,7 @@ macro_rules! distr_float {
                 let mut accum = 0.0;
                 for _ in 0..::RAND_BENCH_N {
                     let x: $ty = distr.sample(&mut rng);
-                    accum = accum + x;
+                    accum += x;
                 }
                 black_box(accum);
             });

examples/monty-hall.rs

@@ -58,7 +58,7 @@ fn simulate<R: Rng>(random_door: &Range<RangeInt<u32>>, rng: &mut R)
         choice = switch_door(choice, open);
     }
 
-    SimulationResult { win: choice == car, switch: switch }
+    SimulationResult { win: choice == car, switch }
 }
 
 // Returns the door the game host opens given our choice and knowledge of

src/distributions/binomial.rs

@@ -41,7 +41,7 @@ impl Binomial {
     pub fn new(n: u64, p: f64) -> Binomial {
         assert!(p > 0.0, "Binomial::new called with p <= 0");
         assert!(p < 1.0, "Binomial::new called with p >= 1");
-        Binomial { n: n, p: p }
+        Binomial { n, p }
     }
 }
 

src/distributions/float.rs

@@ -25,7 +25,6 @@ pub(crate) trait IntoFloat {
     /// The resulting value will fall in a range that depends on the exponent.
     /// As an example the range with exponent 0 will be
     /// [2<sup>0</sup>..2<sup>1</sup>), which is [1..2).
-    #[inline(always)]
     fn into_float_with_exponent(self, exponent: i32) -> Self::F;
 }
 

src/distributions/gamma.rs

@@ -109,7 +109,7 @@ impl Gamma {
         } else {
             Large(GammaLargeShape::new_raw(shape, scale))
         };
-        Gamma { repr: repr }
+        Gamma { repr }
     }
 }
 
@@ -126,9 +126,9 @@ impl GammaLargeShape {
     fn new_raw(shape: f64, scale: f64) -> GammaLargeShape {
         let d = shape - 1. / 3.;
         GammaLargeShape {
-            scale: scale,
+            scale,
             c: 1. / (9. * d).sqrt(),
-            d: d
+            d
         }
     }
 }
@@ -211,7 +211,7 @@ impl ChiSquared {
             assert!(k > 0.0, "ChiSquared::new called with `k` < 0");
             DoFAnythingElse(Gamma::new(0.5 * k, 2.0))
         };
-        ChiSquared { repr: repr }
+        ChiSquared { repr }
     }
 }
 impl Distribution<f64> for ChiSquared {

src/distributions/log_gamma.rs

@@ -39,13 +39,13 @@ pub fn log_gamma(x: f64) -> f64 {
     // the first few terms of the series for Ag(x)
     let mut a = 1.000000000190015;
     let mut denom = x;
-    for j in 0..6 {
+    for coeff in &coefficients {
         denom += 1.0;
-        a += coefficients[j] / denom;
+        a += coeff / denom;
     }
 
     // get everything together
     // a is Ag(x)
     // 2.5066... is sqrt(2pi)
-    return log + (2.5066282746310005 * a / x).ln();
+    log + (2.5066282746310005 * a / x).ln()
 }

src/distributions/mod.rs

@@ -273,7 +273,7 @@ impl<'a, T: Clone> WeightedChoice<'a, T> {
         assert!(running_total != 0, "WeightedChoice::new called with a total weight of 0");
 
         WeightedChoice {
-            items: items,
+            items,
             // we're likely to be generating numbers in this range
             // relatively often, so might as well cache it
             weight_range: Range::new(0, running_total)
@@ -320,7 +320,7 @@ impl<'a, T: Clone> Distribution<T> for WeightedChoice<'a, T> {
             }
             modifier /= 2;
         }
-        return self.items[idx + 1].item.clone();
+        self.items[idx + 1].item.clone()
     }
 }
 

src/distributions/normal.rs

@@ -104,8 +104,8 @@ impl Normal {
     pub fn new(mean: f64, std_dev: f64) -> Normal {
         assert!(std_dev >= 0.0, "Normal::new called with `std_dev` < 0");
         Normal {
-            mean: mean,
-            std_dev: std_dev
+            mean,
+            std_dev
         }
     }
 }

src/distributions/other.rs

@@ -58,7 +58,7 @@ impl Distribution<char> for Uniform {
 impl Distribution<char> for Alphanumeric {
     fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> char {
         const RANGE: u32 = 26 + 26 + 10;
-        const GEN_ASCII_STR_CHARSET: &'static [u8] =
+        const GEN_ASCII_STR_CHARSET: &[u8] =
             b"ABCDEFGHIJKLMNOPQRSTUVWXYZ\
                 abcdefghijklmnopqrstuvwxyz\
                 0123456789";

src/distributions/poisson.rs

@@ -46,9 +46,9 @@ impl Poisson {
         assert!(lambda > 0.0, "Poisson::new called with lambda <= 0");
         let log_lambda = lambda.ln();
         Poisson {
-            lambda: lambda,
+            lambda,
             exp_lambda: (-lambda).exp(),
-            log_lambda: log_lambda,
+            log_lambda,
             sqrt_2lambda: (2.0 * lambda).sqrt(),
             magic_val: lambda * log_lambda - log_gamma(1.0 + lambda),
         }