f32 :: NAN锈封闭的值，以省略“ NaN”值

Question

I have the following closure.

let ss = aa.iter().fold(0., |sum: f32,x| if *x != f32::NAN { sum + e } else { sum + 0. })

I am trying to sum all the values omitting f32::NAN if any in the vector(I have couple of NaN values in the vector).

But, My return gives me NaN value because my condition if *x != f32::NAN does not seem to be valid. Because, the following closure yields the original vector instead of omitting NaN value.

let bb = aa.iter().filter(|x| **x != f32::NAN).map(|x| x)

My question is, how do I match f32::NAN value in a if condition? In a broader perspective, How do I omit NaN values in a vector?

Answer 1

You cannot check for NaN that way, since NaN == NaN evaluates to false . Use f32::is_nan instead. Furthermore, you can use Iterator::filter to filter out elements of an iterator and Iterator::sum to sum all values.

This results in this code ( Playground ):

let aa = [3.14f32, std::f32::NAN, 2.71, 27.99];
let ss = aa.iter()
    .filter(|n| !n.is_nan())
    .sum::<f32>();

println!("{}", ss);

Answer 2

With the right directional help of Warren Weckesser Managed to make the closure work.

Here is the solution for those who might need.

let ss = aa.iter().fold(0., |sum: f32, x| if x.is_nan() { sum + 0. } else { sum + x });

Alternatively,

let ss = aa.iter().fold(0., |sum: f32, x| if x.is_nan() { sum } else { sum + x });

if one cares about a unnecessary + operation.

Performance Comparison

extern crate rand;

use rand::Rng;
fn main() {
    let mut a [f32; 1000] = [0.; 1000];
    for i in 0..1000 {
        a[i] = rand::thread_rng().gen_range(1,11);
    }
}

Approach-I:

let ss = a.iter()
        .filter(|n| !n.is_nan())
        .sum::<f32>();

Callgrind

>> cargo profiler callgrind -n 10

Compiling playground in debug mode...

Profiling playground with callgrind...

Total Instructions...3,959,454

177,532 (4.5%) isaac64.rs:rand::prng::isaac64::Isaac64Rng::isaac64
-----------------------------------------------------------------------
121,742 (3.1%) memmove-vec-unaligned-erms.S:memcpy@GLIBC_2.2.5
-----------------------------------------------------------------------
104,224 (2.6%) dl-lookup.c:do_lookup_x
-----------------------------------------------------------------------
102,982 (2.6%) ptr.rs:core::ptr::swap_nonoverlapping_one
-----------------------------------------------------------------------
99,660 (2.5%) intrinsics.rs:core::intrinsics::copy_nonoverlapping
-----------------------------------------------------------------------
76,555 (1.9%) strcmp.S:strcmp
-----------------------------------------------------------------------
72,997 (1.8%) local.rs:_..std..thread..local..LocalKey..T....::try_with
-----------------------------------------------------------------------
72,063 (1.8%) ptr.rs:_..core..ptr..NonNull..T....::as_ref
-----------------------------------------------------------------------
70,028 (1.8%) rc.rs:alloc::rc::RcBoxPtr::strong
-----------------------------------------------------------------------
62,000 (1.6%) ptr.rs:core::ptr::swap_nonoverlapping_one
-----------------------------------------------------------------------

Approach-II:

let ss = a.iter()
        .fold(0., |sum: f32, x| if x.is_nan() { sum } else { sum + x });

Callgrind

>> cargo profiler callgrind -n 10

Compiling playground in debug mode...

Profiling playground with callgrind...

Total Instructions...3,938,312

177,532 (4.5%) isaac64.rs:rand::prng::isaac64::Isaac64Rng::isaac64
-----------------------------------------------------------------------
121,766 (3.1%) memmove-vec-unaligned-erms.S:memcpy@GLIBC_2.2.5
-----------------------------------------------------------------------
104,224 (2.6%) dl-lookup.c:do_lookup_x
-----------------------------------------------------------------------
102,982 (2.6%) ptr.rs:core::ptr::swap_nonoverlapping_one
-----------------------------------------------------------------------
99,660 (2.5%) intrinsics.rs:core::intrinsics::copy_nonoverlapping
-----------------------------------------------------------------------
76,555 (1.9%) strcmp.S:strcmp
-----------------------------------------------------------------------
72,997 (1.9%) local.rs:_..std..thread..local..LocalKey..T....::try_with
-----------------------------------------------------------------------
72,063 (1.8%) ptr.rs:_..core..ptr..NonNull..T....::as_ref
-----------------------------------------------------------------------
70,028 (1.8%) rc.rs:alloc::rc::RcBoxPtr::strong
-----------------------------------------------------------------------
62,000 (1.6%) ptr.rs:core::ptr::swap_nonoverlapping_one
-----------------------------------------------------------------------

Looking at the Total Instructions , Approach-II fares well in terms of run-time performance with ~20,000 instructions less than Approach-I for 1000 element array. Anticipating this difference will positively translate in to enhanced run-time performance for Approach-II . Investigating, from where the difference stem from.