Thank Tarik

Both are the same, Discard my previous mail 

Bur surely they are not both the same, as I indicated in my initial email ? Is it not the case that mean1 is a parametrically polymorphic functiion, while mean is a simple function ?  My question is about the relative advantages and disadvantes of each Thanks again J On Saturday, May 8, 2021, 02:12:26 PM GMT+1, Tarik ÖZKANLI wrote: No sorry, Both are the same, Discard my previous mail  Regards. Tarık On Sat, 8 May 2021 at 16:07, Tarik ÖZKANLI wrote:

Hello,

In standard usage there is not much difference. But in Haskell, people prefer to write in curried form (first implementation of yours) which has the advantage of using partially applied form when suitable.

Regards.

Tarık Özkanlı

On Sat, 8 May 2021 at 12:43, Joe King wrote:

...

Greeetings I am new here and pretty new to Haskell.

I was wondering what are the relative advanatges/disadvatnages of specifying a mean function in these two ways:

mean :: [Double] -> Double mean xs = sum xs / fromIntegral (length xs)

and

mean1 :: (Real a, Fractional b) => [a] -> b mean1 xs = realToFrac (sum xs) / genericLength xs

I understand that mean1 has the advantage that it can be called with lists of any Real type, so would work with things like 

foo :: [Int] foo = [1,2,3]

mean foo -- type mismatch error

mean1 foo -- no error

But suppose that I know I will only ever use lists of Double, is there still any advantage (or disadvantage of using mean1). For example is there any performance benefit by using mean in that case since mean1 has additional function evaluation. 

Are there any other considerations ?

Thanks in advance JK _______________________________________________ Beginners mailing list Beginners@haskell.org http://mail.haskell.org/cgi-bin/mailman/listinfo/beginners

_______________________________________________ Beginners mailing list Beginners@haskell.org http://mail.haskell.org/cgi-bin/mailman/listinfo/beginners

If you want a much more performant solution, go around the list once. Another advantage is that it will run in constant memory. ``` -- requires BangPatterns extension; bonus questions: -- * Can you predict what will happen with out bang patterns? -- * Would `foldl'` work even without any bang patterns? mean5 :: [Double] -> Double mean5 = snd . foldl (\(!n, !r) a -> (n + 1, a / n + (n - 1) / n * r)) (1, 0) ``` `mean5` on my system reports: ```    1,840,101,632 bytes allocated in the heap          197,896 bytes copied during GC           44,408 bytes maximum residency (2 sample(s))           29,320 bytes maximum slop                2 MiB total memory in use (0 MB lost due to fragmentation)                                      Tot time (elapsed)  Avg pause  Max pause   Gen  0      1774 colls,     0 par    0.005s   0.006s     0.0000s    0.0000s   Gen  1         2 colls,     0 par    0.000s   0.000s     0.0001s    0.0001s   INIT    time    0.000s  (  0.000s elapsed)   MUT     time    0.236s  (  0.235s elapsed)   GC      time    0.005s  (  0.006s elapsed)   EXIT    time    0.000s  (  0.000s elapsed)   Total   time    0.241s  (  0.241s elapsed)   %GC     time       0.0%  (0.0% elapsed)   Alloc rate    7,803,840,935 bytes per MUT second   Productivity  97.9% of total user, 97.5% of total elapsed ``` while `mean` ```    1,280,101,688 bytes allocated in the heap    1,099,489,280 bytes copied during GC      294,937,752 bytes maximum residency (12 sample(s))       50,518,888 bytes maximum slop              670 MiB total memory in use (0 MB lost due to fragmentation)                                      Tot time (elapsed)  Avg pause  Max pause   Gen  0      1209 colls,     0 par    0.379s   0.381s     0.0003s    0.0012s   Gen  1        12 colls,     0 par    0.976s   0.976s     0.0813s    0.3921s   INIT    time    0.000s  (  0.000s elapsed)   MUT     time    0.324s  (  0.322s elapsed)   GC      time    1.355s  (  1.357s elapsed)   EXIT    time    0.000s  (  0.000s elapsed)   Total   time    1.679s  (  1.679s elapsed)   %GC     time       0.0%  (0.0% elapsed)   Alloc rate    3,956,490,811 bytes per MUT second   Productivity  19.3% of total user, 19.2% of total elapsed ``` I  compiled both with `ghc -O2 -rtsopts` and run them with `./Mean +RTS -s` (one does not nead to link the profiled RTS for `-s` to work). Cheers, Marcin Sent with ProtonMail Secure Email. ‐‐‐‐‐‐‐ Original Message ‐‐‐‐‐‐‐ On Monday, May 10th, 2021 at 14:23, David James wrote:

Ugh – sent too soon!

Hello – I wanted to add some comments. mean is as you describe.

mean1 as defined can take a list of any Real type, and return any Fractional type. These types need not be the same, and it’s up to the *caller* of mean1 to say what types they want to give and get returned, e.g. the following is possible:

...

:m +Data.Ratio

...

:m +Data.Complex

...

mean1 [6%5, 2%3] :: Complex Double

0.9333333333333333 :+ 0.0

This may not be what you were expecting? There’s also no need to restrict to Real, since it is valid to calculate the mean of a list of e.g. complex numbers. So maybe you want something like this:

mean2 :: (Fractional a) => [a] -> a

mean2 xs = sum xs / genericLength xs

(the realToFrac is now unnecessary). The caller still decides the type, but the argument and result type now have to be the same.

You can’t now do mean2 foo, but you can do mean2 [1,2,3] (and the 1, 2, 3 are interpreted as the default fractional type, probably Double).

I personally prefer to write “utility” functions to be as generic as possible. (Imagine you’re including them in some standard library for the whole world to use). But I’m sure there are other opinions.

Re performance, there is a comment against “genericLength” to say that it is not as efficient as length. And, as used above, this is the case. So maybe you actually want:

mean3 :: (Fractional a) => [a] -> a

mean3 xs = sum xs / fromIntegral (length xs)

which is as efficient as mean.

If you are especially interested in performance, you might want to read this. It’s not really “beginner level” but does look at some issues with mean in some detail (and in particular why it can use so much memory and what you can do about that). Performance of Haskell code is often more difficult to predict than for other languages, for example due to lazy evaluation and some amazing transformations of you code done by GHC.

Incidentally, I am in the middle of drafting a page about numbers to include in the Haskell wikibook that might be interesting. It discusses types, classes, defaults numeric conversions, etc. I would be very happy if for any feedback (please leave any on the “Discussion” tab on the page).

FYI: I tested performance (on GHC 8.4.3 on Windows) with this:

{-

compile: ghc -O2 -prof -fprof-auto -rtsopts Mean.hs

run: Mean +RTS -p     > nul

-}

module Main (main) where

import Data.List

mean :: [Double] -> Double

mean xs = sum xs / fromIntegral (length xs)

mean1 :: (Real a, Fractional b) => [a] -> b

mean1 xs = realToFrac (sum xs) / genericLength xs

mean2 :: (Fractional a) => [a] -> a

mean2 xs = sum xs / genericLength xs

mean3 :: (Fractional a) => [a] -> a

mean3 xs = sum xs / fromIntegral (length xs)

mean4 :: (Fractional a) => [a] -> a

mean4 xs = sum xs / fromIntegral (genericLength xs :: Int)

main :: IO ()

main = do

  let xs = [1 .. 10000000] :: [Double] --may default to Integer unless specified as Double.

  print $ mean xs                      --change to mean1, etc, for different runs

And got:

Total time

Total alloc

mean

0.10

1,680,096,640 bytes

mean1

0.17

2,560,096,656 bytes

mean2

0.17

2,560,096,656 bytes

mean3

0.10

1,680,096,640 bytes

mean4

0.10

1,680,096,640 bytes

mean4 also uses genericLength but is as fast as length. This is due to some cleaverness in GHC, where it uses more efficient code when it knows the required result is integral.

[C41BD4BD0CBD4F519B49D2A93C03CE4A.png]

From: Beginners on behalf of Joe King

Sent: Saturday, May 8, 2021 10:39:50 AM

To: beginners@haskell.org

Subject: [Haskell-beginners] Function to compute the mean

Greeetings I am new here and pretty new to Haskell.

I was wondering what are the relative advanatges/disadvatnages of specifying a mean function in these two ways:

mean :: [Double] -> Double

mean xs = sum xs / fromIntegral (length xs)

and

mean1 :: (Real a, Fractional b) => [a] -> b

mean1 xs = realToFrac (sum xs) / genericLength xs

I understand that mean1 has the advantage that it can be called with lists of any Real type, so would work with things like 

foo :: [Int]

foo = [1,2,3]

mean foo

-- type mismatch error

mean1 foo

-- no error

But suppose that I know I will only ever use lists of Double, is there still any advantage (or disadvantage of using mean1). For example is there any performance benefit by using mean in that case since mean1 has additional function evaluation. 

Are there any other considerations ?

Thanks in advance

JK

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