Averages/Simple moving average
From Rosetta Code
You are encouraged to solve this task according to the task description, using any language you may know.
Computing the simple moving average of a series of numbers.
The task is to:
- Create a stateful function/class/instance that takes a period and returns a routine that takes a number as argument and returns a simple moving average of its arguments so far.
Description
A simple moving average is a method for computing an average of a stream of numbers by only averaging the last P numbers from the stream, where P is known as the period. It can be implemented by calling an initialing routine with P as its argument, I(P), which should then return a routine that when called with individual, successive members of a stream of numbers, computes the mean of (up to), the last P of them, lets call this SMA().
The word stateful in the task description refers to the need for SMA() to remember certain information between calls to it:
- The period, P
- An ordered container of at least the last P numbers from each of its individual calls.
Stateful also means that successive calls to I(), the initializer, should return separate routines that do not share saved state so they could be used on two independent streams of data.
Psudocode for an implementation of SMA is:
function SMA(number: N):
stateful integer: P
stateful list: stream
number: average
stream.append_last(N)
if stream.length() > P:
# Only average the last P elements of the stream
stream.delete_first()
if stream.length() == 0:
average = 0
else:
average = sum( stream.values() ) / stream.length()
return average
See also: Standard Deviation
[edit] AutoHotkey
ahk forum: discussion For Integers:
MsgBox % MovingAverage(5,3) ; 5, averaging length <- 3
MsgBox % MovingAverage(1) ; 3
MsgBox % MovingAverage(-3) ; 1
MsgBox % MovingAverage(8) ; 2
MsgBox % MovingAverage(7) ; 4
MovingAverage(x,len="") { ; for integers (faster)
Static
Static sum:=0, n:=0, m:=10 ; default averaging length = 10
If (len>"") ; non-blank 2nd parameter: set length, reset
sum := n := i := 0, m := len
If (n < m) ; until the buffer is not full
sum += x, n++ ; keep summing data
Else ; when buffer is full
sum += x-v%i% ; add new, subtract oldest
v%i% := x, i := mod(i+1,m) ; remember last m inputs, cycle insertion point
Return sum/n
}
For floating point numbers:
MovingAverage(x,len="") { ; for floating point numbers
Static
Static n:=0, m:=10 ; default averaging length = 10
If (len>"") ; non-blank 2nd parameter: set length, reset
n := i := 0, m := len
n += n < m, sum := 0
v%i% := x, i := mod(i+1,m) ; remember last m inputs, cycle insertion point
Loop %n% ; recompute sum to avoid error accumulation
j := A_Index-1, sum += v%j%
Return sum/n
}
[edit] ALGOL 68
Translation of: C
Works with: ALGOL 68 version Standard - no extensions to language used
Works with: ALGOL 68G version Any - tested with release 1.18.0-9h.tiny
Note: This following code is a direct translation of the C code sample. It mimics C's var_list implementation, and so it probably isn't the most natural way of dong this actual task in ALGOL 68.
MODE SMAOBJ = STRUCT(Output:
LONG REAL sma,
LONG REAL sum,
INT period,
REF[]LONG REAL values,
INT lv
);
MODE SMARESULT = UNION (
REF SMAOBJ # handle #,
LONG REAL # sma #,
REF[]LONG REAL # values #
);
MODE SMANEW = INT,
SMAFREE = STRUCT(REF SMAOBJ free obj),
SMAVALUES = STRUCT(REF SMAOBJ values obj),
SMAADD = STRUCT(REF SMAOBJ add obj, LONG REAL v),
SMAMEAN = STRUCT(REF SMAOBJ mean obj, REF[]LONG REAL v);
MODE ACTION = UNION ( SMANEW, SMAFREE, SMAVALUES, SMAADD, SMAMEAN );
PROC sma = ([]ACTION action)SMARESULT:
(
SMARESULT result;
REF SMAOBJ obj;
LONG REAL v;
FOR i FROM LWB action TO UPB action DO
CASE action[i] IN
(SMANEW period):( # args: INT period #
HEAP SMAOBJ handle;
sma OF handle := 0.0;
period OF handle := period;
values OF handle := HEAP [period OF handle]LONG REAL;
lv OF handle := 0;
sum OF handle := 0.0;
result := handle
),
(SMAFREE args):( # args: REF SMAOBJ free obj #
free obj OF args := REF SMAOBJ(NIL) # let the garbage collector do it's job #
),
(SMAVALUES args):( # args: REF SMAOBJ values obj #
result := values OF values obj OF args
),
(SMAMEAN args):( # args: REF SMAOBJ mean obj #
result := sma OF mean obj OF args
),
(SMAADD args):( # args: REF SMAOBJ add obj, LONG REAL v #
obj := add obj OF args;
v := v OF args;
IF lv OF obj < period OF obj THEN
(values OF obj)[lv OF obj+:=1] := v;
sum OF obj +:= v;
sma OF obj := sum OF obj / lv OF obj
ELSE
sum OF obj -:= (values OF obj)[ 1+ lv OF obj MOD period OF obj];
sum OF obj +:= v;
sma OF obj := sum OF obj / period OF obj;
(values OF obj)[ 1+ lv OF obj MOD period OF obj ] := v; lv OF obj+:=1
FI;
result := sma OF obj
)
OUT
SKIP
ESAC
OD;
result
);
[]LONG REAL v = ( 1, 2, 3, 4, 5, 5, 4, 3, 2, 1 );
main: (
INT i;
REF SMAOBJ h3 := ( sma(SMANEW(3)) | (REF SMAOBJ obj):obj );
REF SMAOBJ h5 := ( sma(SMANEW(5)) | (REF SMAOBJ obj):obj );
FOR i FROM LWB v TO UPB v DO
printf(($"next number "g(0,6)", SMA_3 = "g(0,6)", SMA_5 = "g(0,6)l$,
v[i], (sma(SMAADD(h3, v[i]))|(LONG REAL r):r), ( sma(SMAADD(h5, v[i])) | (LONG REAL r):r )
))
OD#;
sma(SMAFREE(h3));
sma(SMAFREE(h5))
#
)
next number 1.000000, SMA_3 = 1.000000, SMA_5 = 1.000000 next number 2.000000, SMA_3 = 1.500000, SMA_5 = 1.500000 next number 3.000000, SMA_3 = 2.000000, SMA_5 = 2.000000 next number 4.000000, SMA_3 = 3.000000, SMA_5 = 2.500000 next number 5.000000, SMA_3 = 4.000000, SMA_5 = 3.000000 next number 5.000000, SMA_3 = 4.666667, SMA_5 = 3.800000 next number 4.000000, SMA_3 = 4.666667, SMA_5 = 4.200000 next number 3.000000, SMA_3 = 4.000000, SMA_5 = 4.200000 next number 2.000000, SMA_3 = 3.000000, SMA_5 = 3.800000 next number 1.000000, SMA_3 = 2.000000, SMA_5 = 3.000000
[edit] C
#include <stdio.h>
#include <stdlib.h>
#include <stdarg.h>
typedef struct sma_obj {
double sma;
double sum;
int period;
double *values;
int lv;
} sma_obj_t;
typedef union sma_result {
sma_obj_t *handle;
double sma;
double *values;
} sma_result_t;
enum Action { SMA_NEW, SMA_FREE, SMA_VALUES, SMA_ADD, SMA_MEAN };
sma_result_t sma(enum Action action, ...)
{
va_list vl;
sma_result_t r;
sma_obj_t *o;
double v;
va_start(vl, action);
switch(action) {
case SMA_NEW: // args: int period
r.handle = malloc(sizeof(sma_obj_t));
r.handle->sma = 0.0;
r.handle->period = va_arg(vl, int);
r.handle->values = malloc(r.handle->period * sizeof(double));
r.handle->lv = 0;
r.handle->sum = 0.0;
break;
case SMA_FREE: // args: sma_obj_t *handle
r.handle = va_arg(vl, sma_obj_t *);
free(r.handle->values);
free(r.handle);
r.handle = NULL;
break;
case SMA_VALUES: // args: sma_obj_t *handle
o = va_arg(vl, sma_obj_t *);
r.values = o->values;
break;
case SMA_MEAN: // args: sma_obj_t *handle
o = va_arg(vl, sma_obj_t *);
r.sma = o->sma;
break;
case SMA_ADD: // args: sma_obj_t *handle, double value
o = va_arg(vl, sma_obj_t *);
v = va_arg(vl, double);
if ( o->lv < o->period ) {
o->values[o->lv++] = v;
o->sum += v;
o->sma = o->sum / o->lv;
} else {
o->sum -= o->values[ o->lv % o->period];
o->sum += v;
o->sma = o->sum / o->period;
o->values[ o->lv % o->period ] = v; o->lv++;
}
r.sma = o->sma;
break;
}
va_end(vl);
return r;
}
double v[] = { 1, 2, 3, 4, 5, 5, 4, 3, 2, 1 };
int main()
{
int i;
sma_obj_t *h3 = sma(SMA_NEW, 3).handle;
sma_obj_t *h5 = sma(SMA_NEW, 5).handle;
for(i=0; i < sizeof(v)/sizeof(double) ; i++) {
printf("next number %lf, SMA_3 = %lf, SMA_5 = %lf\n",
v[i], sma(SMA_ADD, h3, v[i]).sma, sma(SMA_ADD, h5, v[i]).sma);
}
sma(SMA_FREE, h3);
sma(SMA_FREE, h5);
return 0;
}
[edit] C++
#include <iostream>
using std::cout;
using std::endl;
class SMA {
public:
SMA(unsigned int period) :
period(period), window(new double[period]), head(NULL), tail(NULL),
total(0) {
assert(period >= 1);
}
~SMA() {
delete[] window;
}
// Adds a value to the average, pushing one out if nescessary
void add(double val) {
// Special case: Initialization
if (head == NULL) {
head = window;
*head = val;
tail = head;
inc(tail);
total = val;
return;
}
// Were we already full?
if (head == tail) {
// Fix total-cache
total -= *head;
// Make room
inc(head);
}
// Write the value in the next spot.
*tail = val;
inc(tail);
// Update our total-cache
total += val;
}
// Returns the average of the last P elements added to this SMA.
// If no elements have been added yet, returns 0.0
double avg() const {
ptrdiff_t size = this->size();
if (size == 0) {
return 0; // No entries => 0 average
}
return total / (double) size; // Cast to double for floating point arithmetic
}
private:
unsigned int period;
double * window; // Holds the values to calculate the average of.
// Logically, head is before tail
double * head; // Points at the oldest element we've stored.
double * tail; // Points at the newest element we've stored.
double total; // Cache the total so we don't sum everything each time.
// Bumps the given pointer up by one.
// Wraps to the start of the array if needed.
void inc(double * & p) {
if (++p >= window + period) {
p = window;
}
}
// Returns how many numbers we have stored.
ptrdiff_t size() const {
if (head == NULL)
return 0;
if (head == tail)
return period;
return tail - head;
}
};
int main(int argc, char * * argv) {
SMA foo(3);
SMA bar(5);
int data[] = { 1, 2, 3, 4, 5, 5, 4, 3, 2, 1 };
for (int * itr = data; itr < data + 10; itr++) {
foo.add(*itr);
cout << "Added " << *itr << " avg: " << foo.avg() << endl;
}
cout << endl;
for (int * itr = data; itr < data + 10; itr++) {
bar.add(*itr);
cout << "Added " << *itr << " avg: " << bar.avg() << endl;
}
return 0;
}
[edit] C#
Works with: C# version 3
using System;
using System.Collections.Generic;
using System.Linq;
namespace SMA {
class Program {
static void Main(string[] args) {
var nums = Enumerable.Range(1, 5).Select(n => (double)n);
nums = nums.Concat(nums.Reverse());
var sma3 = SMA(3);
var sma5 = SMA(5);
foreach (var n in nums) {
Console.WriteLine("{0} (sma3) {1,-16} (sma5) {2,-16}", n, sma3(n), sma5(n));
}
}
static Func<double, double> SMA(int p) {
Queue<double> s = new Queue<double>(p);
return (x) => {
if (s.Count >= p) {
s.Dequeue();
}
s.Enqueue(x);
return s.Average();
};
}
}
}
Output:
1 (sma3) 1 (sma5) 1 2 (sma3) 1.5 (sma5) 1.5 3 (sma3) 2 (sma5) 2 4 (sma3) 3 (sma5) 2.5 5 (sma3) 4 (sma5) 3 5 (sma3) 4.66666666666667 (sma5) 3.8 4 (sma3) 4.66666666666667 (sma5) 4.2 3 (sma3) 4 (sma5) 4.2 2 (sma3) 3 (sma5) 3.8 1 (sma3) 2 (sma5) 3
[edit] Clojure
This version uses a persistent queue to hold the most recent p values. Each function returned from init-moving-average has its state in an atom holding a queue value.
(import '[clojure.lang PersistentQueue])
(defn enqueue-max [q p n]
(let [q (conj q n)]
(if (<= (count q) p) q (pop q))))
(defn avg [coll] (/ (reduce + coll) (count coll)))
(defn init-moving-avg [p]
(let [state (atom PersistentQueue/EMPTY)]
(fn [n]
(avg (swap! state enqueue-max p n)))))
[edit] Common Lisp
This implementation uses a circular list to store the numbers within the window; at the beginning of each iteration pointer refers to the list cell which holds the value just moving out of the window and to be replaced with the just-added value.
(defun simple-moving-average (period &aux
(sum 0) (count 0) (values (make-list period)) (pointer values))
(setf (rest (last values)) values) ; construct circularity
(lambda (n)
(when (first pointer)
(decf sum (first pointer))) ; subtract old value
(incf sum n) ; add new value
(incf count)
(setf (first pointer) n)
(setf pointer (rest pointer)) ; advance pointer
(/ sum (min count period))))
[edit] D
import std.stdio ;
import std.traits ;
CommonType!(T, float) delegate(T) Sma(T)(int period) {
alias CommonType!(T, float) R ;
T[] data = new T[](period);
T drop, sum = cast(T) 0 ;
int index, filled ;
foreach(ref e ; data) e = cast(T)0 ; // D initialize float type to NaN
R smaAcc(T v) {
drop = data[index] ;
data[index] = v ;
index = (index + 1) % period ;
sum += ( v - drop ) ;
filled = (filled >= period) ? period : filled + 1 ;
return (cast(R) sum) / filled ;
}
return &smaAcc ;
}
void main() {
auto s3 = Sma!(int)(3) ;
auto s5 = Sma!(double)(5) ;
foreach(e ; [1, 2, 3, 4, 5, 5, 4, 3, 2, 1])
writefln("added %d , 3 period sma = %f , 5 period sma = %f", e, s3(e), s5(e)) ;
}
[edit] E
This implementation produces two (function) objects sharing state. It is idiomatic in E to separate input from output (read from write) rather than combining them into one object.
The structure is the same as the implementation of Standard Deviation#E.
pragma.enable("accumulator")
def makeMovingAverage(period) {
def values := ([null] * period).diverge()
var index := 0
var count := 0
def insert(v) {
values[index] := v
index := (index + 1) %% period
count += 1
}
/** Returns the simple moving average of the inputs so far, or null if there
have been no inputs. */
def average() {
if (count > 0) {
return accum 0 for x :notNull in values { _ + x } / count.min(period)
}
}
return [insert, average]
}
? for period in [3, 5] {
> def [insert, average] := makeMovingAverage(period)
> println(`Period $period:`)
> for value in [1,2,3,4,5,5,4,3,2,1] {
> insert(value)
> println(value, "\t", average())
> }
> println()
> }
Period 3:
1 1.0
2 1.5
3 2.0
4 3.0
5 4.0
5 4.666666666666667
4 4.666666666666667
3 4.0
2 3.0
1 2.0
Period 5:
1 1.0
2 1.5
3 2.0
4 2.5
5 3.0
5 3.8
4 4.2
3 4.2
2 3.8
1 3.0
[edit] Forth
: f+! ( f addr -- ) dup f@ f+ f! ;
: ,f0s ( n -- ) falign 0 do 0e f, loop ;
: period @ ;
: used cell+ ;
: head 2 cells + ;
: sum 3 cells + faligned ;
: ring ( addr -- faddr )
dup sum float+ swap head @ floats + ;
: update ( fvalue addr -- addr )
dup ring f@ fnegate dup sum f+!
fdup dup ring f! dup sum f+!
dup head @ 1+ over period mod over head ! ;
: moving-average
create ( period -- ) dup , 0 , 0 , 1+ ,f0s
does> ( fvalue -- avg )
update
dup used @ over period < if 1 over used +! then
dup sum f@ used @ 0 d>f f/ ;
3 moving-average sma
1e sma f. \ 1.
2e sma f. \ 1.5
3e sma f. \ 2.
4e sma f. \ 3.
[edit] Fortran
Works with: Fortran version 90 and later
program Movavg
implicit none
integer :: i
write (*, "(a)") "SIMPLE MOVING AVERAGE: PERIOD = 3"
do i = 1, 5
write (*, "(a, i2, a, f8.6)") "Next number:", i, " sma = ", sma(real(i))
end do
do i = 5, 1, -1
write (*, "(a, i2, a, f8.6)") "Next number:", i, " sma = ", sma(real(i))
end do
contains
function sma(n)
real :: sma
real, intent(in) :: n
real, save :: a(3) = 0
integer, save :: count = 0
if (count < 3) then
count = count + 1
a(count) = n
else
a = eoshift(a, 1, n)
end if
sma = sum(a(1:count)) / real(count)
end function
end program Movavg
[edit] Groovy
Translation of: Ruby
def simple_moving_average = { size ->
def nums = []
double total = 0.0
return { newElement ->
nums += newElement
oldestElement = nums.size() > size ? nums.remove(0) : 0
total += newElement - oldestElement
total / nums.size()
}
}
ma5 = simple_moving_average(5)
(1..5).each{ printf( "%1.1f ", ma5(it)) }
(5..1).each{ printf( "%1.1f ", ma5(it)) }
Sample output:
1.0 1.5 2.0 2.5 3.0 3.8 4.2 4.2 3.8 3.0
[edit] Haskell
Works with: GHC version 6.10.4
import Data.List
import Control.Arrow
import Control.Monad
sMA p = map (head *** head ).tail.
scanl (\(y,_) -> (id &&& return. av) . (: if length y == p then init y else y)) ([],[])
where av = liftM2 (/) sum (fromIntegral.length)
printSMA n p = mapM_ (\(n,a) -> putStrLn $ "Next number: " ++ show n ++ " Average: " ++ show a)
. take n . sMA p $ [1..5]++[5,4..1]++[3..]
Output:
*Main> sequence_ [putStrLn "Moving Average Period 3:",printSMA 10 3 ,putStrLn "\nMoving Average Period 5:",printSMA 10 5] Moving Average Period 3: Next number: 1.0 Average: 1.0 Next number: 2.0 Average: 1.5 Next number: 3.0 Average: 2.0 Next number: 4.0 Average: 3.0 Next number: 5.0 Average: 4.0 Next number: 5.0 Average: 4.666666666666667 Next number: 4.0 Average: 4.666666666666667 Next number: 3.0 Average: 4.0 Next number: 2.0 Average: 3.0 Next number: 1.0 Average: 2.0 Moving Average Period 5: Next number: 1.0 Average: 1.0 Next number: 2.0 Average: 1.5 Next number: 3.0 Average: 2.0 Next number: 4.0 Average: 2.5 Next number: 5.0 Average: 3.0 Next number: 5.0 Average: 3.8 Next number: 4.0 Average: 4.2 Next number: 3.0 Average: 4.2 Next number: 2.0 Average: 3.8 Next number: 1.0 Average: 3.0
[edit] HicEst
REAL :: n=10, nums(n)
nums = (1,2,3,4,5, 5,4,3,2,1)
DO i = 1, n
WRITE() "num=", i, "SMA3=", SMA(3,nums(i)), "SMA5=",SMA(5,nums(i))
ENDDO
END ! of "main"
FUNCTION SMA(period, num) ! maxID independent streams
REAL :: maxID=10, now(maxID), Periods(maxID), Offsets(maxID), Pool(1000)
ID = INDEX(Periods, period)
IF( ID == 0) THEN ! initialization
IDs = IDs + 1
ID = IDs
Offsets(ID) = SUM(Periods) + 1
Periods(ID) = period
ENDIF
now(ID) = now(ID) + 1
ALIAS(Pool,Offsets(ID), Past,Periods(ID)) ! renames relevant part of data pool
Past = Past($+1) ! shift left
Past(Periods(ID)) = num
SMA = SUM(Past) / MIN( now(ID), Periods(ID) )
END
num=1 SMA3=1 SMA5=1 num=2 SMA3=1.5 SMA5=1.5 num=3 SMA3=2 SMA5=2 num=4 SMA3=3 SMA5=2.5 num=5 SMA3=4 SMA5=3 num=6 SMA3=4.666666667 SMA5=3.8 num=7 SMA3=4.666666667 SMA5=4.2 num=8 SMA3=4 SMA5=4.2 num=9 SMA3=3 SMA5=3.8 num=10 SMA3=2 SMA5=3
[edit] Icon and Unicon
[edit] Unicon
procedure main(A)
sma := buildSMA(3) # Use better name than "I".
every write(sma(!A))
end
procedure buildSMA(P)
local stream
c := create {
stream := []
while n := (avg@&source)[1] do {
put(stream, n)
if *stream > P then pop(stream)
every (avg := 0.0) +:= !stream
avg := avg/*stream
}
}
return (@c, c)
end
and a sample run:
->ravg 3 1 4 1 5 9 2 6 3 8 3.0 2.0 2.666666666666667 2.0 3.333333333333333 5.0 5.333333333333333 5.666666666666667 3.666666666666667 5.666666666666667 ->
If the Utils package is imported from the Unicon code library then another solution is:
import Utils
procedure main(A)
sma1 := closure(SMA,[],3)
sma2 := closure(SMA,[],4)
every every n := !A do write(left(sma1(n),20), sma2(n))
end
procedure SMA(stream,P,n)
put(stream, n)
if *stream > P then pop(stream)
every (avg := 0.0) +:= !stream
return avg / *stream
end
with the sample run:
->ravg 3 1 4 1 5 9 2 6 3 8 3.0 3.0 2.0 2.0 2.666666666666667 2.666666666666667 2.0 2.25 3.333333333333333 2.75 5.0 4.75 5.333333333333333 4.25 5.666666666666667 5.5 3.666666666666667 5.0 5.666666666666667 4.75 ->
[edit] J
Note: J is block-oriented, not stream oriented. That is, J expresses algorithms with the semantics that all the data is available at once (rather than maintaining state and waiting for the next item).
In that context, moving average is expressed very concisely in J as (+/%#)\, though it is worth noting that this approach does not provide averages for the initial cases where not all data would be available yet:
5 (+/%#)\ 1 2 3 4 5 5 4 3 2 1 NB. not a solution for this task
3 3.8 4.2 4.2 3.8 3
In the context of the task, we need to produce a stateful function to consume streams. Since J does not have native lexical closure, we need to implement it. Thus the streaming solution is more complex:
lex =: 1 :'(a[n__a=.m#_.[a=.18!:3$~0)&(4 :''(+/%#)(#~1-128!:5)n__x=.1|.!.y n__x'')'
Example:
sma =: 5 lex
sma&> 1 2 3 4 5 5 4 3 2 1
1 1.5 2 2.5 3 3.8 4.2 4.2 3.8 3
Here, the &> is analogous to the "for each" of other languages.
[edit] Java
Works with: Java version 1.5+
import java.util.LinkedList;
import java.util.Queue;
public class MovingAverage {
private final Queue<Double> window = new LinkedList<Double>();
private final int period;
private double sum;
public MovingAverage(int period) {
assert period > 0 : "Period must be a positive integer";
this.period = period;
}
public void newNum(double num) {
sum += num;
window.add(num);
if (window.size() > period) {
sum -= window.remove();
}
}
public double getAvg() {
if (window.isEmpty()) return 0; // technically the average is undefined
return sum / window.size();
}
public static void main(String[] args) {
double[] testData = {1,2,3,4,5,5,4,3,2,1};
int[] windowSizes = {3,5};
for (int windSize : windowSizes) {
MovingAverage ma = new MovingAverage(windSize);
for (double x : testData) {
ma.newNum(x);
System.out.println("Next number = " + x + ", SMA = " + ma.getAvg());
}
System.out.println();
}
}
}
Output:
Next number = 1.0, SMA = 1.0 Next number = 2.0, SMA = 1.5 Next number = 3.0, SMA = 2.0 Next number = 4.0, SMA = 3.0 Next number = 5.0, SMA = 4.0 Next number = 5.0, SMA = 4.666666666666667 Next number = 4.0, SMA = 4.666666666666667 Next number = 3.0, SMA = 4.0 Next number = 2.0, SMA = 3.0 Next number = 1.0, SMA = 2.0 Next number = 1.0, SMA = 1.0 Next number = 2.0, SMA = 1.5 Next number = 3.0, SMA = 2.0 Next number = 4.0, SMA = 2.5 Next number = 5.0, SMA = 3.0 Next number = 5.0, SMA = 3.8 Next number = 4.0, SMA = 4.2 Next number = 3.0, SMA = 4.2 Next number = 2.0, SMA = 3.8 Next number = 1.0, SMA = 3.0
[edit] JavaScript
function simple_moving_averager(period) {
var nums = [];
return function(num) {
nums.push(num);
if (nums.length > period)
nums.splice(0,1); // remove the first element of the array
var sum = 0;
for (var i in nums)
sum += nums[i];
var n = period;
if (nums.length < period)
n = nums.length;
return(sum/n);
}
}
var sma3 = simple_moving_averager(3);
var sma5 = simple_moving_averager(5);
var data = [1,2,3,4,5,5,4,3,2,1];
for (var i in data) {
var n = data[i];
// using WSH
WScript.Echo("Next number = " + n + ", SMA_3 = " + sma3(n) + ", SMA_5 = " + sma5(n));
}
output:
Next number = 1, SMA_3 = 1, SMA_5 = 1 Next number = 2, SMA_3 = 1.5, SMA_5 = 1.5 Next number = 3, SMA_3 = 2, SMA_5 = 2 Next number = 4, SMA_3 = 3, SMA_5 = 2.5 Next number = 5, SMA_3 = 4, SMA_5 = 3 Next number = 5, SMA_3 = 4.666666666666667, SMA_5 = 3.8 Next number = 4, SMA_3 = 4.666666666666667, SMA_5 = 4.2 Next number = 3, SMA_3 = 4, SMA_5 = 4.2 Next number = 2, SMA_3 = 3, SMA_5 = 3.8 Next number = 1, SMA_3 = 2, SMA_5 = 3
[edit] Logo
Although Logo does not support closures, some varieties of Logo support enough metaprogramming to accomplish this task.
Works with: UCB Logo
UCB Logo has a DEFINE primitive to construct functions from structured instruction lists. In addition, UCB Logo supports a compact template syntax for quoting lists (backquote "`") and replacing components of quoted lists (comma ","). These facilities can be used together in order to create templated function-defining-functions.
to average :l
output quotient apply "sum :l count :l
end
to make.sma :name :period
localmake "qn word :name ".queue
make :qn []
define :name `[ [n] ; parameter list
[if equal? count :,:qn ,:period [ignore dequeue ",:qn]]
[queue ",:qn :n]
[output average :,:qn]
]
end
make.sma "avg3 3
show map "avg3 [1 2 3 4 5] ; [1 1.5 2 3 4]
show text "avg3 ; examine what substitutions took place
[[n] [if equal? count :avg3.queue 3 [ignore dequeue "avg3.queue]] [queue "avg3.queue :n] [output average :avg3.queue]]
; the internal queue is in the global namespace, easy to inspect
show :avg3.queue ; [3 4 5]
If namespace pollution is a concern, UCB Logo supplies a GENSYM command to obtain unique names in order to avoid collisions.
...
localmake "qn word :name gensym
...
; list user-defined functions and variables
show procedures ; [average avg3 make.sma]
show names ; [[[] [avg3.g1]]
[edit] Lua
do
local t = {}
function f(a, b, ...) if b then return f(a+b, ...) else return a end end
function average(n)
if #t == 10 then table.remove(t, 1) end
t[#t + 1] = n
return f(unpack(t)) / #t
end
end
for v=1,30 do print(average(v)) end
[edit] OCaml
let sma (n, s, q) x =
let l = Queue.length q and s = s +. x in
Queue.push x q;
if l < n then
(n, s, q), s /. float (l + 1)
else (
let s = s -. Queue.pop q in
(n, s, q), s /. float l
)
let _ =
let periodLst = [ 3; 5 ] in
let series = [ 1.; 2.; 3.; 4.; 5.; 5.; 4.; 3.; 2.; 1. ] in
List.iter (fun d ->
Printf.printf "SIMPLE MOVING AVERAGE: PERIOD = %d\n" d;
ignore (
List.fold_left (fun o x ->
let o, m = sma o x in
Printf.printf "Next number = %-2g, SMA = %g\n" x m;
o
) (d, 0., Queue.create ()) series;
);
print_newline ();
) periodLst
Output:
SIMPLE MOVING AVERAGE: PERIOD = 3 Next number = 1 , SMA = 1 Next number = 2 , SMA = 1.5 Next number = 3 , SMA = 2 Next number = 4 , SMA = 3 Next number = 5 , SMA = 4 Next number = 5 , SMA = 4.66667 Next number = 4 , SMA = 4.66667 Next number = 3 , SMA = 4 Next number = 2 , SMA = 3 Next number = 1 , SMA = 2 SIMPLE MOVING AVERAGE: PERIOD = 5 Next number = 1 , SMA = 1 Next number = 2 , SMA = 1.5 Next number = 3 , SMA = 2 Next number = 4 , SMA = 2.5 Next number = 5 , SMA = 3 Next number = 5 , SMA = 3.8 Next number = 4 , SMA = 4.2 Next number = 3 , SMA = 4.2 Next number = 2 , SMA = 3.8 Next number = 1 , SMA = 3
More imperatively:
let sma_create period =
let q = Queue.create ()
and sum = ref 0.0 in
fun x ->
sum := !sum +. x;
Queue.push x q;
if Queue.length q > period then
sum := !sum -. Queue.pop q;
!sum /. float (Queue.length q)
let () =
let periodLst = [ 3; 5 ] in
let series = [ 1.; 2.; 3.; 4.; 5.; 5.; 4.; 3.; 2.; 1. ] in
List.iter (fun d ->
Printf.printf "SIMPLE MOVING AVERAGE: PERIOD = %d\n" d;
let sma = sma_create d in
List.iter (fun x ->
Printf.printf "Next number = %-2g, SMA = %g\n" x (sma x);
) series;
print_newline ();
) periodLst
[edit] Mathematica
This version uses a list entry so it can use the built-in function.
MA[x_List, r_] := Join[Table[Mean[x[[1;;y]]],{y,r-1}], MovingAverage[x,r]]
This version is stateful instead.
MAData = {{}, 0};
MAS[x_, t_: Null] :=
With[{r = If[t === Null, MAData[[2]], t]},
Mean[MAData[[1]] =
If[Length[#] > (MAData[[2]] = r), #[[-r ;; -1]], #] &@
Append[MAData[[1]], x]]]
Tests:
MA[{1, 2, 3, 4, 5, 5, 4, 3, 2, 1}, 5]
=> {1, 3/2, 2, 5/2, 3, 19/5, 21/5, 21/5, 19/5, 3}
MAS[1, 5] => 1
MAS[2] => 3/2
MAS[3] => 2
MAS[4] => 5/2
MAS[5] => 3
MAS[5] => 19/5
MAS[4] => 21/5
MAS[3] => 21/5
MAS[2] => 19/5
MAS[1] => 3
[edit] Oz
declare
fun {CreateSMA Period}
Xs = {NewCell nil}
in
fun {$ X}
Xs := {List.take X|@Xs Period}
{FoldL @Xs Number.'+' 0.0}
/
{Int.toFloat {Min Period {Length @Xs}}}
end
end
in
for Period in [3 5] do
SMA = {CreateSMA Period}
in
{System.showInfo "\nSTART PERIOD "#Period}
for I in 1..5 do
{System.showInfo " Number = "#I#" , SMA = "#{SMA {Int.toFloat I}}}
end
for I in 5..1;~1 do
{System.showInfo " Number = "#I#" , SMA = "#{SMA {Int.toFloat I}}}
end
end
[edit] Perl
sub sma ($)
{my ($period, $sum, @a) = shift, 0;
return sub
{unshift @a, shift;
$sum += $a[0];
@a > $period and $sum -= pop @a;
return $sum / @a;}}
[edit] Perl 6
Works with: Rakudo Star version 2010-08
sub sma (Int $period where (* > 0)) returns Sub {
my $sum = 0;
my @a;
return sub ($x) {
@a.push: $x;
$sum += $x;
$sum -= @a.shift if @a > $period;
return $sum / @a;
}
}
[edit] PL/I
SMA: procedure (N) returns (float byaddr);
declare N fixed;
declare A(*) fixed controlled,
(p, q) fixed binary static initial (0);
if allocation(A) = 0 then signal error;
p = p + 1; if q < 20 then q = q + 1;
if p > hbound(A, 1) then p = 1;
A(p) = N;
return (sum(float(A))/q);
I: ENTRY (Period);
declare Period fixed binary;
if allocation(A) > 0 then FREE A;
allocate A(Period);
A = 0;
p = 0;
end SMA;
[edit] PicoLisp
(de sma (@Len)
(let Data NIL
(curry (@Len Data) (N)
(push 'Data N)
(and (nth Data @Len) (con @)) # Truncate
(*/ (apply + Data) (length Data)) ) ) )
(def 'sma3 (sma 3))
(def 'sma5 (sma 5))
(scl 2)
(for N (1.0 2.0 3.0 4.0 5.0 5.0 4.0 3.0 2.0 1.0)
(prinl
(format N *Scl)
" (sma3) "
(format (sma3 N) *Scl)
" (sma5) "
(format (sma5 N) *Scl) ) )
Output:
1.00 (sma3) 1.00 (sma5) 1.00 2.00 (sma3) 1.50 (sma5) 1.50 3.00 (sma3) 2.00 (sma5) 2.00 4.00 (sma3) 3.00 (sma5) 2.50 5.00 (sma3) 4.00 (sma5) 3.00 5.00 (sma3) 4.67 (sma5) 3.80 4.00 (sma3) 4.67 (sma5) 4.20 3.00 (sma3) 4.00 (sma5) 4.20 2.00 (sma3) 3.00 (sma5) 3.80 1.00 (sma3) 2.00 (sma5) 3.00
[edit] PureBasic
Procedure.d SMA(Number, Period=0)
Static P
Static NewList L()
Protected Sum=0
If Period<>0
P=Period
EndIf
LastElement(L())
AddElement(L())
L()=Number
While ListSize(L())>P
FirstElement(L())
DeleteElement(L(),1)
Wend
ForEach L()
sum+L()
Next
ProcedureReturn sum/ListSize(L())
EndProcedure
[edit] Python
Works with: Python version 3.x
Both implementations use the deque datatype.
[edit] Procedural
from collections import deque
def simplemovingaverage(period):
assert period == int(period) and period > 0, "Period must be an integer >0"
summ = n = 0.0
values = deque([0.0] * period) # old value queue
def sma(x):
nonlocal summ, n
values.append(x)
summ += x - values.popleft()
n = min(n+1, period)
return summ / n
return sma
[edit] Class based
from collections import deque
class Simplemovingaverage():
def __init__(self, period):
assert period == int(period) and period > 0, "Period must be an integer >0"
self.period = period
self.stream = deque()
def __call__(self, n):
stream = self.stream
stream.append(n) # appends on the right
streamlength = len(stream)
if streamlength > self.period:
stream.popleft()
streamlength -= 1
if streamlength == 0:
average = 0
else:
average = sum( stream ) / streamlength
return average
Tests
if __name__ == '__main__':
for period in [3, 5]:
print ("\nSIMPLE MOVING AVERAGE (procedural): PERIOD =", period)
sma = simplemovingaverage(period)
for i in range(1,6):
print (" Next number = %-2g, SMA = %g " % (i, sma(i)))
for i in range(5, 0, -1):
print (" Next number = %-2g, SMA = %g " % (i, sma(i)))
for period in [3, 5]:
print ("\nSIMPLE MOVING AVERAGE (class based): PERIOD =", period)
sma = Simplemovingaverage(period)
for i in range(1,6):
print (" Next number = %-2g, SMA = %g " % (i, sma(i)))
for i in range(5, 0, -1):
print (" Next number = %-2g, SMA = %g " % (i, sma(i)))
Sample output
SIMPLE MOVING AVERAGE (procedural): PERIOD = 3 Next number = 1 , SMA = 1 Next number = 2 , SMA = 1.5 Next number = 3 , SMA = 2 Next number = 4 , SMA = 3 Next number = 5 , SMA = 4 Next number = 5 , SMA = 4.66667 Next number = 4 , SMA = 4.66667 Next number = 3 , SMA = 4 Next number = 2 , SMA = 3 Next number = 1 , SMA = 2 SIMPLE MOVING AVERAGE (procedural): PERIOD = 5 Next number = 1 , SMA = 1 Next number = 2 , SMA = 1.5 Next number = 3 , SMA = 2 Next number = 4 , SMA = 2.5 Next number = 5 , SMA = 3 Next number = 5 , SMA = 3.8 Next number = 4 , SMA = 4.2 Next number = 3 , SMA = 4.2 Next number = 2 , SMA = 3.8 Next number = 1 , SMA = 3 SIMPLE MOVING AVERAGE (class based): PERIOD = 3 Next number = 1 , SMA = 1 Next number = 2 , SMA = 1.5 Next number = 3 , SMA = 2 Next number = 4 , SMA = 3 Next number = 5 , SMA = 4 Next number = 5 , SMA = 4.66667 Next number = 4 , SMA = 4.66667 Next number = 3 , SMA = 4 Next number = 2 , SMA = 3 Next number = 1 , SMA = 2 SIMPLE MOVING AVERAGE (class based): PERIOD = 5 Next number = 1 , SMA = 1 Next number = 2 , SMA = 1.5 Next number = 3 , SMA = 2 Next number = 4 , SMA = 2.5 Next number = 5 , SMA = 3 Next number = 5 , SMA = 3.8 Next number = 4 , SMA = 4.2 Next number = 3 , SMA = 4.2 Next number = 2 , SMA = 3.8 Next number = 1 , SMA = 3
[edit] R
This is easiest done with two functions: one to handle the state (i.e. the numbers already entered), and one to calculate the average.
#concat concatenates the new values to the existing vector of values, then discards any values that are too old.
lastvalues <- local(
{
values <- c();
function(x, len)
{
values <<- c(values, x);
lenv <- length(values);
if(lenv > len) values <<- values[(len-lenv):-1]
values
}
})
#moving.average accepts a numeric scalars input (and optionally a length, i.e. the number of values to retain) and calculates the stateful moving average.
moving.average <- function(latestvalue, len=3)
{
#Check that all inputs are numeric scalars
is.numeric.scalar <- function(x) is.numeric(x) && length(x)==1L
if(!is.numeric.scalar(latestvalue) || !is.numeric.scalar(len))
{
stop("all arguments must be numeric scalars")
}
#Calculate mean of variables so far
mean(lastvalues(latestvalue, len))
}
moving.average(5) # 5
moving.average(1) # 3
moving.average(-3) # 1
moving.average(8) # 2
moving.average(7) # 4
[edit] Ruby
A closure:
def simple_moving_average(size)
nums = []
sum = 0.0
lambda do |hello|
nums << hello
goodbye = nums.length > size ? nums.shift : 0
sum += hello - goodbye
sum / nums.length
end
end
ma3 = simple_moving_average(3)
ma5 = simple_moving_average(5)
(1.upto(5).to_a + 5.downto(1).to_a).each do |num|
printf "Next number = %d, SMA_3 = %.3f, SMA_5 = %.1f\n",
num, ma3.call(num), ma5.call(num)
end
A class
class MovingAverager
def initialize(size)
@size = size
@nums = []
@sum = 0.0
end
def <<(hello)
@nums << hello
goodbye = @nums.length > @size ? @nums.shift : 0
@sum += hello - goodbye
self
end
def average
@sum / @nums.length
end
alias to_f average
def to_s
average.to_s
end
end
ma3 = MovingAverager.new(3)
ma5 = MovingAverager.new(5)
(1.upto(5).to_a + 5.downto(1).to_a).each do |num|
printf "Next number = %d, SMA_3 = %.3f, SMA_5 = %.1f\n",
num, ma3 << num, ma5 <<num
end
[edit] Scala
class MovingAverage(period: Int) {
private var queue = new scala.collection.mutable.Queue[Double]()
def apply(n: Double) = {
queue.enqueue(n)
if (queue.size > period)
queue.dequeue
queue.sum / queue.size
}
override def toString = queue.mkString("(", ", ", ")")+", period "+period+", average "+(queue.sum / queue.size)
def clear = queue.clear
}
scala> List(3,5) foreach { period =>
| println("SIMPLE MOVING AVERAGE: PERIOD = "+period)
| val sma = new MovingAverage(period)
| 1.0 to 5.0 by 1.0 foreach {i => println(" Next number = %-2g, SMA = %g " format (i, sma(i)))}
| 5.0 to 1.0 by -1.0 foreach {i => println(" Next number = %-2g, SMA = %g " format (i, sma(i)))}
| println(sma+"\n")
| }
SIMPLE MOVING AVERAGE: PERIOD = 3
Next number = 1.00000, SMA = 1.00000
Next number = 2.00000, SMA = 1.50000
Next number = 3.00000, SMA = 2.00000
Next number = 4.00000, SMA = 3.00000
Next number = 5.00000, SMA = 4.00000
Next number = 5.00000, SMA = 4.66667
Next number = 4.00000, SMA = 4.66667
Next number = 3.00000, SMA = 4.00000
Next number = 2.00000, SMA = 3.00000
Next number = 1.00000, SMA = 2.00000
(3.0, 2.0, 1.0), period 3, average 2.0
SIMPLE MOVING AVERAGE: PERIOD = 5
Next number = 1.00000, SMA = 1.00000
Next number = 2.00000, SMA = 1.50000
Next number = 3.00000, SMA = 2.00000
Next number = 4.00000, SMA = 2.50000
Next number = 5.00000, SMA = 3.00000
Next number = 5.00000, SMA = 3.80000
Next number = 4.00000, SMA = 4.20000
Next number = 3.00000, SMA = 4.20000
Next number = 2.00000, SMA = 3.80000
Next number = 1.00000, SMA = 3.00000
(5.0, 4.0, 3.0, 2.0, 1.0), period 5, average 3.0
[edit] Scheme
(define ((simple-moving-averager size . nums) num)
(set! nums (cons num (if (= (length nums) size) (reverse (cdr (reverse nums))) nums)))
(/ (apply + nums) (length nums)))
(define av (simple-moving-averager 3))
(map av '(1 2 3 4 5 5 4 3 2 1))
Output:
(1 3/2 2 3 4 14/3 14/3 4 3 2)
[edit] Smalltalk
Works with: GNU Smalltalk
Object subclass: MovingAverage [
|valueCollection period collectedNumber sum|
MovingAverage class >> newWithPeriod: thePeriod [
|r|
r := super basicNew.
^ r initWithPeriod: thePeriod
]
initWithPeriod: thePeriod [
valueCollection := OrderedCollection new: thePeriod.
period := thePeriod.
collectedNumber := 0.
sum := 0
]
sma [ collectedNumber < period
ifTrue: [ ^ sum / collectedNumber ]
ifFalse: [ ^ sum / period ] ]
add: value [
collectedNumber < period
ifTrue: [
sum := sum + value.
valueCollection add: value.
collectedNumber := collectedNumber + 1.
]
ifFalse: [
sum := sum - (valueCollection removeFirst).
sum := sum + value.
valueCollection add: value
].
^ self sma
]
].
|sma3 sma5|
sma3 := MovingAverage newWithPeriod: 3.
sma5 := MovingAverage newWithPeriod: 5.
#( 1 2 3 4 5 5 4 3 2 1 ) do: [ :v |
('Next number %1, SMA_3 = %2, SMA_5 = %3' % {
v . (sma3 add: v) asFloat . (sma5 add: v) asFloat
}) displayNl
]
[edit] Tcl
Works with: Tcl version 8.6 or Library: TclOO
oo::class create SimpleMovingAverage {
variable vals idx
constructor {{period 3}} {
set idx end-[expr {$period-1}]
set vals {}
}
method val x {
set vals [lrange [list {*}$vals $x] $idx end]
expr {[tcl::mathop::+ {*}$vals]/double([llength $vals])}
}
}
Demonstration:
SimpleMovingAverage create averager3
SimpleMovingAverage create averager5 5
foreach n {1 2 3 4 5 5 4 3 2 1} {
puts "Next number = $n, SMA_3 = [averager3 val $n], SMA_5 = [averager5 val $n]"
}
Output:
Next number = 1, SMA_3 = 1.0, SMA_5 = 1.0 Next number = 2, SMA_3 = 1.5, SMA_5 = 1.5 Next number = 3, SMA_3 = 2.0, SMA_5 = 2.0 Next number = 4, SMA_3 = 3.0, SMA_5 = 2.5 Next number = 5, SMA_3 = 4.0, SMA_5 = 3.0 Next number = 5, SMA_3 = 4.666666666666667, SMA_5 = 3.8 Next number = 4, SMA_3 = 4.666666666666667, SMA_5 = 4.2 Next number = 3, SMA_3 = 4.0, SMA_5 = 4.2 Next number = 2, SMA_3 = 3.0, SMA_5 = 3.8 Next number = 1, SMA_3 = 2.0, SMA_5 = 3.0
[edit] TI-83 BASIC
Prompts for a source list A and the length K of the moving average. The 'L' in "LB" and "LB" is found in "List"/"OPS".
:Prompt LA,K
:
:For(I,1,dim(LA))
:0→S
:For(J,I-K+1,I)
:If J≥1
:S+LA(J)→S
:End
:S/K→LB(I)
:End
[edit] TI-89 BASIC
Function that returns a list containging the averaged data of the supplied argument
movinavg(list,p)
Func
Local r, i, z
For i,1,dim(list)
max(i-p,0)→z
sum(mid(list,z+1,i-z))/(i-z)→r[i]
EndFor
r
EndFunc
Program that returns a simple value at each invocation:
movinav2(x_,v_)
Prgm
If getType(x_)="STR" Then
{}→list
v_→p
Return
EndIf
right(augment(list,{x_}),p)→list
sum(list)/dim(list)→#v_
EndPrgm
Example1: Using the function
movinavg({1,2,3,4,5,6,7,8,9,10},5)
list is the list being averaged: {1,2,3,4,5,6,7,8,9,10}
p is the period: 5
returns the averaged list: {1, 3/2, 2, 5/2, 3, 4, 5, 6, 7, 8}
Example 2: Using the program
movinav2("i",5) - Initializing moving average calculation, and define period of 5
movinav2(3, "x"):x - new data in the list (value 3), and result will be stored on variable x, and displayed
movinav2(4, "x"):x - new data (value 4), and the new result will be stored on variable x, and displayed (4+3)/2
...
Description of the function movinavg:
variable r - is the result (the averaged list) that will be returned
variable i - is the index variable, and it points to the end of the sub-list the list being averaged.
variable z - an helper variable
The function uses variable i to determine which values of the list will be considered in the next average calculation.
At every iteration, variable i points to the last value in the list that will be used in the average calculation.
So we only need to figure out which will be the first value in the list.
Usually we'll have to consider p elements, so the first element will be the one indexed by (i-p+1).
However on the first iterations that calculation will usually be negative, so the following equation will avoid negative indexes: max(i-p+1,1) or, arranging the equation, max(i-p,0)+1.
But the number of elements on the first iterations will also be smaller, the correct value will be (end index - begin index + 1) or, arranging the equation, (i - (max(i-p,0)+1) +1) ,and then, (i-max(i-p,0)).
Variable z holds the common value (max(i-p),0) so the begin_index will be (z+1) and the number_of_elements will be (i-z)
mid(list,z+1, i-z) will return the list of value that will be averaged
sum(...) will sum them
sum(...)/(i-z) → r[i] will average them and store the result in the appropriate place in the result list
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