Averages/Simple moving average: Difference between revisions

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'''Description'''<br>

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().

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:

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end Main;</lang>

Output:

<pre>Inserting 1 into max-3: 1.00000E+00

Inserting 1 into max-5: 1.00000E+00

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sma(SMAFREE(h5))

#

)</lang>~~Output:~~

)</lang>

<pre>

next number 1.000000, SMA_3 = 1.000000, SMA_5 = 1.000000

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IF window%(period%)<period% window%(period%) += 1

= accum(period%) / window%(period%)</lang>

Output:

<pre>

Number = 1 SMA3 = 1 SMA5 = 1

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)

);</lang>

Output:

<pre>1 - sma3: 1 sma5: 1

2 - sma3: 3/2 sma5: 3/2

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}</lang>

Output:

<pre>1 - SMA3: 1 SMA5: 1

2 - SMA3: 1.5 SMA5: 1.5

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}</lang>

Output:

<pre>

1 (sma3) 1 (sma5) 1

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console.log i, sma3(i), sma7(i), sma11(i)

</lang>

⚫

output

<~~lang~~>

<pre>

> coffee moving_average.coffee

1 1 1 1

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9 8 6 5

10 9 7 5.5

</~~lang~~>

</pre>

=={{header|Common Lisp}}==

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===Using a Struct===

This version avoids the heap allocation of the closure ~~keeping the data in the stack frame of the main function. Same output:~~

This version avoids the heap allocation of the closure

keeping the data in the stack frame of the main function.

⚫

Same output:

<lang d>import std.stdio, std.traits, std.algorithm;

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=={{header|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.~~

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]].

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end.</lang>

Output:

<lang erlang>9> sma:main().

Added 1, sma(3) -> 1.000000, sma(5) -> 1.000000

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[ 1.;2.;3.;4.;5.;5.;4.;3.;2.;1.] |> sma 5 (printf "%.2f ")

printfn ""</lang>

~~Output:~~<pre>sma3: 1.00 1.50 2.00 3.00 4.00 4.67 4.67 4.00 3.00 2.00

<pre>sma3: 1.00 1.50 2.00 3.00 4.00 4.67 4.67 4.00 3.00 2.00

sma5: 1.00 1.50 2.00 2.50 3.00 3.80 4.20 4.20 3.80 3.00</pre>

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</lang>

~~Sample output~~ for a period of 5:

{{out}} for a period of 5:

<pre>

After 0 numbers list is [,] average is 0.0

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}

}</lang>

Output:

<pre>

x sma3 sma5

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(1..5).each{ printf( "%1.1f ", ma5(it)) }

(5..1).each{ printf( "%1.1f ", ma5(it)) }</lang>

Sample output:

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putStrLn $ "Next number = " ++ (show n) ++ ", SMA_3 = " ++ (show mm3) ++ ", SMA_5 = " ++ (show mm5)

)</lang>

output:

<pre>Next number = 1.0, SMA_3 = 1.0, SMA_5 = 1.0

Next number = 2.0, SMA_3 = 1.5, SMA_5 = 1.5

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}

}</lang>

Output:

<pre>Next number = 1.0, SMA = 1.0

Next number = 2.0, SMA = 1.5

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WScript.Echo("Next number = " + n + ", SMA_3 = " + sma3(n) + ", SMA_5 = " + sma5(n));

}</lang>

output:

<pre>Next number = 1, SMA_3 = 1, SMA_5 = 1

Next number = 2, SMA_3 = 1.5, SMA_5 = 1.5

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return

</lang>

'''Output:'''

Next number = 1.0, SMA = 1.000000000

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for i in 1..5: echo sma2(float(i))

for i in countdown(5,1): echo sma2(float(i))</lang>

Output:

<pre>1.0000000000000000e+00

1.5000000000000000e+00

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</lang>

Output:

<pre>

Next number = 1.0, SMA = 1.0

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) periodLst</lang>

Output:

<pre>

SIMPLE MOVING AVERAGE: PERIOD = 3

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return sum / queue~items

</lang>

Output:

<pre>

Period size = 3

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" (sma5) "

(format (sma5 N) *Scl) ) )</lang>

Output:

<pre>1.00 (sma3) 1.00 (sma5) 1.00

2.00 (sma3) 1.50 (sma5) 1.50

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print (" Next number = %-2g, SMA = %g " % (i, sma(i)))</lang>

'''Sample output'''

<pre>SIMPLE MOVING AVERAGE (procedural): PERIOD = 3

Next number = 1 , SMA = 1

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end

return s/i</lang>

~~'''output'''~~ using the defaults

{{out}} using the defaults

item 1= 1

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(map av '(1 2 3 4 5 5 4 3 2 1))

</lang>

Output:

<pre>

(1 3/2 2 3 4 14/3 14/3 4 3 2)

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puts "Next number = $n, SMA_3 = [averager3 val $n], SMA_5 = [averager5 val $n]"

}</lang>

Output:

<pre>Next number = 1, SMA_3 = 1.0, SMA_5 = 1.0

Next number = 2, SMA_3 = 1.5, SMA_5 = 1.5