Simple Moving Average - Algorithm by TimeSeries

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Simple Moving Average This algorithm creates a Simple Moving Average for a time series. Table of Contents Introduction Inputs Outputs Algorithm Console Introduction This algorthm creates a simple moving average over the previous K datapoints in a timeseries graph. Inputs This algorithm has two input formats; JSON Formatting and Array Formatting. JSON Format { 
 "data":Double[],
 "lagTime": Int,
}
 { 
 "data": [0,1,2,3,4,5,6,20,8,9,10,11,12],
 "lagTime": 5
}
 data - _(required)_ - The timeseries input data you wish to create a simple moving average for, this algorithm assumes the values are evenly spaced. ( dx(1) == dx(n) ) lagTime - _(optional)_ - The lagtime for the average, if there is a lag of n, each point is replaced by the average of itself and the n points that proceeded it, or, if the point is within the lag factor of the the start of the series, with the average of it and all earlier points. Array Format [
 data: Double[],
 lagTime: Int
]
 [[0,1,2,3,4,5,6,20,8,9,10,11,12],5]
 data - _(required)_ - The timeseries input data you wish to create a simple moving average for, this algorithm assumes the values are evenly spaced. ( dx(1) == dx(n) ) lagTime - _(optional)_ - The lagtime for the average, if there is a lag of n, each point is replaced by the average of itself and the n points that proceeded it, or, if the point is within the lag factor of the the start of the series, with the average of it and all earlier points. Outputs This algorithm has json output for json input, and array output for array input. JSON Format { 
 "output": Double[]
}
 { 
 "output": [0, 0.5, 1, 1.5, 2, 3, 4, 7.6, 8.6, 9.6, 10.6, 11.6, 10]
}
 output - The simple moving average for your dataset. Array Format output: Double[]
 { 
 "output": [0, 0.5, 1, 1.5, 2, 3, 4, 7.6, 8.6, 9.6, 10.6, 11.6, 10]
}
 output - The simple moving average for your dataset.

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1. Type your input

2. See the result

Running algorithm...

curl -X POST -d '{{input | formatInput:"curl"}}' -H 'Content-Type: application/json' -H 'Authorization: Simple YOUR_API_KEY' https://api.algorithmia.com/v1/algo/TimeSeries/SimpleMovingAverage/0.2.0

View cURL Docs

algo auth
# Enter API Key: YOUR_API_KEY
algo run algo://TimeSeries/SimpleMovingAverage/0.2.0 -d '{{input | formatInput:"cli"}}'

View CLI Docs

import (
  algorithmia "github.com/algorithmiaio/algorithmia-go"
)

input := {{input | formatInput:"go"}}

var client = algorithmia.NewClient("YOUR_API_KEY", "")
algo, _ := client.Algo("algo://TimeSeries/SimpleMovingAverage/0.2.0")
resp, _ := algo.Pipe(input)
response := resp.(*algorithmia.AlgoResponse)
fmt.Println(response.Result)

View Go Docs

import com.algorithmia.*;
import com.algorithmia.algo.*;

String input = "{{input | formatInput:"java"}}";
AlgorithmiaClient client = Algorithmia.client("YOUR_API_KEY");
Algorithm algo = client.algo("algo://TimeSeries/SimpleMovingAverage/0.2.0");
AlgoResponse result = algo.pipeJson(input);
System.out.println(result.asJsonString());

View Java Docs

import com.algorithmia._
import com.algorithmia.algo._

val input = {{input | formatInput:"scala"}}
val client = Algorithmia.client("YOUR_API_KEY")
val algo = client.algo("algo://TimeSeries/SimpleMovingAverage/0.2.0")
val result = algo.pipeJson(input)
System.out.println(result.asJsonString)

View Scala Docs

var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://TimeSeries/SimpleMovingAverage/0.2.0")
           .pipe(input)
           .then(function(output) {
             console.log(output);
           });

View Javascript Docs

using Algorithmia;

var input = "{{input | formatInput:"cs"}}";
var client = new Client("YOUR_API_KEY");
var algorithm = client.algo("algo://TimeSeries/SimpleMovingAverage/0.2.0");
var response = algorithm.pipe<object>(input);
Console.WriteLine(response.result);

View .NET/C# Docs

var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://TimeSeries/SimpleMovingAverage/0.2.0")
           .pipe(input)
           .then(function(response) {
             console.log(response.get());
           });

View NodeJS Docs

import Algorithmia

input = {{input | formatInput:"python"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('TimeSeries/SimpleMovingAverage/0.2.0')
print algo.pipe(input)

View Python Docs

library(algorithmia)

input <- {{input | formatInput:"r"}}
client <- getAlgorithmiaClient("YOUR_API_KEY")
algo <- client$algo("TimeSeries/SimpleMovingAverage/0.2.0")
result <- algo$pipe(input)$result
print(result)

View R Docs

require 'algorithmia'

input = {{input | formatInput:"ruby"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('TimeSeries/SimpleMovingAverage/0.2.0')
puts algo.pipe(input).result

View Ruby Docs

use algorithmia::Algorithmia;

let input = {{input | formatInput:"rust"}};
let client = Algorithmia::client("YOUR_API_KEY");
let algo = client.algo("TimeSeries/SimpleMovingAverage/0.2.0");
let response = algo.pipe(input);

View Rust Docs

import Algorithmia

let input = "{{input | formatInput:"swift"}}";
let client = Algorithmia.client(simpleKey: "YOUR_API_KEY")
let algo = client.algo(algoUri: "TimeSeries/SimpleMovingAverage/0.2.0") { resp, error in
  print(resp)
}

View Swift Docs

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