Exponential Moving Average - Algorithm by TimeSeries

No algorithm description given

Takes a time series and returns the exponential moving average ( http://en.wikipedia.org/wiki/Moving_average#Exponential_moving_average ). This can be used to smooth or denoise a time series. The user can optionally supply an alpha parameter (specifying how heavily the past is weighted) as second argument. If not supplied a default of 0.5 is used.

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For additional details on how pricing works, see Algorithmia pricing.

Internet access

This algorithm has Internet access. This is necessary for algorithms that rely on external services, however it also implies that this algorithm is able to send your input data outside of the Algorithmia platform.

To understand more about how algorithm permissions work, see the permissions documentation.

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/ExponentialMovingAverage/0.1.0

View cURL Docs

algo auth
# Enter API Key: YOUR_API_KEY
algo run algo://TimeSeries/ExponentialMovingAverage/0.1.0 -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/ExponentialMovingAverage/0.1.0")
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/ExponentialMovingAverage/0.1.0");
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/ExponentialMovingAverage/0.1.0")
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/ExponentialMovingAverage/0.1.0")
           .pipe(input)
           .then(function(output) {
             console.log(output);
           });

View Javascript Docs

var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://TimeSeries/ExponentialMovingAverage/0.1.0")
           .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/ExponentialMovingAverage/0.1.0')
print algo.pipe(input)

View Python Docs

library(algorithmia)

input <- {{input | formatInput:"r"}}
client <- getAlgorithmiaClient("YOUR_API_KEY")
algo <- client$algo("TimeSeries/ExponentialMovingAverage/0.1.0")
result <- algo$pipe(input)$result
print(result)

View R Docs

require 'algorithmia'

input = {{input | formatInput:"ruby"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('TimeSeries/ExponentialMovingAverage/0.1.0')
puts algo.pipe(input).result

View Ruby Docs

use algorithmia::*;

let input = {{input | formatInput:"rust"}};
let client = Algorithmia::client("YOUR_API_KEY");
let algo = client.algo("TimeSeries/ExponentialMovingAverage/0.1.0");
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/ExponentialMovingAverage/0.1.0") { resp, error in
  print(resp)
}

View Swift Docs

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