Fourier Clean

No algorithm description given

This algorithm takes a time series and a parameter k. It takes the Fourier transform of the series, zeroes out the top k weakest frequencies, and maps the result back into a time series with an inverse Fourier transform. This is a speculative algorithm for removing cleaning and smoothing - use it for exploratory analysis but try not to draw too many conclusions unless you corroborate with other methods. This is based on an implementation of the Fast Fourier Transform (in this the real Fourier Transform in the JTranforms library - ) Note that there are many different conventions used in signal processing, so be careful as the ones chosen here may not be the ones you need.

(no tags)

Cost Breakdown

0 cr
royalty per call
1 cr
usage per second
avg duration

Cost Calculator

API call duration (sec)
API calls
Estimated cost
per calls
for large volume discounts
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...

3. Use this algorithm

curl -X POST -d '{{input | formatInput:"curl"}}' -H 'Content-Type: application/json' -H 'Authorization: Simple YOUR_API_KEY'
View cURL Docs
algo auth
algo run algo://TimeSeries/FourierClean/0.1.0 -d '{{input | formatInput:"cli"}}'
View CLI Docs
import (
  algorithmia ""

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

var client = algorithmia.NewClient("YOUR_API_KEY", "")
algo, _ := client.Algo("algo://TimeSeries/FourierClean/0.1.0")
resp, _ := algo.Pipe(input)
response := resp.(*algorithmia.AlgoResponse)
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/FourierClean/0.1.0");
AlgoResponse result = algo.pipeJson(input);
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/FourierClean/0.1.0")
val result = algo.pipeJson(input)
View Scala Docs
var input = {{input | formatInput:"javascript"}};
           .then(function(output) {
View Javascript Docs
var input = {{input | formatInput:"javascript"}};
           .then(function(response) {
View NodeJS Docs
import Algorithmia

input = {{input | formatInput:"python"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('TimeSeries/FourierClean/0.1.0')
print algo.pipe(input)
View Python Docs

input <- {{input | formatInput:"r"}}
client <- getAlgorithmiaClient("YOUR_API_KEY")
algo <- client$algo("TimeSeries/FourierClean/0.1.0")
result <- algo$pipe(input)$result
View R Docs
require 'algorithmia'

input = {{input | formatInput:"ruby"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('TimeSeries/FourierClean/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/FourierClean/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/FourierClean/0.1.0") { resp, error in
View Swift Docs
  • {{comment.username}}