Gregory-Loredo Algorithm

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Computes the Gregory-Loredo algorithm on a list of arrival times This function computes the likelihood of a set of arrival times originating from a periodic process rather than constant rate (Poisson) process (e.g. background noise). based on Gregory, P. C. and Thomas. J. Loredo, 1992, "A New Method For The Detection Of A Periodic Signal Of Unknown Shape And Period" in The Astrophysical Journal, Astrophysical J., 398, p.146 Inputs Tlist (required)- a list of arrival times m_max  (optional, default m_max=12) - number of phase bins w_range (optional, default min(20,N/10)*pi/T, N= number of arrival times, T= max(Tlist)) - frequency range to scan for periodicity ni (optional, default ni=10) - number of bins for numerical integration of the phase from 0:2pi/m parallel (optional, default parallel=False) - parallel execution flag Outputs O_period - odds ratio for periodic process p_period - probability of periodic process (0<=p_period<=1) m_opt - optimal bin size S - spectrum for m_opt w - frequency range of S w_peak - most likely frequency w_mean - mean frequency w_conf - 95% confidence interval of frequency   Other sample inputs:  {"Tlist" : [80,921,2281,5831,6095,7703,8205,8761,11010,11095,14201,22531], "m_max" : 5} {"Tlist" : [80,921,2281,5831,6095,7703,8205,8761,11010,11095,14201,22531],"m_max" :5, "ni" : 20}

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1. Type your input

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3. Use this 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/fdarvas/GregoryLoredoAlgorithm/0.2.0
View cURL Docs
algo auth
# Enter API Key: YOUR_API_KEY
algo run algo://fdarvas/GregoryLoredoAlgorithm/0.2.0 -d '{{input | formatInput:"cli"}}'
View CLI 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://fdarvas/GregoryLoredoAlgorithm/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://fdarvas/GregoryLoredoAlgorithm/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://fdarvas/GregoryLoredoAlgorithm/0.2.0")
           .pipe(input)
           .then(function(output) {
             console.log(output);
           });
View Javascript Docs
var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://fdarvas/GregoryLoredoAlgorithm/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('fdarvas/GregoryLoredoAlgorithm/0.2.0')
print algo.pipe(input)
View Python Docs
library(algorithmia)

input <- {{input | formatInput:"r"}}
client <- getAlgorithmiaClient("YOUR_API_KEY")
algo <- client$algo("fdarvas/GregoryLoredoAlgorithm/0.2.0")
result <- algo$pipe(input)$result
print(result)
View R Docs
require 'algorithmia'

input = {{input | formatInput:"ruby"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('fdarvas/GregoryLoredoAlgorithm/0.2.0')
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('fdarvas/GregoryLoredoAlgorithm/0.2.0');
let response = algo.pipe(input);
View Rust Docs
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