GeosPy: Geolocation Inference Made Easy

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Introduction GeosPy is based off of Jurgens et al. (2015) , implementing state-of-the-art methods for geolocation inference. It allows the user to locate nodes with unknown locations based solely on network-based relationships. Geolocation inference is the identification of the real-world geographic location of an object on Earth based off of available data. GeosPy currently only supports network based inference methods. Input: (Required) : node_location_data: Coordinates for all data points. (Required) : node_connections: Connected nodes. (Required) : infered_nodes: Node(s) that we want to infer. (Optional) : model_type: Type of inference model you want to use. (default = "backstorm")* * Note: Only two type of models are supported: jakartr backstrom Output: Inferred coordinates for asked nodes. Examples Example 1. Parameter 1: Coordinates for all data points. Parameter 2: Node connections. Parameter 3: Nodes asked for inference. {
 "node_location_data": {
 "Tyler": [44, -71.5],
 "Tim": [45.5, -73.5],
 "Gwyn": [44.5, -89.5],
 "Conor":[55.0, -106.0],
 "Sam": [25.7, -80.2]
 "node_connections": {
 "OffTheGrid": ["Tyler", "Sam", "Gwyn", "Conor", "Tim"]
} Output: {
 "OffTheGrid": [45.5, -73.5]
} Example 2. Parameter 1: Coordinates for all data points. Parameter 2: Node connections. Parameter 3: Node asked for inference. Parameter 4: Model type used for inference. {
 "node_location_data": {
 "Tyler": [44, -71.5],
 "Tim": [45.5, -73.5],
 "Gwyn": [44.5, -89.5],
 "Conor":[55.0, -106.0],
 "Sam": [25.7, -80.2]
 "node_connections": {
 "James": ["Gwyn", "Conor", "Tim"],
 "Patrick": ["Tyler", "Sam"]
 "model_type": "backstrom"
} Output: {
 "James": [44.5,-89.5],
 "Patrick": [44,-71.5]
} Credits For more information, please refer to: or  Geolocation Prediction in Twitter Using Social Networks: A Critical Analysis and Review of Current Practice by David Jurgens, Tyler Finnethy, James McCorriston, Yi Tian Xu, Derek Ruths. (2015)

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curl -X POST -d '{{input | formatInput:"curl"}}' -H 'Content-Type: application/json' -H 'Authorization: Simple YOUR_API_KEY'
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algo auth
algo run algo://Geo/GeosPy/0.1.0 -d '{{input | formatInput:"cli"}}'
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import com.algorithmia.*;
import com.algorithmia.algo.*;

String input = "{{input | formatInput:"java"}}";
AlgorithmiaClient client = Algorithmia.client("YOUR_API_KEY");
Algorithm algo = client.algo("algo://Geo/GeosPy/0.1.0");
AlgoResponse result = algo.pipeJson(input);
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import com.algorithmia._
import com.algorithmia.algo._

val input = {{input | formatInput:"scala"}}
val client = Algorithmia.client("YOUR_API_KEY")
val algo = client.algo("algo://Geo/GeosPy/0.1.0")
val result = algo.pipeJson(input)
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var input = {{input | formatInput:"javascript"}};
           .then(function(output) {
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var input = {{input | formatInput:"javascript"}};
           .then(function(response) {
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import Algorithmia

input = {{input | formatInput:"python"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('Geo/GeosPy/0.1.0')
print algo.pipe(input)
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input <- {{input | formatInput:"r"}}
client <- getAlgorithmiaClient("YOUR_API_KEY")
algo <- client$algo("Geo/GeosPy/0.1.0")
result <- algo$pipe(input)$result
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require 'algorithmia'

input = {{input | formatInput:"ruby"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('Geo/GeosPy/0.1.0')
puts algo.pipe(input).result
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use algorithmia::*;

let input = {{input | formatInput:"rust"}};
let client = Algorithmia::client("YOUR_API_KEY");
let algo = client.algo("Geo/GeosPy/0.1.0");
let response = algo.pipe(input);
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import Algorithmia

let input = "{{input | formatInput:"swift"}}";
let client = Algorithmia.client(simpleKey: "YOUR_API_KEY")
let algo = client.algo(algoUri: "Geo/GeosPy/0.1.0") { resp, error in
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