s2gpp 1.0.2

Algorithm for Highly Efficient Detection of Correlation Anomalies in Multivariate Time Series
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140

pub mod utils;

use crate::cluster_listener::ClusterMemberListener;
use crate::data_manager::data_reader::read_data_;
use crate::parameters::{Parameters, Role};
use crate::training::{Clustering, StartTrainingMessage, Training};
use crate::utils::ClusterNodes;
use crate::{s2gpp, SyncInterface};
use actix::prelude::*;
use actix_rt::System;
use actix_telepathy::Cluster;
use ndarray_linalg::close_l1;
use port_scanner::request_open_port;
use rayon::iter::{IntoParallelIterator, ParallelIterator};
use std::env::temp_dir;
use std::fs::remove_file;

const ESTIMATED_SCORES_PATH: &str = "ts_0.csv.scores";
const EXPECTED_SCORES_PATH: &str = "data/ts_0.csv.scores";

fn get_output_path() -> String {
    let mut dir = temp_dir();
    dir.push(ESTIMATED_SCORES_PATH);
    dir.to_str().unwrap().to_string()
}

#[test]
#[ignore] // takes some time
fn global_test_kde_clustering() {
    let params: Parameters = Parameters {
        role: Role::Main {
            data_path: Some("data/ts_0.csv".to_string()),
        },
        local_host: "127.0.0.1:1992".parse().unwrap(),
        score_output_path: Some(get_output_path()),
        clustering: Clustering::MultiKDE,
        ..Default::default()
    };

    run_single_global_comut(params);

    check_for_comut_score();
}

#[test]
#[ignore] // takes some time
fn global_test_kde_clustering_provided_data() {
    let params: Parameters = Parameters {
        clustering: Clustering::MultiKDE,
        ..Default::default()
    };

    let data = read_data_("data/ts_0.csv");

    let result = s2gpp(params, Some(data)).unwrap();

    assert!(result.is_some());
}

#[test]
#[ignore] // takes some time
fn global_comut_distributed_2() {
    setup_distributed_global_comut(1)
}

fn setup_distributed_global_comut(n_subhosts: usize) {
    let mainhost = format!("127.0.0.1:{}", request_open_port().unwrap_or(1992))
        .parse()
        .unwrap();

    let mut parameters = vec![Parameters {
        role: Role::Main {
            data_path: Some("data/ts_0.csv".to_string()),
        },
        local_host: mainhost,
        score_output_path: Some(get_output_path()),
        n_cluster_nodes: n_subhosts + 1,
        ..Default::default()
    }];

    for i in 0..n_subhosts {
        let subhost = format!(
            "127.0.0.1:{}",
            request_open_port().unwrap_or((1993 + i) as u16)
        )
        .parse()
        .unwrap();

        parameters.push(Parameters {
            role: Role::Sub { mainhost },
            local_host: subhost,
            n_cluster_nodes: n_subhosts + 1,
            ..Default::default()
        });
    }

    parameters
        .into_par_iter()
        .for_each(|p| run_single_global_comut(p));

    check_for_comut_score();
}

fn run_single_global_comut(params: Parameters) {
    println!("{:?}", params);

    let system = System::new();

    system.block_on(async {
        let host = params.local_host;
        let seed_nodes = match &params.role {
            Role::Sub { mainhost } => vec![mainhost.clone()],
            _ => vec![],
        };

        let training = Training::init(params.clone()).start();
        if params.n_cluster_nodes > 1 {
            let _cluster = Cluster::new(host, seed_nodes);
            let _cluster_listener = ClusterMemberListener::new(params, training).start();
        } else {
            let nodes = ClusterNodes::new();
            training.do_send(StartTrainingMessage {
                nodes,
                source: None,
                data: None,
            });
        }
    });

    system.run().unwrap();
}

fn check_for_comut_score() {
    let estimated_scores_path = get_output_path();
    let expected_scores = read_data_(EXPECTED_SCORES_PATH);
    let estimated_scores = read_data_(&estimated_scores_path);
    remove_file(&estimated_scores_path).expect("Could not delete test file!");

    close_l1(&estimated_scores, &expected_scores, 0.000001);
}