{
  "_id": "6ab4f01a3d719c1f8409784f",
  "Package": "cyclicwave",
  "Type": "Package",
  "Title": "Cyclic Wave Analysis for Time-Series Clustering",
  "Version": "0.1.0",
  "Authors@R": "c(\nperson(given = \"Şule Şevval\",\nfamily = \"Karakaya\",\nemail = \"sule.karakaya@metu.edu.tr\",\nrole = c(\"aut\", \"cre\")),\nperson(given = \"Ahmet\",\nfamily = \"Bursalı\",\nemail = \"ahmet.bursali@huawei.com\",\nrole = \"aut\"),\nperson(given = \"Vilda\",\nfamily = \"Purutçuoğlu\",\nemail = \"vpurutucu@metu.edu.tr\",\nrole = \"aut\")\n)",
  "Description": "A modular toolkit for feature extraction and density-based\nclustering of time-series data. It provides classical\nstatistical, discrete wavelet, Hilbert-based phase, and\ncircular statistical features. The Hilbert-based phase\nrepresentation can support the analysis of periodic patterns,\nphase relationships, and circular behavior in time-series data.\nThe package supports DBSCAN and OPTICS clustering, cluster\nevaluation, visualization, data preparation, and comparison of\nmultiple feature extraction and clustering combinations.\nMethods are described in Karakaya and Purutcuoglu (2026)\n<doi:10.15672/hujms.1821412> and Karakaya et al. (2026)\n<doi:10.1007/978-3-032-17020-0_27>.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "Config/testthat/edition": "3",
  "Config/roxygen2/version": "8.0.0",
  "VignetteBuilder": "knitr",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-09-24 09:37:39 UTC",
    "User": "root"
  },
  "Author": "Şule Şevval Karakaya [aut, cre], Ahmet Bursalı [aut], Vilda\nPurutçuoğlu [aut]",
  "Maintainer": "Şule Şevval Karakaya <sule.karakaya@metu.edu.tr>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2026-07-03 12:00:08 UTC",
  "RemoteUrl": "https://github.com/cran/cyclicwave",
  "RemoteRef": "HEAD",
  "RemoteSha": "b53ff7f579ae08763985039e942511a9a74803df",
  "_user": "cran",
  "_type": "src",
  "_file": "cyclicwave_0.1.0.tar.gz",
  "_fileid": "https://r2.ropensci.org/8211aadb11c6d2428df54efadba10669d4c47780f4d03b2d5e9aff30b21565a4",
  "_filesize": 923084,
  "_sha256": "8211aadb11c6d2428df54efadba10669d4c47780f4d03b2d5e9aff30b21565a4",
  "_expires": "2027-01-02T09:40:39.000Z",
  "_created": "2026-09-24T09:37:39.000Z",
  "_published": "2026-09-24T09:40:42.333Z",
  "_jobs": [
    {
      "job": 107577206035,
      "time": 134,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "10800527637"
    },
    {
      "job": 107577206111,
      "time": 138,
      "config": "linux-release-x86_64",
      "r": "4.6.1",
      "check": "OK",
      "artifact": "10800966596"
    },
    {
      "job": 107576069477,
      "time": 204,
      "config": "source",
      "r": "4.6.1",
      "check": "OK",
      "artifact": "10800732788"
    },
    {
      "job": 107577206019,
      "time": 119,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "10800862288"
    },
    {
      "job": 107577206185,
      "time": 75,
      "config": "windows-devel-x86_64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "10800323011"
    },
    {
      "job": 107577206177,
      "time": 73,
      "config": "windows-release-x86_64",
      "r": "4.6.1",
      "check": "OK",
      "artifact": "10800931083"
    }
  ],
  "_host": "GitHub-Actions",
  "_buildurl": "https://github.com/r-universe/cran/actions/runs/35982015988",
  "_status": "success",
  "_upstream": "https://github.com/cran/cyclicwave",
  "_commit": {
    "id": "b53ff7f579ae08763985039e942511a9a74803df",
    "author": "Şule Şevval Karakaya <sule.karakaya@metu.edu.tr>",
    "committer": "cran-robot <csardi.gabor+cran@gmail.com>",
    "message": "version 0.1.0\n",
    "time": 1783080008
  },
  "_maintainer": {
    "name": "Şule Şevval Karakaya",
    "email": "sule.karakaya@metu.edu.tr"
  },
  "_distro": "resolute",
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 3.5.0",
      "role": "Depends"
    },
    {
      "package": "stats",
      "role": "Imports"
    },
    {
      "package": "utils",
      "role": "Imports"
    },
    {
      "package": "dbscan",
      "role": "Imports"
    },
    {
      "package": "gsignal",
      "role": "Imports"
    },
    {
      "package": "waveslim",
      "role": "Imports"
    },
    {
      "package": "MASS",
      "role": "Imports"
    },
    {
      "package": "e1071",
      "role": "Imports"
    },
    {
      "package": "ggplot2",
      "role": "Imports"
    },
    {
      "package": "FNN",
      "role": "Suggests"
    },
    {
      "package": "testthat",
      "version": ">= 3.0.0",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    }
  ],
  "_owner": "cran",
  "_selfowned": false,
  "_usedby": 0,
  "_updates": [
    {
      "week": "2026-27",
      "n": 1
    }
  ],
  "_tags": [
    {
      "name": "0.1.0",
      "date": "2026-07-03"
    }
  ],
  "_stars": 0,
  "_userbio": {
    "uuid": 6899542,
    "type": "organization",
    "name": "cran",
    "followers": 630,
    "description": "Unofficial read-only mirror of all CRAN R packages"
  },
  "_downloads": {
    "count": 345,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/cyclicwave"
  },
  "_searchresults": 0,
  "_rbuild": "4.6.1",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/cyclicwave.html",
    "extra/manual.pdf",
    "extra/readme.html",
    "extra/readme.md",
    "LICENSE"
  ],
  "_realowner": "cran",
  "_cranurl": false,
  "_releases": [
    {
      "version": "0.1.0",
      "date": "2026-07-03"
    }
  ],
  "_exports": [
    "a_star_statistic",
    "a_statistic",
    "analytic_signal",
    "best_map",
    "chord_length",
    "circ_mean",
    "circ_r",
    "circ_std",
    "circ_var",
    "circular_distance_measures",
    "cluster_accuracy",
    "compare_methods",
    "compute_phase",
    "davies_bouldin",
    "extract_circular_features",
    "find_elbow",
    "first_difference",
    "flatten_with_zones",
    "label_by_quantile",
    "M_statistic",
    "mardia_kurtosis",
    "normalize_features",
    "plot_clusters_pca",
    "plot_k_distance",
    "plot_reachability",
    "prepare_features",
    "rolling_stats",
    "run_dbscan",
    "run_optics",
    "segment_signal",
    "select_numeric_columns",
    "thin_data",
    "wavelet_approx",
    "wavelet_transform",
    "window_moments",
    "wrap_to_pi"
  ],
  "_datasets": [
    {
      "name": "power_consumption",
      "title": "Tetouan Power Consumption Data",
      "object": "power_consumption",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Datetime",
        "Temperature",
        "Humidity",
        "WindSpeed",
        "GeneralDiffuseFlows",
        "DiffuseFlows",
        "PowerConsumption_Zone1",
        "PowerConsumption_Zone2",
        "PowerConsumption_Zone3"
      ],
      "rows": 13906,
      "table": true,
      "tojson": true
    },
    {
      "name": "steel_industry",
      "title": "Steel Industry Energy Consumption Data",
      "object": "steel_industry",
      "class": [
        "data.frame"
      ],
      "fields": [
        "date",
        "Usage_kWh",
        "Lagging_Current_Reactive.Power_kVarh",
        "Leading_Current_Reactive_Power_kVarh",
        "CO2.tCO2.",
        "Lagging_Current_Power_Factor",
        "Leading_Current_Power_Factor",
        "NSM",
        "WeekStatus",
        "Day_of_week",
        "Load_Type"
      ],
      "rows": 35040,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "a_star_statistic",
      "title": "A-Star Statistic",
      "topics": [
        "a_star_statistic"
      ]
    },
    {
      "page": "a_statistic",
      "title": "A Statistic",
      "topics": [
        "a_statistic"
      ]
    },
    {
      "page": "analytic_signal",
      "title": "Analytic Signal",
      "topics": [
        "analytic_signal"
      ]
    },
    {
      "page": "best_map",
      "title": "Match Predicted Cluster Labels",
      "topics": [
        "best_map"
      ]
    },
    {
      "page": "chord_length",
      "title": "Chord Length Statistic",
      "topics": [
        "chord_length"
      ]
    },
    {
      "page": "circ_mean",
      "title": "Circular Mean",
      "topics": [
        "circ_mean"
      ]
    },
    {
      "page": "circ_r",
      "title": "Mean Resultant Length",
      "topics": [
        "circ_r"
      ]
    },
    {
      "page": "circ_std",
      "title": "Circular Standard Deviation",
      "topics": [
        "circ_std"
      ]
    },
    {
      "page": "circ_var",
      "title": "Circular Variance",
      "topics": [
        "circ_var"
      ]
    },
    {
      "page": "circular_distance_measures",
      "title": "Calculate Circular Distance Measures",
      "topics": [
        "circular_distance_measures"
      ]
    },
    {
      "page": "cluster_accuracy",
      "title": "Clustering Accuracy",
      "topics": [
        "cluster_accuracy"
      ]
    },
    {
      "page": "compare_methods",
      "title": "Compare Feature and Clustering Methods",
      "topics": [
        "compare_methods"
      ]
    },
    {
      "page": "compute_phase",
      "title": "Instantaneous Phase",
      "topics": [
        "compute_phase"
      ]
    },
    {
      "page": "davies_bouldin",
      "title": "Davies-Bouldin Index",
      "topics": [
        "davies_bouldin"
      ]
    },
    {
      "page": "extract_circular_features",
      "title": "Extract Circular Features",
      "topics": [
        "extract_circular_features"
      ]
    },
    {
      "page": "find_elbow",
      "title": "Find an Elbow Point",
      "topics": [
        "find_elbow"
      ]
    },
    {
      "page": "first_difference",
      "title": "First Differences",
      "topics": [
        "first_difference"
      ]
    },
    {
      "page": "flatten_with_zones",
      "title": "Flatten Data with Group Labels",
      "topics": [
        "flatten_with_zones"
      ]
    },
    {
      "page": "label_by_quantile",
      "title": "Create Labels from Quantile Groups",
      "topics": [
        "label_by_quantile"
      ]
    },
    {
      "page": "M_statistic",
      "title": "M Statistic",
      "topics": [
        "M_statistic"
      ]
    },
    {
      "page": "mardia_kurtosis",
      "title": "Mardia Kurtosis",
      "topics": [
        "mardia_kurtosis"
      ]
    },
    {
      "page": "normalize_features",
      "title": "Normalize Feature Columns",
      "topics": [
        "normalize_features"
      ]
    },
    {
      "page": "plot_clusters_pca",
      "title": "Plot Clusters Using PCA",
      "topics": [
        "plot_clusters_pca"
      ]
    },
    {
      "page": "plot_k_distance",
      "title": "Plot k-Distance Graph",
      "topics": [
        "plot_k_distance"
      ]
    },
    {
      "page": "plot_reachability",
      "title": "Plot OPTICS Reachability",
      "topics": [
        "plot_reachability"
      ]
    },
    {
      "page": "power_consumption",
      "title": "Tetouan Power Consumption Data",
      "topics": [
        "power_consumption"
      ]
    },
    {
      "page": "prepare_features",
      "title": "Prepare a Feature Matrix",
      "topics": [
        "prepare_features"
      ]
    },
    {
      "page": "rolling_stats",
      "title": "Rolling Statistics",
      "topics": [
        "rolling_stats"
      ]
    },
    {
      "page": "run_dbscan",
      "title": "DBSCAN Clustering",
      "topics": [
        "run_dbscan"
      ]
    },
    {
      "page": "run_optics",
      "title": "OPTICS Clustering",
      "topics": [
        "run_optics"
      ]
    },
    {
      "page": "segment_signal",
      "title": "Segment a Signal",
      "topics": [
        "segment_signal"
      ]
    },
    {
      "page": "select_numeric_columns",
      "title": "Select Numeric Columns",
      "topics": [
        "select_numeric_columns"
      ]
    },
    {
      "page": "steel_industry",
      "title": "Steel Industry Energy Consumption Data",
      "topics": [
        "steel_industry"
      ]
    },
    {
      "page": "thin_data",
      "title": "Thin a Dataset",
      "topics": [
        "thin_data"
      ]
    },
    {
      "page": "wavelet_approx",
      "title": "Multi-Level Wavelet Approximation",
      "topics": [
        "wavelet_approx"
      ]
    },
    {
      "page": "wavelet_transform",
      "title": "Single-Level Wavelet Transform",
      "topics": [
        "wavelet_transform"
      ]
    },
    {
      "page": "window_moments",
      "title": "Window Summary Statistics",
      "topics": [
        "window_moments"
      ]
    },
    {
      "page": "wrap_to_pi",
      "title": "Wrap Angles",
      "topics": [
        "wrap_to_pi"
      ]
    }
  ],
  "_readme": "https://github.com/cran/cyclicwave/raw/HEAD/README.md",
  "_rundeps": [
    "class",
    "cli",
    "cpp11",
    "dbscan",
    "e1071",
    "farver",
    "generics",
    "ggplot2",
    "glue",
    "gsignal",
    "gtable",
    "isoband",
    "labeling",
    "lifecycle",
    "MASS",
    "multitaper",
    "pracma",
    "proxy",
    "R6",
    "RColorBrewer",
    "Rcpp",
    "rlang",
    "S7",
    "scales",
    "vctrs",
    "viridisLite",
    "waveslim",
    "withr"
  ],
  "_vignettes": [
    {
      "source": "comparing-methods.Rmd",
      "filename": "comparing-methods.html",
      "title": "Comparing Feature Engineering Approaches",
      "engine": "knitr::rmarkdown",
      "headings": [
        "All combinations",
        "Preparing the data",
        "Ground-truth labels",
        "Defining the feature methods",
        "Defining the clustering methods",
        "One call to rule them all"
      ],
      "created": "2026-07-03 12:00:08",
      "modified": "2026-07-03 12:00:08",
      "commits": 1
    },
    {
      "source": "getting-started.Rmd",
      "filename": "getting-started.html",
      "title": "Getting Started with cyclicwave",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Overview",
        "The data",
        "Step 1: reshape into long format",
        "Step 2: extract rolling features",
        "Step 3: normalize",
        "Step 4: choose epsilon (visual heuristic)",
        "Step 5: run DBSCAN",
        "Step 6: evaluate"
      ],
      "created": "2026-07-03 12:00:08",
      "modified": "2026-07-03 12:00:08",
      "commits": 1
    }
  ],
  "_score": 3,
  "_indexed": true,
  "_nocasepkg": "cyclicwave",
  "_universes": [
    "cran"
  ],
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "0.1.0",
      "date": "2026-09-24T09:39:58.000Z",
      "distro": "resolute",
      "commit": "b53ff7f579ae08763985039e942511a9a74803df",
      "fileid": "https://r2.ropensci.org/d022ad11fce131c3eda193713b46e7e0f3a94f5114786dbbc82ae409859ac77b",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/35982015988"
    },
    {
      "r": "4.6.1",
      "os": "linux",
      "version": "0.1.0",
      "date": "2026-09-24T09:40:01.000Z",
      "distro": "resolute",
      "commit": "b53ff7f579ae08763985039e942511a9a74803df",
      "fileid": "https://r2.ropensci.org/3d0c02fdadae931828677b9da5dba46847b43bc9eb9c6320036a65b022639951",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/35982015988"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "0.1.0",
      "date": "2026-09-24T09:39:59.000Z",
      "commit": "b53ff7f579ae08763985039e942511a9a74803df",
      "fileid": "https://r2.ropensci.org/52d8c9cad59dfa34cf2021eb6e53a8356ec969ddc3e385dfbbc84fe53877894e",
      "status": "success",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/35982015988"
    },
    {
      "r": "4.7.0",
      "os": "win",
      "version": "0.1.0",
      "date": "2026-09-24T09:38:55.000Z",
      "commit": "b53ff7f579ae08763985039e942511a9a74803df",
      "fileid": "https://r2.ropensci.org/56985879d7ccbbf6f94cf8e3c612fa882269e12ba4a4168860a54d5e50347b64",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/35982015988"
    },
    {
      "r": "4.6.1",
      "os": "win",
      "version": "0.1.0",
      "date": "2026-09-24T09:38:52.000Z",
      "commit": "b53ff7f579ae08763985039e942511a9a74803df",
      "fileid": "https://r2.ropensci.org/5d2035700514ee25fb38e79b06242d4e466ac062663070e22d639b45b1a24f9d",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/35982015988"
    }
  ]
}