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  "Title": "Plots for Visualizing the Data Produced by the 'irace' Package",
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  "Description": "Graphical visualization tools for analyzing the data\nproduced by 'irace'. The 'iraceplot' package enables users to\nanalyze the performance and the parameter space data sampled by\nthe configuration during the search process. It provides a set\nof functions that generate different plots to visualize the\nconfigurations sampled during the execution of 'irace' and\ntheir performance. The functions just require the log file\ngenerated by 'irace' and, in some cases, they can be used with\nuser-provided data.",
  "License": "MIT + file LICENSE",
  "URL": "https://auto-optimization.github.io/iraceplot/,\nhttps://github.com/auto-optimization/iraceplot/",
  "BugReports": "https://github.com/auto-optimization/iraceplot/issues",
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  "Repository": "https://auto-optimization.r-universe.dev",
  "Date/Publication": "2025-12-11 13:51:12 UTC",
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    "parameters_summarise",
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    "plot_model",
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    "read_logfile",
    "report",
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    "sampling_frequency",
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    "sampling_heatmap",
    "sampling_heatmap2",
    "sampling_pie",
    "scatter_performance",
    "scatter_test",
    "scatter_training",
    "summarise_by_configuration",
    "summarise_by_instance",
    "summarise_by_iteration"
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    {
      "page": "iraceplot-package",
      "title": "The iraceplot package: Plots for Visualizing the Data Produced by the 'irace' Package",
      "topics": [
        "iraceplot-package",
        "iraceplot"
      ]
    },
    {
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      "title": "Create plot from an ablation log",
      "topics": [
        "ablation_plot"
      ]
    },
    {
      "page": "boxplot_performance",
      "title": "Box Plot of the performance of a set of configurations",
      "topics": [
        "boxplot_performance"
      ]
    },
    {
      "page": "boxplot_test",
      "title": "Box Plot Testing Performance",
      "topics": [
        "boxplot_test"
      ]
    },
    {
      "page": "boxplot_training",
      "title": "Box Plot Training",
      "topics": [
        "boxplot_training"
      ]
    },
    {
      "page": "configurations_display",
      "title": "The configurations by iteration and instance",
      "topics": [
        "configurations_display"
      ]
    },
    {
      "page": "distance_config",
      "title": "Distance between configurations",
      "topics": [
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      ]
    },
    {
      "page": "parallel_cat",
      "title": "Parallel Coordinates Category",
      "topics": [
        "parallel_cat"
      ]
    },
    {
      "page": "parallel_coord",
      "title": "Parallel Coordinates Plot",
      "topics": [
        "parallel_coord"
      ]
    },
    {
      "page": "parameters_summarise",
      "title": "Summarise parameters space",
      "topics": [
        "parameters_summarise"
      ]
    },
    {
      "page": "parameters_tree",
      "title": "Print parameter dependencies as a tree",
      "topics": [
        "parameters_tree"
      ]
    },
    {
      "page": "plot_configurations",
      "title": "Plot parameter configurations using parallel coordinates",
      "topics": [
        "plot_configurations"
      ]
    },
    {
      "page": "plot_experiments_matrix",
      "title": "Heat Map Plot",
      "topics": [
        "plot_experiments_matrix"
      ]
    },
    {
      "page": "plot_model",
      "title": "Plot the sampling models used by irace",
      "topics": [
        "plot_model"
      ]
    },
    {
      "page": "report",
      "title": "Create HTML Report from irace data",
      "topics": [
        "report"
      ]
    },
    {
      "page": "sampling_distance",
      "title": "Sampling distance Plot",
      "topics": [
        "sampling_distance"
      ]
    },
    {
      "page": "sampling_frequency",
      "title": "Parameter Frequency and Density Plot",
      "topics": [
        "sampling_frequency"
      ]
    },
    {
      "page": "sampling_frequency_iteration",
      "title": "Frequency and Density plot based on its iteration",
      "topics": [
        "sampling_frequency_iteration"
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    {
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      "topics": [
        "sampling_heatmap"
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        "scatter_training"
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