Struct FeatureExporter 

pub struct FeatureExporter { /* private fields */ }

Feature exporter for aprender format

Implementations

impl FeatureExporter

pub fn new(format: ExportFormat) -> Self

Create a new feature exporter with specified format

Arguments

• format - Export format (Json, Binary, or Parquet)

Examples

use organizational_intelligence_plugin::export::{FeatureExporter, ExportFormat};

let exporter = FeatureExporter::new(ExportFormat::Json);

pub fn to_matrix(features: &[CommitFeatures]) -> Result<Matrix<f32>>

Convert CommitFeatures to aprender Matrix

Arguments

• features - Slice of CommitFeatures to convert

Returns

• Ok(Matrix<f32>) with shape [n_samples, FEATURE_DIMENSION]
• Err if features slice is empty

Examples

use organizational_intelligence_plugin::export::FeatureExporter;
use organizational_intelligence_plugin::features::CommitFeatures;

let features = vec![
    CommitFeatures {
        defect_category: 0,
        files_changed: 2.0,
        lines_added: 10.0,
        lines_deleted: 5.0,
        complexity_delta: 0.0,
        timestamp: 1700000000.0,
        hour_of_day: 14,
        day_of_week: 2,
        ..Default::default()
    },
];

let matrix = FeatureExporter::to_matrix(&features).unwrap();
assert_eq!(matrix.n_rows(), 1);
assert_eq!(matrix.n_cols(), 14);  // NLP-014: 14 dimensions

pub fn encode_label(category: DefectCategory) -> u8

Encode DefectCategory to label index (0-17)

Arguments

• category - DefectCategory to encode

Returns

• Label index (0-17)

Examples

use organizational_intelligence_plugin::export::FeatureExporter;
use organizational_intelligence_plugin::classifier::DefectCategory;

let label = FeatureExporter::encode_label(DefectCategory::MemorySafety);
assert_eq!(label, 0);

let label = FeatureExporter::encode_label(DefectCategory::TraitBounds);
assert_eq!(label, 17);

pub fn decode_label(label: u8) -> Result<DefectCategory>

Decode label index back to DefectCategory

Arguments

• label - Label index (0-17)

Returns

• Ok(DefectCategory) if label is valid
• Err if label is out of range

Examples

use organizational_intelligence_plugin::export::FeatureExporter;
use organizational_intelligence_plugin::classifier::DefectCategory;

let category = FeatureExporter::decode_label(0).unwrap();
assert_eq!(category, DefectCategory::MemorySafety);

let result = FeatureExporter::decode_label(18);
assert!(result.is_err());

pub fn encode_labels(categories: &[DefectCategory]) -> Vec<u8>

Encode multiple DefectCategories to label vector

Arguments

• categories - Slice of DefectCategories

Returns

• Vector of label indices

pub fn category_names() -> Vec<String>

Get all category names in label order

Returns

• Vector of category names indexed by label

pub fn export( &self, features: &[CommitFeatures], categories: &[DefectCategory], ) -> Result<ExportedDataset>

Export features and labels to ExportedDataset

Arguments

• features - CommitFeatures to export
• categories - Corresponding DefectCategories

Returns

• Ok(ExportedDataset) with features and labels
• Err if lengths mismatch or empty input

pub fn save<P: AsRef<Path>>( &self, dataset: &ExportedDataset, path: P, ) -> Result<()>

Save exported dataset to file

Arguments

• dataset - ExportedDataset to save
• path - Output file path

Returns

• Ok(()) if successful
• Err if write fails

pub fn load<P: AsRef<Path>>( path: P, format: ExportFormat, ) -> Result<ExportedDataset>

Load exported dataset from file

Arguments

• path - Input file path
• format - Format to expect

Returns

• Ok(ExportedDataset) if successful
• Err if read/parse fails

pub fn to_aprender_matrix(dataset: &ExportedDataset) -> Result<Matrix<f32>>

Convert ExportedDataset to aprender Matrix

Arguments

• dataset - ExportedDataset to convert

Returns

• Ok(Matrix<f32>) feature matrix

Trait Implementations

impl Default for FeatureExporter

fn default() -> Self

Returns the “default value” for a type.