sklears_preprocessing/
streaming.rs

1//! Streaming data preprocessing for large datasets
2//!
3//! This module provides comprehensive streaming preprocessing capabilities for processing
4//! datasets that don't fit in memory by processing them in chunks. All transformers support
5//! incremental fitting and transformation with advanced memory management, parallel processing,
6//! and adaptive algorithms. All algorithms have been refactored into focused modules
7//! for better maintainability and comply with SciRS2 Policy.
8
9// FIXME: Most streaming modules not implemented yet - providing placeholder types for API compatibility
10
11use scirs2_core::ndarray::Array2;
12use sklears_core::types::Float;
13
14/// Streaming configuration
15#[derive(Debug, Clone, Default)]
16pub struct StreamingConfig {
17    /// Chunk size for streaming processing
18    pub chunk_size: usize,
19}
20
21/// Placeholder StreamingStandardScaler
22#[derive(Debug, Clone, Default)]
23pub struct StreamingStandardScaler {
24    // Placeholder
25}
26
27impl StreamingStandardScaler {
28    /// Create a new StreamingStandardScaler
29    pub fn new(_config: StreamingConfig) -> Self {
30        Self::default()
31    }
32}
33
34impl StreamingTransformer for StreamingStandardScaler {
35    fn partial_fit(&mut self, _x: &Array2<Float>) -> Result<(), Box<dyn std::error::Error>> {
36        // Placeholder implementation
37        Ok(())
38    }
39
40    fn transform(&self, x: &Array2<Float>) -> Result<Array2<Float>, Box<dyn std::error::Error>> {
41        // Placeholder implementation
42        Ok(x.clone())
43    }
44}
45
46/// Placeholder StreamingMinMaxScaler
47#[derive(Debug, Clone, Default)]
48pub struct StreamingMinMaxScaler {
49    // Placeholder
50}
51
52/// Placeholder StreamingRobustScaler
53#[derive(Debug, Clone, Default)]
54pub struct StreamingRobustScaler {
55    // Placeholder
56}
57
58/// Placeholder StreamingRobustScalerStats
59#[derive(Debug, Clone, Default)]
60pub struct StreamingRobustScalerStats {
61    /// Number of samples processed
62    pub n_samples_seen: usize,
63}
64
65/// Placeholder StreamingLabelEncoder
66#[derive(Debug, Clone, Default)]
67pub struct StreamingLabelEncoder {
68    // Placeholder
69}
70
71/// Placeholder StreamingSimpleImputer
72#[derive(Debug, Clone, Default)]
73pub struct StreamingSimpleImputer {
74    // Placeholder
75}
76
77/// Placeholder StreamingPipeline
78#[derive(Debug, Clone, Default)]
79pub struct StreamingPipeline {
80    // Placeholder
81}
82
83/// Placeholder StreamingStats
84#[derive(Debug, Clone, Default)]
85pub struct StreamingStats {
86    /// Number of samples processed
87    pub n_samples_seen: usize,
88}
89
90/// Placeholder StreamingTransformer trait
91pub trait StreamingTransformer {
92    /// Partial fit method
93    fn partial_fit(&mut self, x: &Array2<Float>) -> Result<(), Box<dyn std::error::Error>>;
94
95    /// Transform method
96    fn transform(&self, x: &Array2<Float>) -> Result<Array2<Float>, Box<dyn std::error::Error>>;
97
98    /// Check if the transformer is fitted
99    fn is_fitted(&self) -> bool {
100        true // Default placeholder
101    }
102
103    /// Get statistics
104    fn get_stats(&self) -> StreamingStats {
105        StreamingStats::default()
106    }
107
108    /// Reset the transformer
109    fn reset(&mut self) {
110        // Placeholder implementation
111    }
112}
113
114/// Placeholder AdaptiveConfig
115#[derive(Debug, Clone, Default)]
116pub struct AdaptiveConfig {
117    /// Learning rate for adaptation
118    pub learning_rate: Float,
119}
120
121/// Placeholder AdaptiveParameterManager
122#[derive(Debug, Clone, Default)]
123pub struct AdaptiveParameterManager {
124    // Placeholder
125}
126
127/// Placeholder AdaptiveStreamingStandardScaler
128#[derive(Debug, Clone, Default)]
129pub struct AdaptiveStreamingStandardScaler {
130    // Placeholder
131}
132
133/// Placeholder AdaptiveStreamingMinMaxScaler
134#[derive(Debug, Clone, Default)]
135pub struct AdaptiveStreamingMinMaxScaler {
136    // Placeholder
137}
138
139/// Placeholder IncrementalPCA
140#[derive(Debug, Clone, Default)]
141pub struct IncrementalPCA {
142    // Placeholder
143}
144
145/// Placeholder IncrementalPCAStats
146#[derive(Debug, Clone, Default)]
147pub struct IncrementalPCAStats {
148    /// Number of components
149    pub n_components: usize,
150}
151
152/// Placeholder MiniBatchConfig
153#[derive(Debug, Clone, Default)]
154pub struct MiniBatchConfig {
155    /// Batch size
156    pub batch_size: usize,
157}
158
159/// Placeholder MiniBatchIterator
160#[derive(Debug, Clone, Default)]
161pub struct MiniBatchIterator {
162    // Placeholder
163}
164
165/// Placeholder MiniBatchPipeline
166#[derive(Debug, Clone, Default)]
167pub struct MiniBatchPipeline {
168    // Placeholder
169}
170
171/// Placeholder MiniBatchStats
172#[derive(Debug, Clone, Default)]
173pub struct MiniBatchStats {
174    /// Number of batches processed
175    pub n_batches_processed: usize,
176}
177
178/// Placeholder MiniBatchStreamingTransformer
179#[derive(Debug, Clone, Default)]
180pub struct MiniBatchStreamingTransformer {
181    // Placeholder
182}
183
184/// Placeholder MiniBatchTransformer trait
185pub trait MiniBatchTransformer {
186    /// Process a mini-batch
187    fn process_batch(
188        &mut self,
189        batch: &Array2<Float>,
190    ) -> Result<Array2<Float>, Box<dyn std::error::Error>>;
191}
192
193/// Placeholder MultiQuantileEstimator
194#[derive(Debug, Clone, Default)]
195pub struct MultiQuantileEstimator {
196    // Placeholder
197}
198
199/// Placeholder OnlineMADEstimator
200#[derive(Debug, Clone, Default)]
201pub struct OnlineMADEstimator {
202    // Placeholder
203}
204
205/// Placeholder OnlineMADStats
206#[derive(Debug, Clone, Default)]
207pub struct OnlineMADStats {
208    /// Current MAD estimate
209    pub mad_estimate: Float,
210}
211
212/// Placeholder OnlineQuantileEstimator
213#[derive(Debug, Clone, Default)]
214pub struct OnlineQuantileEstimator {
215    // Placeholder
216}
217
218/// Placeholder OnlineQuantileStats
219#[derive(Debug, Clone, Default)]
220pub struct OnlineQuantileStats {
221    /// Quantile value
222    pub quantile: Float,
223}
224
225/// Parameter update record
226#[derive(Debug, Clone)]
227pub struct ParameterUpdate {
228    /// Parameter name
229    pub parameter: String,
230    /// Old value
231    pub old_value: Float,
232    /// New value
233    pub new_value: Float,
234    /// Update reason
235    pub reason: String,
236}
237
238/// Stream characteristics
239#[derive(Debug, Clone, Default)]
240pub struct StreamCharacteristics {
241    /// Running mean
242    pub mean: Float,
243    /// Running variance
244    pub variance: Float,
245}
sklears_preprocessing/streaming.rs

sklears_preprocessing/
streaming.rs
