Struct FittedNormalizer 

pub struct FittedNormalizer<F> { /* private fields */ }

A fitted Normalizer.

Normalizer is stateless — its fit (sklearn Normalizer.fit, _data.py:2062-2083, “Only validates estimator’s parameters”) learns NO statistics; it merely validates the input and records n_features_in_. The fitted type therefore carries only the configured norm, the copy flag, and the recorded feature count. Its Transform::transform reuses the very same row-norm logic as the stateless Normalizer/normalize path, so the two paths are bit-identical.

Implementations

impl<F: Float + Send + Sync + 'static> FittedNormalizer<F>

pub fn n_features_in(&self) -> usize

Return the number of features (columns) seen during Fit::fit.

Mirrors scikit-learn’s Normalizer.n_features_in_ (_data.py:2082).

pub fn norm(&self) -> NormType

Return the configured norm type.

pub fn copy(&self) -> bool

Return the configured copy flag (no-op; see Normalizer::with_copy).

Trait Implementations

impl<F: Clone> Clone for FittedNormalizer<F>

fn clone(&self) -> FittedNormalizer<F>

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<F: Debug> Debug for FittedNormalizer<F>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<F: Float + Send + Sync + 'static> Transform<ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>> for FittedNormalizer<F>

fn transform(&self, x: &Array2<F>) -> Result<Array2<F>, FerroError>

Normalize each row of x to unit norm, delegating to the SAME row-norm logic as the stateless Normalizer / normalize path.

First validates that x has the same number of columns recorded during Fit::fit (sklearn _validate_data(reset=False), sklearn/preprocessing/_data.py:2104) and applies the REQ-2 check_array guards, then calls the shared normalize free function with axis=1 (sklearn Normalizer.transform -> normalize(X, norm=self.norm, axis=1), :2106). The output is therefore byte-identical to Normalizer::transform.

Errors

Returns FerroError::ShapeMismatch if the column count differs from n_features_in_. Returns FerroError::InsufficientSamples for zero rows and FerroError::InvalidParameter for zero features or any non-finite value (REQ-2, via normalize).

type Output = ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>

The transformed output type.

type Error = FerroError

The error type returned by transform.