Enum ResampleMethod 

pub enum ResampleMethod {
    Linear,
    BoxcarAverage,
    Gaussian,
}

Method used when resampling a spectrum to a new wavelength axis.

Variants

Linear

Linear interpolation between adjacent input samples.

Each output value is computed by linearly interpolating between the two nearest input wavelengths. Output wavelengths outside the input range are clamped to the nearest endpoint (no extrapolation).

Works for both upsampling and downsampling.

BoxcarAverage

Boxcar (rectangular window) averaging.

For each output wavelength λ, all input samples within the half-step window [λ − step/2, λ + step/2] are averaged, where step is the mean spacing of the target axis. Falls back to linear interpolation for any output wavelength whose window contains no input samples.

Most appropriate when downsampling to a coarser grid (e.g. 1 nm → 10 nm).

Assumes a regular (uniformly-spaced) target grid. The window half-width is derived from the mean spacing of the entire target axis; for irregular target grids the bins may overlap or leave gaps. Use a WavelengthAxis with range_nm (start / end / interval) to guarantee a regular grid.

Gaussian

Gaussian kernel resampling.

Each output value is a weighted average of the input samples, where the weight of input sample at w is exp(−½ ((w − λ) / σ)²). Samples further than 3σ from the output wavelength are excluded. Weights are normalised by their sum, so output values at the edges of the input range are not artificially attenuated.

The kernel FWHM is resolved in this order:

1. metadata.measurement_conditions.spectral_resolution_nm — the instrument’s optical resolution, physically the most meaningful choice.
2. Mean step size of the target axis — used as a fallback when no resolution is recorded, matching the kernel width to the output sampling interval.

σ is derived from the FWHM as FWHM / (2√(2 ln 2)) ≈ FWHM / 2.355.

If the FWHM is much smaller than the input sampling interval the kernel degenerates toward nearest-neighbour interpolation; if no input samples fall within the 3σ window the method falls back to linear interpolation.

Trait Implementations

impl Clone for ResampleMethod

fn clone(&self) -> ResampleMethod

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ResampleMethod

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

Formats the value using the given formatter.

impl PartialEq for ResampleMethod

fn eq(&self, other: &ResampleMethod) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Copy for ResampleMethod

impl Eq for ResampleMethod

impl StructuralPartialEq for ResampleMethod