Module scale 

Data scaling and value normalization for visualization.

This module provides methods for mapping raw data values to normalized [0.0, 1.0] range for colormap sampling. It supports multiple scaling strategies:

• Linear: Direct linear mapping (val - min) / (max - min)
• Logarithmic: log(val / min) / log(max / min) for positive data with wide dynamic range
• SymLog: Symmetric logarithm for data containing both positive and negative values
• Asinh: Inverse hyperbolic sine for data with wide dynamic range
• Histogram Equalization: Perceptual stretching using histogram distribution

Handling Invalid Data

The NegMode enum controls treatment of masked/invalid pixels:

• NegMode::Zero: Render as minimum value
• NegMode::Unseen: Render as bad color (typically white)

Examples

use map2fig::scale::{scale_value, Scale};
use map2fig::NegMode;

let scaled = scale_value(5.0, 0.0, 10.0, Scale::Linear, NegMode::Zero, None, None);
// Result: PixelValue::Color(0.5)

Structs

HistogramScale

ScaleCache

Pre-computed scale transformation constants to avoid per-pixel recomputation.

Enums

HistogramRange

Scale

Functions

build_histogram_scale

generate_colorbar_ticks

scale_value

unsafe_float_cmp

Direct float comparison using std::cmp for faster sorting. This avoids the NaN check overhead since data is pre-validated.

validate_scale_config

Validate scaling configuration parameters.