lux-rs 0.1.1

Pure Rust lighting and color science library inspired by LuxPy
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182

use crate::error::{LuxError, LuxResult};
use crate::spectrum::{getwld, Spectrum};

struct SpectralMismatchContext {
    spacing: Vec<f64>,
    target: Vec<f64>,
    relative_detectors: Vec<Vec<f64>>,
}

pub fn spectral_mismatch_f1prime(
    detector: &Spectrum,
    calibration_illuminant: &Spectrum,
    target_responsivity: &Spectrum,
) -> LuxResult<f64> {
    Ok(spectral_mismatch_f1primes(
        &Spectrum::new(
            detector.wavelengths().to_vec(),
            vec![detector.values().to_vec()],
        )?,
        calibration_illuminant,
        target_responsivity,
    )?[0])
}

pub fn spectral_mismatch_f1primes(
    detectors: &Spectrum,
    calibration_illuminant: &Spectrum,
    target_responsivity: &Spectrum,
) -> LuxResult<Vec<f64>> {
    let context = build_context(
        detectors,
        calibration_illuminant,
        target_responsivity,
        detectors.wavelengths(),
    )?;
    let target_integral = weighted_sum(&context.target, &context.spacing);
    if target_integral == 0.0 {
        return Err(LuxError::InvalidInput(
            "target responsivity integral must be non-zero",
        ));
    }

    Ok(context
        .relative_detectors
        .iter()
        .map(|relative_detector| {
            weighted_sum_abs_difference(relative_detector, &context.target, &context.spacing)
                / target_integral
        })
        .collect())
}

pub fn spectral_mismatch_correction_factor(
    measured_source: &Spectrum,
    detector: &Spectrum,
    calibration_illuminant: &Spectrum,
    target_responsivity: &Spectrum,
) -> LuxResult<f64> {
    Ok(spectral_mismatch_correction_factors(
        &Spectrum::new(
            measured_source.wavelengths().to_vec(),
            vec![measured_source.values().to_vec()],
        )?,
        &Spectrum::new(
            detector.wavelengths().to_vec(),
            vec![detector.values().to_vec()],
        )?,
        calibration_illuminant,
        target_responsivity,
    )?[0][0])
}

pub fn spectral_mismatch_correction_factors(
    measured_sources: &Spectrum,
    detectors: &Spectrum,
    calibration_illuminant: &Spectrum,
    target_responsivity: &Spectrum,
) -> LuxResult<Vec<Vec<f64>>> {
    let context = build_context(
        detectors,
        calibration_illuminant,
        target_responsivity,
        measured_sources.wavelengths(),
    )?;

    measured_sources
        .spectra()
        .iter()
        .map(|source| {
            let numerator = weighted_dot(source, &context.target, &context.spacing);
            context
                .relative_detectors
                .iter()
                .map(|relative_detector| {
                    let denominator = weighted_dot(source, relative_detector, &context.spacing);
                    if denominator == 0.0 {
                        Err(LuxError::InvalidInput(
                            "spectral mismatch denominator must be non-zero",
                        ))
                    } else {
                        Ok(numerator / denominator)
                    }
                })
                .collect()
        })
        .collect()
}

fn build_context(
    detectors: &Spectrum,
    calibration_illuminant: &Spectrum,
    target_responsivity: &Spectrum,
    wavelengths: &[f64],
) -> LuxResult<SpectralMismatchContext> {
    let spacing = getwld(wavelengths)?;
    let target = target_responsivity.interpolate_linear(wavelengths)?;
    let calibration = calibration_illuminant.interpolate_linear(wavelengths)?;
    let detectors = detectors.cie_interp_linear(wavelengths, true)?;

    let calibration_weights: Vec<f64> = calibration
        .values()
        .iter()
        .zip(spacing.iter())
        .map(|(value, dl)| value * dl)
        .collect();
    let target_weighted_sum = dot(target.values(), &calibration_weights);
    if target_weighted_sum == 0.0 {
        return Err(LuxError::InvalidInput(
            "target responsivity under calibration illuminant must be non-zero",
        ));
    }

    let relative_detectors = detectors
        .spectra()
        .iter()
        .map(|detector| {
            let detector_weighted_sum = dot(detector, &calibration_weights);
            if detector_weighted_sum == 0.0 {
                Err(LuxError::InvalidInput(
                    "detector responsivity under calibration illuminant must be non-zero",
                ))
            } else {
                let scale = target_weighted_sum / detector_weighted_sum;
                Ok(detector.iter().map(|value| value * scale).collect())
            }
        })
        .collect::<LuxResult<Vec<Vec<f64>>>>()?;

    Ok(SpectralMismatchContext {
        spacing,
        target: target.values().to_vec(),
        relative_detectors,
    })
}

fn weighted_dot(lhs: &[f64], rhs: &[f64], weights: &[f64]) -> f64 {
    lhs.iter()
        .zip(rhs.iter())
        .zip(weights.iter())
        .map(|((lhs, rhs), weight)| lhs * rhs * weight)
        .sum()
}

fn weighted_sum(values: &[f64], weights: &[f64]) -> f64 {
    values
        .iter()
        .zip(weights.iter())
        .map(|(value, weight)| value * weight)
        .sum()
}

fn weighted_sum_abs_difference(lhs: &[f64], rhs: &[f64], weights: &[f64]) -> f64 {
    lhs.iter()
        .zip(rhs.iter())
        .zip(weights.iter())
        .map(|((lhs, rhs), weight)| (lhs - rhs).abs() * weight)
        .sum()
}

fn dot(lhs: &[f64], rhs: &[f64]) -> f64 {
    lhs.iter().zip(rhs.iter()).map(|(lhs, rhs)| lhs * rhs).sum()
}