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
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
pub use deltae::{DEMethod, LabValue, Delta};
use crate::*;
impl Cgats {
pub fn delta(&self, other: &Self, method: DEMethod) -> Result<Self> {
self.can_delta(other)?;
let lab_ref_l = self.get_col_by_field(&LAB_L).ok_or("unable to find reference L* column")?;
let lab_ref_a = self.get_col_by_field(&LAB_A).ok_or("unable to find reference a* column")?;
let lab_ref_b = self.get_col_by_field(&LAB_B).ok_or("unable to find reference b* column")?;
let lab_sam_l = other.get_col_by_field(&LAB_L).ok_or("unable to find sample L* column")?;
let lab_sam_a = other.get_col_by_field(&LAB_A).ok_or("unable to find sample a* column")?;
let lab_sam_b = other.get_col_by_field(&LAB_B).ok_or("unable to find sample b* column")?;
let labify = |lab: ((&DataPoint, &DataPoint), &DataPoint)| {
LabValue {
l: lab.0.0.to_float_unchecked(),
a: lab.0.1.to_float_unchecked(),
b: lab.1.to_float_unchecked(),
}
};
let lab_ref = lab_ref_l
.zip(lab_ref_a)
.zip(lab_ref_b)
.map(labify);
let lab_sam = lab_sam_l
.zip(lab_sam_a)
.zip(lab_sam_b)
.map(labify);
let delta = lab_ref.zip(lab_sam)
.map(|(lab_ref, lab_sam)| DataPoint::new_float(*lab_ref.delta(lab_sam, method).value()))
.collect::<Vec<_>>();
let mut cgats = Cgats::default();
cgats.data_format.fields = vec![Field::from(method)];
cgats.data = delta;
cgats.reindex_sample_id();
Ok(cgats)
}
pub fn de_report(&self, other: &Self, method: DEMethod, upper_pct: f32) -> Result<DeReport> {
let delta = self.delta(other, method)?;
let mut values: Vec<f32> = delta.get_col_by_field(&Field::from(method))
.unwrap()
.map(DataPoint::to_float_unchecked)
.collect();
values.sort_by(|a,b| a.partial_cmp(b).unwrap());
Ok(DeReport {
method,
values,
upper_pct,
})
}
pub fn can_delta(&self, other: &Self) -> Result<()> {
if !self.has_color_type(&ColorType::Lab) || !other.has_color_type(&ColorType::Lab) {
return err!("data set does not contain Lab data")
}
if self.n_rows() != other.n_rows() {
return err!("data sets do not contain the same number of samples")
}
Ok(())
}
}
impl From<DEMethod> for Field {
fn from(method: DEMethod) -> Self {
match method {
DEMethod::DE2000 => Field::DE_2000,
DEMethod::DE1976 => Field::DE_1976,
DEMethod::DE1994G => Field::DE_1994,
DEMethod::DE1994T => Field::DE_1994T,
DEMethod::DECMC(a, b) => {
if a == b {
Field::DE_CMC
} else if a / b == 2.0 {
Field::DE_CMC2
} else {
Field::Other(format!("DECMC({a},{b})"))
}
}
}
}
}
impl TryFrom<Field> for DEMethod {
type Error = BoxErr;
fn try_from(field: Field) -> Result<Self> {
Ok(match field {
Field::DE_2000 => DEMethod::DE2000,
Field::DE_1976 => DEMethod::DE1976,
Field::DE_1994 => DEMethod::DE1994G,
Field::DE_1994T => DEMethod::DE1994T,
Field::DE_CMC => DEMethod::DECMC(1.0, 1.0),
Field::DE_CMC2 => DEMethod::DECMC(2.0, 1.0),
other => return err!(format!("not a valid DEMethod: '{}'", other)),
})
}
}
pub struct DeReport {
method: DEMethod,
values: Vec<f32>,
upper_pct: f32,
}
impl DeReport {
pub fn n_samples(&self) -> usize {
self.values.len()
}
fn n_samples_pct(&self, pct: f32) -> usize {
n_samples_pct(self.n_samples(), pct)
}
pub fn method(&self) -> &DEMethod {
&self.method
}
fn overall(&self) -> AvgMinMax {
AvgMinMax {
name: "OVERALL".to_string(),
pct: 1.0,
count: self.n_samples(),
avg: self.values.iter()
.partial_avg()
.expect("DE is empty"),
min: *self.values.iter().min_by(|a,b| a.partial_cmp(b).unwrap()).expect("DE is empty"),
max: *self.values.iter().max_by(|a,b| a.partial_cmp(b).unwrap()).expect("DE is empty"),
stdev: stdev(self.values.iter()),
}
}
fn best(&self) -> AvgMinMax {
let take = self.n_samples_pct(self.upper_pct);
AvgMinMax {
name: "BEST".to_string(),
pct: self.upper_pct,
count: self.n_samples_pct(self.upper_pct),
avg: self.values.iter()
.take(take)
.partial_avg()
.expect("DE is empty"),
min: *self.values.iter().take(take).min_by(|a,b| a.partial_cmp(b).unwrap()).expect("DE is empty"),
max: *self.values.iter().take(take).max_by(|a,b| a.partial_cmp(b).unwrap()).expect("DE is empty"),
stdev: stdev(self.values.iter().take(take)),
}
}
fn worst(&self) -> AvgMinMax {
let skip = self.n_samples_pct(self.upper_pct);
AvgMinMax {
name: "WORST".to_string(),
pct: 1.0 - self.upper_pct,
count: self.n_samples_pct(1.0 - self.upper_pct),
avg: self.values.iter()
.skip(skip)
.partial_avg()
.expect("DE is empty"),
min: *self.values.iter().skip(skip).min_by(|a,b| a.partial_cmp(b).unwrap()).expect("DE is empty"),
max: *self.values.iter().skip(skip).max_by(|a,b| a.partial_cmp(b).unwrap()).expect("DE is empty"),
stdev: stdev(self.values.iter().skip(skip)),
}
}
pub fn efactor(&self) -> f32 {
*self.values.get(self.n_samples_pct(0.95)).unwrap()
}
pub fn values(&self) -> impl Iterator<Item=&f32> {
self.values.iter()
}
}
impl fmt::Display for DeReport {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
writeln!(f, "Number of Samples: {}", self.n_samples())?;
writeln!(f, "DE Formula: {}", self.method)?;
writeln!(f, "E-Factor (95th Percentile): {:0.2}\n", self.efactor())?;
match f.precision() {
Some(p) => {
writeln!(f, "{:.p$}", self.overall())?;
writeln!(f, "{:.p$}", self.best())?;
writeln!(f, "{:.p$}", self.worst())
}
None => {
writeln!(f, "{}", self.overall())?;
writeln!(f, "{}", self.best())?;
writeln!(f, "{}", self.worst())
}
}
}
}
fn n_samples_pct(pop: usize, pct: f32) -> usize {
(pct.clamp(0.0, 1.0) * pop as f32).round() as usize
}
#[test]
fn percentile() {
assert_eq!(n_samples_pct(100, 0.95), 95);
assert_eq!(n_samples_pct(100, 0.05), 5);
assert_eq!(n_samples_pct(126, 0.90), 113);
assert_eq!(n_samples_pct(126, 0.10), 13);
assert_eq!(n_samples_pct(1, 0.95), 1);
assert_eq!(n_samples_pct(1, 0.50), 1);
assert_eq!(n_samples_pct(1, 0.49), 0);
assert_eq!(n_samples_pct(1, 0.05), 0);
assert_eq!(n_samples_pct(2, 0.49), 1);
assert_eq!(n_samples_pct(2, 0.50), 1);
assert_eq!(n_samples_pct(2, 0.51), 1);
}
fn stdev<'a, I: Iterator<Item=&'a f32>>(iter: I) -> f32 {
let values = iter.copied().collect::<Vec<_>>();
let len = values.len() as f32;
let avg = values.iter().sum::<f32>() / len as f32;
f32::sqrt(values.into_iter().map(|val| (val - avg).powi(2)).sum::<f32>() / len)
}
#[test]
fn stdev_test() {
let values = [1.0, 3.0, 4.0, 7.0, 8.0];
assert_eq!(stdev(values.iter()), 2.57682);
let values = [9.0, 2.0, 5.0, 4.0, 12.0, 7.0, 8.0, 11.0, 9.0, 3.0, 7.0, 4.0, 12.0, 5.0, 4.0, 10.0, 9.0, 6.0, 9.0, 4.0];
assert_eq!(stdev(values.iter()), 2.9832866);
}
struct AvgMinMax {
name: String,
pct: f32,
count: usize,
avg: f32,
min: f32,
max: f32,
stdev: f32,
}
impl fmt::Display for AvgMinMax {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
let p = f.precision().unwrap_or(4);
writeln!(f, "{} {:0.0}% - ({} colors)", self.name, self.pct * 100.0, self.count)?;
writeln!(f, "{:>18}: {:0.p$}", "Average DE", self.avg)?;
writeln!(f, "{:>18}: {:0.p$}", "Max DE", self.max)?;
writeln!(f, "{:>18}: {:0.p$}", "Min DE", self.min)?;
writeln!(f, "{:>18}: {:0.p$}", "StDev DE", self.stdev)
}
}