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
|
/*
* (C) Copyright 1996- ECMWF.
*
* This software is licensed under the terms of the Apache Licence Version 2.0
* which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
*
* In applying this licence, ECMWF does not waive the privileges and immunities
* granted to it by virtue of its status as an intergovernmental organisation nor
* does it submit to any jurisdiction.
*/
#include <memory>
#include <ostream>
#include <vector>
#include "eckit/testing/Test.h"
#include "eckit/types/FloatCompare.h"
#include "mir/param/SimpleParametrisation.h"
#include "mir/stats/field/CentralMomentStats.h"
#include "mir/stats/field/CounterStats.h"
#include "mir/stats/field/ModeStats.h"
#include "mir/util/Log.h"
constexpr double EPS = 1e-6;
#define EXPECTV(a) \
Log::info() << "EXPECT(" << #a << ")" << std::endl; \
EXPECT(a)
#define EXPECT_APPROX_V(a, b) \
Log::info() << "EXPECT(" << #a << " ~= " << #b << ")" << std::endl; \
EXPECT(eckit::types::is_approximately_equal(static_cast<double>(a), static_cast<double>(b), EPS))
namespace mir::tests::unit {
struct case_t {
double mode;
double median;
double mean;
double min;
double max;
bool disambiguateMax;
std::vector<double> data;
friend std::ostream& operator<<(std::ostream& s, const case_t& c) {
s << "case: { statistic-disambiguate-max: " << c.disambiguateMax << ", data: [";
const auto* sep = "";
for (auto d : c.data) {
s << sep << d;
sep = ", ";
}
s << "]}";
return s;
}
};
CASE("mir::stats::Field") {
std::vector<case_t> cases{case_t{42., 42., 42, 42., 42., true, {42}},
case_t{4., 2., 2.4, 1., 4., true, {1, 1, 2, 4, 4}},
case_t{1., 2., 2.4, 1., 4., false, {1, 1, 2, 4, 4}},
case_t{6., 6., 8., 1., 22., true, {22, 1, 3, 6, 6, 6, 6, 7, 7, 12, 12}},
case_t{2., 3., 4., 1., 9., true, {1, 2, 2, 3, 4, 7, 9}},
case_t{3., 6., 5.285714, 1., 9., true, {1, 3, 3, 6, 7, 8, 9}}};
SECTION("ModeIntegral") {
for (auto& c : cases) {
param::SimpleParametrisation param;
param.set("mode-disambiguate-max", c.disambiguateMax);
std::unique_ptr<stats::Field> mode(stats::FieldFactory::build("mode-integral", param));
Log::info() << "Test " << c << ':' << std::endl;
for (auto d : c.data) {
mode->count(d);
}
Log::info() << "mode=" << mode->value() << std::endl;
EXPECT_APPROX_V(mode->value(), c.mode);
}
}
SECTION("MedianIntegral") {
for (auto& c : cases) {
param::SimpleParametrisation param;
param.set("mode-disambiguate-max", c.disambiguateMax);
std::unique_ptr<stats::Field> median(stats::FieldFactory::build("median-integral", param));
Log::info() << "Test " << c << ':' << std::endl;
for (auto d : c.data) {
median->count(d);
}
Log::info() << "median=" << *median << std::endl;
EXPECT_APPROX_V(median->value(), c.median);
}
}
SECTION("Mean") {
for (auto& c : cases) {
param::SimpleParametrisation param;
std::unique_ptr<stats::Field> mean(stats::FieldFactory::build("mean", param));
Log::info() << "Test " << c << ':' << std::endl;
for (auto d : c.data) {
mean->count(d);
}
Log::info() << "mean=" << *mean << std::endl;
EXPECT_APPROX_V(mean->value(), c.mean);
}
}
SECTION("Counter") {
for (auto& c : cases) {
const std::vector<double> modeValues{4., 5.};
const std::vector<double> modeLimits{4.5};
param::SimpleParametrisation param;
param.set("counter-lower-limit", modeLimits.back());
param.set("counter-upper-limit", modeLimits.back());
param.set("mode-disambiguate-max", c.disambiguateMax);
param.set("mode-real-values", modeValues);
param.set("mode-real-min", modeLimits);
std::unique_ptr<stats::Field> above(stats::FieldFactory::build("count-above-upper-limit", param));
std::unique_ptr<stats::Field> below(stats::FieldFactory::build("count-below-lower-limit", param));
std::unique_ptr<stats::Field> mode(stats::FieldFactory::build("mode-real", param));
Log::info() << "Test " << c << ':' << std::endl;
for (auto d : c.data) {
above->count(d);
below->count(d);
mode->count(d);
}
Log::info() << "above=" << *above << std::endl;
Log::info() << "below=" << *below << std::endl;
EXPECT_APPROX_V(above->value() + below->value(), c.data.size());
Log::info() << "mode=" << *mode << std::endl;
EXPECT_APPROX_V(mode->value(), above->value() < below->value() ? modeValues.front() : modeValues.back());
}
}
}
} // namespace mir::tests::unit
int main(int argc, char** argv) {
return eckit::testing::run_tests(argc, argv);
}
|
