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
|
#include <getopt.h>
#include <iomanip>
#include "fits.hpp"
int main(int argc, char* argv[]) {
unsigned N = 80;
int opt;
while ((opt = getopt(argc, argv, "M:s:S:B:i:N:")) != -1) {
switch (opt) {
case 'N':
N = (unsigned)atof(optarg);
break;
default:
exit(1);
}
}
std::string firstline;
std::getline(std::cin, firstline);
std::stringstream ss;
ss << firstline;
Data data;
while (!ss.eof()) {
Real x, y;
ss >> x;
ss >> y;
data.push_back({x,y});
}
Rng r;
std::cout << std::setprecision(15);
for (unsigned i = 0; i < 5; i++) {
Vector a₀ = Vector::Zero(N);
for (Real& aa : a₀) {
aa = r.variate<Real, std::normal_distribution>(0, 2e-2);
}
Vector a = stochasticGradientDescent(data, a₀, 10, 1e12);
for (Real ai : a) {
std::cout << ai << " ";
}
std::cout << std::endl;
}
for (unsigned i = 0; i < 5; i++) {
Vector a₀ = Vector::Zero(N);
for (Real& aa : a₀) {
aa = r.variate<Real, std::normal_distribution>(0, 5);
}
Vector a = stochasticGradientDescent(data, a₀, 10, 1e12);
for (Real ai : a) {
std::cout << ai << " ";
}
std::cout << std::endl;
}
return 0;
}
|