-
Notifications
You must be signed in to change notification settings - Fork 2
/
test_fit.c
86 lines (77 loc) · 2.21 KB
/
test_fit.c
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
/*
* Test fit_lognorm.c with randomly drawn read lengths.
*
* Copyright (c) 2017 Graham Gower <[email protected]>
*
* Permission to use, copy, modify, and distribute this software for any
* purpose with or without fee is hereby granted, provided that the above
* copyright notice and this permission notice appear in all copies.
*
* THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
* WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
* MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
* ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
* WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
* ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
* OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
*/
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <stdint.h>
#include <sys/types.h>
#include <math.h>
#include "kmath.h"
int fit_lognorm(const uint64_t *hist, int len, uint64_t area, double *mu, double *sigma);
static krand_t *kr;
uint
rlognorm(double mu, double sigma)
{
double x = kr_normal(kr);
return round(exp(mu + x*sigma));
}
void
sample(uint64_t *hist, int len, size_t n,
double mu, double sigma)
{
int i;
for (i=0; i<n; i++) {
uint x = rlognorm(mu, sigma);
if (x > len)
x = len;
hist[x]++;
}
}
#define HIST_SIZE 141
#define NSAMPLES 100
#define SAMPLE_SIZE 10000
int
main()
{
uint64_t hist[HIST_SIZE+1];
double mu, sigma;
double est_mu, est_sigma;
double ssqe_mu, ssqe_sigma;
uint64_t tsum;
int i;
kr = kr_srand(31415);
for (mu=4.0; mu<5.55; mu+=0.1) {
for (sigma=0.2; sigma<0.55; sigma+=0.1) {
ssqe_mu = ssqe_sigma = 0;
tsum = 0;
for (i=0; i<NSAMPLES; i++) {
memset(hist, 0, sizeof(hist));
sample(hist, HIST_SIZE, SAMPLE_SIZE, mu, sigma);
fit_lognorm(hist, HIST_SIZE, SAMPLE_SIZE, &est_mu, &est_sigma);
ssqe_mu += (mu-est_mu)*(mu-est_mu);
ssqe_sigma += (sigma-est_sigma)*(sigma-est_sigma);
tsum += hist[HIST_SIZE];
}
printf("mu=%.3lf (msqe=%.3lg), sigma=%.3lf (msqe=%.3lg), tail=%.3lg\n",
mu, ssqe_mu/NSAMPLES,
sigma, ssqe_sigma/NSAMPLES,
(double)tsum/NSAMPLES/SAMPLE_SIZE);
}
}
free(kr);
}