forked from personal/squiggle.c
add serious model, add template.
This commit is contained in:
parent
84399e60a2
commit
9c19095955
14
README.md
14
README.md
|
|
@ -20,12 +20,14 @@ A self-contained C99 library that provides a subset of [Squiggle](https://www.sq
|
|||
|
||||
You can follow some example usage in the examples/ folder
|
||||
|
||||
1. In the first example, we define a small model, and draw one sample from it
|
||||
2. In the second example, we define a small model, and return many samples
|
||||
3. In the third example, we use a gcc extension—nested functions—to rewrite the code from point 2. in a more linear way.
|
||||
4. In the fourth example, we define some simple cdfs, and we draw samples from those cdfs. We see that this approach is slower than using the built-in samplers, e.g., the normal sampler.
|
||||
5. In the fifth example, we define the cdf for the beta distribution, and we draw samples from it.
|
||||
6. In the sixth example, we take samples from simple gamma and beta distributions, using the samplers provided by this library.
|
||||
1. In the 1st example, we define a small model, and draw one sample from it
|
||||
2. In the 2nd example, we define a small model, and return many samples
|
||||
3. In the 3rd example, we use a gcc extension—nested functions—to rewrite the code from point 2. in a more linear way.
|
||||
4. In the 4th example, we define some simple cdfs, and we draw samples from those cdfs. We see that this approach is slower than using the built-in samplers, e.g., the normal sampler.
|
||||
5. In the 5th example, we define the cdf for the beta distribution, and we draw samples from it.
|
||||
6. In the 6th example, we take samples from simple gamma and beta distributions, using the samplers provided by this library.
|
||||
7. In the 7th example, we get the 90% confidence interval of a beta distribution
|
||||
8. The 8th example translates the models from Eli and Nuño from [Samotsvety Nuclear Risk Forecasts — March 2022](https://forum.nunosempere.com/posts/KRFXjCqqfGQAYirm5/samotsvety-nuclear-risk-forecasts-march-2022#Nu_o_Sempere) into squiggle.c, then creates a mixture from both, and returns the mean probability of death per month and the 90% confidence interval.
|
||||
|
||||
## Commentary
|
||||
|
||||
|
|
|
|||
14
examples/00_example_template/example.c
Normal file
14
examples/00_example_template/example.c
Normal file
|
|
@ -0,0 +1,14 @@
|
|||
#include "../../squiggle.h"
|
||||
#include <stdint.h>
|
||||
#include <stdio.h>
|
||||
#include <stdlib.h>
|
||||
|
||||
int main()
|
||||
{
|
||||
// set randomness seed
|
||||
uint64_t* seed = malloc(sizeof(uint64_t));
|
||||
*seed = 1000; // xorshift can't start with 0
|
||||
|
||||
|
||||
free(seed);
|
||||
}
|
||||
53
examples/00_example_template/makefile
Normal file
53
examples/00_example_template/makefile
Normal file
|
|
@ -0,0 +1,53 @@
|
|||
# Interface:
|
||||
# make
|
||||
# make build
|
||||
# make format
|
||||
# make run
|
||||
|
||||
# Compiler
|
||||
CC=gcc
|
||||
# CC=tcc # <= faster compilation
|
||||
|
||||
# Main file
|
||||
SRC=example.c ../../squiggle.c
|
||||
OUTPUT=example
|
||||
|
||||
## Dependencies
|
||||
MATH=-lm
|
||||
|
||||
## Flags
|
||||
DEBUG= #'-g'
|
||||
STANDARD=-std=c99
|
||||
WARNINGS=-Wall
|
||||
OPTIMIZED=-O3 #-Ofast
|
||||
# OPENMP=-fopenmp
|
||||
|
||||
## Formatter
|
||||
STYLE_BLUEPRINT=webkit
|
||||
FORMATTER=clang-format -i -style=$(STYLE_BLUEPRINT)
|
||||
|
||||
## make build
|
||||
build: $(SRC)
|
||||
$(CC) $(OPTIMIZED) $(DEBUG) $(SRC) $(MATH) -o $(OUTPUT)
|
||||
|
||||
format: $(SRC)
|
||||
$(FORMATTER) $(SRC)
|
||||
|
||||
run: $(SRC) $(OUTPUT)
|
||||
OMP_NUM_THREADS=1 ./$(OUTPUT) && echo
|
||||
|
||||
time-linux:
|
||||
@echo "Requires /bin/time, found on GNU/Linux systems" && echo
|
||||
|
||||
@echo "Running 100x and taking avg time $(OUTPUT)"
|
||||
@t=$$(/usr/bin/time -f "%e" -p bash -c 'for i in {1..100}; do $(OUTPUT); done' 2>&1 >/dev/null | grep real | awk '{print $$2}' ); echo "scale=2; 1000 * $$t / 100" | bc | sed "s|^|Time using 1 thread: |" | sed 's|$$|ms|' && echo
|
||||
|
||||
## Profiling
|
||||
|
||||
profile-linux:
|
||||
echo "Requires perf, which depends on the kernel version, and might be in linux-tools package or similar"
|
||||
echo "Must be run as sudo"
|
||||
$(CC) $(SRC) $(MATH) -o $(OUTPUT)
|
||||
sudo perf record ./$(OUTPUT)
|
||||
sudo perf report
|
||||
rm perf.data
|
||||
56
squiggle.c
56
squiggle.c
|
|
@ -94,12 +94,12 @@ double sample_gamma(double alpha, uint64_t* seed)
|
|||
// A Simple Method for Generating Gamma Variables, Marsaglia and Wan Tsang, 2001
|
||||
// https://dl.acm.org/doi/pdf/10.1145/358407.358414
|
||||
// see also the references/ folder
|
||||
// Note that the Wikipedia page for the gamma distribution includes a scaling parameter
|
||||
// k or beta
|
||||
// https://en.wikipedia.org/wiki/Gamma_distribution
|
||||
// such that gamma_k(alpha, k) = k * gamma(alpha)
|
||||
// or gamma_beta(alpha, beta) = gamma(alpha) / beta
|
||||
// So far I have not needed to use this, and thus the second parameter is by default 1.
|
||||
// Note that the Wikipedia page for the gamma distribution includes a scaling parameter
|
||||
// k or beta
|
||||
// https://en.wikipedia.org/wiki/Gamma_distribution
|
||||
// such that gamma_k(alpha, k) = k * gamma(alpha)
|
||||
// or gamma_beta(alpha, beta) = gamma(alpha) / beta
|
||||
// So far I have not needed to use this, and thus the second parameter is by default 1.
|
||||
if (alpha >= 1) {
|
||||
double d, c, x, v, u;
|
||||
d = alpha - 1.0 / 3.0;
|
||||
|
|
@ -386,38 +386,40 @@ struct box sampler_cdf_double(double cdf(double), uint64_t* seed)
|
|||
// Get confidence intervals, given a sampler
|
||||
|
||||
struct c_i {
|
||||
float low;
|
||||
float high;
|
||||
float low;
|
||||
float high;
|
||||
};
|
||||
int compare_doubles(const void *p, const void *q) {
|
||||
// https://wikiless.esmailelbob.xyz/wiki/Qsort?lang=en
|
||||
double x = *(const double *)p;
|
||||
double y = *(const double *)q;
|
||||
int compare_doubles(const void* p, const void* q)
|
||||
{
|
||||
// https://wikiless.esmailelbob.xyz/wiki/Qsort?lang=en
|
||||
double x = *(const double*)p;
|
||||
double y = *(const double*)q;
|
||||
|
||||
/* Avoid return x - y, which can cause undefined behaviour
|
||||
because of signed integer overflow. */
|
||||
if (x < y)
|
||||
return -1; // Return -1 if you want ascending, 1 if you want descending order.
|
||||
return -1; // Return -1 if you want ascending, 1 if you want descending order.
|
||||
else if (x > y)
|
||||
return 1; // Return 1 if you want ascending, -1 if you want descending order.
|
||||
return 1; // Return 1 if you want ascending, -1 if you want descending order.
|
||||
|
||||
return 0;
|
||||
}
|
||||
struct c_i get_90_confidence_interval(double (*sampler)(uint64_t*), uint64_t* seed){
|
||||
int n = 100 * 1000;
|
||||
double* samples_array = malloc(n * sizeof(double));
|
||||
for(int i=0; i<n; i++){
|
||||
samples_array[i] = sampler(seed);
|
||||
}
|
||||
qsort(samples_array, n, sizeof(double), compare_doubles);
|
||||
struct c_i get_90_confidence_interval(double (*sampler)(uint64_t*), uint64_t* seed)
|
||||
{
|
||||
int n = 100 * 1000;
|
||||
double* samples_array = malloc(n * sizeof(double));
|
||||
for (int i = 0; i < n; i++) {
|
||||
samples_array[i] = sampler(seed);
|
||||
}
|
||||
qsort(samples_array, n, sizeof(double), compare_doubles);
|
||||
|
||||
struct c_i result = {
|
||||
.low = samples_array[5000],
|
||||
.high =samples_array[94999],
|
||||
};
|
||||
free(samples_array);
|
||||
struct c_i result = {
|
||||
.low = samples_array[5000],
|
||||
.high = samples_array[94999],
|
||||
};
|
||||
free(samples_array);
|
||||
|
||||
return result;
|
||||
return result;
|
||||
}
|
||||
|
||||
/* Could also define other variations, e.g.,
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user