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#include "../../../squiggle.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);
}

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#include "../../../squiggle.h"
#include <stdio.h>
#include <stdlib.h>
// Estimate functions
double sample_0(uint64_t* seed) { UNUSED(seed); return 0; }
double sample_1(uint64_t* seed) { UNUSED(seed); return 1; }
double sample_few(uint64_t* seed) { return sample_to(1, 3, seed); }
double sample_many(uint64_t* seed) { return sample_to(2, 10, seed); }
double sample_model(uint64_t* seed){
double p_a = 0.8;
double p_b = 0.5;
double p_c = p_a * p_b;
int n_dists = 4;
double weights[] = { 1 - p_c, p_c / 2, p_c / 4, p_c / 4 };
double (*samplers[])(uint64_t*) = { sample_0, sample_1, sample_few, sample_many };
double result = sample_mixture(samplers, weights, n_dists, seed);
return result;
}
int main()
{
// set randomness seed
uint64_t* seed = malloc(sizeof(uint64_t));
*seed = 1000; // xorshift can't start with 0
printf("result_one: %f\n", sample_model(seed));
free(seed);
}

@ -0,0 +1,38 @@
#include "../../../squiggle.h"
#include <stdio.h>
#include <stdlib.h>
double sample_0(uint64_t* seed) { UNUSED(seed); return 0; }
double sample_1(uint64_t* seed) { UNUSED(seed); return 1; }
double sample_few(uint64_t* seed) { return sample_to(1, 3, seed); }
double sample_many(uint64_t* seed) { return sample_to(2, 10, seed); }
double sample_model(uint64_t* seed){
double p_a = 0.8;
double p_b = 0.5;
double p_c = p_a * p_b;
int n_dists = 4;
double weights[] = { 1 - p_c, p_c / 2, p_c / 4, p_c / 4 };
double (*samplers[])(uint64_t*) = { sample_0, sample_1, sample_few, sample_many };
double result = sample_mixture(samplers, weights, n_dists, seed);
return result;
}
int main()
{
// set randomness seed
uint64_t* seed = malloc(sizeof(uint64_t));
*seed = 1000; // xorshift can't start with 0
int n_samples = 1000000;
double* result_many = (double*)malloc((size_t)n_samples * sizeof(double));
for (int i = 0; i < n_samples; i++) {
result_many[i] = sample_model(seed);
}
printf("Mean: %f\n", array_mean(result_many, n_samples));
free(seed);
}

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#include "../../../squiggle.h"
#include <stdio.h>
#include <stdlib.h>
double sample_model(uint64_t* seed){
double sample_0(uint64_t* seed) { UNUSED(seed); return 0; }
// Using a gcc extension, you can define a function inside another function
double sample_1(uint64_t* seed) { UNUSED(seed); return 1; }
double sample_few(uint64_t* seed) { return sample_to(1, 3, seed); }
double sample_many(uint64_t* seed) { return sample_to(2, 10, seed); }
double p_a = 0.8;
double p_b = 0.5;
double p_c = p_a * p_b;
int n_dists = 4;
double weights[] = { 1 - p_c, p_c / 2, p_c / 4, p_c / 4 };
double (*samplers[])(uint64_t*) = { sample_0, sample_1, sample_few, sample_many };
double result = sample_mixture(samplers, weights, n_dists, seed);
return result;
}
int main()
{
// set randomness seed
uint64_t* seed = malloc(sizeof(uint64_t));
*seed = 1000; // xorshift can't start with 0
int n_samples = 1000000;
double* result_many = (double*)malloc((size_t)n_samples * sizeof(double));
for (int i = 0; i < n_samples; i++) {
result_many[i] = sample_model(seed);
}
printf("result_many: [");
for (int i = 0; i < 100; i++) {
printf("%.2f, ", result_many[i]);
}
printf("]\n");
free(seed);
}

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#include "../../../squiggle.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
int n = 1000 * 1000;
double* gamma_array = malloc(sizeof(double) * (size_t)n);
for (int i = 0; i < n; i++) {
gamma_array[i] = sample_gamma(1.0, seed);
}
printf("gamma(1) summary statistics = mean: %f, std: %f\n", array_mean(gamma_array, n), array_std(gamma_array, n));
printf("\n");
double* beta_array = malloc(sizeof(double) * (size_t)n);
for (int i = 0; i < n; i++) {
beta_array[i] = sample_beta(1, 2.0, seed);
}
printf("beta(1,2) summary statistics: mean: %f, std: %f\n", array_mean(beta_array, n), array_std(beta_array, n));
printf("\n");
free(gamma_array);
free(beta_array);
free(seed);
}

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#include "../../../squiggle.h"
#include <stdio.h>
#include <stdlib.h>
// Estimate functions
int main()
{
// set randomness seed
uint64_t* seed = malloc(sizeof(uint64_t));
*seed = 1000; // xorshift can't start with 0
for (int i = 0; i < 100; i++) {
double sample = sample_lognormal(0, 10, seed);
printf("%f\n", sample);
}
free(seed);
}

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#include "../../../squiggle.h"
#include <math.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
double sample_fermi_logspace(uint64_t * seed)
{
// Replicate <https://arxiv.org/pdf/1806.02404.pdf>, and in particular the red line in page 11.
// You can see a simple version of this function in naive.c in this same folder
double log_rate_of_star_formation = sample_uniform(log(1), log(100), seed);
double log_fraction_of_stars_with_planets = sample_uniform(log(0.1), log(1), seed);
double log_number_of_habitable_planets_per_star_system = sample_uniform(log(0.1), log(1), seed);
double log_rate_of_life_formation_in_habitable_planets = sample_normal(1, 50, seed);
double log_fraction_of_habitable_planets_in_which_any_life_appears;
/*
Consider:
a = underlying normal
b = rate_of_life_formation_in_habitable_planets = exp(underlying normal) = exp(a)
c = 1 - exp(-b) = fraction_of_habitable_planets_in_which_any_life_appears
d = log(c)
Looking at the Taylor expansion for c = 1 - exp(-b), it's
b - b^2/2 + b^3/6 - x^b/24, etc.
<https://www.wolframalpha.com/input?i=1-exp%28-x%29>
When b ~ 0 (as is often the case), this is close to b.
But now, if b ~ 0, c ~ b
and d = log(c) ~ log(b) = log(exp(a)) = a
Now, we could play around with estimating errors,
and indeed if we want b^2/2 = exp(a)^2/2 < 10^(-n), i.e., to have n decimal digits of precision,
we could compute this as e.g., a < (nlog(10) + log(2))/2
so for example if we want ten digits of precision, that's a < -11
Empirically, the two numbers as calculated in C do become really close around 11 or so,
and at 38 that calculation results in a -inf (so probably a floating point error or similar.)
So we should be using that formula for somewhere between -38 << a < -11
I chose -16 as a happy medium after playing around with
double invert(double x){
return log(1-exp(-exp(-x)));
}
for(int i=0; i<64; i++){
double j = i;
printf("for %lf, log(1-exp(-exp(-x))) is calculated as... %lf\n", j, invert(j));
}
and <https://www.wolframalpha.com/input?i=log%281-exp%28-exp%28-16%29%29%29>
*/
if (log_rate_of_life_formation_in_habitable_planets < -16) {
log_fraction_of_habitable_planets_in_which_any_life_appears = log_rate_of_life_formation_in_habitable_planets;
} else {
double rate_of_life_formation_in_habitable_planets = exp(log_rate_of_life_formation_in_habitable_planets);
double fraction_of_habitable_planets_in_which_any_life_appears = -expm1(-rate_of_life_formation_in_habitable_planets);
log_fraction_of_habitable_planets_in_which_any_life_appears = log(fraction_of_habitable_planets_in_which_any_life_appears);
}
double log_fraction_of_planets_with_life_in_which_intelligent_life_appears = sample_uniform(log(0.001), log(1), seed);
double log_fraction_of_intelligent_planets_which_are_detectable_as_such = sample_uniform(log(0.01), log(1), seed);
double log_longevity_of_detectable_civilizations = sample_uniform(log(100), log(10000000000), seed);
double log_n =
log_rate_of_star_formation +
log_fraction_of_stars_with_planets +
log_number_of_habitable_planets_per_star_system +
log_fraction_of_habitable_planets_in_which_any_life_appears +
log_fraction_of_planets_with_life_in_which_intelligent_life_appears +
log_fraction_of_intelligent_planets_which_are_detectable_as_such +
log_longevity_of_detectable_civilizations;
return log_n;
}
double sample_are_we_alone_logspace(uint64_t * seed)
{
double log_n = sample_fermi_logspace(seed);
return ((log_n > 0) ? 1 : 0);
// log_n > 0 => n > 1
}
int main()
{
// set randomness seed
uint64_t* seed = malloc(sizeof(uint64_t));
*seed = 1001; // xorshift can't start with a seed of 0
double logspace_fermi_proportion = 0;
int n_samples = 1000 * 1000;
for (int i = 0; i < n_samples; i++) {
double result = sample_are_we_alone_logspace(seed);
logspace_fermi_proportion += result;
}
double p_not_alone = logspace_fermi_proportion / n_samples;
printf("Probability that we are not alone: %lf (%.lf%%)\n", p_not_alone, p_not_alone * 100);
free(seed);
}

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#include "../../../squiggle.h"
#include <math.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#define VERBOSE 0
double sample_loguniform(double a, double b, uint64_t* seed)
{
return exp(sample_uniform(log(a), log(b), seed));
}
int main()
{
// Replicate <https://arxiv.org/pdf/1806.02404.pdf>, and in particular the red line in page 11.
// Could also be interesting to just produce and save many samples.
// set randomness seed
uint64_t* seed = malloc(sizeof(uint64_t));
*seed = UINT64_MAX / 64; // xorshift can't start with a seed of 0
// Do this naïvely, without worrying that much about numerical precision
double sample_fermi_naive(uint64_t * seed)
{
double rate_of_star_formation = sample_loguniform(1, 100, seed);
double fraction_of_stars_with_planets = sample_loguniform(0.1, 1, seed);
double number_of_habitable_planets_per_star_system = sample_loguniform(0.1, 1, seed);
double rate_of_life_formation_in_habitable_planets = sample_lognormal(1, 50, seed);
double fraction_of_habitable_planets_in_which_any_life_appears = -expm1(-rate_of_life_formation_in_habitable_planets);
// double fraction_of_habitable_planets_in_which_any_life_appears = 1-exp(-rate_of_life_formation_in_habitable_planets);
// but with more precision
double fraction_of_planets_with_life_in_which_intelligent_life_appears = sample_loguniform(0.001, 1, seed);
double fraction_of_intelligent_planets_which_are_detectable_as_such = sample_loguniform(0.01, 1, seed);
double longevity_of_detectable_civilizations = sample_loguniform(100, 10000000000, seed);
if(VERBOSE) printf(" rate_of_star_formation = %lf\n", rate_of_star_formation);
if(VERBOSE) printf(" fraction_of_stars_with_planets = %lf\n", fraction_of_stars_with_planets);
if(VERBOSE) printf(" number_of_habitable_planets_per_star_system = %lf\n", number_of_habitable_planets_per_star_system);
if(VERBOSE) printf(" rate_of_life_formation_in_habitable_planets = %.16lf\n", rate_of_life_formation_in_habitable_planets);
if(VERBOSE) printf(" fraction_of_habitable_planets_in_which_any_life_appears = %lf\n", fraction_of_habitable_planets_in_which_any_life_appears);
if(VERBOSE) printf(" fraction_of_planets_with_life_in_which_intelligent_life_appears = %lf\n", fraction_of_planets_with_life_in_which_intelligent_life_appears);
if(VERBOSE) printf(" fraction_of_intelligent_planets_which_are_detectable_as_such = %lf\n", fraction_of_intelligent_planets_which_are_detectable_as_such);
if(VERBOSE) printf(" longevity_of_detectable_civilizations = %lf\n", longevity_of_detectable_civilizations);
// Expected number of civilizations in the Milky way;
// see footnote 3 (p. 5)
double n = rate_of_star_formation * fraction_of_stars_with_planets * number_of_habitable_planets_per_star_system * fraction_of_habitable_planets_in_which_any_life_appears * fraction_of_planets_with_life_in_which_intelligent_life_appears * fraction_of_intelligent_planets_which_are_detectable_as_such * longevity_of_detectable_civilizations;
return n;
}
double sample_are_we_alone_naive(uint64_t * seed)
{
double n = sample_fermi_naive(seed);
return ((n > 1) ? 1 : 0);
}
double n = 1000000;
double naive_fermi_proportion = 0;
for (int i = 0; i < n; i++) {
double result = sample_are_we_alone_naive(seed);
if(VERBOSE) printf("result: %lf\n", result);
naive_fermi_proportion += result;
}
printf("Naïve %% that we are not alone: %lf\n", naive_fermi_proportion / n);
free(seed);
/*
double invert(double x){
return log(1-exp(-exp(-x)));
}
for(int i=0; i<64; i++){
double j = i;
printf("for %lf, log(1-exp(-exp(-x))) is calculated as... %lf\n", j, invert(j));
}
*/
}

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# Interface:
# make all
# make format-all
# make run-all
# make one DIR=01_one_sample
# make format-one DIR=01_one_sample
# make run-one DIR=01_one_sample
# make time-linux-one DIR=01_one_sample
# make profile-one DIR=01_one_sample
# Compiler
CC=gcc
# CC=tcc # <= faster compilation
# Main file
SRC=example.c
OUTPUT=example
## Dependencies
SQUIGGLE=../../squiggle.c
MATH=-lm
DEPS=$(SQUIGGLE) $(MATH)
## Flags
# DEBUG=-fsanitize=address,undefined -fanalyzer
# DEBUG=-g
# DEBUG=
WARN=-Wall -Wextra -Wdouble-promotion -Wconversion
STANDARD=-std=c99
OPTIMIZED=-O3 #-Ofast
## Formatter
STYLE_BLUEPRINT=webkit
FORMATTER=clang-format -i -style=$(STYLE_BLUEPRINT)
## make all
all:
$(CC) $(OPTIMIZED) $(DEBUG) $(WARN) 00_example_template/$(SRC) $(DEPS) -o 00_example_template/$(OUTPUT)
$(CC) $(OPTIMIZED) $(DEBUG) $(WARN) 01_one_sample/$(SRC) $(DEPS) -o 01_one_sample/$(OUTPUT)
$(CC) $(OPTIMIZED) $(DEBUG) $(WARN) 02_time_to_botec/$(SRC) $(DEPS) -o 02_time_to_botec/$(OUTPUT)
$(CC) $(OPTIMIZED) $(DEBUG) $(WARN) 03_gcc_nested_function/$(SRC) $(DEPS) -o 03_gcc_nested_function/$(OUTPUT)
$(CC) $(OPTIMIZED) $(DEBUG) $(WARN) 04_gamma_beta/$(SRC) $(DEPS) -o 04_gamma_beta/$(OUTPUT)
$(CC) $(OPTIMIZED) $(DEBUG) $(WARN) 05_hundred_lognormals/$(SRC) $(DEPS) -o 05_hundred_lognormals/$(OUTPUT)
$(CC) $(OPTIMIZED) $(DEBUG) $(WARN) 06_dissolving_fermi_paradox/$(SRC) $(DEPS) -o 06_dissolving_fermi_paradox/$(OUTPUT)
format-all:
$(FORMATTER) 00_example_template/$(SRC)
$(FORMATTER) 01_one_sample/$(SRC)
$(FORMATTER) 02_time_to_botec/$(SRC)
$(FORMATTER) 03_gcc_nested_function/$(SRC)
$(FORMATTER) 04_gamma_beta/$(SRC)
$(FORMATTER) 05_hundred_lognormals/$(SRC)
$(FORMATTER) 06_dissolving_fermi_paradox/$(SRC)
run-all:
00_example_template/$(OUTPUT)
01_one_sample/$(OUTPUT)
02_time_to_botec/$(OUTPUT)
03_gcc_nested_function/$(OUTPUT)
04_gamma_beta/$(OUTPUT)
05_hundred_lognormals/$(OUTPUT)
06_dissolving_fermi_paradox/$(OUTPUT)
## make one DIR=01_one_sample
one: $(DIR)/$(SRC)
$(CC) $(OPTIMIZED) $(DEBUG) $(WARN) $(DIR)/$(SRC) $(DEPS) -o $(DIR)/$(OUTPUT)
## make format-one DIR=01_one_sample
format-one: $(DIR)/$(SRC)
$(FORMATTER) $(DIR)/$(SRC)
## make run-one DIR=01_one_sample
run-one: $(DIR)/$(OUTPUT)
$(DIR)/$(OUTPUT) && echo
## make time-linux-one DIR=01_one_sample
time-linux-one: $(DIR)/$(OUTPUT)
@echo "Requires /bin/time, found on GNU/Linux systems" && echo
@echo "Running 100x and taking avg time $(DIR)/$(OUTPUT)"
@t=$$(/usr/bin/time -f "%e" -p bash -c 'for i in {1..100}; do $(DIR)/$(OUTPUT); done' 2>&1 >/dev/null | grep real | awk '{print $$2}' ); echo "scale=2; 1000 * $$t / 100" | bc | sed "s|^|Time using 1 thread: |" | sed 's|$$|ms|' && echo
## e.g., make profile-linux-one DIR=01_one_sample
profile-linux-one:
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) $(OPTIMIZED) $(DEBUG) $(WARN) $(DIR)/$(SRC) $(DEPS) -o $(DIR)/$(OUTPUT)
# $(CC) $(SRC) $(DEPS) -o $(OUTPUT)
sudo perf record $(DIR)/$(OUTPUT)
sudo perf report
rm perf.data

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#include "../../../squiggle.h"
#include "../../../squiggle_more.h"
#include <stdio.h>
#include <stdlib.h>
double sample_model(uint64_t* seed){
return sample_to(1, 10, seed);
}
int main()
{
// set randomness seed
uint64_t* seed = malloc(sizeof(uint64_t));
*seed = 1000; // xorshift can't start with 0
// ...
free(seed);
}

@ -0,0 +1,30 @@
#include "../../../squiggle.h"
#include "../../../squiggle_more.h"
#include <stdio.h>
#include <stdlib.h>
// Estimate functions
double sample_beta_3_2(uint64_t* seed)
{
return sample_beta(3.0, 2.0, seed);
}
int main()
{
// set randomness seed
uint64_t* seed = malloc(sizeof(uint64_t));
*seed = 1000; // xorshift can't start with 0
int n_samples = 1 * MILLION;
double* xs = malloc(sizeof(double) * (size_t)n_samples);
for (int i = 0; i < n_samples; i++) {
xs[i] = sample_beta_3_2(seed);
}
printf("\n# Stats\n");
array_print_stats(xs, n_samples);
printf("\n# Histogram\n");
array_print_histogram(xs, n_samples, 23);
free(seed);
}

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#include "../../../squiggle.h"
#include "../../../squiggle_more.h"
#include <stdio.h>
#include <stdlib.h>
// Estimate functions
double sample_beta_3_2(uint64_t* seed)
{
return sample_beta(3.0, 2.0, seed);
}
int main()
{
// set randomness seed
uint64_t* seed = malloc(sizeof(uint64_t));
*seed = 1000; // xorshift can't start with 0
int n_samples = 1 * MILLION;
double* xs = malloc(sizeof(double) * (size_t)n_samples);
sampler_parallel(sample_beta_3_2, xs, 16, n_samples);
printf("\n# Stats\n");
array_print_stats(xs, n_samples);
printf("\n# Histogram\n");
array_print_histogram(xs, n_samples, 23);
free(seed);
}

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#include "../../../squiggle.h"
#include "../../../squiggle_more.h"
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
double probability_of_dying_nuno(uint64_t* seed)
{
double first_year_russian_nuclear_weapons = 1953;
double current_year = 2022;
double laplace_probability_nuclear_exchange_year = sample_beta(1, current_year - first_year_russian_nuclear_weapons + 1, seed);
double laplace_probability_nuclear_exchange_month = 1 - pow(1 - laplace_probability_nuclear_exchange_year, (1.0 / 12.0));
double london_hit_conditional_on_russia_nuclear_weapon_usage = sample_beta(7.67, 69.65, seed);
// I.e., a beta distribution with a range of 0.05 to 0.16 into: https://nunosempere.com/blog/2023/03/15/fit-beta/
// 0.05 were my estimate and Samotsvety's estimate in March 2022, respectively:
// https://forum.effectivealtruism.org/posts/KRFXjCqqfGQAYirm5/samotsvety-nuclear-risk-forecasts-march-2022#Nu_o_Sempere
double informed_actor_not_able_to_escape = sample_beta(3.26212166586967, 3.26228162008564, seed);
// 0.2 to 0.8, i.e., 20% to 80%, again using the previous tool
double proportion_which_die_if_bomb_drops_in_london = sample_beta(10.00, 2.45, seed); // 60% to 95%
double probability_of_dying = laplace_probability_nuclear_exchange_month * london_hit_conditional_on_russia_nuclear_weapon_usage * informed_actor_not_able_to_escape * proportion_which_die_if_bomb_drops_in_london;
return probability_of_dying;
}
double probability_of_dying_eli(uint64_t* seed)
{
double russia_nato_nuclear_exchange_in_next_month = sample_beta(1.30, 1182.99, seed); // .0001 to .003
double london_hit_conditional = sample_beta(3.47, 8.97, seed); // 0.1 to 0.5
double informed_actors_not_able_to_escape = sample_beta(2.73, 5.67, seed); // .1 to .6
double proportion_which_die_if_bomb_drops_in_london = sample_beta(3.00, 1.46, seed); // 0.3 to 0.95;
double probability_of_dying = russia_nato_nuclear_exchange_in_next_month * london_hit_conditional * informed_actors_not_able_to_escape * proportion_which_die_if_bomb_drops_in_london;
return probability_of_dying;
}
double sample_nuclear_model(uint64_t* seed)
{
double (*samplers[])(uint64_t*) = { probability_of_dying_nuno, probability_of_dying_eli };
double weights[] = { 0.5, 0.5 };
return sample_mixture(samplers, weights, 2, seed);
}
int main()
{
// set randomness seed
uint64_t* seed = malloc(sizeof(uint64_t));
*seed = 1000; // xorshift can't start with 0
int n = 1 * MILLION;
double* xs = malloc(sizeof(double) * (size_t)n);
for (int i = 0; i < n; i++) {
xs[i] = sample_nuclear_model(seed);
}
printf("\n# Stats\n");
array_print_stats(xs, n);
printf("\n# Histogram\n");
array_print_90_ci_histogram(xs, n, 20);
free(xs);
free(seed);
}

@ -0,0 +1,20 @@
#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
double firstYearRussianNuclearWeapons = 1953;
double currentYear = 2023;
for(int i=0; i<10; i++){
double laplace_beta = sample_beta(currentYear-firstYearRussianNuclearWeapons + 1, 1, seed);
printf("%f\n", laplace_beta);
}
free(seed);
}

@ -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

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#include "../../../squiggle.h"
#include "../../../squiggle_more.h"
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
double sample_minutes_per_day_jumping_rope_needed_to_burn_10kg(uint64_t* seed)
{
double kcal_jumping_rope_minute = sample_to(15, 20, seed);
double kcal_jumping_rope_hour = kcal_jumping_rope_minute * 60;
double kcal_in_kg_of_fat = 7700;
double num_kg_of_fat_to_lose = 10;
double hours_jumping_rope_needed = kcal_in_kg_of_fat * num_kg_of_fat_to_lose / kcal_jumping_rope_hour;
double days_until_end_of_year = 152; // as of 2023-08-01
double hours_per_day = hours_jumping_rope_needed / days_until_end_of_year;
double minutes_per_day = hours_per_day * 60;
return minutes_per_day;
}
int main()
{
// set randomness seed
uint64_t* seed = malloc(sizeof(uint64_t));
*seed = 1000; // xorshift can't start with 0
int n = 1000 * 1000;
double* xs = malloc(sizeof(double) * (size_t)n);
for (int i = 0; i < n; i++) {
xs[i] = sample_minutes_per_day_jumping_rope_needed_to_burn_10kg(seed);
}
printf("## How many minutes per day do I have to jump rope to lose 10kg of fat by the end of the year?\n");
printf("\n# Stats\n");
array_print_stats(xs, n);
printf("\n# Histogram\n");
array_print_histogram(xs, n, 23);
free(seed);
}

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#include "../../../squiggle.h"
#include "../../../squiggle_more.h"
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
double yearly_probability_nuclear_collapse(double year, uint64_t* seed)
{
double successes = 0;
double failures = (year - 1960);
return sample_laplace(successes, failures, seed);
// ^ can change to (successes + 1)/(trials + 2)
// to get a probability,
// rather than sampling from a distribution over probabilities.
}
double yearly_probability_nuclear_collapse_2023(uint64_t* seed)
{
return yearly_probability_nuclear_collapse(2023, seed);
}
double yearly_probability_nuclear_collapse_after_recovery(double year, double rebuilding_period_length_years, uint64_t* seed)
{
// assumption: nuclear
double successes = 1.0;
double failures = (year - rebuilding_period_length_years - 1960 - 1);
return sample_laplace(successes, failures, seed);
}
double yearly_probability_nuclear_collapse_after_recovery_example(uint64_t* seed)
{
double year = 2070;
double rebuilding_period_length_years = 30;
// So, there was a nuclear collapse in 2040,
// then a recovery period of 30 years
// and it's now 2070
return yearly_probability_nuclear_collapse_after_recovery(year, rebuilding_period_length_years, seed);
}
double yearly_probability_nuclear_collapse_after_recovery_antiinductive(uint64_t* seed)
{
return yearly_probability_nuclear_collapse(2023, seed) / 2;
}
int main()
{
// set randomness seed
uint64_t* seed = malloc(sizeof(uint64_t));
*seed = 1000; // xorshift can't start with 0
int n_samples = 1000000;
// Before a first nuclear collapse
printf("## Before the first nuclear collapse\n");
double* yearly_probability_nuclear_collapse_2023_samples = malloc(sizeof(double) * (size_t)n_samples);
for (int i = 0; i < n_samples; i++) {
yearly_probability_nuclear_collapse_2023_samples[i] = yearly_probability_nuclear_collapse_2023(seed);
}
ci ci_90_2023 = array_get_90_ci(yearly_probability_nuclear_collapse_2023_samples, n_samples);
printf("90%% confidence interval: [%f, %f]\n", ci_90_2023.low, ci_90_2023.high);
// After the first nuclear collapse
printf("\n## After the first nuclear collapse\n");
double* yearly_probability_nuclear_collapse_after_recovery_samples = malloc(sizeof(double) * (size_t)n_samples);
for (int i = 0; i < n_samples; i++) {
yearly_probability_nuclear_collapse_after_recovery_samples[i] = yearly_probability_nuclear_collapse_after_recovery_example(seed);
}
ci ci_90_2070 = array_get_90_ci(yearly_probability_nuclear_collapse_after_recovery_samples, 1000000);
printf("90%% confidence interval: [%f, %f]\n", ci_90_2070.low, ci_90_2070.high);
// After the first nuclear collapse (antiinductive)
printf("\n## After the first nuclear collapse (antiinductive)\n");
double* yearly_probability_nuclear_collapse_after_recovery_antiinductive_samples = malloc(sizeof(double) * (size_t)n_samples);
for (int i = 0; i < n_samples; i++) {
yearly_probability_nuclear_collapse_after_recovery_antiinductive_samples[i] = yearly_probability_nuclear_collapse_after_recovery_antiinductive(seed);
}
ci ci_90_antiinductive = array_get_90_ci(yearly_probability_nuclear_collapse_after_recovery_antiinductive_samples, 1000000);
printf("90%% confidence interval: [%f, %f]\n", ci_90_antiinductive.low, ci_90_antiinductive.high);
// free seeds
free(yearly_probability_nuclear_collapse_2023_samples);
free(yearly_probability_nuclear_collapse_after_recovery_samples);
free(yearly_probability_nuclear_collapse_after_recovery_antiinductive_samples);
free(seed);
}

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#include "../../../squiggle.h"
#include "../../../squiggle_more.h"
#include <math.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
normal_params n1 = { .mean = 1.0, .std = 3.0 };
normal_params n2 = { .mean = 2.0, .std = 4.0 };
normal_params sn = algebra_sum_normals(n1, n2);
printf("The sum of Normal(%f, %f) and Normal(%f, %f) is Normal(%f, %f)\n",
n1.mean, n1.std, n2.mean, n2.std, sn.mean, sn.std);
lognormal_params ln1 = { .logmean = 1.0, .logstd = 3.0 };
lognormal_params ln2 = { .logmean = 2.0, .logstd = 4.0 };
lognormal_params sln = algebra_product_lognormals(ln1, ln2);
printf("The product of Lognormal(%f, %f) and Lognormal(%f, %f) is Lognormal(%f, %f)\n",
ln1.logmean, ln1.logstd, ln2.logmean, ln2.logstd, sln.logmean, sln.logstd);
free(seed);
}

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#include "../../../squiggle.h"
#include "../../../squiggle_more.h"
#include <math.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
// Convert to 90% confidence interval form and back
lognormal_params ln1 = { .logmean = 1.0, .logstd = 3.0 };
ci ln1_ci = convert_lognormal_params_to_ci(ln1);
printf("The 90%% confidence interval of Lognormal(%f, %f) is [%f, %f]\n",
ln1.logmean, ln1.logstd,
ln1_ci.low, ln1_ci.high);
lognormal_params ln1_params2 = convert_ci_to_lognormal_params(ln1_ci);
printf("The lognormal which has 90%% confidence interval [%f, %f] is Lognormal(%f, %f)\n",
ln1_ci.low, ln1_ci.high,
ln1_params2.logmean, ln1_params2.logstd);
lognormal_params ln2 = convert_ci_to_lognormal_params((ci) { .low = 1, .high = 10 });
lognormal_params ln3 = convert_ci_to_lognormal_params((ci) { .low = 5, .high = 50 });
lognormal_params sln = algebra_product_lognormals(ln2, ln3);
ci sln_ci = convert_lognormal_params_to_ci(sln);
printf("Result of some lognormal products: to(%f, %f)\n", sln_ci.low, sln_ci.high);
free(seed);
}

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