forked from personal/squiggle.c
split into squiggle and extra.
This commit is contained in:
parent
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302
extra.c
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302
extra.c
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@ -0,0 +1,302 @@
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#include <float.h>
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#include <limits.h>
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#include <math.h>
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#include <stdint.h>
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#include <stdio.h>
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#include <stdlib.h>
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#include <sys/types.h>
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#include <time.h>
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// Some error niceties; these won't be used until later
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#define MAX_ERROR_LENGTH 500
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#define EXIT_ON_ERROR 0
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#define PROCESS_ERROR(error_msg) process_error(error_msg, EXIT_ON_ERROR, __FILE__, __LINE__)
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// # More cool stuff
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// This is no longer necessary to do basic estimation,
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// but is still cool
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// ## Sample from an arbitrary cdf
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struct box {
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int empty;
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double content;
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char* error_msg;
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};
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struct box process_error(const char* error_msg, int should_exit, char* file, int line)
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{
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if (should_exit) {
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printf("@, in %s (%d)", file, line);
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exit(1);
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} else {
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char error_msg[MAX_ERROR_LENGTH];
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snprintf(error_msg, MAX_ERROR_LENGTH, "@, in %s (%d)", file, line); // NOLINT: We are being carefull here by considering MAX_ERROR_LENGTH explicitly.
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struct box error = { .empty = 1, .error_msg = error_msg };
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return error;
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}
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}
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// Inverse cdf at point
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// Two versions of this function:
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// - raw, dealing with cdfs that return doubles
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// - input: cdf: double => double, p
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// - output: Box(number|error)
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// - box, dealing with cdfs that return a box.
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// - input: cdf: double => Box(number|error), p
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// - output: Box(number|error)
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struct box inverse_cdf_double(double cdf(double), double p)
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{
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// given a cdf: [-Inf, Inf] => [0,1]
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// returns a box with either
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// x such that cdf(x) = p
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// or an error
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// if EXIT_ON_ERROR is set to 1, it exits instead of providing an error
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double low = -1.0;
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double high = 1.0;
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// 1. Make sure that cdf(low) < p < cdf(high)
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int interval_found = 0;
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while ((!interval_found) && (low > -FLT_MAX / 4) && (high < FLT_MAX / 4)) {
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// ^ Using FLT_MIN and FLT_MAX is overkill
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// but it's also the *correct* thing to do.
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int low_condition = (cdf(low) < p);
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int high_condition = (p < cdf(high));
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if (low_condition && high_condition) {
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interval_found = 1;
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} else if (!low_condition) {
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low = low * 2;
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} else if (!high_condition) {
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high = high * 2;
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}
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}
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if (!interval_found) {
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return PROCESS_ERROR("Interval containing the target value not found, in function inverse_cdf");
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} else {
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int convergence_condition = 0;
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int count = 0;
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while (!convergence_condition && (count < (INT_MAX / 2))) {
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double mid = (high + low) / 2;
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int mid_not_new = (mid == low) || (mid == high);
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// double width = high - low;
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// if ((width < 1e-8) || mid_not_new){
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if (mid_not_new) {
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convergence_condition = 1;
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} else {
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double mid_sign = cdf(mid) - p;
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if (mid_sign < 0) {
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low = mid;
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} else if (mid_sign > 0) {
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high = mid;
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} else if (mid_sign == 0) {
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low = mid;
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high = mid;
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}
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}
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}
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if (convergence_condition) {
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struct box result = { .empty = 0, .content = low };
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return result;
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} else {
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return PROCESS_ERROR("Search process did not converge, in function inverse_cdf");
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}
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}
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}
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struct box inverse_cdf_box(struct box cdf_box(double), double p)
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{
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// given a cdf: [-Inf, Inf] => Box([0,1])
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// returns a box with either
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// x such that cdf(x) = p
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// or an error
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// if EXIT_ON_ERROR is set to 1, it exits instead of providing an error
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double low = -1.0;
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double high = 1.0;
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// 1. Make sure that cdf(low) < p < cdf(high)
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int interval_found = 0;
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while ((!interval_found) && (low > -FLT_MAX / 4) && (high < FLT_MAX / 4)) {
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// ^ Using FLT_MIN and FLT_MAX is overkill
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// but it's also the *correct* thing to do.
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struct box cdf_low = cdf_box(low);
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if (cdf_low.empty) {
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return PROCESS_ERROR(cdf_low.error_msg);
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}
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struct box cdf_high = cdf_box(high);
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if (cdf_high.empty) {
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return PROCESS_ERROR(cdf_low.error_msg);
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}
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int low_condition = (cdf_low.content < p);
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int high_condition = (p < cdf_high.content);
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if (low_condition && high_condition) {
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interval_found = 1;
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} else if (!low_condition) {
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low = low * 2;
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} else if (!high_condition) {
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high = high * 2;
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}
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}
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if (!interval_found) {
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return PROCESS_ERROR("Interval containing the target value not found, in function inverse_cdf");
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} else {
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int convergence_condition = 0;
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int count = 0;
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while (!convergence_condition && (count < (INT_MAX / 2))) {
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double mid = (high + low) / 2;
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int mid_not_new = (mid == low) || (mid == high);
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// double width = high - low;
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if (mid_not_new) {
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// if ((width < 1e-8) || mid_not_new){
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convergence_condition = 1;
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} else {
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struct box cdf_mid = cdf_box(mid);
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if (cdf_mid.empty) {
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return PROCESS_ERROR(cdf_mid.error_msg);
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}
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double mid_sign = cdf_mid.content - p;
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if (mid_sign < 0) {
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low = mid;
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} else if (mid_sign > 0) {
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high = mid;
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} else if (mid_sign == 0) {
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low = mid;
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high = mid;
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}
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}
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}
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if (convergence_condition) {
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struct box result = { .empty = 0, .content = low };
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return result;
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} else {
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return PROCESS_ERROR("Search process did not converge, in function inverse_cdf");
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}
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}
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}
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// Sampler based on inverse cdf and randomness function
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struct box sampler_cdf_box(struct box cdf(double), uint64_t* seed)
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{
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double p = sample_unit_uniform(seed);
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struct box result = inverse_cdf_box(cdf, p);
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return result;
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}
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struct box sampler_cdf_double(double cdf(double), uint64_t* seed)
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{
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double p = sample_unit_uniform(seed);
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struct box result = inverse_cdf_double(cdf, p);
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return result;
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}
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/* Could also define other variations, e.g.,
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double sampler_danger(struct box cdf(double), uint64_t* seed)
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{
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double p = sample_unit_uniform(seed);
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struct box result = inverse_cdf_box(cdf, p);
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if(result.empty){
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exit(1);
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}else{
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return result.content;
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}
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}
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*/
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// Get confidence intervals, given a sampler
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typedef struct ci_t {
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float low;
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float high;
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} ci;
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int compare_doubles(const void* p, const void* q)
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{
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// https://wikiless.esmailelbob.xyz/wiki/Qsort?lang=en
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double x = *(const double*)p;
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double y = *(const double*)q;
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/* Avoid return x - y, which can cause undefined behaviour
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because of signed integer overflow. */
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if (x < y)
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return -1; // Return -1 if you want ascending, 1 if you want descending order.
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else if (x > y)
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return 1; // Return 1 if you want ascending, -1 if you want descending order.
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return 0;
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}
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ci get_90_confidence_interval(double (*sampler)(uint64_t*), uint64_t* seed)
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{
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int n = 100 * 1000;
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double* samples_array = malloc(n * sizeof(double));
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for (int i = 0; i < n; i++) {
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samples_array[i] = sampler(seed);
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}
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qsort(samples_array, n, sizeof(double), compare_doubles);
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ci result = {
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.low = samples_array[5000],
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.high = samples_array[94999],
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};
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free(samples_array);
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return result;
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}
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// # Small algebra manipulations
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// here I discover named structs,
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// which mean that I don't have to be typing
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// struct blah all the time.
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typedef struct normal_params_t {
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double mean;
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double std;
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} normal_params;
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normal_params algebra_sum_normals(normal_params a, normal_params b)
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{
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normal_params result = {
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.mean = a.mean + b.mean,
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.std = sqrt((a.std * a.std) + (b.std * b.std)),
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};
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return result;
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}
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typedef struct lognormal_params_t {
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double logmean;
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double logstd;
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} lognormal_params;
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lognormal_params algebra_product_lognormals(lognormal_params a, lognormal_params b)
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{
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lognormal_params result = {
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.logmean = a.logmean + b.logmean,
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.logstd = sqrt((a.logstd * a.logstd) + (b.logstd * b.logstd)),
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};
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return result;
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}
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lognormal_params convert_ci_to_lognormal_params(ci x)
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{
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double loghigh = logf(x.high);
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double loglow = logf(x.low);
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double logmean = (loghigh + loglow) / 2.0;
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double logstd = (loghigh - loglow) / (2.0 * NORMAL90CONFIDENCE);
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lognormal_params result = { .logmean = logmean, .logstd = logstd };
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return result;
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}
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ci convert_lognormal_params_to_ci(lognormal_params y)
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{
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double h = y.logstd * NORMAL90CONFIDENCE;
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double loghigh = y.logmean + h;
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double loglow = y.logmean - h;
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ci result = { .low = exp(loglow), .high = exp(loghigh) };
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return result;
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}
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52
extra.h
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52
extra.h
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@ -0,0 +1,52 @@
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#ifndef SQUIGGLE_C_EXTRA
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#define SQUIGGLE_C_EXTRA
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// Box
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struct box {
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int empty;
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double content;
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char* error_msg;
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};
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// Macros to handle errors
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#define MAX_ERROR_LENGTH 500
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#define EXIT_ON_ERROR 0
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#define PROCESS_ERROR(error_msg) process_error(error_msg, EXIT_ON_ERROR, __FILE__, __LINE__)
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struct box process_error(const char* error_msg, int should_exit, char* file, int line);
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// Inverse cdf
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struct box inverse_cdf_double(double cdf(double), double p);
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struct box inverse_cdf_box(struct box cdf_box(double), double p);
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// Samplers from cdf
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struct box sampler_cdf_double(double cdf(double), uint64_t* seed);
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struct box sampler_cdf_box(struct box cdf(double), uint64_t* seed);
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// Get 90% confidence interval
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typedef struct ci_t {
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float low;
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float high;
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} ci;
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ci get_90_confidence_interval(double (*sampler)(uint64_t*), uint64_t* seed);
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// small algebra manipulations
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typedef struct normal_params_t {
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double mean;
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double std;
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} normal_params;
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normal_params algebra_sum_normals(normal_params a, normal_params b);
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typedef struct lognormal_params_t {
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double logmean;
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double logstd;
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} lognormal_params;
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lognormal_params algebra_product_lognormals(lognormal_params a, lognormal_params b);
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lognormal_params convert_ci_to_lognormal_params(ci x);
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ci convert_lognormal_params_to_ci(lognormal_params y);
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#endif
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294
squiggle.c
294
squiggle.c
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@ -7,11 +7,6 @@
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#include <sys/types.h>
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#include <time.h>
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// Some error niceties; these won't be used until later
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#define MAX_ERROR_LENGTH 500
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#define EXIT_ON_ERROR 0
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#define PROCESS_ERROR(error_msg) process_error(error_msg, EXIT_ON_ERROR, __FILE__, __LINE__)
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#define PI 3.14159265358979323846 // M_PI in gcc gnu99
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#define NORMAL90CONFIDENCE 1.6448536269514727
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@ -235,292 +230,3 @@ double sample_mixture(double (*samplers[])(uint64_t*), double* weights, int n_di
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free(cumsummed_normalized_weights);
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return result;
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}
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// # More cool stuff
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// This is no longer necessary to do basic estimation,
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// but is still cool
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// ## Sample from an arbitrary cdf
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struct box {
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int empty;
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double content;
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char* error_msg;
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};
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struct box process_error(const char* error_msg, int should_exit, char* file, int line)
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{
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if (should_exit) {
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printf("@, in %s (%d)", file, line);
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exit(1);
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} else {
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char error_msg[MAX_ERROR_LENGTH];
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snprintf(error_msg, MAX_ERROR_LENGTH, "@, in %s (%d)", file, line); // NOLINT: We are being carefull here by considering MAX_ERROR_LENGTH explicitly.
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struct box error = { .empty = 1, .error_msg = error_msg };
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return error;
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}
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}
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// Inverse cdf at point
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// Two versions of this function:
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// - raw, dealing with cdfs that return doubles
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// - input: cdf: double => double, p
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// - output: Box(number|error)
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// - box, dealing with cdfs that return a box.
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// - input: cdf: double => Box(number|error), p
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// - output: Box(number|error)
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struct box inverse_cdf_double(double cdf(double), double p)
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{
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// given a cdf: [-Inf, Inf] => [0,1]
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// returns a box with either
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// x such that cdf(x) = p
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// or an error
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// if EXIT_ON_ERROR is set to 1, it exits instead of providing an error
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double low = -1.0;
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double high = 1.0;
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// 1. Make sure that cdf(low) < p < cdf(high)
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int interval_found = 0;
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while ((!interval_found) && (low > -FLT_MAX / 4) && (high < FLT_MAX / 4)) {
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// ^ Using FLT_MIN and FLT_MAX is overkill
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// but it's also the *correct* thing to do.
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int low_condition = (cdf(low) < p);
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int high_condition = (p < cdf(high));
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if (low_condition && high_condition) {
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interval_found = 1;
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} else if (!low_condition) {
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low = low * 2;
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} else if (!high_condition) {
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high = high * 2;
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}
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}
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if (!interval_found) {
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return PROCESS_ERROR("Interval containing the target value not found, in function inverse_cdf");
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} else {
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int convergence_condition = 0;
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int count = 0;
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while (!convergence_condition && (count < (INT_MAX / 2))) {
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double mid = (high + low) / 2;
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int mid_not_new = (mid == low) || (mid == high);
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// double width = high - low;
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// if ((width < 1e-8) || mid_not_new){
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if (mid_not_new) {
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convergence_condition = 1;
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} else {
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double mid_sign = cdf(mid) - p;
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if (mid_sign < 0) {
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low = mid;
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} else if (mid_sign > 0) {
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high = mid;
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} else if (mid_sign == 0) {
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low = mid;
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high = mid;
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}
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}
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}
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if (convergence_condition) {
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struct box result = { .empty = 0, .content = low };
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return result;
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} else {
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return PROCESS_ERROR("Search process did not converge, in function inverse_cdf");
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}
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}
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}
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struct box inverse_cdf_box(struct box cdf_box(double), double p)
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{
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// given a cdf: [-Inf, Inf] => Box([0,1])
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// returns a box with either
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// x such that cdf(x) = p
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// or an error
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// if EXIT_ON_ERROR is set to 1, it exits instead of providing an error
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double low = -1.0;
|
||||
double high = 1.0;
|
||||
|
||||
// 1. Make sure that cdf(low) < p < cdf(high)
|
||||
int interval_found = 0;
|
||||
while ((!interval_found) && (low > -FLT_MAX / 4) && (high < FLT_MAX / 4)) {
|
||||
// ^ Using FLT_MIN and FLT_MAX is overkill
|
||||
// but it's also the *correct* thing to do.
|
||||
struct box cdf_low = cdf_box(low);
|
||||
if (cdf_low.empty) {
|
||||
return PROCESS_ERROR(cdf_low.error_msg);
|
||||
}
|
||||
|
||||
struct box cdf_high = cdf_box(high);
|
||||
if (cdf_high.empty) {
|
||||
return PROCESS_ERROR(cdf_low.error_msg);
|
||||
}
|
||||
|
||||
int low_condition = (cdf_low.content < p);
|
||||
int high_condition = (p < cdf_high.content);
|
||||
if (low_condition && high_condition) {
|
||||
interval_found = 1;
|
||||
} else if (!low_condition) {
|
||||
low = low * 2;
|
||||
} else if (!high_condition) {
|
||||
high = high * 2;
|
||||
}
|
||||
}
|
||||
|
||||
if (!interval_found) {
|
||||
return PROCESS_ERROR("Interval containing the target value not found, in function inverse_cdf");
|
||||
} else {
|
||||
|
||||
int convergence_condition = 0;
|
||||
int count = 0;
|
||||
while (!convergence_condition && (count < (INT_MAX / 2))) {
|
||||
double mid = (high + low) / 2;
|
||||
int mid_not_new = (mid == low) || (mid == high);
|
||||
// double width = high - low;
|
||||
if (mid_not_new) {
|
||||
// if ((width < 1e-8) || mid_not_new){
|
||||
convergence_condition = 1;
|
||||
} else {
|
||||
struct box cdf_mid = cdf_box(mid);
|
||||
if (cdf_mid.empty) {
|
||||
return PROCESS_ERROR(cdf_mid.error_msg);
|
||||
}
|
||||
double mid_sign = cdf_mid.content - p;
|
||||
if (mid_sign < 0) {
|
||||
low = mid;
|
||||
} else if (mid_sign > 0) {
|
||||
high = mid;
|
||||
} else if (mid_sign == 0) {
|
||||
low = mid;
|
||||
high = mid;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (convergence_condition) {
|
||||
struct box result = { .empty = 0, .content = low };
|
||||
return result;
|
||||
} else {
|
||||
return PROCESS_ERROR("Search process did not converge, in function inverse_cdf");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Sampler based on inverse cdf and randomness function
|
||||
struct box sampler_cdf_box(struct box cdf(double), uint64_t* seed)
|
||||
{
|
||||
double p = sample_unit_uniform(seed);
|
||||
struct box result = inverse_cdf_box(cdf, p);
|
||||
return result;
|
||||
}
|
||||
struct box sampler_cdf_double(double cdf(double), uint64_t* seed)
|
||||
{
|
||||
double p = sample_unit_uniform(seed);
|
||||
struct box result = inverse_cdf_double(cdf, p);
|
||||
return result;
|
||||
}
|
||||
|
||||
/* Could also define other variations, e.g.,
|
||||
double sampler_danger(struct box cdf(double), uint64_t* seed)
|
||||
{
|
||||
double p = sample_unit_uniform(seed);
|
||||
struct box result = inverse_cdf_box(cdf, p);
|
||||
if(result.empty){
|
||||
exit(1);
|
||||
}else{
|
||||
return result.content;
|
||||
}
|
||||
}
|
||||
*/
|
||||
|
||||
// Get confidence intervals, given a sampler
|
||||
|
||||
typedef struct ci_t {
|
||||
float low;
|
||||
float high;
|
||||
} ci;
|
||||
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.
|
||||
else if (x > y)
|
||||
return 1; // Return 1 if you want ascending, -1 if you want descending order.
|
||||
|
||||
return 0;
|
||||
}
|
||||
ci 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);
|
||||
|
||||
ci result = {
|
||||
.low = samples_array[5000],
|
||||
.high = samples_array[94999],
|
||||
};
|
||||
free(samples_array);
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
// # Small algebra manipulations
|
||||
|
||||
// here I discover named structs,
|
||||
// which mean that I don't have to be typing
|
||||
// struct blah all the time.
|
||||
typedef struct normal_params_t {
|
||||
double mean;
|
||||
double std;
|
||||
} normal_params;
|
||||
|
||||
normal_params algebra_sum_normals(normal_params a, normal_params b)
|
||||
{
|
||||
normal_params result = {
|
||||
.mean = a.mean + b.mean,
|
||||
.std = sqrt((a.std * a.std) + (b.std * b.std)),
|
||||
};
|
||||
return result;
|
||||
}
|
||||
|
||||
typedef struct lognormal_params_t {
|
||||
double logmean;
|
||||
double logstd;
|
||||
} lognormal_params;
|
||||
|
||||
lognormal_params algebra_product_lognormals(lognormal_params a, lognormal_params b)
|
||||
{
|
||||
lognormal_params result = {
|
||||
.logmean = a.logmean + b.logmean,
|
||||
.logstd = sqrt((a.logstd * a.logstd) + (b.logstd * b.logstd)),
|
||||
};
|
||||
return result;
|
||||
}
|
||||
|
||||
lognormal_params convert_ci_to_lognormal_params(ci x)
|
||||
{
|
||||
double loghigh = logf(x.high);
|
||||
double loglow = logf(x.low);
|
||||
double logmean = (loghigh + loglow) / 2.0;
|
||||
double logstd = (loghigh - loglow) / (2.0 * NORMAL90CONFIDENCE);
|
||||
lognormal_params result = { .logmean = logmean, .logstd = logstd };
|
||||
return result;
|
||||
}
|
||||
|
||||
ci convert_lognormal_params_to_ci(lognormal_params y)
|
||||
{
|
||||
double h = y.logstd * NORMAL90CONFIDENCE;
|
||||
double loghigh = y.logmean + h;
|
||||
double loglow = y.logmean - h;
|
||||
ci result = { .low = exp(loglow), .high = exp(loghigh) };
|
||||
return result;
|
||||
}
|
||||
|
|
|
|||
52
squiggle.h
52
squiggle.h
|
|
@ -1,5 +1,5 @@
|
|||
#ifndef SQUIGGLEC
|
||||
#define SQUIGGLEC
|
||||
#ifndef SQUIGGLE_C_CORE
|
||||
#define SQUIGGLE_C_CORE
|
||||
|
||||
// uint64_t header
|
||||
#include <stdint.h>
|
||||
|
|
@ -30,52 +30,4 @@ double array_std(double* array, int length);
|
|||
// Mixture function
|
||||
double sample_mixture(double (*samplers[])(uint64_t*), double* weights, int n_dists, uint64_t* seed);
|
||||
|
||||
// Box
|
||||
struct box {
|
||||
int empty;
|
||||
double content;
|
||||
char* error_msg;
|
||||
};
|
||||
|
||||
// Macros to handle errors
|
||||
#define MAX_ERROR_LENGTH 500
|
||||
#define EXIT_ON_ERROR 0
|
||||
#define PROCESS_ERROR(error_msg) process_error(error_msg, EXIT_ON_ERROR, __FILE__, __LINE__)
|
||||
struct box process_error(const char* error_msg, int should_exit, char* file, int line);
|
||||
|
||||
// Inverse cdf
|
||||
struct box inverse_cdf_double(double cdf(double), double p);
|
||||
struct box inverse_cdf_box(struct box cdf_box(double), double p);
|
||||
|
||||
// Samplers from cdf
|
||||
struct box sampler_cdf_double(double cdf(double), uint64_t* seed);
|
||||
struct box sampler_cdf_box(struct box cdf(double), uint64_t* seed);
|
||||
|
||||
// Get 90% confidence interval
|
||||
typedef struct ci_t {
|
||||
float low;
|
||||
float high;
|
||||
} ci;
|
||||
ci get_90_confidence_interval(double (*sampler)(uint64_t*), uint64_t* seed);
|
||||
|
||||
// small algebra manipulations
|
||||
|
||||
typedef struct normal_params_t {
|
||||
double mean;
|
||||
double std;
|
||||
} normal_params;
|
||||
normal_params algebra_sum_normals(normal_params a, normal_params b);
|
||||
|
||||
typedef struct lognormal_params_t {
|
||||
double logmean;
|
||||
double logstd;
|
||||
} lognormal_params;
|
||||
lognormal_params algebra_product_lognormals(lognormal_params a, lognormal_params b);
|
||||
|
||||
|
||||
lognormal_params convert_ci_to_lognormal_params(ci x);
|
||||
|
||||
|
||||
ci convert_lognormal_params_to_ci(lognormal_params y);
|
||||
|
||||
#endif
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user