remove functionality
- Sample from arbitrary cdf: unused complexity - Sample confidence interval directly from cdf: makes sampling function/array function boundary unclear.
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								squiggle_more.c
									
									
									
									
									
								
							
							
						
						
									
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								squiggle_more.c
									
									
									
									
									
								
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			@ -194,6 +194,17 @@ double array_get_median(double xs[], int n){
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    return quickselect(median_k, xs, n);
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}
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/* array print: potentially useful for debugging */
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void array_print(double xs[], int n)
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{
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    printf("[");
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    for (int i = 0; i < n - 1; i++) {
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        printf("%f, ", xs[i]);
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    }
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    printf("%f", xs[n - 1]);
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    printf("]\n");
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}
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void array_print_stats(double xs[], int n){
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    ci ci_90 = array_get_ci((ci) { .low = 0.05, .high = 0.95 }, xs, n);
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    ci ci_80 = array_get_ci((ci) { .low = 0.1, .high = 0.9 }, xs, n);
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			@ -391,23 +402,6 @@ void array_print_90_ci_histogram(double* xs, int n_samples, int n_bins){
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}
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// Replicate some of the above functions over samplers
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// However, in the future I'll delete this
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// There should be a clear boundary between working with samplers and working with an array of samples
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ci sampler_get_ci(ci interval, double (*sampler)(uint64_t*), int n, uint64_t* seed)
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{
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    UNUSED(seed); // don't want to use it right now, but want to preserve ability to do so (e.g., remove parallelism from internals). Also nicer for consistency.
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    double* xs = malloc((size_t)n * sizeof(double));
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    sampler_parallel(sampler, xs, 16, n);
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    ci result = array_get_ci(interval, xs, n);
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    free(xs);
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    return result;
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}
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ci sampler_get_90_ci(double (*sampler)(uint64_t*), int n, uint64_t* seed)
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{
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    return sampler_get_ci((ci) { .low = 0.05, .high = 0.95 }, sampler, n, seed);
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}
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/* Algebra manipulations */
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#define NORMAL90CONFIDENCE 1.6448536269514727
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			@ -458,216 +452,3 @@ ci convert_lognormal_params_to_ci(lognormal_params y)
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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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/* Scaffolding to handle errors */
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// We will sample from an arbitrary cdf
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// and that operation might fail
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// so we build some scaffolding here
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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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typedef struct box_t {
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    int empty;
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    double content;
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    char* error_msg;
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} box;
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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("%s, @, in %s (%d)", error_msg, 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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        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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/* Invert an arbitrary cdf at a point */
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// Version #1:
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// - input: (cdf: double => double, p)
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// - output: Box(number|error)
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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 > -DBL_MAX / 4) && (high < DBL_MAX / 4)) {
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        // for floats, use FLT_MAX instead
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        // Note that this approach 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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            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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// Version #2:
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// - input: (cdf: double => Box(number|error), p)
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// - output: Box(number|error)
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box inverse_cdf_box(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 > -DBL_MAX / 4) && (high < DBL_MAX / 4)) {
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        // for floats, use FLT_MAX instead
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        // Note that this approach is overkill
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        // but it's also the *correct* thing to do.
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        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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        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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                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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            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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/* Sample from an arbitrary cdf */
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// Before: invert an arbitrary cdf at a point
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// Now: from an arbitrary cdf, get a sample
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box sampler_cdf_box(box cdf(double), uint64_t* seed)
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{
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    double p = sample_unit_uniform(seed);
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    box result = inverse_cdf_box(cdf, p);
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    return result;
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}
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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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    box result = inverse_cdf_double(cdf, p);
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    return result;
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}
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double sampler_cdf_danger(box cdf(double), uint64_t* seed)
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{
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    double p = sample_unit_uniform(seed);
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    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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/* array print: potentially useful for debugging */
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void array_print(double xs[], int n)
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{
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    printf("[");
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    for (int i = 0; i < n - 1; i++) {
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        printf("%f, ", xs[i]);
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    }
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    printf("%f", xs[n - 1]);
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    printf("]\n");
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}
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