continue with big refactor

- delete cdf functions from header file
- delete docs
- rework examples so as to not use sample_90_ci function
- add a few items to README

README.md

@@ -195,10 +195,6 @@ The bailey:
 - I think the core interface is not likely to change much, though I've recently changed the interface for parallelism and for getting confidence intervals.
 - I am using this code for a few important consulting projects, and I trust myself to operate it correctly.
 
-## Licensing
-
-This project is released under the MIT license, a permissive open-source license. You can see it in the LICENSE.txt file. 
-
 ## squiggle extra functions
 
 ### Division between core functions and squiggle_more expansions
@@ -250,32 +246,7 @@ That said, I found adding parallelism to be an interesting an engaging task. Mos
 
 `squiggle_more.c` has some functions to do some simple algebra manipulations: sums of normals and products of lognormals. You can see some example usage [here](examples/more/07_algebra/example.c) and [here](examples/more/08_algebra_and_conversion/example.c).
 
-#### Extra: cdf auxiliary functions
+## Licensing
 
-I provide some auxiliary functions that take a cdf, and return a sample from the distribution produced by that cdf. This might make it easier to program models, at the cost of a 20x to 60x slowdown in the parts of the code that use it. 
+This project is released under the MIT license, a permissive open-source license. You can see it in the LICENSE.txt file. 
-
-I don't have any immediate plans or reason to delete these functions, but I probably will, since they are too slow/inefficient for my taste.
-
-#### Extra: Error propagation vs exiting on error
-
-The process of taking a cdf and returning a sample might fail, e.g., it's a Newton method which might fail to converge because of cdf artifacts. The cdf itself might also fail, e.g., if a distribution only accepts a range of parameters, but is fed parameters outside that range.
-
-This library provides two approaches:
-
-1. Print the line and function in which the error occurred, then exit on error
-2. In situations where there might be an error, return a struct containing either the correct value or an error message:
-
-```C
-struct box {
-    int empty;
-    double content;
-    char* error_msg;
-};
-```
-
-The first approach produces terser programs but might not scale. The second approach seems like it could lead to more robust programs, but is more verbose.
-
-Behaviour on error can be toggled by the `EXIT_ON_ERROR` variable. This library also provides a convenient macro, `PROCESS_ERROR`, to make error handling in either case much terser—see the usage in example 4 in the examples/ folder.
-
-Overall, I'd describe the error handling capabilities of this library as pretty rudimentary. For example, this program might fail in surprising ways if you ask for a lognormal with negative standard deviation, because I haven't added error checking for that case yet.
 

ROADMAP.md

@@ -2,15 +2,17 @@
 
 ## To do
 
-- [ ] Big refactor
+- [x] Big refactor
   - [ ] Come up with a better headline example; fermi paradox paper is too complicated
-  - [ ] Make README.md less messy
+  - [x] Make README.md less messy
   - [ ] Give examples of new functions
+  - [ ] Reference commit with cdf functions, even though deleted
 - [ ] Post on suckless subreddit
 - [ ] Drive in a few more real-life applications
   - [ ] US election modelling?
 - [ ] Look into using size_t instead of int for sample numbers
 - [ ] Reorganize code a little bit to reduce usage of gcc's nested functions
+- [ ] Rename examples
 
 ## Done
 

examples/more/01_sample_from_cdf/example.c

@@ -1,102 +0,0 @@
-#include "../../../squiggle.h"
-#include "../../../squiggle_more.h"
-#include <math.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <time.h>
-
-#define NUM_SAMPLES 1000000
-
-// Example cdf
-double cdf_uniform_0_1(double x)
-{
-    if (x < 0) {
-        return 0;
-    } else if (x > 1) {
-        return 1;
-    } else {
-        return x;
-    }
-}
-
-double cdf_squared_0_1(double x)
-{
-    if (x < 0) {
-        return 0;
-    } else if (x > 1) {
-        return 1;
-    } else {
-        return x * x;
-    }
-}
-
-double cdf_normal_0_1(double x)
-{
-    double mean = 0;
-    double std = 1;
-    return 0.5 * (1 + erf((x - mean) / (std * sqrt(2)))); // erf from math.h
-}
-
-// Some testers
-void test_inverse_cdf_double(char* cdf_name, double cdf_double(double))
-{
-    box result = inverse_cdf_double(cdf_double, 0.5);
-    if (result.empty) {
-        printf("Inverse for %s not calculated\n", cdf_name);
-        exit(1);
-    } else {
-        printf("Inverse of %s at %f is: %f\n", cdf_name, 0.5, result.content);
-    }
-}
-
-void test_and_time_sampler_double(char* cdf_name, double cdf_double(double), uint64_t* seed)
-{
-    printf("\nGetting some samples from %s:\n", cdf_name);
-    clock_t begin = clock();
-    for (int i = 0; i < NUM_SAMPLES; i++) {
-        box sample = sampler_cdf_double(cdf_double, seed);
-        if (sample.empty) {
-            printf("Error in sampler function for %s", cdf_name);
-        } else {
-            // printf("%f\n", sample.content);
-        }
-    }
-    clock_t end = clock();
-    double time_spent = (double)(end - begin) / CLOCKS_PER_SEC;
-    printf("Time spent: %f\n", time_spent);
-}
-
-int main()
-{
-    // Test inverse cdf double
-    test_inverse_cdf_double("cdf_uniform_0_1", cdf_uniform_0_1);
-    test_inverse_cdf_double("cdf_squared_0_1", cdf_squared_0_1);
-    test_inverse_cdf_double("cdf_normal_0_1", cdf_normal_0_1);
-
-    // Testing samplers
-    // set randomness seed
-    uint64_t* seed = malloc(sizeof(uint64_t));
-    *seed = 1000; // xorshift can't start with 0
-
-    // Test double sampler
-    test_and_time_sampler_double("cdf_uniform_0_1", cdf_uniform_0_1, seed);
-    test_and_time_sampler_double("cdf_squared_0_1", cdf_squared_0_1, seed);
-    test_and_time_sampler_double("cdf_normal_0_1", cdf_normal_0_1, seed);
-
-    // Get some normal samples using a previous approach
-    printf("\nGetting some samples from sample_unit_normal\n");
-
-    clock_t begin_2 = clock();
-    double* normal_samples = malloc(NUM_SAMPLES * sizeof(double));
-    for (int i = 0; i < NUM_SAMPLES; i++) {
-        normal_samples[i] = sample_unit_normal(seed);
-        // printf("%f\n", normal_sample);
-    }
-
-    clock_t end_2 = clock();
-    double time_spent_2 = (double)(end_2 - begin_2) / CLOCKS_PER_SEC;
-    printf("Time spent: %f\n", time_spent_2);
-
-    free(seed);
-    return 0;
-}

examples/more/02_sample_from_cdf_beta/example.c

@@ -1,168 +0,0 @@
-#include "../../../squiggle.h"
-#include "../../../squiggle_more.h"
-#include <math.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <time.h>
-
-#define NUM_SAMPLES 10000
-#define STOP_BETA 1.0e-8
-#define TINY_BETA 1.0e-30
-
-// Incomplete beta function
-box incbeta(double a, double b, double x)
-{
-    // Descended from <https://github.com/codeplea/incbeta/blob/master/incbeta.c>,
-    // <https://codeplea.com/incomplete-beta-function-c>
-    // but modified to return a box struct and doubles instead of doubles.
-    // [ ] to do: add attribution in README
-    // Original code under this license:
-    /*
-		 * zlib License
-		 *
-		 * Regularized Incomplete Beta Function
-		 *
-		 * Copyright (c) 2016, 2017 Lewis Van Winkle
-		 * http://CodePlea.com
-		 *
-		 * This software is provided 'as-is', without any express or implied
-		 * warranty. In no event will the authors be held liable for any damages
-		 * arising from the use of this software.
-		 *
-		 * Permission is granted to anyone to use this software for any purpose,
-		 * including commercial applications, and to alter it and redistribute it
-		 * freely, subject to the following restrictions:
-		 *
-		 * 1. The origin of this software must not be misrepresented; you must not
-		 *    claim that you wrote the original software. If you use this software
-		 *    in a product, an acknowledgement in the product documentation would be
-		 *    appreciated but is not required.
-		 * 2. Altered source versions must be plainly marked as such, and must not be
-		 *    misrepresented as being the original software.
-		 * 3. This notice may not be removed or altered from any source distribution.
-		 */
-    if (x < 0.0 || x > 1.0) {
-        return PROCESS_ERROR("x out of bounds [0, 1], in function incbeta");
-    }
-
-    /*The continued fraction converges nicely for x < (a+1)/(a+b+2)*/
-    if (x > (a + 1.0) / (a + b + 2.0)) {
-        box symmetric_incbeta = incbeta(b, a, 1.0 - x);
-        if (symmetric_incbeta.empty) {
-            return symmetric_incbeta; // propagate error
-        } else {
-            box result = {
-                .empty = 0,
-                .content = 1 - symmetric_incbeta.content
-            };
-            return result;
-        }
-    }
-
-    /*Find the first part before the continued fraction.*/
-    const double lbeta_ab = lgamma(a) + lgamma(b) - lgamma(a + b);
-    const double front = exp(log(x) * a + log(1.0 - x) * b - lbeta_ab) / a;
-
-    /*Use Lentz's algorithm to evaluate the continued fraction.*/
-    double f = 1.0, c = 1.0, d = 0.0;
-
-    int i, m;
-    for (i = 0; i <= 200; ++i) {
-        m = i / 2;
-
-        double numerator;
-        if (i == 0) {
-            numerator = 1.0; /*First numerator is 1.0.*/
-        } else if (i % 2 == 0) {
-            numerator = (m * (b - m) * x) / ((a + 2.0 * m - 1.0) * (a + 2.0 * m)); /*Even term.*/
-        } else {
-            numerator = -((a + m) * (a + b + m) * x) / ((a + 2.0 * m) * (a + 2.0 * m + 1)); /*Odd term.*/
-        }
-
-        /*Do an iteration of Lentz's algorithm.*/
-        d = 1.0 + numerator * d;
-        if (fabs(d) < TINY_BETA)
-            d = TINY_BETA;
-        d = 1.0 / d;
-
-        c = 1.0 + numerator / c;
-        if (fabs(c) < TINY_BETA)
-            c = TINY_BETA;
-
-        const double cd = c * d;
-        f *= cd;
-
-        /*Check for stop.*/
-        if (fabs(1.0 - cd) < STOP_BETA) {
-            box result = {
-                .empty = 0,
-                .content = front * (f - 1.0)
-            };
-            return result;
-        }
-    }
-
-    return PROCESS_ERROR("More loops needed, did not converge, in function incbeta");
-}
-
-box cdf_beta(double x)
-{
-    if (x < 0) {
-        box result = { .empty = 0, .content = 0 };
-        return result;
-    } else if (x > 1) {
-        box result = { .empty = 0, .content = 1 };
-        return result;
-    } else {
-        double successes = 1, failures = (2023 - 1945);
-        return incbeta(successes, failures, x);
-    }
-}
-
-// Some testers
-void test_inverse_cdf_box(char* cdf_name, box cdf_box(double))
-{
-    box result = inverse_cdf_box(cdf_box, 0.5);
-    if (result.empty) {
-        printf("Inverse for %s not calculated\n", cdf_name);
-        exit(1);
-    } else {
-        printf("Inverse of %s at %f is: %f\n", cdf_name, 0.5, result.content);
-    }
-}
-
-void test_and_time_sampler_box(char* cdf_name, box cdf_box(double), uint64_t* seed)
-{
-    printf("\nGetting some samples from %s:\n", cdf_name);
-    clock_t begin = clock();
-    for (int i = 0; i < NUM_SAMPLES; i++) {
-        box sample = sampler_cdf_box(cdf_box, seed);
-        if (sample.empty) {
-            printf("Error in sampler function for %s", cdf_name);
-        } else {
-            // printf("%f\n", sample.content);
-        }
-    }
-    clock_t end = clock();
-    double time_spent = (double)(end - begin) / CLOCKS_PER_SEC;
-    printf("Time spent: %f\n", time_spent);
-}
-
-int main()
-{
-    // Test inverse cdf box
-    test_inverse_cdf_box("cdf_beta", cdf_beta);
-
-    // Test box sampler
-    uint64_t* seed = malloc(sizeof(uint64_t));
-    *seed = 1000; // xorshift can't start with 0
-    test_and_time_sampler_box("cdf_beta", cdf_beta, seed);
-    // Ok, this is slower than python!!
-    // Partly this is because I am using a more general algorithm,
-    //   which applies to any cdf
-    // But I am also using absurdly precise convergence conditions.
-    // This could be optimized.
-
-    free(seed);
-    return 0;
-}

examples/more/03_ci_beta/example.c

@@ -4,9 +4,9 @@
 #include <stdlib.h>
 
 // Estimate functions
-double beta_1_2_sampler(uint64_t* seed)
+double sample_beta_3_2(uint64_t* seed)
 {
-    return sample_beta(1, 2.0, seed);
+    return sample_beta(3.0, 2.0, seed);
 }
 
 int main()
@@ -15,9 +15,16 @@ int main()
     uint64_t* seed = malloc(sizeof(uint64_t));
     *seed = 1000; // xorshift can't start with 0
 
-    ci beta_1_2_ci_90 = sampler_get_90_ci(beta_1_2_sampler, 1000000, seed);
+    int n_samples = 1 * MILLION;
-    printf("90%% confidence interval of beta(1,2) is [%f, %f]\n", beta_1_2_ci_90.low, beta_1_2_ci_90.high);
+    double* xs = malloc(sizeof(double) * (size_t)n_samples);
-    printf("You can check this in <https://nunosempere.com/blog/2023/03/15/fit-beta/>\n");
+    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);
 }

examples/more/04_nuclear_war/example.c

@@ -34,7 +34,7 @@ double probability_of_dying_eli(uint64_t* seed)
     return probability_of_dying;
 }
 
-double mixture(uint64_t* seed)
+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 };
@@ -47,23 +47,17 @@ int main()
     uint64_t* seed = malloc(sizeof(uint64_t));
     *seed = 1000; // xorshift can't start with 0
 
-    int n = 1000 * 1000;
+    int n = 1 * MILLION;
-
+    double* xs = malloc(sizeof(double) * (size_t)n);
-    double* mixture_result = malloc(sizeof(double) * (size_t)n);
     for (int i = 0; i < n; i++) {
-        mixture_result[i] = mixture(seed);
+        xs[i] = sample_nuclear_model(seed);
     }
 
-    printf("mixture_result: [ ");
+    printf("\n# Stats\n");
-    for (int i = 0; i < 9; i++) {
+    array_print_stats(xs, n);
-        printf("%.6f, ", mixture_result[i]);
+    printf("\n# Histogram\n");
-    }
+    array_print_90_ci_histogram(xs, n, 20);
-    printf("... ]\n");
 
-    ci ci_90 = sampler_get_90_ci(mixture, 1000000, seed);
+    free(xs);
-    printf("mean: %f\n", array_mean(mixture_result, n));
-    printf("90%% confidence interval: [%f, %f]\n", ci_90.low, ci_90.high);
-
-    free(mixture_result);
     free(seed);
 }

examples/more/05_burn_10kg_fat/example.c

@@ -27,22 +27,17 @@ int main()
     *seed = 1000; // xorshift can't start with 0
 
     int n = 1000 * 1000;
-
+    double* xs = malloc(sizeof(double) * (size_t)n);
-    double* result = malloc(sizeof(double) * (size_t)n);
     for (int i = 0; i < n; i++) {
-        result[i] = sample_minutes_per_day_jumping_rope_needed_to_burn_10kg(seed);
+        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("Mean: %f\n", array_mean(result, n));
-    printf("A few samples: [ ");
-    for (int i = 0; i < 9; i++) {
-        printf("%.6f, ", result[i]);
-    }
-    printf("... ]\n");
 
-    ci ci_90 = sampler_get_90_ci(sample_minutes_per_day_jumping_rope_needed_to_burn_10kg, 1000000, seed);
+    printf("\n# Stats\n");
-    printf("90%% confidence interval: [%f, %f]\n", ci_90.low, ci_90.high);
+    array_print_stats(xs, n);
+    printf("\n# Histogram\n");
+    array_print_histogram(xs, n, 23);
 
     free(seed);
 }

examples/more/06_nuclear_recovery/example.c

@@ -46,41 +46,37 @@ int main()
     uint64_t* seed = malloc(sizeof(uint64_t));
     *seed = 1000; // xorshift can't start with 0
 
-    int num_samples = 1000000;
+    int n_samples = 1000000;
 
     // Before a first nuclear collapse
     printf("## Before the first nuclear collapse\n");
-    ci ci_90_2023 = sampler_get_90_ci(yearly_probability_nuclear_collapse_2023, 1000000, seed);
+    double* yearly_probability_nuclear_collapse_2023_samples = malloc(sizeof(double) * (size_t)n_samples);
-    printf("90%% confidence interval: [%f, %f]\n", ci_90_2023.low, ci_90_2023.high);
+    for (int i = 0; i < n_samples; i++) {
-
-    double* yearly_probability_nuclear_collapse_2023_samples = malloc(sizeof(double) * (size_t)num_samples);
-    for (int i = 0; i < num_samples; i++) {
         yearly_probability_nuclear_collapse_2023_samples[i] = yearly_probability_nuclear_collapse_2023(seed);
     }
-    printf("mean: %f\n", array_mean(yearly_probability_nuclear_collapse_2023_samples, num_samples));
+    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");
-    ci ci_90_2070 = sampler_get_90_ci(yearly_probability_nuclear_collapse_after_recovery_example, 1000000, seed);
-    printf("90%% confidence interval: [%f, %f]\n", ci_90_2070.low, ci_90_2070.high);
 
-    double* yearly_probability_nuclear_collapse_after_recovery_samples = malloc(sizeof(double) * (size_t)num_samples);
+    double* yearly_probability_nuclear_collapse_after_recovery_samples = malloc(sizeof(double) * (size_t)n_samples);
-    for (int i = 0; i < num_samples; i++) {
+    for (int i = 0; i < n_samples; i++) {
         yearly_probability_nuclear_collapse_after_recovery_samples[i] = yearly_probability_nuclear_collapse_after_recovery_example(seed);
     }
-    printf("mean: %f\n", array_mean(yearly_probability_nuclear_collapse_after_recovery_samples, num_samples));
+    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");
-    ci ci_90_antiinductive = sampler_get_90_ci(yearly_probability_nuclear_collapse_after_recovery_antiinductive, 1000000, seed);
+    double* yearly_probability_nuclear_collapse_after_recovery_antiinductive_samples = malloc(sizeof(double) * (size_t)n_samples);
-    printf("90%% confidence interval: [%f, %f]\n", ci_90_antiinductive.low, ci_90_antiinductive.high);
+    for (int i = 0; i < n_samples; i++) {
-
-    double* yearly_probability_nuclear_collapse_after_recovery_antiinductive_samples = malloc(sizeof(double) * (size_t)num_samples);
-    for (int i = 0; i < num_samples; i++) {
         yearly_probability_nuclear_collapse_after_recovery_antiinductive_samples[i] = yearly_probability_nuclear_collapse_after_recovery_antiinductive(seed);
     }
-    printf("mean: %f\n", array_mean(yearly_probability_nuclear_collapse_after_recovery_antiinductive_samples, num_samples));
+    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);

examples/more/makefile

@@ -39,8 +39,6 @@ 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) $(WARN) 01_sample_from_cdf/$(SRC)              $(DEPS) -o 01_sample_from_cdf/$(OUTPUT)
-	$(CC) $(OPTIMIZED) $(DEBUG) $(WARN) 02_sample_from_cdf_beta/$(SRC)         $(DEPS) -o 02_sample_from_cdf_beta/$(OUTPUT)
 	$(CC) $(OPTIMIZED) $(DEBUG) $(WARN) 03_ci_beta/$(SRC)                      $(DEPS) -o 03_ci_beta/$(OUTPUT)
 	$(CC) $(OPTIMIZED) $(DEBUG) $(WARN) 04_nuclear_war/$(SRC)                  $(DEPS) -o 04_nuclear_war/$(OUTPUT)
 	$(CC) $(OPTIMIZED) $(DEBUG) $(WARN) 05_burn_10kg_fat/$(SRC)                $(DEPS) -o 05_burn_10kg_fat/$(OUTPUT)

squiggle_more.c

@@ -212,15 +212,15 @@ void array_print_stats(double xs[], int n){
     double median = array_get_median(xs, n);
     double mean = array_mean(xs, n);
     double std = array_std(xs, n);
-    printf("Mean: %lf\n"
+    printf("Avg: %lf\n"
-           " Std: %lf\n"
+           "Std: %lf\n"
-           "  5%%: %lf\n"
+           " 5%%: %lf\n"
-           " 10%%: %lf\n"
+           "10%%: %lf\n"
-           " 25%%: %lf\n"
+           "25%%: %lf\n"
-           " 50%%: %lf\n"
+           "50%%: %lf\n"
-           " 75%%: %lf\n"
+           "75%%: %lf\n"
-           " 90%%: %lf\n"
+           "90%%: %lf\n"
-           " 95%%: %lf\n",
+           "95%%: %lf\n",
            mean, std, ci_90.low, ci_80.low, ci_50.low, median, ci_50.high, ci_80.high, ci_90.high);
 }
 
@@ -293,7 +293,7 @@ void array_print_histogram(double* xs, int n_samples, int n_bins) {
             decimalPlaces = -magnitude;
             decimalPlaces = decimalPlaces > 10 ? 10 : decimalPlaces;  
         }
-        printf("  [%*.*f, %*.*f", 4+decimalPlaces, decimalPlaces, bin_start, 4+decimalPlaces, decimalPlaces, bin_end);
+        printf("[%*.*f, %*.*f", 4+decimalPlaces, decimalPlaces, bin_start, 4+decimalPlaces, decimalPlaces, bin_end);
         char interval_delimiter = ')';
         if(i == (n_bins-1)){
             interval_delimiter = ']'; // last bucket is inclusive
@@ -377,12 +377,12 @@ void array_print_90_ci_histogram(double* xs, int n_samples, int n_bins){
         decimalPlaces = -magnitude;
         decimalPlaces = decimalPlaces > 10 ? 10 : decimalPlaces;  
     }
-    printf(  "  (-∞, %*.*f):  %d\n", 4+decimalPlaces, decimalPlaces, min_value, below_min);
+    printf(  "(-∞, %*.*f):  %d\n", 4+decimalPlaces, decimalPlaces, min_value, below_min);
     for (int i = 0; i < n_bins; i++) {
         double bin_start = min_value + i * bin_width;
         double bin_end = bin_start + bin_width;
 
-        printf("  [%*.*f, %*.*f", 4+decimalPlaces, decimalPlaces, bin_start, 4+decimalPlaces, decimalPlaces, bin_end);
+        printf("[%*.*f, %*.*f", 4+decimalPlaces, decimalPlaces, bin_start, 4+decimalPlaces, decimalPlaces, bin_end);
         char interval_delimiter = ')';
         if(i == (n_bins-1)){
             interval_delimiter = ']'; // last bucket is inclusive
@@ -395,7 +395,7 @@ void array_print_90_ci_histogram(double* xs, int n_samples, int n_bins){
         }
         printf(" %d\n", bins[i]);
     }
-    printf(  "  (%*.*f, +∞):  %d\n", 4+decimalPlaces, decimalPlaces, max_value, above_max);
+    printf(  "(%*.*f, +∞):  %d\n", 4+decimalPlaces, decimalPlaces, max_value, above_max);
 
     // Free the allocated memory for bins
     free(bins);

squiggle_more.h

@@ -17,10 +17,6 @@ void array_print_stats(double xs[], int n);
 void array_print_histogram(double* xs, int n_samples, int n_bins);
 void array_print_90_ci_histogram(double* xs, int n, int n_bins);
 
-// Deprecated: get confidence intervals directly from samplers
-ci sampler_get_ci(ci interval, double (*sampler)(uint64_t*), int n, uint64_t* seed);
-ci sampler_get_90_ci(double (*sampler)(uint64_t*), int n, uint64_t* seed);
-
 /* Algebra manipulations */
 
 typedef struct normal_params_t {
@@ -38,24 +34,9 @@ lognormal_params algebra_product_lognormals(lognormal_params a, lognormal_params
 lognormal_params convert_ci_to_lognormal_params(ci x);
 ci convert_lognormal_params_to_ci(lognormal_params y);
 
-/* Error handling */
+/* Utilities */
-typedef struct box_t {
-    int empty;
-    double content;
-    char* error_msg;
-} box;
-#define MAX_ERROR_LENGTH 500
-#define EXIT_ON_ERROR 0
-#define PROCESS_ERROR(error_msg) process_error(error_msg, EXIT_ON_ERROR, __FILE__, __LINE__)
-box process_error(const char* error_msg, int should_exit, char* file, int line);
-void array_print(double* array, int length);
 
-/* Inverse cdf */
+#define THOUSAND 1000
-box inverse_cdf_double(double cdf(double), double p);
+#define MILLION 1000000
-box inverse_cdf_box(box cdf_box(double), double p);
-
-/* Samplers from cdf */
-box sampler_cdf_double(double cdf(double), uint64_t* seed);
-box sampler_cdf_box(box cdf(double), uint64_t* seed);
 
 #endif