fix various errors from compiler warnings

examples/core/02_time_to_botec/example.c

@@ -22,7 +22,7 @@ int main()
     double (*samplers[])(uint64_t*) = { sample_0, sample_1, sample_few, sample_many };
 
     int n_samples = 1000000;
-    double* result_many = (double*)malloc(n_samples * sizeof(double));
+    double* result_many = (double*)malloc((size_t) n_samples * sizeof(double));
     for (int i = 0; i < n_samples; i++) {
         result_many[i] = sample_mixture(samplers, weights, n_dists, seed);
     }

examples/core/03_gcc_nested_function/example.c

@@ -24,7 +24,7 @@ int main()
     double weights[] = { 1 - p_c, p_c / 2, p_c / 4, p_c / 4 };
 
     int n_samples = 1000000;
-    double* result_many = (double*)malloc(n_samples * sizeof(double));
+    double* result_many = (double*)malloc((size_t) n_samples * sizeof(double));
     for (int i = 0; i < n_samples; i++) {
         result_many[i] = sample_mixture(samplers, weights, n_dists, seed);
     }

examples/core/04_gamma_beta/example.c

@@ -19,7 +19,7 @@ int main()
 		printf("\n");
 		*/
 
-    double* gamma_1_array = malloc(sizeof(double) * n);
+    double* gamma_1_array = malloc(sizeof(double) * (size_t) n);
     for (int i = 0; i < n; i++) {
         double gamma_1 = sample_gamma(1.0, seed);
         // printf("sample_gamma(1.0): %f\n", gamma_1);
@@ -29,7 +29,7 @@ int main()
     free(gamma_1_array);
     printf("\n");
 
-    double* beta_1_2_array = malloc(sizeof(double) * n);
+    double* beta_1_2_array = malloc(sizeof(double) * (size_t) n);
     for (int i = 0; i < n; i++) {
         double beta_1_2 = sample_beta(1, 2.0, seed);
         // printf("sample_beta(1.0, 2.0): %f\n", beta_1_2);

examples/core/makefile

@@ -22,8 +22,10 @@ MATH=-lm
 DEPS=$(SQUIGGLE) $(MATH)
 
 ## Flags
-DEBUG= #'-g'
-WARN=-Wall -Wextra -Wdouble-promotion
+# DEBUG=-fsanitize=address,undefined
+# DEBUG=-g
+DEBUG=
+WARN=-Wall -Wextra -Wdouble-promotion -Wconversion
 STANDARD=-std=c99
 OPTIMIZED=-O3  #-Ofast
 

examples/more/04_nuclear_war/example.c

@@ -49,7 +49,7 @@ int main()
 
     int n = 1000 * 1000;
 
-    double* mixture_result = malloc(sizeof(double) * n);
+    double* mixture_result = malloc(sizeof(double) * (size_t) n);
     for (int i = 0; i < n; i++) {
         mixture_result[i] = mixture(seed);
     }
@@ -64,5 +64,6 @@ int main()
     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

@@ -28,7 +28,7 @@ int main()
 
     int n = 1000 * 1000;
 
-    double* result = malloc(sizeof(double) * 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);
     }

examples/more/06_nuclear_recovery/example.c

@@ -53,7 +53,7 @@ int main()
     ci ci_90_2023 = sampler_get_90_ci(yearly_probability_nuclear_collapse_2023, 1000000, seed);
     printf("90%% confidence interval: [%f, %f]\n", ci_90_2023.low, ci_90_2023.high);
 
-    double* yearly_probability_nuclear_collapse_2023_samples = malloc(sizeof(double) * num_samples);
+    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);
     }
@@ -64,7 +64,7 @@ int main()
     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) * num_samples);
+    double* yearly_probability_nuclear_collapse_after_recovery_samples = malloc(sizeof(double) * (size_t) num_samples);
     for (int i = 0; i < num_samples; i++) {
         yearly_probability_nuclear_collapse_after_recovery_samples[i] = yearly_probability_nuclear_collapse_after_recovery_example(seed);
     }
@@ -75,11 +75,14 @@ int main()
     ci ci_90_antiinductive = sampler_get_90_ci(yearly_probability_nuclear_collapse_after_recovery_antiinductive, 1000000, seed);
     printf("90%% confidence interval: [%f, %f]\n", ci_90_antiinductive.low, ci_90_antiinductive.high);
 
-    double* yearly_probability_nuclear_collapse_after_recovery_antiinductive_samples = malloc(sizeof(double) * num_samples);
+    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));
 
+    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);
 }

examples/more/11_billion_lognormals_paralell/example.c

@@ -17,7 +17,7 @@ int main()
     {
         return sample_lognormal(0, 10, seed);
     }
-    double* results = malloc(n_samples * sizeof(double));
+    double* results = malloc((size_t) n_samples * sizeof(double));
 
     sampler_parallel(sampler, results, n_threads, n_samples);
     double avg = array_sum(results, n_samples) / n_samples;

examples/more/12_time_to_botec_parallel/example.c

@@ -23,7 +23,7 @@ int main()
     }
 
     int n_samples = 1000 * 1000, n_threads = 16;
-    double* results = malloc(n_samples * sizeof(double));
+    double* results = malloc((size_t) n_samples * sizeof(double));
     sampler_parallel(sampler_result, results, n_threads, n_samples);
     printf("Avg: %f\n", array_sum(results, n_samples) / n_samples);
     free(results);

examples/more/13_parallelize_min/example.c

@@ -30,7 +30,7 @@ int main()
     }
 
     int n_samples = 1000000, n_threads = 16;
-    double* results = malloc(n_samples * sizeof(double));
+    double* results = malloc((size_t) n_samples * sizeof(double));
     sampler_parallel(sample_min_of_1000, results, n_threads, n_samples);
     printf("Mean of the distribution of (taking the min of 1000 samples of a normal(5,2)): %f\n", array_mean(results, n_samples));
     free(results);
@@ -51,7 +51,7 @@ int main()
         {
             return sample_min_of_n(seed, quotient);
         }
-        double* results_quotient = malloc(quotient * sizeof(double));
+        double* results_quotient = malloc((size_t) quotient * sizeof(double));
         sampler_parallel(sample_min_of_quotient, results_quotient, n_threads, quotient);
 
         double min = results_quotient[0];

examples/more/14_check_confidence_interval/example.c

@@ -10,12 +10,13 @@ int main()
     *seed = 1000; // xorshift can't start with a seed of 0
 
     int n = 1000000;
-    double* xs = malloc(sizeof(double) * n);
+    double* xs = malloc(sizeof(double) * (size_t) n);
     for (int i = 0; i < n; i++) {
         xs[i] = sample_to(10, 100, seed);
     }
     ci ci_90 = array_get_90_ci(xs, n);
     printf("Recovering confidence interval of sample_to(10, 100):\n  low: %f, high: %f\n", ci_90.low, ci_90.high);
 
+    free(xs);
     free(seed);
 }

examples/more/makefile

@@ -24,8 +24,10 @@ OPENMP=-fopenmp
 DEPS=$(SQUIGGLE) $(SQUIGGLE_MORE) $(MATH) $(OPENMP)
 
 ## Flags
-DEBUG= #'-g'
-WARN=-Wall -Wextra -Wdouble-promotion
+# DEBUG=-fsanitize=address,undefined
+# DEBUG=-g
+DEBUG=
+WARN=-Wall -Wextra -Wdouble-promotion -Wconversion
 STANDARD=-std=c99
 WARNINGS=-Wall
 OPTIMIZED=-O3  #-Ofast

squiggle.c

@@ -102,8 +102,8 @@ double sample_to(double low, double high, uint64_t* seed)
     // Key idea: If we want a lognormal with 90% confidence interval [a, b]
     // we need but get a normal with 90% confidence interval [log(a), log(b)].
     // Then see code for sample_normal_from_90_confidence_interval
-    double loglow = logf(low);
-    double loghigh = logf(high);
+    double loglow = log(low);
+    double loghigh = log(high);
     return exp(sample_normal_from_90_confidence_interval(loglow, loghigh, seed));
 }
 
@@ -204,7 +204,7 @@ double sample_mixture(double (*samplers[])(uint64_t*), double* weights, int n_di
 {
     // Sample from samples with frequency proportional to their weights.
     double sum_weights = array_sum(weights, n_dists);
-    double* cumsummed_normalized_weights = (double*)malloc(n_dists * sizeof(double));
+    double* cumsummed_normalized_weights = (double*)malloc((size_t) n_dists * sizeof(double));
     cumsummed_normalized_weights[0] = weights[0] / sum_weights;
     for (int i = 1; i < n_dists; i++) {
         cumsummed_normalized_weights[i] = cumsummed_normalized_weights[i - 1] + weights[i] / sum_weights;

squiggle_more.c

@@ -28,7 +28,7 @@ void sampler_parallel(double (*sampler)(uint64_t* seed), double* results, int n_
     int quotient = n_samples / n_threads;
     int divisor_multiple = quotient * n_threads;
 
-    uint64_t** seeds = malloc(n_threads * sizeof(uint64_t*));
+    uint64_t** seeds = malloc((size_t) n_threads * sizeof(uint64_t*));
     srand(1);
     for (int i = 0; i < n_threads; i++) {
         seeds[i] = malloc(sizeof(uint64_t));
@@ -88,7 +88,7 @@ static int partition(int low, int high, double xs[], int length)
         exit(1);
     }
     // Note: the scratchpad/ folder in commit 578bfa27 has printfs sprinkled throughout
-    int pivot = low + floor((high - low) / 2);
+    int pivot = low + (int) floor((high - low) / 2);
     double pivot_value = xs[pivot];
     swp(pivot, high, xs);
     int gt = low; /* This pointer will iterate until finding an element which is greater than the pivot. Then it will move elements that are smaller before it--more specifically, it will move elements to its position and then increment. As a result all elements between gt and i will be greater than the pivot. */
@@ -125,8 +125,8 @@ static double quickselect(int k, double xs[], int n)
 ci array_get_ci(ci interval, double* xs, int n)
 {
 
-    int low_k = floor(interval.low * n);
-    int high_k = ceil(interval.high * n);
+    int low_k = (int) floor(interval.low * n);
+    int high_k = (int) ceil(interval.high * n);
     ci result = {
         .low = quickselect(low_k, xs, n),
         .high = quickselect(high_k, xs, n),
@@ -141,7 +141,7 @@ ci array_get_90_ci(double xs[], int n)
 ci sampler_get_ci(ci interval, double (*sampler)(uint64_t*), int n, uint64_t* seed)
 {
     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.
-    double* xs = malloc(n * sizeof(double));
+    double* xs = malloc((size_t) n * sizeof(double));
     sampler_parallel(sampler, xs, 16, n);
     ci result = array_get_ci(interval, xs, n);
     free(xs);
@@ -186,8 +186,8 @@ lognormal_params algebra_product_lognormals(lognormal_params a, lognormal_params
 
 lognormal_params convert_ci_to_lognormal_params(ci x)
 {
-    double loghigh = logf(x.high);
-    double loglow = logf(x.low);
+    double loghigh = log(x.high);
+    double loglow = log(x.low);
     double logmean = (loghigh + loglow) / 2.0;
     double logstd = (loghigh - loglow) / (2.0 * NORMAL90CONFIDENCE);
     lognormal_params result = { .logmean = logmean, .logstd = logstd };