forked from personal/squiggle.c
move squiggle_c to its own repository
This commit is contained in:
commit
9578461494
BIN
examples/01_one_sample/example
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BIN
examples/01_one_sample/example
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50
examples/01_one_sample/example.c
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examples/01_one_sample/example.c
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#include "../../squiggle.h"
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#include <stdint.h>
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#include <stdlib.h>
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#include <stdio.h>
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// Estimate functions
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float sample_0(uint32_t* seed)
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{
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return 0;
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}
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float sample_1(uint32_t* seed)
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{
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return 1;
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}
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float sample_few(uint32_t* seed)
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{
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return random_to(1, 3, seed);
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}
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float sample_many(uint32_t* seed)
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{
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return random_to(2, 10, seed);
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}
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int main(){
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// set randomness seed
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uint32_t* seed = malloc(sizeof(uint32_t));
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*seed = 1000; // xorshift can't start with 0
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float p_a = 0.8;
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float p_b = 0.5;
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float p_c = p_a * p_b;
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int n_dists = 4;
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float weights[] = { 1 - p_c, p_c / 2, p_c / 4, p_c / 4 };
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float (*samplers[])(uint32_t*) = { sample_0, sample_1, sample_few, sample_many };
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float result_one = mixture(samplers, weights, n_dists, seed);
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printf("result_one: %f\n", result_one);
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}
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/*
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Aggregation mechanisms:
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- Quantiles (requires a sort)
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- Sum
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- Average
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- Std
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*/
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53
examples/01_one_sample/makefile
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examples/01_one_sample/makefile
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# Interface:
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# make
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# make build
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# make format
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# make run
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# Compiler
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CC=gcc
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# CC=tcc # <= faster compilation
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# Main file
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SRC=example.c
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OUTPUT=example
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## Dependencies
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MATH=-lm
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## Flags
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DEBUG= #'-g'
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STANDARD=-std=c99
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WARNINGS=-Wall
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OPTIMIZED=-O3 #-Ofast
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# OPENMP=-fopenmp
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## Formatter
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STYLE_BLUEPRINT=webkit
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FORMATTER=clang-format -i -style=$(STYLE_BLUEPRINT)
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## make build
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build: $(SRC)
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$(CC) $(OPTIMIZED) $(DEBUG) $(SRC) $(MATH) -o $(OUTPUT)
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format: $(SRC)
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$(FORMATTER) $(SRC)
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run: $(SRC) $(OUTPUT)
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OMP_NUM_THREADS=1 ./$(OUTPUT) && echo
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time-linux:
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@echo "Requires /bin/time, found on GNU/Linux systems" && echo
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@echo "Running 100x and taking avg time $(OUTPUT)"
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@t=$$(/usr/bin/time -f "%e" -p bash -c 'for i in {1..100}; do $(OUTPUT); done' 2>&1 >/dev/null | grep real | awk '{print $$2}' ); echo "scale=2; 1000 * $$t / 100" | bc | sed "s|^|Time using 1 thread: |" | sed 's|$$|ms|' && echo
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## Profiling
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profile-linux:
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echo "Requires perf, which depends on the kernel version, and might be in linux-tools package or similar"
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echo "Must be run as sudo"
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$(CC) $(SRC) $(MATH) -o $(OUTPUT)
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sudo perf record $(OUTPUT)
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sudo perf report
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rm perf.data
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BIN
examples/02_many_samples/example
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BIN
examples/02_many_samples/example
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examples/02_many_samples/example.c
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examples/02_many_samples/example.c
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#include <stdint.h>
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#include <stdlib.h>
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#include <stdio.h>
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#include "../../squiggle.h"
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// Estimate functions
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float sample_0(uint32_t* seed)
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{
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return 0;
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}
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float sample_1(uint32_t* seed)
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{
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return 1;
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}
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float sample_few(uint32_t* seed)
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{
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return random_to(1, 3, seed);
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}
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float sample_many(uint32_t* seed)
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{
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return random_to(2, 10, seed);
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}
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int main(){
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// set randomness seed
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uint32_t* seed = malloc(sizeof(uint32_t));
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*seed = 1000; // xorshift can't start with 0
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float p_a = 0.8;
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float p_b = 0.5;
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float p_c = p_a * p_b;
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int n_dists = 4;
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float weights[] = { 1 - p_c, p_c / 2, p_c / 4, p_c / 4 };
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float (*samplers[])(uint32_t*) = { sample_0, sample_1, sample_few, sample_many };
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int n_samples = 1000000;
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float* result_many = (float *) malloc(n_samples * sizeof(float));
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for(int i=0; i<n_samples; i++){
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result_many[i] = mixture(samplers, weights, n_dists, seed);
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}
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printf("result_many: [");
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for(int i=0; i<100; i++){
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printf("%.2f, ", result_many[i]);
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}
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printf("]\n");
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}
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/*
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Aggregation mechanisms:
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- Quantiles (requires a sort)
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- Sum
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- Average
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- Std
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*/
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53
examples/02_many_samples/makefile
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examples/02_many_samples/makefile
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# Interface:
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# make
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# make build
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# make format
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# make run
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# Compiler
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CC=gcc
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# CC=tcc # <= faster compilation
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# Main file
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SRC=example.c
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OUTPUT=example
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## Dependencies
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MATH=-lm
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## Flags
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DEBUG= #'-g'
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STANDARD=-std=c99
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WARNINGS=-Wall
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OPTIMIZED=-O3 #-Ofast
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# OPENMP=-fopenmp
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## Formatter
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STYLE_BLUEPRINT=webkit
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FORMATTER=clang-format -i -style=$(STYLE_BLUEPRINT)
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## make build
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build: $(SRC)
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$(CC) $(OPTIMIZED) $(DEBUG) $(SRC) $(MATH) -o $(OUTPUT)
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format: $(SRC)
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$(FORMATTER) $(SRC)
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run: $(SRC) $(OUTPUT)
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OMP_NUM_THREADS=1 ./$(OUTPUT) && echo
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time-linux:
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@echo "Requires /bin/time, found on GNU/Linux systems" && echo
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@echo "Running 100x and taking avg time $(OUTPUT)"
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@t=$$(/usr/bin/time -f "%e" -p bash -c 'for i in {1..100}; do $(OUTPUT); done' 2>&1 >/dev/null | grep real | awk '{print $$2}' ); echo "scale=2; 1000 * $$t / 100" | bc | sed "s|^|Time using 1 thread: |" | sed 's|$$|ms|' && echo
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## Profiling
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profile-linux:
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echo "Requires perf, which depends on the kernel version, and might be in linux-tools package or similar"
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echo "Must be run as sudo"
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$(CC) $(SRC) $(MATH) -o $(OUTPUT)
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sudo perf record $(OUTPUT)
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sudo perf report
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rm perf.data
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109
squiggle.h
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squiggle.h
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#include <math.h>
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#include <stdint.h>
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#include <stdlib.h>
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const float PI = 3.14159265358979323846;
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// Pseudo Random number generator
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uint32_t xorshift32
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(uint32_t* seed)
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{
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// Algorithm "xor" from p. 4 of Marsaglia, "Xorshift RNGs"
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// See <https://stackoverflow.com/questions/53886131/how-does-xorshift32-works>
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// https://en.wikipedia.org/wiki/Xorshift
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// Also some drama: <https://www.pcg-random.org/posts/on-vignas-pcg-critique.html>, <https://prng.di.unimi.it/>
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uint32_t x = *seed;
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x ^= x << 13;
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x ^= x >> 17;
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x ^= x << 5;
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return *seed = x;
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}
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// Distribution & sampling functions
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float rand_0_to_1(uint32_t* seed){
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return ((float) xorshift32(seed)) / ((float) UINT32_MAX);
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}
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float rand_float(float max, uint32_t* seed)
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{
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return rand_0_to_1(seed) * max;
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}
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float ur_normal(uint32_t* seed)
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{
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float u1 = rand_0_to_1(seed);
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float u2 = rand_0_to_1(seed);
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float z = sqrtf(-2.0 * log(u1)) * sin(2 * PI * u2);
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return z;
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}
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float random_uniform(float from, float to, uint32_t* seed)
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{
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return rand_0_to_1(seed) * (to - from) + from;
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}
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float random_normal(float mean, float sigma, uint32_t* seed)
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{
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return (mean + sigma * ur_normal(seed));
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}
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float random_lognormal(float logmean, float logsigma, uint32_t* seed)
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{
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return expf(random_normal(logmean, logsigma, seed));
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}
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float random_to(float low, float high, uint32_t* seed)
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{
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const float NORMAL95CONFIDENCE = 1.6448536269514722;
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float loglow = logf(low);
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float loghigh = logf(high);
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float logmean = (loglow + loghigh) / 2;
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float logsigma = (loghigh - loglow) / (2.0 * NORMAL95CONFIDENCE);
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return random_lognormal(logmean, logsigma, seed);
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}
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// Array helpers
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float array_sum(float* array, int length)
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{
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float output = 0.0;
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for (int i = 0; i < length; i++) {
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output += array[i];
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}
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return output;
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}
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void array_cumsum(float* array_to_sum, float* array_cumsummed, int length)
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{
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array_cumsummed[0] = array_to_sum[0];
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for (int i = 1; i < length; i++) {
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array_cumsummed[i] = array_cumsummed[i - 1] + array_to_sum[i];
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}
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}
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// Mixture function
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float mixture(float (*samplers[])(uint32_t*), float* weights, int n_dists, uint32_t* seed)
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{
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// You can see a simpler version of this function in the git history
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// or in C-02-better-algorithm-one-thread/
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float sum_weights = array_sum(weights, n_dists);
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float* cumsummed_normalized_weights = (float*) malloc(n_dists * sizeof(float));
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cumsummed_normalized_weights[0] = weights[0]/sum_weights;
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for (int i = 1; i < n_dists; i++) {
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cumsummed_normalized_weights[i] = cumsummed_normalized_weights[i - 1] + weights[i]/sum_weights;
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}
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float p = random_uniform(0, 1, seed);
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float result;
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for (int k = 0; k < n_dists; k++) {
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if (p < cumsummed_normalized_weights[k]) {
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result = samplers[k](seed);
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break;
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}
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}
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free(cumsummed_normalized_weights);
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return result;
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}
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9
to-do.md
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9
to-do.md
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- [ ] Add example for only one sample
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- [ ] Add example for many samples
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- [ ] Use gcc extension to define functions nested inside main.
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- [ ] Use OpenMP for acceleration
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- [ ] Chain various mixture functions
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- [ ] Have some more complicated & realistic example
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- [ ] Add summarization functions, like mean, std, 90% ci (or all c.i.?)
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- [ ] Add beta distribution
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