nmr8acme

/**
 * The MIT License (MIT)
 *
 * Copyright (c) 2015 Circle Internet Financial
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is

nmr8acme

An animation of Mitchell’s best-candidate algorithm, which produces samples with blue-noise spectral characteristics that are useful for minimizing aliasing. Unlike uniform random sampling, best-candidate samples are more evenly distributed, with fewer samples close together. (A similar, but more efficient, algorithm is poisson-disc sampling.)

For each new sample, the best-candidate algorithm generates a fixed number of candidate samples, shown in gray. Here, 10 candidates are generated. The best candidate, shown in red, is the one that is farthest away from all previous (non-candidate) samples.

nmr8acme

package pg;

@interface Keep {
}

public class Main {
  public static void main(String[] args) throws Exception {
    System.out.println(
        Class.forName(System.getenv("THE_CLASS"))
            .getMethods()[0].invoke(null));

nmr8acme

all: json2bson
clean:
	rm -f json2bson

json2bson: json2bson.c
	${CC} $(shell pkg-config --cflags json libmongo-client glib-2.0) -Wall -O0 -ggdb3 -std=c99 ${CFLAGS} \
	      $(shell pkg-config --libs json libmongo-client glib-2.0) -o $@ $^

check: all
	./json2bson <test.json >test.bson