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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2014 Google Inc. All rights reserved.
// http://code.google.com/p/ceres-solver/
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
// * Redistributions of source code must retain the above copyright notice,
//   this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright notice,
//   this list of conditions and the following disclaimer in the documentation
//   and/or other materials provided with the distribution.
// * Neither the name of Google Inc. nor the names of its contributors may be
//   used to endorse or promote products derived from this software without
//   specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// Author: sameeragarwal@google.com (Sameer Agarwal)

#ifndef CERES_EXAMPLES_RANDOM_H_
#define CERES_EXAMPLES_RANDOM_H_

#include <math.h>
#include <stdlib.h>

namespace ceres {
namespace examples {

// Return a random number sampled from a uniform distribution in the range
// [0,1].
inline double RandDouble() {
  double r = static_cast<double>(rand());
  return r / RAND_MAX;
}

// Marsaglia Polar method for generation standard normal (pseudo)
// random numbers http://en.wikipedia.org/wiki/Marsaglia_polar_method
inline double RandNormal() {
  double x1, x2, w;
  do {
    x1 = 2.0 * RandDouble() - 1.0;
    x2 = 2.0 * RandDouble() - 1.0;
    w = x1 * x1 + x2 * x2;
  } while ( w >= 1.0 || w == 0.0 );

  w = sqrt((-2.0 * log(w)) / w);
  return x1 * w;
}

}  // namespace examples
}  // namespace ceres

#endif  // CERES_EXAMPLES_RANDOM_H_