#ifndef STAN_IO_RANDOM_VAR_CONTEXT_HPP
#define STAN_IO_RANDOM_VAR_CONTEXT_HPP

#include <stan/io/var_context.hpp>
#include <boost/random/uniform_real_distribution.hpp>
#include <algorithm>
#include <limits>
#include <string>
#include <vector>

namespace stan {
namespace io {

/**
 * This is an implementation of a var_context that initializes
 * the unconstrained values randomly. This is used for initialization.
 */
class random_var_context : public var_context {
 public:
  /**
   * Constructs a random var_context.
   *
   * On construction, this var_context will generate random
   * numbers on the unconstrained scale for the model provided.
   * Once generated, the class is immutable.
   *
   * This class only generates values for the parameters in the
   * Stan program and does not generate values for transformed parameters
   * or generated quantities.
   *
   * @tparam Model Model class
   * @tparam RNG Random number generator type
   * @param[in] model instantiated model to generate variables for
   * @param[in,out] rng pseudo-random number generator
   * @param[in] init_radius the unconstrained variables are uniform draws
   *   from -init_radius to init_radius.
   * @param[in] init_zero indicates whether all unconstrained variables
   *   should be initialized at 0. When init_zero is false, init_radius
   *   must be greater than 0.
   */
  template <class Model, class RNG>
  random_var_context(Model& model, RNG& rng, double init_radius, bool init_zero)
      : unconstrained_params_(model.num_params_r()) {
    size_t num_unconstrained_ = model.num_params_r();
    model.get_param_names(names_);
    model.get_dims(dims_);

    // cutting names_ and dims_ down to just the constrained parameters
    std::vector<std::string> constrained_params_names;
    model.constrained_param_names(constrained_params_names, false, false);
    size_t keep = constrained_params_names.size();
    size_t i = 0;
    size_t num = 0;
    for (i = 0; i < dims_.size(); ++i) {
      size_t size = 1;
      for (size_t n = 0; n < dims_[i].size(); ++n)
        size *= dims_[i][n];
      num += size;
      if (num > keep)
        break;
    }
    dims_.erase(dims_.begin() + i, dims_.end());
    names_.erase(names_.begin() + i, names_.end());

    if (init_zero) {
      for (size_t n = 0; n < num_unconstrained_; ++n)
        unconstrained_params_[n] = 0.0;
    } else {
      boost::random::uniform_real_distribution<double> unif(-init_radius,
                                                            init_radius);
      for (size_t n = 0; n < num_unconstrained_; ++n)
        unconstrained_params_[n] = unif(rng);
    }

    std::vector<double> constrained_params;
    std::vector<int> int_params;
    model.write_array(rng, unconstrained_params_, int_params,
                      constrained_params, false, false, 0);

    vals_r_ = constrained_to_vals_r(constrained_params, dims_);
  }

  /**
   * Destructor.
   */
  ~random_var_context() {}

  /**
   * Return <code>true</code> if the specified variable name is
   * defined. Will return <code>true</code> if the name matches
   * a parameter in the model.
   *
   * @param name Name of variable.
   * @return <code>true</code> if the name is a parameter in the
   * model.
   */
  bool contains_r(const std::string& name) const {
    return std::find(names_.begin(), names_.end(), name) != names_.end();
  }

  /**
   * Returns the values of the constrained variables.
   *
   * @param name Name of variable.
   *
   * @return the constrained values if the variable is in the
   *   var_context; an empty vector is returned otherwise
   */
  std::vector<double> vals_r(const std::string& name) const {
    std::vector<std::string>::const_iterator loc
        = std::find(names_.begin(), names_.end(), name);
    if (loc == names_.end())
      return std::vector<double>();
    return vals_r_[loc - names_.begin()];
  }

  /**
   * Returns the dimensions of the variable
   *
   * @param name Name of variable.
   * @return the dimensions of the variable if it exists; an empty vector
   *   is returned otherwise
   */
  std::vector<size_t> dims_r(const std::string& name) const {
    std::vector<std::string>::const_iterator loc
        = std::find(names_.begin(), names_.end(), name);
    if (loc == names_.end())
      return std::vector<size_t>();
    return dims_[loc - names_.begin()];
  }

  /**
   * Return <code>true</code> if the specified variable name has
   * integer values. Always returns <code>false</code>.
   *
   * @param name Name of variable.
   * @return false
   */
  bool contains_i(const std::string& name) const { return false; }

  /**
   * Returns an empty vector.
   *
   * @param name Name of variable.
   * @return empty vector
   */
  std::vector<int> vals_i(const std::string& name) const {
    std::vector<int> empty_vals_i;
    return empty_vals_i;
  }

  /**
   * Return the dimensions of the specified floating point variable.
   * Returns an empty vector.
   *
   * @param name Name of variable.
   * @return empty vector
   */
  std::vector<size_t> dims_i(const std::string& name) const {
    std::vector<size_t> empty_dims_i;
    return empty_dims_i;
  }

  /**
   * Fill a list of the names of the floating point variables in
   * the context. This will return the names of the parameters in
   * the model.
   *
   * @param names Vector to store the list of names in.
   */
  void names_r(std::vector<std::string>& names) const { names = names_; }

  /**
   * Fill a list of the names of the integer variables in
   * the context. This context has no variables.
   *
   * @param names Vector to store the list of names in.
   */
  void names_i(std::vector<std::string>& names) const { names.clear(); }

  /**
   * Return the random initialization on the unconstrained scale.
   *
   * @return the unconstrained parameters
   */
  std::vector<double> get_unconstrained() const {
    return unconstrained_params_;
  }

 private:
  /**
   * Parameter names in the model
   */
  std::vector<std::string> names_;
  /**
   * Dimensions of parameters in the model
   */
  std::vector<std::vector<size_t> > dims_;
  /**
   * Random parameter values of the model in the
   * unconstrained space
   */
  std::vector<double> unconstrained_params_;
  /**
   * Random parameter values of the model in the
   * constrained space
   */
  std::vector<std::vector<double> > vals_r_;

  /**
   * Computes the size of a variable based on the dim provided.
   *
   * @param dim dimension of the variable
   * @return total size of the variable
   */
  size_t dim_size(const std::vector<size_t>& dim) {
    size_t size = 1;
    for (size_t j = 0; j < dim.size(); ++j)
      size *= dim[j];
    return size;
  }

  /**
   * Returns a vector of constrained values in the format expected
   * out of the vals_r() function.
   *
   * @param[in] constrained constrained parameter values
   * @param[in] dims dimensions of each of the parameter values
   * @return constrained values reshaped to be returned in the vals_r
   *   function
   */
  std::vector<std::vector<double> > constrained_to_vals_r(
      const std::vector<double>& constrained,
      const std::vector<std::vector<size_t> >& dims) {
    std::vector<std::vector<double> > vals_r(dims.size());

    std::vector<double>::const_iterator start = constrained.begin();
    for (size_t i = 0; i < dims.size(); ++i) {
      size_t size = dim_size(dims[i]);
      vals_r[i] = std::vector<double>(start, start + size);
      start += size;
    }
    return vals_r;
  }
};

}  // namespace io
}  // namespace stan
#endif
