/*
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/* 
 * File:   matutils.hpp
 * Author: jens
 *
 * Created on 21. Januar 2022, 08:28
 */

#ifndef MATUTILS_HPP
#define MATUTILS_HPP

#include "RnnTextHelper.hpp"

#include <math.h>

namespace Matutils
{
	const size_t NORMALIZING_DIM = 1;
	inline arma::mat uniform(arma::mat const & sizeMat, double stdDev=1.0, double mu=0.5)
	{
		return stdDev*(arma::randu(arma::size(sizeMat)) + mu - 0.5);
	}

	inline arma::mat sample(const arma::mat &src)
	{
		arma::umat res = (src > uniform(src));
		return arma::conv_to<arma::mat>::from(res);
	}
	
	inline arma::mat prob(const arma::mat &src)
	{
		return 1 / (1 + (arma::exp(-src)));
	}

	inline arma::mat normalize(const arma::mat& src)
	{
		std::cout << "Normalizing Training Data ..." << std::endl;

		// Dim = 0: Normalize over training all training pattern
		// Dim = 1: Normalize over single training pattern
		double k = 1;
		arma::mat mean = arma::mean(src, NORMALIZING_DIM);
		arma::mat stddev = arma::stddev(src, 0, NORMALIZING_DIM);

		arma::mat mean_mat;
		arma::mat std_mat;

		if (NORMALIZING_DIM==0)
		{
			mean_mat = arma::repmat(mean, src.n_rows, 1);
			std_mat = arma::repmat(stddev, src.n_rows, 1);
		}
		else
		{
			mean_mat = arma::repmat(mean, 1, src.n_cols);
			std_mat = arma::repmat(stddev, 1, src.n_cols);
		}

		arma::mat xn = src - mean_mat;
		arma::mat y = xn/(std_mat + 1e-9);
		return y;
	}

	inline arma::mat mean(const arma::mat& src)
	{
		return arma::mean(src, NORMALIZING_DIM);
	}

	inline arma::mat stddev(const arma::mat& src)
	{
		return arma::stddev(src, 0, NORMALIZING_DIM);
	}

	inline arma::mat char2vec(char c, size_t len)
	{
		arma::mat result = arma::zeros(1, len);
		int idx = RnnTextHelper::ch2idx(c);
		result[idx] = 1;
		
		return result;
	}
	
	inline char vec2char(arma::mat const &vec)
	{
		char result = RnnTextHelper::idx2ch(vec.index_max());
		
		return result;
	}

}

#endif /* MATUTILS_HPP */