/* -*- c-basic-offset: 4; indent-tabs-mode: nil -*- */
/* ====================================================================
 * Copyright (c) 1999-2004 Carnegie Mellon University.  All rights
 * reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions
 * are met:
 *
 * 1. Redistributions of source code must retain the above copyright
 *    notice, this list of conditions and the following disclaimer. 
 *
 * 2. 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.
 *
 * This work was supported in part by funding from the Defense Advanced 
 * Research Projects Agency and the National Science Foundation of the 
 * United States of America, and the CMU Sphinx Speech Consortium.
 *
 * THIS SOFTWARE IS PROVIDED BY CARNEGIE MELLON UNIVERSITY ``AS IS'' AND 
 * ANY EXPRESSED OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, 
 * THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
 * PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL CARNEGIE MELLON UNIVERSITY
 * NOR ITS EMPLOYEES BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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 * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, 
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 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE 
 * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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 * ====================================================================
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 */
/*
 * vector.h -- vector routines.
 * 
 * **********************************************
 * CMU ARPA Speech Project
 *
 * Copyright (c) 1997 Carnegie Mellon University.
 * ALL RIGHTS RESERVED.
 * **********************************************
 * 
 * HISTORY
 * 
 * 10-Mar-1999	M K Ravishankar (rkm@cs.cmu.edu) at Carnegie Mellon University.
 * 		Added vector_accum(), vector_vqlabel(), and vector_vqgen().
 * 
 * 09-Mar-1999	M K Ravishankar (rkm@cs.cmu.edu) at Carnegie Mellon University.
 * 		Added vector_is_zero(), vector_cmp(), and vector_dist_eucl().
 * 		Changed the name vector_dist_eval to vector_dist_maha.
 * 
 * 30-Dec-95	M K Ravishankar (rkm@cs.cmu.edu) at Carnegie Mellon University.
 * 		Created from Eric Thayer's version.
 */


#ifndef _S3_VECTOR_H_
#define _S3_VECTOR_H_

/** \file vector.h
    \brief operation on Vector
*/
#include <s3types.h>
#include <stdio.h>

#ifdef __cplusplus
extern "C" {
#endif
#if 0
} /* Fool Emacs into not indenting things. */
#endif

typedef float32 *vector_t;


/* Why do these belong here?? */
/** \struct arraysize_t
 * \brief wrapper of array size 
 */
typedef struct {
    int32 r;		/**< #rows, */
    int32 c;		/**< #cols in an array */
} arraysize_t;

/** \struct point_t
 * \brief wrapper of a point in integer
 */

typedef struct {
    int32 x;		/**< x-coordinate, */
    int32 y;		/**< y-coordinate of a point */
} point_t;

/** \struct point_t
 * \brief wrapper of a point in floating point
 */

typedef struct {
    float32 x;		/**< x-coordinate, */
    float32 y;		/**< y-coordinate of a point */
} fpoint_t;		/**< Like point_t, but with float32 values */


/**
 * The reason for some of the "trivial" routines below is that they could be OPTIMIZED for SPEED
 * at some point.
 */


/** Floor all elements of v[0..dim-1] to min value of f */
void vector_floor(vector_t v,  /**< The vector */
		  int32 dim,     /**< The dimension of the vector */
		  float64 f      /**< The floor value */
    );


/** Floor all non-0 elements of v[0..dim-1] to min value of f */
void vector_nz_floor(vector_t v, int32 dim, float64 f);


/** Normalize the vector. */
int32 vector_normalize(vector_t v,  /**< The vector */
		       uint32 dim    /**< The dimension of the vector */
    );


/**
 * Normalize the elements of the given vector so that they sum to 1.0.  If the sum is 0.0
 * to begin with, the vector is left untouched.  
 * @ The normalization factor.
 */
float64 vector_sum_norm(vector_t v, int32 dim);


/** Print vector in one line, in %11.4e format, terminated by newline */
S3DECODER_EXPORT
void vector_print(FILE *fp, vector_t v, int32 dim);


/** Return TRUE iff given vector is all 0.0 */
S3DECODER_EXPORT
int32 vector_is_zero (float32 *vec,	/**< In: Vector to be checked */
		      int32 len	/**< In: Length of above vector */
    );

/** Return TRUE iff one of the component of the vector is nan */
int32 vector_is_nan (float32 *vec, /**< In: Vector to be checked */
		     int32 len     /**< In: Length of above vector */
    );

/**
 * Search for the max or min valued component in the given vector.  The vector length must be
 * strictly > 0 (val[] must have at least one valid value).  If more than one component
 * qualifies, the first one is chosen.
 * Return value: the INDEX of the selected val[] component (not the value itself).
 */
int32 vector_maxcomp_int32 (int32 *val, int32 len);
int32 vector_mincomp_int32 (int32 *val, int32 len);
int32 vector_maxcomp_float32 (float32 *val, int32 len);
int32 vector_mincomp_float32 (float32 *val, int32 len);


/** Accumulate src into dst */
void vector_accum (float32 *dst,	/**< In/Out: dst[i] += src[i] */
		   float32 *src,	/**< In: See above */
		   int32 len		/**< In: Length of above vectors */
    );

/**
 * Compare the two given vectors. 
 * @return -1, 0, or +1 depending on v1 <, =, or > v2 (as determined by the earliest unequal component).
 */
int32 vector_cmp (float32 *v1, float32 *v2,	/**< In: Vectors to be compared */
		  int32 len		/**< In: Length of each vector */
    );

/**
 * Compute the mean vector from the given set of vector data.
 * @return: 0 if successful, -1 if any error (there shouldn't be any error).
 */
int32 vector_mean (float32 *mean,	/**< Out: Computed mean; caller should allocate
					   this memory */
		   float32 **data,	/**< In: Set of data over which mean is computed */
		   int32 n_vec,		/**< In: #Vectors in data */
		   int32 n_dim	/**< In: Dimensionality of each vector (and mean) */
    );

/**
 * Return the Euclidean distance (actually, distance^2) between the two given vectors.
 */
float64 vector_dist_eucl (float32 *v1, float32 *v2,	/**< In: The two input vectors */
			  int32 len	/**< In: Length of each vector */
    );

/**
 * Given a Gaussian density with mean vector m and diagonal variance vector v, and some
 * input vector x, all of length n, the Mahalanobis distance of x from the Gaussian mean m
 * is given by:
 *     {1/sqrt((2pi)^n * det(v))} * exp{-Sum((x[i] - m[i])^2 / (2v[i]))}
 * To speed up this evaluation, the first sub-expression ({1/sqrt...}) can be precomputed at
 * initialization, and so can 1/2v[i] in the second sub-expression.  Secondly, recognition
 * systems work with log-likelihood values, so these distances or likelihood values are
 * computed in log-domain.
 * 
 * Carry out the above precomputations on the given variance vector; update var with 1/2var IN
 * PLACE, and return the value of the first sub-expression as a log value.  (The variance values
 * are assumed to be strictly > 0.0.
 */
float64
vector_maha_precomp (float32 *var,	/**< In/Out: Variance vector, modified to 1/2var */
		     int32 len	/**< In: Length of the above vector */
    );

/**
 * Mahalanobis distance, using some precomputed portions of variance and determinant.
 * (Actually not "distance" at all, but Gaussian density value.)
 * Computed in log domain.
 * Return value: logbase-e(likelihood value).
 */
float64
vector_dist_maha (float32 *vec,		/**< In: Vector for which distance from mean
					   being computed */
		  float32 *mean,	/**< In: Mean vector */
		  float32 *varinv,	/**< In: Variance vector, modified according to
					   vector_maha_precomp() */
		  float64 norm,		/**< In: Normalization factor computed by
					   vector_maha_precomp() */
		  int32 len		/**< In: Length of each vector involved */
    );

/**
 * Generate a vector quantized table for the input data, using the K-means algorithm, and the
 * Euclidean distance measure.
 * Return value: The squared quantization error of the final result.
 */
S3DECODER_EXPORT
float64 vector_vqgen (float32 **data,	/**< In: Input Data to be quantized */
		      int32 rows,	/**< In: #Rows in input data */
		      int32 cols,	/**< In: #Cols in input data (and output VQ table) */
		      int32 vqrows,	/**< In: #Rows in vector quantized result */
		      float64 epsilon,	/**< In: Convergence limit; stop k-means iterations when
					   the relative reduction in total squared error in
					   successive iterations ((sqerr[t]-sqerr[t+1])/sqerr[t])
					   is below this value. */
		      int32 maxiter,	/**< In: Max #iterations, regardless of convlimit */
		      float32 **mean,	/**< Out: Vector quantized array of centroids.  Caller
					   must allocate this array */
		      int32 *map,       /**< Out: data->mean mapping; mean[map[i]] is the closest
					   quantized vector corresponding to the input vector
					   data[i].  Caller must allocate this array */

		      int32 seed      /**< In : The seed for a random generator
					 if it is smaller than 0, use the internal
					 mechanism to generate seed. 
					 else use the seed to seed the random
					 generator.
				      */
    );

/**
 * Find the entry (row) of mean that is closest (according to Euclidean distance) to vec.
 * Return value: index of the selected row.
 */
int32 vector_vqlabel (float32 *vec,	/**< In: Vector to be compared against VQ table */
		      float32 **mean,	/**< In: Table of centroids */
		      int32 rows,	/**< In: #Rows in mean */
		      int32 cols,	/**< In: #Cols in mean (and vec) */
		      float64 *sqerr	/**< Out: Squared error (distance) between vec and the
					   selected codeword.  May be NULL if not needed. */
    );

/**
 * Treat the given vector as a PDF and compute its entropy (-sum(p * log2(p))).  (The PDF values
 * must be >= 0.0, of course.)  The zero elements of the PDF are skipped.
 */
float64 vector_pdf_entropy (float32 *p,	/**< In: Vector (PDF) whose entropy is to be computed */
			    int32 len	/**< In: Length of p[] */
    );

/**
 * Return cross-entropy of two PDFs; like vector_entropy, but (-sum(p1 * log2(p2))).  (The PDF
 * values must be >= 0.0, of course.)  The zero elements of p2 are skipped.
 */
float64 vector_pdf_cross_entropy (float32 *p1,
				  float32 *p2,	/**< In: Zero elements of p2 are skipped */
				  int32 len);

/**
 * Generic table of individual Gaussian vectors, with diagonal co-variance matrices (i.e.,
 * only the diagonal is maintained, as a vector).
 */
typedef struct {
    int32 n_gau;	/**< #Gaussians in table */
    int32 veclen;	/**< Vector length */
    float32 **mean;	/**< n_cw x veclen mean values */
    float32 **var;	/**< n_cw x veclen corresponding (diagonal) variance values */
    float32 *lrd;	/**< Log(Reciprocal(Determinant(Co-var. matrix))) */
    float64 distfloor;	/**< When Mahalanobis distance values are converted to logs3 domain, the
                           int32 result can underflow.  To avoid this, floor before conversion */
} vector_gautbl_t;


/**
 * The obvious allocation and free routines for vector_gautbl_t.{mean,var,lrd}.  Also sets
 * gautbl->{n_mgau, veclen, distfloor}; the last to the equivalent of S3_LOGPROB_ZERO.
 */
void vector_gautbl_alloc (vector_gautbl_t *gautbl,
			  int32 n_gau, int32 veclen);
void vector_gautbl_free (vector_gautbl_t *gautbl);


/**
 * Floor all the variance values in the given Gaussians table.
 */
void vector_gautbl_var_floor (vector_gautbl_t *gautbl,	/**< In/Out: Table to be updated */
			      float64 floor		/**< In: Floor value */
    );

/**
 * Carry out the vector_maha_precomp, above, over all the Gaussians in the given table, updating
 * gau->lrd[] as a result.  The needed memory must have been already allocated by the caller.
 */
void vector_gautbl_maha_precomp (vector_gautbl_t *gau);


/**
 * Compare the input vector to the given range of subvector codewords in the given codebook,
 * Enter the computed Mahalanobis distances, converted into logs3 values, into the given score
 * array.  (Why bother with the {offset,count} range??  For "blocking" such computation so that
 * cache behaviour is improved.)
 */
void
vector_gautbl_eval_logs3 (vector_gautbl_t *gau,	/**< In: Table of Gaussians */
			  int32 offset,	/**< In: First VQ codeword in the range to be evaluated */
			  int32 count,	/**< In: #Codewords to be evaluated (range size) */
			  float32 *x,	/**< In: Input vector being compared to codewords */
			  int32 *scr	/**< Out: Mahalanobis distance scores (logs3 values).
					   Caller must allocate this array.  Note that only
					   score[offset..offset+count-1] are updated. */
    );

#if 0
{ /* Stop indent from complaining */
#endif
#ifdef __cplusplus
}
#endif

#endif /* VECTOR_H */ 


/*
 * Log record.  Maintained by RCS.
 *
 * $Log$
 * Revision 1.2  2006/04/19  18:59:37  arthchan2003
 * Check whether nan appear explicitly in the acoustic models and vector.c, this will make gausubvq works. This shouldn't break the VQ generated in the past.  Because if nan exists in any of the past models, gausubvq will give abnormal results and some of us should have observed.
 * 
 * Revision 1.1  2006/04/05 20:27:30  dhdfu
 * A Great Reorganzation of header files and executables
 *
 * Revision 1.13  2006/02/22 20:35:17  arthchan2003
 * Merge from branch SPHINX3_5_2_RCI_IRII_BRANCH:
 * 1, Not allocated lrd in vector.c because its only consumer subvq.c has done it. 2, Fixed dox-doc.
 *
 * Revision 1.12.4.1  2005/07/05 06:25:40  arthchan2003
 * Fixed dox-doc.
 *
 * Revision 1.12  2005/06/21 21:00:44  arthchan2003
 * Add a statistics inventory structure, it takes care of 1, counters, 2, timers. Interfaces are provided to allow convenient clearing and updating of structures
 *
 * Revision 1.2  2005/06/13 04:02:57  archan
 * Fixed most doxygen-style documentation under libs3decoder.
 *
 * Revision 1.1.1.1  2005/03/24 15:24:00  archan
 * I found Evandro's suggestion is quite right after yelling at him 2 days later. So I decide to check this in again without any binaries. (I have done make distcheck. ) . Again, this is a candidate for s3.6 and I believe I need to work out 4-5 intermediate steps before I can complete the first prototype.  That's why I keep local copies. 
 *
 * Revision 1.11  2004/12/06 10:52:01  arthchan2003
 * Enable doxygen documentation in libs3decoder
 *
 * Revision 1.10  2004/12/05 12:01:31  arthchan2003
 * 1, move libutil/libutil.h to s3types.h, seems to me not very nice to have it in every files. 2, Remove warning messages of main_align.c 3, Remove warning messages in chgCase.c
 *
 * Revision 1.9  2004/11/16 05:13:18  arthchan2003
 * 1, s3cipid_t is upgraded to int16 because we need that, I already check that there are no magic code using 8-bit s3cipid_t
 * 2, Refactor the ep code and put a lot of stuffs into fe.c (should be renamed to something else.
 * 3, Check-in codes of wave2feat and cepview. (cepview will not dump core but Evandro will kill me)
 * 4, Make the same command line frontends for decode, align, dag, astar, allphone, decode_anytopo and ep . Allow the use a file to configure the application.
 * 5, Make changes in test such that test-allphone becomes a repeatability test.
 * 6, cepview, wave2feat and decode_anytopo will not be installed in 3.5 RCIII
 * (Known bugs after this commit)
 * 1, decode_anytopo has strange bugs in some situations that it cannot find the end of the lattice. This is urgent.
 * 2, default argument file's mechanism is not yet supported, we need to fix it.
 * 3, the bug discovered by SonicFoundry is still not fixed.
 *
 * Revision 1.8  2004/11/13 21:25:19  arthchan2003
 * commit of 1, absolute CI-GMMS , 2, fast CI senone computation using svq, 3, Decrease the number of static variables, 4, fixing the random generator problem of vector_vqgen, 5, move all unused files to NOTUSED
 *
 * Revision 1.7  2004/09/13 08:13:26  arthchan2003
 * update copyright notice from 200x to 2004
 *
 * Revision 1.6  2004/07/27 21:53:05  yitao
 *
 * weird.  i only changed kb.c to fix a small bug.  why so many changes?
 *
 * Revision 1.5  2004/07/21 06:12:47  arthchan2003
 * add precompiler directive __cplusplus to all header files
 *
 * Revision 1.2  2004/07/21 05:11:46  archan
 * all sphinx 3.4 files with proper extern C headers
 *
 * Revision 1.1  2004/07/15 08:21:19  archan
 * All header files for sphinx3.4
 *
 * Revision 1.4  2004/05/27 22:47:43  arthchan2003
 * Sphinx 3.4 code commit
 *
 * Revision 1.3  2004/03/11 21:47:57  archan
 * Check-in code for dynamic LM and fixes in Gaussian Selection. Temporarily cover J's change. Waiting for more stable code
 *
 * Revision 1.3  2001/12/11 04:40:56  lenzo
 * License cleanup.
 *
 * Revision 1.2  2001/12/04 02:57:47  egouvea
 * Merged memory leak fixes from RAH  (egouvea@cs.cmu.edu)
 *
 * Revision 1.1.1.1  2001/01/17 05:17:15  ricky
 * Initial Import of the s3.3 decoder, has working decodeaudiofile, s3.3_live
 *
 * Revision 1.1.1.1  2000/02/28 18:05:54  rkm
 * Imported Sources
 *
 * Revision 1.1.1.1  1999/11/23 20:24:18  rkm
 * imported sources
 *
 * Revision 1.2  1995/10/09  20:55:35  eht
 * Changes for prim_type.h
 *
 * Revision 1.1  1995/08/15  13:44:14  eht
 * Initial revision
 *
 *
 */
