/***********************************************************************
* Normalize an array in log space.
***********************************************************************/
void log_normalize
(ATYPE close_enough,
ARRAY_T* array)
{
int i_item;
int num_items;
ATYPE total;
ATYPE this_value;
/* Get the sum of the elements. */
total = log_array_total(array);
/* If the array already sums to zero, don't bother. */
if (almost_equal(total, 0.0, close_enough)) {
return;
}
/* If there's nothing in the array, then return all zeroes. */
if (total < LOG_SMALL) {
init_array(LOG_ZERO, array);
return;
}
num_items = get_array_length(array);
for (i_item = 0; i_item < num_items; i_item++) {
this_value = get_array_item(i_item, array) - total;
/* If this value is small enough, just make it zero. */
if (this_value < LOG_SMALL) {
set_array_item(i_item, LOG_ZERO, array);
} else {
set_array_item(i_item, this_value, array);
}
}
}
/***********************************************************************
* Convert array by compute the average of complementary dna frequencies.
*
* Assumes DNA alphabet in order ACGT.
***********************************************************************/
void balance_complementary_dna_freqs
(ARRAY_T* source)
{
double at = (get_array_item(0, source)+get_array_item(3, source))/2.0;
double cg = (get_array_item(1, source)+get_array_item(2, source))/2.0;
set_array_item(0, at, source); // A -> T
set_array_item(1, cg, source); // C -> G
set_array_item(2, cg, source); // G -> C
set_array_item(3, at, source); // T -> A
fill_in_ambiguous_chars(FALSE, source);
}
/***********************************************************************
* Convert array by compute the average of complementary dna frequencies.
*
* Apparently no-one uses this.
*
* Assumes DNA alphabet in order ACGT.
***********************************************************************/
void balance_complementary_dna_freqs
(ARRAY_T* source)
{
double at = (get_array_item(0, source)+get_array_item(3, source))/2.0;
double cg = (get_array_item(1, source)+get_array_item(2, source))/2.0;
set_array_item(0, at, source); // A -> T
set_array_item(1, cg, source); // C -> G
set_array_item(2, cg, source); // G -> C
set_array_item(3, at, source); // T -> A
calc_ambigs(DNA_ALPH, FALSE, source);
}
void dxml_handle_pos(void *ctx, int pos, double A, double C, double G, double T) {
CTX_T *data;
MOTIF_T *motif;
ARRAY_T *row;
data = (CTX_T*)ctx;
motif = data->motif;
row = get_matrix_row(pos - 1, motif->freqs);
set_array_item(0, A, row);
set_array_item(1, C, row);
set_array_item(2, G, row);
set_array_item(3, T, row);
}
/**************************************************************************
* get_scaled_lo_prior_dist
*
* Takes a scaled distribution of priors and creates a scaled distribution of
* log odds priors. The parameters for the scaling of the input priors are
* in the PRIOR_DIST_T data structure. The output distribution of log odss
* priors are scaled to be in the same range as the PSSM log odds using
* the input parameters pssm_range, pssm_scale, and pssm_offset.
*
* Special handling is required for a uniform distribution of priors.
* In that case the max_prior == min_prior, and the distribution only
* contains one bin.
*
* Returns a new array containing the scaled log odds priors
**************************************************************************/
ARRAY_T *get_scaled_lo_prior_dist(
PRIOR_DIST_T *prior_dist,
double alpha,
int pssm_range,
double pssm_scale,
double pssm_offset
) {
assert(prior_dist != NULL);
// Alocate enought space for elements in [0 ... pssm_range]
ARRAY_T *scaled_lo_prior_dist = allocate_array(pssm_range + 1);
if (prior_dist != NULL) {
ARRAY_T *dist_array = get_prior_dist_array(prior_dist);
int len_prior_dist = get_array_length(dist_array);
double max_prior = get_prior_dist_maximum(prior_dist);
double min_prior = get_prior_dist_minimum(prior_dist);
double prior_dist_scale = get_prior_dist_scale(prior_dist);
double prior_dist_offset = get_prior_dist_offset(prior_dist);
init_array(0.0L, scaled_lo_prior_dist);
if (max_prior == min_prior) {
// Special case for uniform priors
double value = 1.0;
double lo_prior = my_log2(alpha * max_prior / (1.0L - (alpha * max_prior)));
// Convert lo_prior to PSSM scale
int scaled_index = raw_to_scaled(lo_prior, 1.0L, pssm_scale, pssm_offset);
set_array_item(scaled_index, value, scaled_lo_prior_dist);
}
else {
int prior_index = 0;
for (prior_index = 0; prior_index < len_prior_dist; ++prior_index) {
double value = get_array_item(prior_index, dist_array);
// Convert index giving scaled prior to raw prior.
double scaled_prior = ((double) prior_index) + 0.5L;
double prior \
= scaled_to_raw(scaled_prior, 1, prior_dist_scale, prior_dist_offset);
double lo_prior = my_log2(alpha * prior / (1.0L - (alpha * prior)));
// Scale raw lo_prior using parameters from PSSM.
int scaled_index = raw_to_scaled(lo_prior, 1.0L, pssm_scale, pssm_offset);
if (scaled_index < pssm_range) {
double old_value = get_array_item(scaled_index, scaled_lo_prior_dist);
set_array_item(scaled_index, value + old_value, scaled_lo_prior_dist);
}
}
}
}
return scaled_lo_prior_dist;
}
/***********************************************************************
* Compute the reverse complement of one DNA frequency distribution.
*
* Assumes DNA alphabet in order ACGT.
***********************************************************************/
void complement_dna_freqs
(ARRAY_T* source,
ARRAY_T* dest)
{
set_array_item(0, get_array_item(3, source), dest); // A -> T
set_array_item(1, get_array_item(2, source), dest); // C -> G
set_array_item(2, get_array_item(1, source), dest); // G -> C
set_array_item(3, get_array_item(0, source), dest); // T -> A
//check if the frequencies have ambiguous characters
//for example meme does not use ambiguous characters
if (get_array_length(source) > 4) {
fill_in_ambiguous_chars(FALSE, dest);
}
}
void dxml_handle_background(void *ctx, DREME_ALPH_EN alpha, double A, double C,
double G, double T, DREME_BG_EN source, char *file, char *last_mod_date) {
CTX_T *data;
MOTIF_T *motif;
ARRAY_T *bg;
data = (CTX_T*)ctx;
data->file_type_match = 4; // it must be a dreme xml file!
data->fscope.alphabet = DNA_ALPH;
data->fscope.background = allocate_array(4);
bg = data->fscope.background;
set_array_item(0, A, bg);
set_array_item(1, C, bg);
set_array_item(2, G, bg);
set_array_item(3, T, bg);
}
/**************************************************************************
* Get pseudocount frequencies.
*
* The target_freq matrix only has values for the basic alphabet.
* Fill in the ambiguous character pseudocounts afterwards using
* the average of pseudocounts for letters matching the ambiguous ones.
**************************************************************************/
ARRAY_T *get_pseudocount_freqs(
ALPH_T alph,
ARRAY_T * f, /* Foreground distribution. */
ARRAY_T * b, /* Background distribution. */
MATRIX_T * target_freq /* Target frequency matrix. */
)
{
int i, j;
int asize = alph_size(alph, ALPH_SIZE); // excludes ambigs
ARRAY_T *g = allocate_array(alph_size(alph, ALL_SIZE));// includes ambigs
/*
Create pseudocount frequencies.
*/
for (i = 0; i < asize; i++) { /* non-ambiguous freqs */
double gi = 0;
for (j= 0; j < asize; j++) { /* non-ambiguous freqs */
double qij = get_matrix_cell(i, j, target_freq);
double fj = get_array_item(j, f);
double bj = get_array_item(j, b);
gi += (fj/bj) * qij;
} /* j */
set_array_item(i, gi, g);
if (SUBST_MATRIX_DEBUG) printf("%g %g, ", get_array_item(i, f), gi);
} /* i */
calc_ambigs(alph, FALSE, g); /* takes the average pseudocount */
if (SUBST_MATRIX_DEBUG) printf("\n");
return(g); /* return the pseudocounts */
} /* get_pseudocount_freqs */
/***********************************************************************
* Mix two arrays in log space.
***********************************************************************/
void mix_log_arrays
(float mixing, /* Percent of array2 that will be retained. */
ARRAY_T* array1,
ARRAY_T* array2)
{
int i_item;
int num_items;
ATYPE mixed_value;
check_null_array(array1);
check_null_array(array2);
/* Verify that the arrays are of the same length. */
check_array_dimensions(TRUE, array1, array2);
/* Verify that we've got a reasonable mixing parameter. */
if ((mixing > 1.0) || (mixing < 0.0)) {
die("Invalid mixing parameter (%g).\n", mixing);
}
num_items = get_array_length(array1);
for (i_item = 0; i_item < num_items; i_item++) {
mixed_value
= LOG_SUM(my_log2(1.0 - mixing) + get_array_item(i_item, array1),
my_log2(mixing) + get_array_item(i_item, array2));
set_array_item(i_item, mixed_value, array2);
}
}
/***********************************************************************
* Read an array of unknown length from a file.
* Caller is resposbile for freeing array.
***********************************************************************/
ARRAY_T *read_array_from_file(const char* filename) {
int array_size = 100;
int i_item = 0;
int num_read = 0;
ATYPE value;
FILE *array_file = fopen(filename, "r");
if (array_file == NULL) {
die(
"Unable to open file: %s.\nError message: %s.\n",
filename,
strerror(errno)
);
}
ARRAY_T *array = allocate_array(array_size);
while ((num_read = fscanf(array_file, ASCAN, &value)) == 1) {
set_array_item(i_item, value, array);
++i_item;
if (i_item >= array_size) {
resize_array(array, 2 * array_size);
array_size = 2 *array_size;
}
}
if (num_read == 0) {
die("Error reading array at position %d.\n", i_item);
}
fclose(array_file);
resize_array(array, i_item);
return array;
}
/***********************************************************************
* A helper function to normalize a subarray.
***********************************************************************/
void normalize_subarray(
int start_index,
int length,
double tolerance,
ARRAY_T* array
) {
ATYPE total;
int i;
/* Compute the total. */
total = 0.0;
for (i = start_index; i < start_index + length; i++) {
total += get_array_item(i, array);
}
assert(total != 0.0);
/* Don't bother if we're close enough. */
if (almost_equal(1.0, total, tolerance)) {
return;
}
/* Divide each element by the total. */
for (i = start_index; i < start_index + length; i++) {
set_array_item(i, get_array_item(i, array) / total, array);
}
}
/***********************************************************************
* Read the background letter frequencies from XML.
* Caller is responsible for freeing the returned array.
***********************************************************************/
ARRAY_T* read_bg_freqs_from_xml(xmlXPathContextPtr xpath_ctxt, ALPH_T alph) {
xmlXPathObjectPtr xpathObj = NULL;
ATYPE value;
ARRAY_T* bg_freqs;
int a_size = alph_size(alph, ALPH_SIZE);
// Use XPATH to get the background frequencies from XML
xpathObj = xpath_query(
xpath_ctxt,
"//*/background_frequencies/alphabet_array/value"
);
int num_values = (xpathObj->nodesetval ? xpathObj->nodesetval->nodeNr : 0);
xmlXPathFreeObject(xpathObj);
// The number of background frequences should match the alphabet size.
assert(num_values == a_size);
// Allocate the array.
bg_freqs= allocate_array(alph_size(alph, ALL_SIZE));
// XML doesn't enforce any order on the emission probability values,
// so force reading bg frequency values in alphabet order.
const int MAX_XPATH_EXPRESSION = 200;
char xpath_expression[MAX_XPATH_EXPRESSION];
xmlNodePtr currValueNode = NULL;
int i_node = 0;
for (i_node = 0; i_node < a_size; i_node++) {
// Build the XPATH expression to get bg freq for a character.
snprintf(
xpath_expression,
MAX_XPATH_EXPRESSION,
"//*/background_frequencies/"
"alphabet_array/value[@letter_id='letter_%c']",
alph_char(alph, i_node)
);
// Read the selected bg frequency.
xpathObj = xpath_query(xpath_ctxt, xpath_expression);
// Should only find one node
assert(xpathObj->nodesetval->nodeNr == 1);
// Decode from node set to numeric value for bg freq.
currValueNode = xpathObj->nodesetval->nodeTab[0];
xmlXPathFreeObject(xpathObj);
value = xmlXPathCastNodeToNumber(currValueNode);
set_array_item(i_node, value, bg_freqs);
}
// Make sure the frequencies add up to 1.0.
normalize_subarray(0, a_size, 0.0, bg_freqs);
// Fill in ambiguous characters.
calc_ambigs(alph, FALSE, bg_freqs);
return bg_freqs;
}
/***********************************************************************
* Fill an array with a given raw array of values.
***********************************************************************/
void fill_array
(ATYPE* raw_array,
ARRAY_T* array)
{
int i_item;
int num_items;
num_items = get_array_length(array);
for (i_item = 0; i_item < num_items; i_item++) {
set_array_item(i_item, raw_array[i_item], array);
}
}
KARLIN_INPUT_T *make_karlin_input(
MATRIX_T *matrix, /* scoring matrix */
ARRAY_T *probs /* letter freq distribution */
)
{
int i, j;
double escore;
long lowest, highest;
ARRAY_T *score_probs;
int nscores;
int alen = get_num_rows(matrix); /* size of alphabet */
KARLIN_INPUT_T *karlin_input; /* data to return */
/* find the highest and lowest scores in the scoring matrix */
lowest = 1;
highest = -1;
for (i=0; i<alen; i++) {
for (j=0; j<alen; j++) {
double s = get_matrix_cell(i, j, matrix);
if (s < lowest) lowest = s;
if (s > highest) highest = s;
}
}
if (lowest >= 0) die("Lowest score in scoring matrix must be negative, is %f.", (double)lowest);
if (highest<= 0) die("Highest score in scoring matrix must be positve, is %f.", (double)highest);
/* allocate the array of score probabilities and set to 0 */
nscores = highest - lowest + 1;
score_probs = allocate_array(nscores);
init_array(0, score_probs);
/* compute the probabilities of different scores */
escore = 0;
for (i=0; i<alen; i++) {
for (j=0; j<alen; j++) {
int s = get_matrix_cell(i, j, matrix);
double pi = get_array_item(i, probs);
double pj = get_array_item(j, probs);
double sp = get_array_item(s-lowest, score_probs);
set_array_item(s-lowest, sp + pi*pj, score_probs); /* cumulative prob. of score */
escore += pi*pj*s;
/*printf("i %d j %d s %d pi %f pj %f sp %f escore %f\n",i,j,s, pi, pj, sp, escore);*/
}
}
karlin_input = (KARLIN_INPUT_T *)mm_malloc(sizeof(KARLIN_INPUT_T));
karlin_input->low = lowest;
karlin_input->high = highest;
karlin_input->escore = escore;
karlin_input->prob = score_probs;
return(karlin_input);
} /* make_karlin_input */
/*
* Load uniform frequencies into the array.
*/
ARRAY_T* get_uniform_frequencies(ALPH_T alph, ARRAY_T *freqs) {
int i, n;
n = ALPH_ASIZE[alph];
if (freqs == NULL) freqs = allocate_array(alph_size(alph, ALL_SIZE));
assert(get_array_length(freqs) >= alph_size(alph, ALL_SIZE));
for (i = 0; i < n; i++) {
set_array_item(i, 1.0/n, freqs);
}
calc_ambigs(alph, FALSE, freqs);
return freqs;
}
/***********************************************************************
* Initialize a given array with a given value.
***********************************************************************/
void init_array
(ATYPE value,
ARRAY_T* array)
{
int i_item;
int num_items;
num_items = get_array_length(array);
for (i_item = 0; i_item < num_items; i_item++) {
set_array_item(i_item, value, array);
}
}
/*
* Replace the elements an array of frequences with the average
* over complementary bases.
*/
void average_freq_with_complement(ALPH_T alph, ARRAY_T *freqs) {
int a_index, t_index, g_index, c_index;
double at_freq, gc_freq;
assert(alph == DNA_ALPH);
a_index = alph_index(alph, 'A');
t_index = alph_index(alph, 'T');
g_index = alph_index(alph, 'G');
c_index = alph_index(alph, 'C');
at_freq = (get_array_item(a_index, freqs) +
get_array_item(t_index, freqs)) / 2.0;
gc_freq = (get_array_item(g_index, freqs) +
get_array_item(c_index, freqs)) / 2.0;
set_array_item(a_index, at_freq, freqs);
set_array_item(t_index, at_freq, freqs);
set_array_item(g_index, gc_freq, freqs);
set_array_item(c_index, gc_freq, freqs);
}
void unlog_array
(ARRAY_T* array)
{
int i_item;
int num_items;
check_null_array(array);
num_items = get_array_length(array);
for (i_item = 0; i_item < num_items; i_item++) {
set_array_item(i_item, EXP2(get_array_item(i_item, array)), array);
}
}
/*
* Take the counts from an ambiguous character and evenly distribute
* them among the corresponding concrete characters.
*
* This function operates in log space.
*/
static void dist_ambig(ALPH_T alph, char ambig, char *concrete_chars,
ARRAY_T* freqs) {
PROB_T ambig_count, concrete_count;
int ambig_index, num_concretes, i, concrete_index;
// Get the count to be distributed.
ambig_index = alph_index(alph, ambig);
ambig_count = get_array_item(ambig_index, freqs);
// Divide it by the number of corresponding concrete characters.
num_concretes = strlen(concrete_chars);
ambig_count -= my_log2((PROB_T)num_concretes);
// Distribute it in equal portions to the given concrete characters.
for (i = 0; i < num_concretes; i++) {
concrete_index = alph_index(alph, concrete_chars[i]);
concrete_count = get_array_item(concrete_index, freqs);
// Add the ambiguous counts.
concrete_count = LOG_SUM(concrete_count, ambig_count);
set_array_item(concrete_index, concrete_count, freqs);
}
// Set the ambiguous count to zero.
set_array_item(ambig_index, LOG_ZERO, freqs);
}
/***********************************************************************
* Multiply each element of an array by a scalar value.
***********************************************************************/
void scalar_mult
(ATYPE value,
ARRAY_T* array)
{
int i_item;
int num_items;
check_null_array(array);
num_items = get_array_length(array);
for (i_item = 0; i_item < num_items; i_item++) {
set_array_item(i_item, get_array_item(i_item, array) * value, array);
}
}
/***********************************************************************
* Fill an array with random values between 0 and a given maximum.
*
* Assumes that the random number generator is initialized.
***********************************************************************/
void randomize_array
(ATYPE magnitude,
ARRAY_T* array)
{
int num_items;
int i_item;
check_null_array(array);
num_items = get_array_length(array);
for (i_item = 0; i_item < num_items; i_item++) {
set_array_item(i_item, my_drand() * magnitude, array);
}
}
/************************************************************************
* Compute the indices and values of transitions to or from a state.
************************************************************************/
void compute_ins_and_outs
(MHMM_T* the_hmm,
BOOLEAN_T log_form) /* Is the transition matrix in log form? */
{
int i_row, i_col;
int n = the_hmm->num_states;
MATRIX_T *trans = the_hmm->trans;
//
// Visit the transition matrix cells just once each
// to update ntrans, itrans and trans arrays.
// This is quadratic in n.
//
for (i_row = 0; i_row < n; i_row++) {
for (i_col = 0; i_col < n; i_col++) {
double p; // The transition probability.
int old_n, new_n; // Number of transitions.
if (!is_zero((p = get_matrix_cell(i_row, i_col, trans)), log_form)) {
MHMM_STATE_T * out_state = &(the_hmm->states[i_row]);
MHMM_STATE_T * in_state = &(the_hmm->states[i_col]);
// out
old_n = out_state->ntrans_out;
new_n = ++out_state->ntrans_out;
mm_resize(out_state->itrans_out, new_n, int);
out_state->trans_out = resize_array(out_state->trans_out, new_n);
out_state->itrans_out[old_n] = i_col;
set_array_item(old_n, p, out_state->trans_out);
// in
old_n = in_state->ntrans_in;
new_n = ++in_state->ntrans_in;
mm_resize(in_state->itrans_in, new_n, int);
in_state->trans_in = resize_array(in_state->trans_in, new_n);
in_state->itrans_in[old_n] = i_row;
set_array_item(old_n, p, in_state->trans_in);
}
} // col
} // row
/*
* Load the non-redundant database frequencies into the array.
*/
ARRAY_T* get_nrdb_frequencies(ALPH_T alph, ARRAY_T *freqs) {
int i, size;
const PROB_T *nrdb_freqs;
size = ALPH_ASIZE[alph];
if (freqs == NULL) freqs = allocate_array(alph_size(alph, ALL_SIZE));
assert(get_array_length(freqs) >= alph_size(alph, ALL_SIZE));
nrdb_freqs = ALPH_NRDB[alph];
for (i = 0; i < size; ++i) {
set_array_item(i, nrdb_freqs[i], freqs);
}
normalize_subarray(0, size, 0.0, freqs);
calc_ambigs(alph, FALSE, freqs);
return freqs;
}
/***********************************************************************
* Return one column of a motif, as a newly allocated array of counts.
***********************************************************************/
ARRAY_T* get_motif_counts
(int position,
MOTIF_T* motif)
{
ARRAY_T* return_value = allocate_array(motif->alph_size);
int i_alph;
for (i_alph = 0; i_alph < motif->alph_size; i_alph++) {
set_array_item(i_alph,
motif->num_sites * get_matrix_cell(position,
i_alph, motif->freqs),
return_value);
}
return(return_value);
}
/*************************************************************************
* Convert spacer states in a given HMM to free-insertion modules.
* All transitions out of spacers states are set to 1.0.
*
* Note that this function only affects the transitions stored in each
* individual state. It is assumed that build_transition_matrix will
* be called subsequently.
*************************************************************************/
static void convert_to_fims
(MHMM_T *the_hmm)
{
int i_state; /* Index of the current state. */
MHMM_STATE_T * the_state; /* The current state. */
int i_trans; /* Index of outgoing transition. */
for (i_state = 0; i_state < the_hmm->num_states; i_state++) {
the_state = &(the_hmm->states[i_state]);
if (the_state->type == SPACER_STATE) {
for (i_trans = 0; i_trans < the_state->ntrans_out; i_trans++)
set_array_item(i_trans, 1.0, the_state->trans_out);
}
}
}
/***********************************************************************
* Divide corresponding elements in two arrays.
***********************************************************************/
void dot_divide
(ARRAY_T* array1,
ARRAY_T* array2)
{
int i_item;
int num_items;
check_null_array(array1);
check_null_array(array2);
check_array_dimensions(TRUE, array1, array2);
num_items = get_array_length(array1);
for (i_item = 0; i_item < num_items; i_item++) {
set_array_item(i_item, get_array_item(i_item, array1) /
get_array_item(i_item, array2), array2);
}
}
/*
* Make one position in an array the sum of a set of other positions.
*/
static void calc_ambig(ALPH_T alph, BOOLEAN_T log_space, char ambig,
char *sources, ARRAY_T *array) {
char *source;
PROB_T sum;
PROB_T value;
sum = 0.0;
for (source = sources; *source != '\0'; ++source) {
value = get_array_item(alph_index(alph, *source), array);
if (log_space) {
sum = LOG_SUM(sum, value);
} else {
sum += value;
}
}
set_array_item(alph_index(alph, ambig), sum, array);
}
/***********************************************************************
* Read an array of known length from a file.
***********************************************************************/
void read_array
(FILE * infile,
ARRAY_T* array)
{
int i_item;
int num_items;
ATYPE value;
check_null_array(array);
num_items = get_array_length(array);
for (i_item = 0; i_item < num_items; i_item++) {
if (fscanf((FILE *)infile, ASCAN, &value) != 1) {
die("Error reading array at position %d.\n", i_item);
}
set_array_item(i_item, value, array);
}
}
/***********************************************************************
* Create a bootstrapped copy of the given array.
*
* Allocates the bootstrap array; must be freed by caller.
* Assumes that the random number generator is initialized.
***********************************************************************/
ARRAY_T* bootstrap_array
(ARRAY_T* source_array,
int num_items)
{
ARRAY_T* return_array;
check_null_array(source_array);
// Allocate the bootstrap array.
return_array = allocate_array(num_items);
// Fill up the bootstrap array.
int i_item;
int num_inputs = get_array_length(source_array);
for (i_item = 0; i_item < num_items; i_item++) {
int random_index = (int)(my_drand() * (double)(num_inputs));
ATYPE random_item = get_array_item(random_index, source_array);
set_array_item(i_item, random_item, return_array);
}
return(return_array);
}
/***********************************************************************
* Remove one item from an array, shifting everything else left.
***********************************************************************/
void remove_array_item
(int item_index,
ARRAY_T* array)
{
int i_item;
int num_items;
// Shift everything left one position.
num_items = get_array_length(array);
for (i_item = item_index + 1; i_item < num_items; i_item++) {
set_array_item(i_item - 1, get_array_item(i_item, array), array);
}
// Reallocate.
if ((array->items = (ATYPE*)mm_realloc(array->items,
sizeof(ATYPE) * (num_items - 1)))
== NULL) {
die("Error re-allocating array.\n");
}
(array->num_items)--;
}
