true);
struct casereader *rc = casereader_clone (r);
- for ( ; (c = casereader_read (r) ); case_unref (c))
+ for (; (c = casereader_read (r)); case_unref (c))
{
covariance_accumulate_pass1 (cov, c);
}
- for ( ; (c = casereader_read (rc) ); case_unref (c))
+ for (; (c = casereader_read (rc)); case_unref (c))
{
covariance_accumulate_pass2 (cov, c);
}
corr_matrix = correlation_from_covariance (cov_matrix, var_matrix);
- if ( opts->statistics & STATS_DESCRIPTIVES)
+ if (opts->statistics & STATS_DESCRIPTIVES)
output_descriptives (corr, opts, mean_matrix, var_matrix, samples_matrix);
output_correlation (corr, opts, corr_matrix,
lex_match (lexer, T_EQUALS);
while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
{
- if ( lex_match_id (lexer, "TWOTAIL"))
+ if (lex_match_id (lexer, "TWOTAIL"))
opts.tails = 2;
else if (lex_match_id (lexer, "ONETAIL"))
opts.tails = 1;
lex_match (lexer, T_EQUALS);
while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
{
- if ( lex_match_id (lexer, "DESCRIPTIVES"))
+ if (lex_match_id (lexer, "DESCRIPTIVES"))
opts.statistics = STATS_DESCRIPTIVES;
else if (lex_match_id (lexer, "XPROD"))
opts.statistics = STATS_XPROD;
corr = xrealloc (corr, sizeof (*corr) * (n_corrs + 1));
corr[n_corrs].n_vars_total = corr[n_corrs].n_vars1 = 0;
- if ( ! parse_variables_const (lexer, dict, &corr[n_corrs].vars,
+ if (! parse_variables_const (lexer, dict, &corr[n_corrs].vars,
&corr[n_corrs].n_vars_total,
PV_NUMERIC))
{
corr[n_corrs].n_vars1 = corr[n_corrs].n_vars_total;
- if ( lex_match (lexer, T_WITH))
+ if (lex_match (lexer, T_WITH))
{
- if ( ! parse_variables_const (lexer, dict,
+ if (! parse_variables_const (lexer, dict,
&corr[n_corrs].vars, &corr[n_corrs].n_vars_total,
PV_NUMERIC | PV_APPEND))
{
/* FIXME: No need to iterate the data multiple times */
struct casereader *r = casereader_clone (group);
- if ( opts.missing_type == CORR_LISTWISE)
+ if (opts.missing_type == CORR_LISTWISE)
r = casereader_create_filter_missing (r, all_vars, n_all_vars,
opts.exclude, NULL, NULL);