Change how checking for missing values works.

[pspp] / src / math / covariance.c

diff --git a/src/math/covariance.c b/src/math/covariance.c
index 8aa652b5bded81924b6f9317b9353043168a1c5f..79fce25cef28362dbe7b404377d436e92727111c 100644 (file)
--- a/src/math/covariance.c
+++ b/src/math/covariance.c
@@ -72,7 +72,7 @@ struct covariance
 {
   /* True if the covariances are centerered. (ie Real covariances) */
   bool centered;
-  
+
   /* The variables for which the covariance matrix is to be calculated. */
   size_t n_vars;
   const struct variable *const *vars;
@@ -129,7 +129,7 @@ struct covariance
    be identical.  If missing values are involved, then element (i,j)
    is the moment of the i th variable, when paired with the j th variable.
  */
-const gsl_matrix *
+gsl_matrix *
 covariance_moments (const struct covariance *cov, int m)
 {
   return cov->moments[m];
@@ -145,7 +145,7 @@ covariance_1pass_create (size_t n_vars, const struct variable *const *vars,
                         bool centered)
 {
   size_t i;
-  struct covariance *cov = xzalloc (sizeof *cov);
+  struct covariance *cov = XZALLOC (struct covariance);
 
   cov->centered = centered;
   cov->passes = 1;
@@ -165,7 +165,7 @@ covariance_1pass_create (size_t n_vars, const struct variable *const *vars,
 
   cov->exclude = exclude;
 
-  cov->n_cm = (n_vars * (n_vars - 1)  ) / 2;
+  cov->n_cm = (n_vars * (n_vars - 1)) / 2;
 
 
   cov->cm = xcalloc (cov->n_cm, sizeof *cov->cm);
@@ -232,13 +232,13 @@ cm_idx (const struct covariance *cov, int i, int j)
   assert (i >= 0);
   assert (j < cov->dim);
 
-  if ( i == 0)
+  if (i == 0)
     return -1;
 
   if (j >= cov->dim - 1)
     return -1;
 
-  if ( i <= j)
+  if (i <= j)
     return -1 ;
 
   as = nj * (nj + 1) ;
@@ -262,14 +262,14 @@ is_missing (const struct covariance *cov, int i, const struct ccase *c)
 
   const union value *val = case_data (c, var);
 
-  return var_is_value_missing (var, val, cov->exclude);
+  return (var_is_value_missing (var, val) & cov->exclude) != 0;
 }
 
 
 static double
 get_val (const struct covariance *cov, int i, const struct ccase *c)
 {
-  if ( i < cov->n_vars)
+  if (i < cov->n_vars)
     {
       const struct variable *var = cov->vars[i];
 
@@ -301,7 +301,7 @@ void
 covariance_accumulate_pass1 (struct covariance *cov, const struct ccase *c)
 {
   size_t i, j, m;
-  const double weight = cov->wv ? case_data (c, cov->wv)->f : 1.0;
+  const double weight = cov->wv ? case_num (c, cov->wv) : 1.0;
 
   assert (cov->passes == 2);
   if (!cov->pass_one_first_case_seen)
@@ -317,14 +317,14 @@ covariance_accumulate_pass1 (struct covariance *cov, const struct ccase *c)
     {
       double v1 = get_val (cov, i, c);
 
-      if ( is_missing (cov, i, c))
+      if (is_missing (cov, i, c))
        continue;
 
       for (j = 0 ; j < cov->dim; ++j)
        {
          double pwr = 1.0;
 
-         if ( is_missing (cov, j, c))
+         if (is_missing (cov, j, c))
            continue;
 
          for (m = 0 ; m <= MOMENT_MEAN; ++m)
@@ -346,7 +346,7 @@ void
 covariance_accumulate_pass2 (struct covariance *cov, const struct ccase *c)
 {
   size_t i, j;
-  const double weight = cov->wv ? case_data (c, cov->wv)->f : 1.0;
+  const double weight = cov->wv ? case_num (c, cov->wv) : 1.0;
 
   assert (cov->passes == 2);
   assert (cov->state >= 1);
@@ -365,7 +365,7 @@ covariance_accumulate_pass2 (struct covariance *cov, const struct ccase *c)
       if (cov->categoricals)
        cov->dim += categoricals_df_total (cov->categoricals);
 
-      cov->n_cm = (cov->dim * (cov->dim - 1)  ) / 2;
+      cov->n_cm = (cov->dim * (cov->dim - 1)) / 2;
       cov->cm = xcalloc (cov->n_cm, sizeof *cov->cm);
 
       /* Grow the moment matrices so that they're large enough to accommodate the
@@ -419,7 +419,7 @@ covariance_accumulate_pass2 (struct covariance *cov, const struct ccase *c)
     {
       double v1 = get_val (cov, i, c);
 
-      if ( is_missing (cov, i, c))
+      if (is_missing (cov, i, c))
        continue;
 
       for (j = 0 ; j < cov->dim; ++j)
@@ -430,7 +430,7 @@ covariance_accumulate_pass2 (struct covariance *cov, const struct ccase *c)
 
          const double s = pow2 (v1 - gsl_matrix_get (cov->moments[MOMENT_MEAN], i, j)) * weight;
 
-         if ( is_missing (cov, j, c))
+         if (is_missing (cov, j, c))
            continue;
 
          {
@@ -464,13 +464,13 @@ void
 covariance_accumulate (struct covariance *cov, const struct ccase *c)
 {
   size_t i, j, m;
-  const double weight = cov->wv ? case_data (c, cov->wv)->f : 1.0;
+  const double weight = cov->wv ? case_num (c, cov->wv) : 1.0;
 
   assert (cov->passes == 1);
 
-  if ( !cov->pass_one_first_case_seen)
+  if (!cov->pass_one_first_case_seen)
     {
-      assert ( cov->state == 0);
+      assert (cov->state == 0);
       cov->state = 1;
     }
 
@@ -478,7 +478,7 @@ covariance_accumulate (struct covariance *cov, const struct ccase *c)
     {
       const union value *val1 = case_data (c, cov->vars[i]);
 
-      if ( is_missing (cov, i, c))
+      if (is_missing (cov, i, c))
        continue;
 
       for (j = 0 ; j < cov->dim; ++j)
@@ -487,7 +487,7 @@ covariance_accumulate (struct covariance *cov, const struct ccase *c)
          int idx;
          const union value *val2 = case_data (c, cov->vars[j]);
 
-         if ( is_missing (cov, j, c))
+         if (is_missing (cov, j, c))
            continue;
 
          idx = cm_idx (cov, i, j);
@@ -521,7 +521,7 @@ cm_to_gsl (struct covariance *cov)
   gsl_matrix *m = gsl_matrix_calloc (cov->dim, cov->dim);
 
   /* Copy the non-diagonal elements from cov->cm */
-  for ( j = 0 ; j < cov->dim - 1; ++j)
+  for (j = 0 ; j < cov->dim - 1; ++j)
     {
       for (i = j+1 ; i < cov->dim; ++i)
        {
@@ -555,7 +555,7 @@ covariance_calculate_double_pass (struct covariance *cov)
          *x /= gsl_matrix_get (cov->moments[MOMENT_NONE], i, j);
 
          idx = cm_idx (cov, i, j);
-         if ( idx >= 0)
+         if (idx >= 0)
            {
              x = &cov->cm [idx];
              *x /= gsl_matrix_get (cov->moments[MOMENT_NONE], i, j);
@@ -575,7 +575,7 @@ covariance_calculate_single_pass (struct covariance *cov)
   for (m = 0; m < n_MOMENTS; ++m)
     {
       /* Divide the moments by the number of samples */
-      if ( m > 0)
+      if (m > 0)
        {
          for (i = 0 ; i < cov->dim; ++i)
            {
@@ -584,7 +584,7 @@ covariance_calculate_single_pass (struct covariance *cov)
                  double *x = gsl_matrix_ptr (cov->moments[m], i, j);
                  *x /= gsl_matrix_get (cov->moments[0], i, j);
 
-                 if ( m == MOMENT_VARIANCE)
+                 if (m == MOMENT_VARIANCE)
                    *x -= pow2 (gsl_matrix_get (cov->moments[1], i, j));
                }
            }
@@ -594,7 +594,7 @@ covariance_calculate_single_pass (struct covariance *cov)
   if (cov->centered)
     {
       /* Centre the moments */
-      for ( j = 0 ; j < cov->dim - 1; ++j)
+      for (j = 0 ; j < cov->dim - 1; ++j)
        {
          for (i = j + 1 ; i < cov->dim; ++i)
            {
@@ -622,7 +622,7 @@ covariance_calculate_single_pass (struct covariance *cov)
 gsl_matrix *
 covariance_calculate (struct covariance *cov)
 {
-  if ( cov->state <= 0 )
+  if (cov->state <= 0)
     return NULL;
 
   switch (cov->passes)
@@ -664,7 +664,7 @@ covariance_calculate_single_pass_unnormalized (struct covariance *cov)
            }
        }
 
-      for ( j = 0 ; j < cov->dim - 1; ++j)
+      for (j = 0 ; j < cov->dim - 1; ++j)
        {
          for (i = j + 1 ; i < cov->dim; ++i)
            {
@@ -678,7 +678,7 @@ covariance_calculate_single_pass_unnormalized (struct covariance *cov)
            }
        }
     }
-  
+
   return cm_to_gsl (cov);
 }
 
@@ -690,7 +690,7 @@ covariance_calculate_single_pass_unnormalized (struct covariance *cov)
 const gsl_matrix *
 covariance_calculate_unnormalized (struct covariance *cov)
 {
-  if ( cov->state <= 0 )
+  if (cov->state <= 0)
     return NULL;
 
   if (cov->unnormalised != NULL)