cluster.patch

--- original/cluster-1.50/src/cluster.c
+++ patch/cluster-1.50/src/cluster.c
@@ -1470,6 +1470,81 @@
 /* *********************************************************************  */
 
 static
+double inner_product(int n, double** data1, double** data2, int** mask1,
+  int** mask2, const double weight[], int index1, int index2, int transpose)
+/*
+Purpose
+=======
+
+The inner_product routine calculates the inner product distance between two rows or
+columns. The inner_product distance is defined as zero minus the inner product. 
+
+Arguments
+=========
+
+n      (input) int
+The number of elements in a row or column. If transpose==0, then n is the number
+of columns; otherwise, n is the number of rows.
+
+data1  (input) double array
+The data array containing the first vector.
+
+data2  (input) double array
+The data array containing the second vector.
+
+mask1  (input) int array
+This array which elements in data1 are missing. If mask1[i][j]==0, then
+data1[i][j] is missing.
+
+mask2  (input) int array
+This array which elements in data2 are missing. If mask2[i][j]==0, then
+data2[i][j] is missing.
+
+weight (input) double[n]
+These weights are ignored, but included for consistency with other distance
+measures.
+
+index1     (input) int
+Index of the first row or column.
+
+index2     (input) int
+Index of the second row or column.
+
+transpose (input) int
+If transpose==0, the distance between two rows in the matrix is calculated.
+Otherwise, the distance between two columns in the matrix is calculated.
+============================================================================
+*/
+{ int i;
+  double result = 0.;
+
+  if (transpose==0)
+  { for (i = 0; i < n; i++)
+    { if (mask1[index1][i] && mask2[index2][i])
+      { 
+        result += data1[index1][i] * data2[index2][i];
+      }
+    }
+  }
+  else
+  { for (i = 0; i < n; i++)
+    { if (mask1[i][index1] && mask2[i][index2])
+      { 
+        result += data1[i][index1] * data2[i][index2];
+      }
+    }
+  }
+  
+  if ( result > 1000 )
+  {
+    fprintf("%s", "Warning, inner_product < 1000 assumption violated. May product nonsense correlations\n");
+	}
+  result = 0. - result/1000;
+  return result;
+}
+/* *********************************************************************  */
+
+static
 double spearman (int n, double** data1, double** data2, int** mask1,
   int** mask2, const double weight[], int index1, int index2, int transpose)
 /*
@@ -1719,6 +1794,7 @@
     case 'x': return &uacorrelation;
     case 's': return &spearman;
     case 'k': return &kendall;
+    case 'i': return &inner_product;
     default: return &euclid;
   }
   return NULL; /* Never get here */