Corrected Moran library model and function input consistency test

There was a confusion in the library model between the weight matrix and
the gaml grid.
The error in the consistency test was due to being tested on the library
model.
Also added a neighbours spatial weight case. Fairly common with Moran
index and easy to test.

msi.gama.core/src/msi/gaml/operators/Spatial.java

@@ -7261,7 +7261,7 @@ public static double moranIndex(final IScope scope, final IList<Double> vals, fi
 			if (weightMatrix == null || weightMatrix.numCols != weightMatrix.numRows) throw GamaRuntimeException
 					.error("A squared weight matrix should be given for the moran index computation", scope);
 			final int N = vals.size();
-			if (N != weightMatrix.numRows * weightMatrix.numCols) throw GamaRuntimeException
+			if (N != weightMatrix.numRows) throw GamaRuntimeException
 					.error("The lengths of the value list and of the weight matrix do not match", scope);
 			double I = 0.0;
 			double sumWeights = 0.0;

msi.gama.models/models/Modeling/Spatial Topology/Spatial Operators/models/Moran Index.gaml

@@ -9,7 +9,7 @@ model moranIndex
 
 global {
 	string grid_spatial_init <- "random" among: ["random", "checkerboard", "blocks"];
-	string weight_type <- "overlapping" among: ["overlapping", "distance"];
+	string weight_type <- "neighbors" among: ["overlapping", "neighbors", "distance"];
 	int grid_size <- 20;
 
 	list<float> vals;
@@ -27,30 +27,34 @@ global {
 		}
 		vals <- cell collect (each.color = #white ? 0.0 : 1.0);
 		weights <- 0.0 as_matrix {grid_size, grid_size};
-		loop i from: 0 to: grid_size -1 {
-			loop j from: 0 to:grid_size -1 {
-				if (i = j) {weights[i,j] <- 0.0;}
-				else {
-					switch weight_type {
-						match "overlapping" {
-							weights[i,j] <- (cell[i] overlaps cell[j]) ? 1.0 : 0.0;
+		ask cell {
+			switch weight_type {
+				match "neighbors" {
+					ask self.neighbors {
+						weights[int(self), int(myself)] <- 1.0;
+					}
+				}
+				match "overlapping" {
+					ask cell overlapping self {
+						if self != myself {
+							weights[int(self), int(myself)] <- 1.0;
 						}
-						match "distance" {
-							using topology(cell) {
-								weights[i,j] <- 1/(cell[i] distance_to cell[j]);
-							}
+					}
+				}
+				match "distance" {
+					ask cell {
+						if self != myself {
+							weights[int(self), int(myself)] <- 1/(self distance_to myself);
 						}
-
 					}
-
-				}	
+				}
 			}
 		}
 		I <- moran(vals, weights);
 		write "moran I: " + I;
 	}
 }
-grid cell width: grid_size height: grid_size neighbors: 8;
+grid cell width: grid_size height: grid_size neighbors: 4;
 
 experiment "Moran" type: gui {
 	parameter "grid size: " var: grid_size min: 2 max: 100;