replaces randsample with a custom-built randSample function and removes range

utilities/misc/randSample.m

@@ -16,23 +16,36 @@
   % weights : vector
   %   a weight vector, where the i'th index of ``weights`` is the 
   %   weight for the i'th member of the population.
+  %
+  % Returns
+  % -------
+  % vector
+  %   The resulting sample of values.
+  %
 
   % if the user is trying to get multiple items from a single-integer array,
   % assume that they want to sample between 1 and n
-  if isscalar(population) && numItems > 1
-    population = 1:population;
+  arguments
+    population (1,:) double {mustBeNonempty}
+    numItems int16 {mustBeNonempty, mustBeInteger, mustBePositive}
+    weights (1,:) double = []
   end
 
-  nargs = nargin;
-
-  if nargs > 3
-    error("Too many arguments.")
+  if isscalar(population) && numItems > 1
+    population = 1:population;
   end
 
-  if nargs == 3
-
+  if isempty(weights)
+    if numItems > length(population)
+      coderException(coderEnums.errorCodes.invalidOption, 'numItems is larger than the number of items in the population.')
+    end
+      % to generate unweighted numbers without replacement, we just randomise
+      % the array and take the first numItems items
+      population = population(randperm(length(population)));
+      outputSample = population(1:numItems);
+  else
     if length(weights) ~= length(population)
-      error("Weights and population must be the same length.")
+      coderException(coderEnums.errorCodes.invalidOption, 'Weights and population must be the same length.')
     end
 
     % we generate weighted random integers by creating bins from our weights
@@ -45,13 +58,5 @@
 
     outputSample = population(randomIndices);
 
-  % we can generate unweighted numbers far more efficiently
-  % just randomise the array and return the first numItems items
-  else
-    if numItems > length(population)
-      error("numItems is larger than the number of items in the population.")
-    end
-      population = population(randperm(length(population)));
-      outputSample = population(1:numItems);
   end
 end