Remove backported rand func (Superseded)

game/scripts/inventory/game.rpy

@@ -59,7 +59,7 @@ init python:
         @weather.setter
         def weather(self, value):
             if value == "random":
-                value = random_choices(self.weather_types, weights=self.weather_weights)[0]
+                value = renpy.python.random.choices(self.weather_types, weights=self.weather_weights)[0]
 
             if not value in self.weather_types:
                 raise ValueError("Unsupported weather type: '{}'".format(value))

game/scripts/utility/common_functions.rpy

@@ -145,45 +145,6 @@ init -1 python:
         """Mutates the original list."""
         l[val1], l[val2] = l[val2], l[val1]
 
-    def random_choices(population, weights=None, cum_weights=None, k=1):
-        """Backported from python 3.6
-
-        Return a k sized list of population elements chosen with replacement.
-        If the relative weights or cumulative weights are not specified,
-        the selections are made with equal probability.
-        """
-
-        def accumulate(iterable, func=_add, initial=None):
-            it = iter(iterable)
-            total = initial
-            if initial is None:
-                try:
-                    total = next(it)
-                except StopIteration:
-                    return
-            yield total
-            for element in it:
-                total = func(total, element)
-                yield total
-
-        random = renpy.random.random
-        if cum_weights is None:
-            if weights is None:
-                _int = int
-                total = len(population)
-                return [population[_int(random() * total)] for i in range(k)]
-            cum_weights = list(accumulate(weights))
-        elif weights is not None:
-            raise TypeError('Cannot specify both weights and cumulative weights')
-
-        if len(cum_weights) != len(population):
-            raise ValueError('The number of weights does not match the population')
-
-        #bisect = _bisect.bisect
-        total = cum_weights[-1]
-        hi = len(cum_weights) - 1
-        return [population[bisect(cum_weights, random() * total, 0, hi)] for i in range(k)]
-
     def natsort_key(s, pattern=re.compile("([0-9]+)")):
         return [int(t) if t.isdigit() else t.lower() for t in pattern.split(str(s))]