diff --git a/priorConditionedAnnealing/noise.py b/priorConditionedAnnealing/noise.py
index 03a01c3..95e266a 100644
--- a/priorConditionedAnnealing/noise.py
+++ b/priorConditionedAnnealing/noise.py
@@ -103,15 +103,15 @@ class Perlin_Noise():
         self.octave = octave
         self.magic = 3.141592653589  # Axis offset, should be (kinda) irrational
         # We want to genrate samples, that approx ~N(0,1)
-        self.normal_factor = 14/99
-        self.clear_cache_every = 1024
+        self.normal_factor = 14.99
+        self.clear_cache_every = 128
         self.reset()
 
     def __call__(self, shape=None):
         if shape == None:
             shape = self.known_shape
         self.index += 1
-        noise = [self.noise([self.index*self.scale, self.magic*a]) / self.normal_factor
+        noise = [self.noise([self.index*self.scale, self.magic*(1+a)]) / self.normal_factor
                  for a in range(shape[-1])]
         if self.index % self.clear_cache_every == 0:
             self.noise.cache = {}