diff --git a/priorConditionedAnnealing/noise.py b/priorConditionedAnnealing/noise.py
index 224dbd2..230711d 100644
--- a/priorConditionedAnnealing/noise.py
+++ b/priorConditionedAnnealing/noise.py
@@ -93,14 +93,14 @@ class Perlin_Noise():
         self.known_shape = known_shape
         self.scale = scale
         self.octaves = octaves
-        self.magic = 0.141592653589  # Axis offset, should be (kinda) irrational
+        self.magic = 3.141592653589  # Axis offset, should be (kinda) irrational
         # We want to genrate samples, that approx ~N(0,1)
         self.normal_factor = 0.0471
         self.reset()
 
     def __call__(self, shape):
         self.index += 1
-        noise = [self.noise([self.index*self.scale, self.magic*(a+1)]) / self.normal_factor
+        noise = [self.noise([self.index*self.scale, self.magic*a]) / self.normal_factor
                  for a in range(self.known_shape[-1])]
         return th.Tensor(noise)