safeguards main.py

CellularAutomaton.py

@@ -10,12 +10,12 @@
 os.environ['CUDA_HOME']      = r'C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7' #install cuda toolkit from nvidia and put the correct path here (should not really change much tho, except v11.7)
 
 #custom vars
-perc = 30/100 #for custom starting frame 
+perc = 3/100 #for custom starting frame 
 
 #IMG SIZE
 _SHOWSIMULATION = True
-_SIZE = (120, 120) #size of the output image inverse of the resolution you want i.e: 1920x1080 => (1080, 1920)
-_STEPS = 15 #number of steps to simulate
+_SIZE = (1000, 1000) #size of the output image inverse of the resolution you want i.e: 1920x1080 => (1080, 1920)
+_STEPS = 10000 #number of steps to simulate
 _LOOPPAUSETIME = 1 #pause between each calculations (indirectly fps)
 _SKIPONEFRAME = True #renders 2 frames but only show one (epilepsy brrrrr)
 _SKIPTWOFRAME = False #renders 3 frames but only show one (works only if _SKIPONEFRAME = True)(epilepsy brrrrr)
@@ -42,14 +42,14 @@
 
 
 #SIM
-_CUSTOMFRAME = True #whether or not to use the custom function for starting frame
-RandomStartingFrame = True #generates a random image to start
+_CUSTOMFRAME = False #whether or not to use the custom function for starting frame
+RandomStartingFrame = False #generates a random image to start
 RandomIntStartingFrame = True #generates a random image to start with only 1 and 0
 ZerosStartingFrame = False #blank 0 frame
 _LOOP = False
 @cuda.jit
 def ActFunction(x):
-    #return x*x
+    return x*x
     #return -1./pow(2., (0.6*pow(x, 2.)))+1. #worms
     #return -1./(0.9*pow(x, 2.)+1.)+1. #Mitosis
     #return -1./(0.89*pow(x, 2.)+1.)+1. #slime
@@ -63,13 +63,13 @@ def ActFunction(x):
         return 0
     """
 
+"""
     #cave generator
     if x>4:
         return 1
     else:
         return 0
 """
-"""
 #Chose your filter / make a new one
 """
 NCA_Filter = np.array([ [0.1 , -0.1  , 0.3   ],
@@ -121,12 +121,12 @@ def ActFunction(x):
 NCA_Filter = np.array([ [0.565 ,    -0.716  ,   0.565 ],
                         [-0.716   ,  0.627 ,  -0.716 ],
                         [0.565,     -0.716  ,   0.565   ]])
-
+"""
 #Super cool growing spaceships, use x*x activ function
 NCA_Filter = np.array([[-0.8300993,  -0.44785473,  0.979766  ],
                        [-0.47983372,  0.07656833, -0.35514032],
                        [ 0.53823346,  0.43503127,  0.2492277 ]])
-
+"""
 #Conway  game of life
 NCA_Filter = np.array([ [1 ,    1  ,   1  ],
                         [1   ,  9 ,  1 ],
@@ -137,12 +137,12 @@ def ActFunction(x):
                        [ 0.82367216,  0.31695098,  0.82367216],
                        [-0.99038735,  0.82367216, -0.99038735]])
 
-"""
+
 #cave generator
 NCA_Filter = np.array([[1, 1, 1],
                        [1, 0, 1],
                        [1, 1, 1]])
-
+"""
 
 
 
@@ -357,6 +357,6 @@ def NextStep(input, filter, activFunction):
 
 
 
-
+    os.system("pause")
 
 #

main.py

@@ -17,7 +17,6 @@
 
 
 
-#https://317070.github.io/python/
 
 
 
@@ -36,8 +35,13 @@ def MakeFrame(input):
 
 
 
+if __name__ == "__main__":
+    print("Please use CellularAutomaton.py")
 
 
+"""
+#https://317070.github.io/python/
+
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description=__doc__)
     required = parser.add_argument_group('required arguments')
@@ -59,7 +63,7 @@ def MakeFrame(input):
             videostream.send_video_frame(StreamFrame)
 
 
-
+"""