compatibility fixes

.gitignore

 *.pyc
+*.txt
+*.png

ShowerGAN_signal.py

@@ -14,6 +14,7 @@ import tensorflow as tf
 
 
 KTF.set_session(utils.get_session())  # Allows 2 jobs per GPU, Please do not change this during the tutorial
+log_dir="."
 
 EPOCHS = 10
 GRADIENT_PENALTY_WEIGHT = 10
@@ -21,13 +22,12 @@ BATCH_SIZE = 256
 NCR = 5
 latent_size = 512
 # load trainings data
-Folder = '/home/JGlombitza/DataLink/ToyMC/PreProData' # Training no black tanks
-filenames=glob.glob(Folder + "/PlanarWaveShower_PrePro_2*")
 
-shower_maps, Energy, shower_axis = utils.ReadInData(filenames)
-shower_maps=shower_maps[:,:,:,0]
-np.savez("Data", Energy=Energy, shower_maps=shower_maps)
-shower_maps = shower_maps[:,:,:,1,np.newaxis]
+filenames=glob.glob("*.npz")
+
+shower_maps, Energy = utils.ReadInData(filenames)
+#shower_maps = shower_maps[:,:,:,1,np.newaxis]
+#np.savez("Data", Energy=Energy, shower_maps=shower_maps)
 Energy = Energy/np.max(Energy)
 utils.plot_multiple_signalmaps(shower_maps[:,:,:,0], log_dir=log_dir, title='Footprints', epoch='Real')
 

utils.py

@@ -15,21 +15,15 @@ def get_session(gpu_fraction=0.40):
 
 
 def ReadInData(filenames):
-    N = 10000 *len(filenames)
-    a = 10000 # packagesize
-    Input2 = np.zeros(N*9*9*2).reshape(N,9,9,2)
+    N = 100000 *len(filenames)
+    a = 100000
+    shower_maps = np.zeros(N*9*9*1).reshape(N,9,9,1)
     Energy = np.zeros(N)
-    showeraxis = np.zeros(N*3).reshape(N,3)
-    
     for i in range(0, len(filenames)):
         data = np.load(filenames[i])
         Energy[a*i:a*(i+1)] = data['Energy']
-        Input2[a*i:a*(i+1)] = data['Input2'].reshape(a,9,9,2)
-        showeraxis[a*i:a*(i+1)] = data['showeraxis']
-    Input2[:,:,:,0] = Input2[:,:,:,0] - np.min(Input2[:,:,:,0], axis=(1,2))[:,np.newaxis,np.newaxis] + 1
-    Filter = Input2[:,:,:,1] == 0
-    Input2[:,:,:,0][Filter] = 0
-    return Input2, Energy, showeraxis
+        shower_maps[a*i:a*(i+1)] = data['shower_maps'].reshape(a,9,9,1)
+    return shower_maps, Energy
 
 
 def ang2vec(phi, zenith):