snapshot...

modules/deeplearning/icing_dnn.py

@@ -130,7 +130,7 @@ def build_residual_block(input, drop_rate, num_neurons, activation, block_name,
 class IcingIntensityDNN:
     
     def __init__(self, y_dim_len=IMG_WIDTH, x_dim_len=IMG_WIDTH,
-                 day_night='DAY', l1b_or_l2='both', use_flight_altitude=False, datapath=None):
+                 day_night='DAY', l1b_or_l2='l2', use_flight_altitude=False, datapath=None):
         print('day_night: ', day_night)
         print('l1b_or_l2: ', l1b_or_l2)
         print('use_flight_altitude: ', use_flight_altitude)
@@ -400,8 +400,7 @@ class IcingIntensityDNN:
             else:
                 h5f = self.h5f_l2_trn
             time = h5f['time']
-            # trn_idxs = np.arange(time.shape[0])
-            trn_idxs = np.arange(50000)
+            trn_idxs = np.arange(time.shape[0])
             if seed is not None:
                 np.random.seed(seed)
             np.random.shuffle(trn_idxs)
@@ -411,8 +410,7 @@ class IcingIntensityDNN:
             else:
                 h5f = self.h5f_l2_tst
             time = h5f['time']
-            # tst_idxs = np.arange(time.shape[0])
-            tst_idxs = np.arange(5000)
+            tst_idxs = np.arange(time.shape[0])
             if seed is not None:
                 np.random.seed(seed)
             np.random.shuffle(tst_idxs)
@@ -481,7 +479,7 @@ class IcingIntensityDNN:
             flat = self.input
             n_hidden = self.input.shape[1]
 
-        fac = 2
+        fac = 6
 
         fc = build_residual_block(flat, drop_rate, fac * n_hidden, activation, 'Residual_Block_1', doDropout=True,
                                   doBatchNorm=True)