snapshot...

modules/deeplearning/icing_fcn.py

@@ -413,26 +413,6 @@ class IcingIntensityFCN:
     def get_in_mem_data_batch_test(self, idxs):
         return self.get_in_mem_data_batch(idxs, False)
 
-    # For full image processing, not quite there yet :(
-    # def get_in_mem_data_batch_eval(self, idxs):
-    #     data = []
-    #     for param in self.train_params:
-    #         nda = self.data_dct[param]
-    #         nda = normalize(nda, param, mean_std_dct)
-    #         data.append(nda)
-    #     data = np.stack(data)
-    #     data = data.astype(np.float32)
-    #     data = np.transpose(data, axes=(1, 2, 0))
-    #     data = np.expand_dims(data, axis=0)
-    #
-    #     nda = np.zeros([1])
-    #     nda[0] = self.flight_level
-    #     nda = tf.one_hot(nda, 5).numpy()
-    #     nda = np.expand_dims(nda, axis=0)
-    #     nda = np.expand_dims(nda, axis=0)
-    #
-    #     return data, nda
-
     def get_in_mem_data_batch_eval(self, idxs):
         # sort these to use as numpy indexing arrays
         nd_idxs = np.array(idxs)