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Commit 31064ac5 authored by tomrink's avatar tomrink
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modules/deeplearning/cnn_cld_frac.py
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...@@ -219,7 +219,7 @@ class CNN: ...@@ -219,7 +219,7 @@ class CNN:
self.test_data_nda = None self.test_data_nda = None
self.test_label_nda = None self.test_label_nda = None
self.n_chans = len(data_params) + 2 self.n_chans = len(data_params) + 1
self.X_img = tf.keras.Input(shape=(None, None, self.n_chans)) self.X_img = tf.keras.Input(shape=(None, None, self.n_chans))
# self.X_img = tf.keras.Input(shape=(36, 36, self.n_chans)) # self.X_img = tf.keras.Input(shape=(36, 36, self.n_chans))
...@@ -269,7 +269,7 @@ class CNN: ...@@ -269,7 +269,7 @@ class CNN:
tmp = input_data[:, label_idx, slc_y_2, slc_x_2] tmp = input_data[:, label_idx, slc_y_2, slc_x_2]
tmp = tmp[:, slc_y, slc_x] tmp = tmp[:, slc_y, slc_x]
tmp = np.where(np.isnan(tmp), 0, tmp) # shouldn't need this tmp = np.where(np.isnan(tmp), 0, tmp) # shouldn't need this
data_norm.append(tmp) ##data_norm.append(tmp)
# --------- # ---------
data = np.stack(data_norm, axis=3) data = np.stack(data_norm, axis=3)
data = data.astype(np.float32) data = data.astype(np.float32)
......
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