Updated docstring and decreased step size

nns/Cnn_test.py

@@ -127,16 +127,16 @@ class NeuralNetwork(object):
 
     def predict(self, x, clean_signal=True, return_probs=False):
         """Given sequences input as x, predict if they contain target k-mer.
-        Assumes that read is already split up into smaller batches.
+        Assumes the sequence x is a read that has been normalised,
+        but not cut into smaller chunks
 
         :param x: Squiggle as numeric representation
         :type x: np.ndarray
-        :param clean_signal:
         :param return_probs:
         :return: unnormalized predicted values
         :rtype: np.array of posteriors
         """
-        offset = self.filter_width // 4
+        offset = self.filter_width // 5
         ho = offset // 2
         lb, rb = self.hfw - ho, self.hfw + ho + 1
         idx = np.arange(self.filter_width, len(x) + offset, offset)
@@ -147,7 +147,6 @@ class NeuralNetwork(object):
                                              truncating='post',
                                              dtype='float32'), -1)
 
-        # Put predicted class = 1 where posterior is larger than threshold
         posteriors = self.model.predict(x_pad)
         y_hat = posteriors > self.threshold
         y_out = np.zeros(len(x), dtype=int)