remove MAX_MESSAGE_SAMPLES threshold in auto interpretation

src/urh/ainterpretation/AutoInterpretation.py

@@ -11,9 +11,6 @@
 from urh.cythonext import signal_functions
 from urh.cythonext import util
 
-# Maximum number of samples to consider when summing all samples over all messages during segmentation for performance.
-MAX_MESSAGE_SAMPLES = int(1e6)
-
 
 def max_without_outliers(data: np.ndarray, z=3):
     if len(data) == 0:
@@ -78,15 +75,15 @@ def detect_noise_level(magnitudes):
     return math.ceil(result * 10000) / 10000
 
 
-def segment_messages_from_magnitudes(magnitudes: np.ndarray, noise_threshold: float, max_message_samples=0):
+def segment_messages_from_magnitudes(magnitudes: np.ndarray, noise_threshold: float):
     """
     Get the list of start, end indices of messages
 
     :param magnitudes: Magnitudes of samples
-    :param q: Factor which controls how many samples of previous above noise plateau must be under noise to be counted as noise
+    :param noise_threshold: Threshold for noise
     :return:
     """
-    return c_auto_interpretation.segment_messages_from_magnitudes(magnitudes, noise_threshold, max_message_samples)
+    return c_auto_interpretation.segment_messages_from_magnitudes(magnitudes, noise_threshold)
 
 
 def merge_message_segments_for_ook(segments: list):
@@ -353,9 +350,7 @@ def estimate(signal: np.ndarray, noise: float = None, modulation: str = None) ->
     noise = detect_noise_level(magnitudes) if noise is None else noise
 
     # segment messages
-    message_indices = segment_messages_from_magnitudes(magnitudes,
-                                                       noise_threshold=noise,
-                                                       max_message_samples=MAX_MESSAGE_SAMPLES)
+    message_indices = segment_messages_from_magnitudes(magnitudes, noise_threshold=noise)
 
     # detect modulation
     modulation = detect_modulation_for_messages(signal, message_indices) if modulation is None else modulation

src/urh/cythonext/auto_interpretation.pyx

@@ -46,7 +46,7 @@ cpdef tuple k_means(float[:] data, unsigned int k=2):
     return centers, clusters
 
 
-def segment_messages_from_magnitudes(float[:] magnitudes, float noise_threshold, unsigned long max_message_samples=0):
+def segment_messages_from_magnitudes(float[:] magnitudes, float noise_threshold):
     """
     Get the list of start, end indices of messages
 
@@ -98,9 +98,6 @@ def segment_messages_from_magnitudes(float[:] magnitudes, float noise_threshold,
             start = i - conseq_above
             conseq_below = conseq_above = 0
 
-        if max_message_samples > 0 and summed_message_samples > max_message_samples:
-            return result
-
     # append last message
     if state == 1 and start < N - conseq_below:
         result.append((start, N - conseq_below))