Updated docstring.

Author: zafarrafii

repet.py

@@ -1,16 +1,5 @@
 """
 This Python module implements a number of functions for the REpeating Pattern Extraction Technique (REPET).
-    Repetition is a fundamental element in generating and perceiving structure. In audio, mixtures are 
-    often composed of structures where a repeating background signal is superimposed with a varying 
-    foreground signal (e.g., a singer overlaying varying vocals on a repeating accompaniment or a varying 
-    speech signal mixed up with a repeating background noise). On this basis, we present the REpeating 
-    Pattern Extraction Technique (REPET), a simple approach for separating the repeating background from 
-    the non-repeating foreground in an audio mixture. The basic idea is to find the repeating elements in 
-    the mixture, derive the underlying repeating models, and extract the repeating background by comparing 
-    the models to the mixture. Unlike other separation approaches, REPET does not depend on special 
-    parameterizations, does not rely on complex frameworks, and does not require external information. 
-    Because it is only based on repetition, it has the advantage of being simple, fast, blind, and 
-    therefore completely and easily automatable.
 
 Functions:
     original - Compute the original REPET.
@@ -30,7 +19,7 @@
     http://zafarrafii.com
     https://github.com/zafarrafii
     https://www.linkedin.com/in/zafarrafii/
-    01/20/21
+    01/21/21
 """
 
 import numpy as np
@@ -67,8 +56,6 @@
 def original(audio_signal, sampling_frequency):
     """
     Compute the original REPET.
-        The original REPET aims at identifying and extracting the repeating patterns in an audio mixture, by estimating
-        a period of the underlying repeating structure and modeling a segment of the periodically repeating background.
 
     Inputs:
         audio_signal: audio signal (number_samples, number_channels)
@@ -207,8 +194,6 @@ def original(audio_signal, sampling_frequency):
 def extended(audio_signal, sampling_frequency):
     """
     Compute REPET extended.
-        The original REPET can be easily extended to handle varying repeating structures, by simply applying the method
-        along time, on individual segments or via a sliding window.
 
     Inputs:
         audio_signal: audio signal (number_samples, number_channels)
@@ -426,11 +411,6 @@ def extended(audio_signal, sampling_frequency):
 def adaptive(audio_signal, sampling_frequency):
     """
     Compute the adaptive REPET.
-        The original REPET works well when the repeating background is relatively stable (e.g., a verse or the chorus in
-        a song); however, the repeating background can also vary over time (e.g., a verse followed by the chorus in the
-        song). The adaptive REPET is an extension of the original REPET that can handle varying repeating structures, by
-        estimating the time-varying repeating periods and extracting the repeating background locally, without the need
-        for segmentation or windowing.
 
     Inputs:
         audio_signal: audio signal (number_samples, number_channels)
@@ -577,10 +557,6 @@ def adaptive(audio_signal, sampling_frequency):
 def sim(audio_signal, sampling_frequency):
     """
     Compute REPET-SIM.
-        The REPET methods work well when the repeating background has periodically repeating patterns (e.g., jackhammer
-        noise); however, the repeating patterns can also happen intermittently or without a global or local periodicity
-        (e.g., frogs by a pond). REPET-SIM is a generalization of REPET that can also handle non-periodically repeating
-        structures, by using a similarity matrix to identify the repeating elements.
 
     Inputs:
         audio_signal: audio signal (number_samples, number_channels)
@@ -720,9 +696,6 @@ def sim(audio_signal, sampling_frequency):
 def simonline(audio_signal, sampling_frequency):
     """
     Compute the online REPET-SIM.
-        REPET-SIM can be easily implemented online to handle real-time computing, particularly for real-time speech
-        enhancement. The online REPET-SIM simply processes the time frames of the mixture one after the other given a
-        buffer that temporally stores past frames.
 
      Inputs:
         audio_signal: audio signal (number_samples, number_channels)