updated test.py with new functions
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								code/test.py
									
									
									
									
									
								
							@ -100,14 +100,41 @@ def AM(EODf, stimulus):
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    return AM, nyquist
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					    return AM, nyquist
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def remove_poor(files):
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					def remove_poor(files):
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    good_files =files
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					    """
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    print('x')
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					    Removes poor datasets from the set of files for analysis
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					    Parameters
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					    ----------
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					    files : list 
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					        list of files.
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					    Returns
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					    -------
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					    good_files : list
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					        list of files without the ones with the label poor.
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					    """
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					    # create list for good files
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					    good_files = []
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					    # loop over files
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					    for i in range(len(files)):
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					        # print(files[i])
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					        # load the file (takes some time)
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					        data = rlx.Dataset(files[i])
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					        # get the quality
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					        quality = str.lower(data.metadata["Recording"]["Recording quality"][0][0])
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					        # check the quality
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					        if quality != "poor":
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					            # if its good or fair add it to the good files
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					            good_files.append(files[i])
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    return good_files
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					    return good_files
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#find example data
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					#find example data
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datafolder = "../../data"
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					datafolder = "../../data"
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example_file = datafolder + "/" + "2024-10-16-ad-invivo-1.nix"
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					example_file = datafolder + "/" + "2024-10-16-ah-invivo-1.nix"
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					data_files = glob.glob("../../data/*.nix")
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#load dataset
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					#load dataset
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dataset = rlx.Dataset(example_file)
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					dataset = rlx.Dataset(example_file)
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