def test_catalogue_constructor():
    if os.path.exists('test_catalogueconstructor'):
        shutil.rmtree('test_catalogueconstructor')
        
    dataio = DataIO(dirname='test_catalogueconstructor')
    localdir, filenames, params = download_dataset(name='olfactory_bulb')
    dataio.set_data_source(type='RawData', filenames=filenames, **params)
    
    channels=range(14)
    dataio.set_manual_channel_group(channels, chan_grp=0)
    
    catalogueconstructor = CatalogueConstructor(dataio=dataio)
    
    for memory_mode in ['ram', 'memmap']:
    #~ for memory_mode in ['memmap']:
    
        print()
        print(memory_mode)
        catalogueconstructor.set_preprocessor_params(chunksize=1024,
                memory_mode=memory_mode,
                
                #signal preprocessor
                highpass_freq=300,
                backward_chunksize=1280,
                #~ backward_chunksize=1024*2,
                
                #peak detector
                peakdetector_engine='numpy',
                peak_sign='-', relative_threshold=7, peak_span=0.0005,
                
                #waveformextractor
                #~ n_left=-20, n_right=30, 
                
                )
        t1 = time.perf_counter()
        catalogueconstructor.estimate_signals_noise(seg_num=0, duration=10.)
        t2 = time.perf_counter()
        print('estimate_signals_noise', t2-t1)
        
        t1 = time.perf_counter()
        for seg_num in range(dataio.nb_segment):
            #~ print('seg_num', seg_num)
            catalogueconstructor.run_signalprocessor_loop_one_segment(seg_num=seg_num, duration=10.)
        t2 = time.perf_counter()
        print('run_signalprocessor_loop', t2-t1)

        t1 = time.perf_counter()
        catalogueconstructor.finalize_signalprocessor_loop()
        t2 = time.perf_counter()
        print('finalize_signalprocessor_loop', t2-t1)
        
        for seg_num in range(dataio.nb_segment):
            mask = catalogueconstructor.all_peaks['segment']==seg_num
            print('seg_num', seg_num, np.sum(mask))
        
        
        t1 = time.perf_counter()
        catalogueconstructor.extract_some_waveforms(n_left=-25, n_right=40, mode='rand', nb_max=5000)
        t2 = time.perf_counter()
        print('extract_some_waveforms rand', t2-t1)
        print(catalogueconstructor.some_waveforms.shape)

        t1 = time.perf_counter()
        catalogueconstructor.find_good_limits()
        t2 = time.perf_counter()
        print('find_good_limits', t2-t1)
        print(catalogueconstructor.some_waveforms.shape)

        t1 = time.perf_counter()
        catalogueconstructor.extract_some_waveforms(n_left=None, n_right=None, mode='rand', nb_max=2000)
        t2 = time.perf_counter()
        print('extract_some_waveforms rand', t2-t1)
        print(catalogueconstructor.some_waveforms.shape)


        #~ break


        
        # PCA
        t1 = time.perf_counter()
        catalogueconstructor.project(method='pca', n_components=7, batch_size=16384)
        t2 = time.perf_counter()
        print('project pca', t2-t1)

        # peak_max
        #~ t1 = time.perf_counter()
        #~ catalogueconstructor.project(method='peak_max')
        #~ t2 = time.perf_counter()
        #~ print('project peak_max', t2-t1)
        #~ print(catalogueconstructor.some_features.shape)

        t1 = time.perf_counter()
        catalogueconstructor.extract_some_waveforms(index=np.arange(1000))
        t2 = time.perf_counter()
        print('extract_some_waveforms others', t2-t1)
        print(catalogueconstructor.some_waveforms.shape)

        
        # cluster
        t1 = time.perf_counter()
        catalogueconstructor.find_clusters(method='kmeans', n_clusters=11)
        t2 = time.perf_counter()
        print('find_clusters', t2-t1)