def setup_catalogue(dirname, dataset_name='olfactory_bulb'):
if os.path.exists(dirname):
shutil.rmtree(dirname)
dataio = DataIO(dirname=dirname)
localdir, filenames, params = download_dataset(name=dataset_name)
dataio.set_data_source(type='RawData', filenames=filenames, **params)
if dataset_name=='olfactory_bulb':
channels = [5, 6, 7, 8, 9]
else:
channels = [0,1,2,3]
dataio.add_one_channel_group(channels=channels)
catalogueconstructor = CatalogueConstructor(dataio=dataio)
params = {
'duration' : 60.,
'preprocessor' : {
'highpass_freq' : 300.,
'chunksize' : 1024,
'lostfront_chunksize' : 100,
},
'peak_detector' : {
'peak_sign' : '-',
'relative_threshold' : 7.,
'peak_span_ms' : 0.5,
},
'extract_waveforms' : {
'wf_left_ms' : -2.5,
'wf_right_ms' : 4.0,
'nb_max' : 10000,
},
'clean_waveforms' : {
'alien_value_threshold' : 60.,
},
'noise_snippet' : {
'nb_snippet' : 300,
},
'feature_method': 'global_pca',
'feature_kargs':{'n_components': 5},
'cluster_method' : 'kmeans',
'cluster_kargs' : {'n_clusters': 12},
'clean_cluster' : False,
'clean_cluster_kargs' : {},
}
apply_all_catalogue_steps(catalogueconstructor, params, verbose=True)
catalogueconstructor.trash_small_cluster()
catalogueconstructor.order_clusters(by='waveforms_rms')
catalogueconstructor.make_catalogue_for_peeler()
