def tdc_helper(*, tmpdir, params, recording):
import tridesclous as tdc
# nb_chan = recording.get_num_channels()
# check params and OpenCL when many channels
use_sparse_template = False
use_opencl_with_sparse = False
# if nb_chan > 64: # this limit depend on the platform of course
# if tdc.cltools.HAVE_PYOPENCL:
# # force opencl
# self.params['fullchain_kargs']['preprocessor']['signalpreprocessor_engine'] = 'opencl'
# use_sparse_template = True
# use_opencl_with_sparse = True
# else:
# print('OpenCL is not available processing will be slow, try install it')
tdc_dataio = tdc.DataIO(dirname=str(tmpdir))
# make catalogue
chan_grps = list(tdc_dataio.channel_groups.keys())
for chan_grp in chan_grps:
cc = tdc.CatalogueConstructor(dataio=tdc_dataio, chan_grp=chan_grp)
tdc.apply_all_catalogue_steps(cc, verbose=True, **params)
cc.make_catalogue_for_peeler()
# apply Peeler (template matching)
initial_catalogue = tdc_dataio.load_catalogue(chan_grp=chan_grp)
peeler = tdc.Peeler(tdc_dataio)
peeler.change_params(
catalogue=initial_catalogue,
use_sparse_template=use_sparse_template,
sparse_threshold_mad=1.5,
use_opencl_with_sparse=use_opencl_with_sparse,
)
peeler.run(duration=None, progressbar=False)
sorting = se.TridesclousSortingExtractor(tmpdir)
return sorting
def get_result_from_folder(output_folder):
sorting = se.TridesclousSortingExtractor(output_folder)
return sorting