gui.py 文件源码

def finalize(self, event):


        if comm.rank == 0:
            self.app.setOverrideCursor(QCursor(Qt.WaitCursor))
            self.mpi_wait = comm.bcast(numpy.array([1], dtype=numpy.int32), root=0)

        comm.Barrier()
        self.all_merges = comm.bcast(self.all_merges, root=0)
        self.to_delete  = comm.bcast(self.to_delete, root=0)

        slice_templates(self.params, to_merge=self.all_merges, to_remove=list(self.to_delete), extension=self.ext_out)
        slice_clusters(self.params, self.clusters, to_merge=self.all_merges, to_remove=list(self.to_delete), extension=self.ext_out, light=True)

        if comm.rank == 0:
            new_result = {'spiketimes' : {}, 'amplitudes' : {}}

            to_keep = set(numpy.unique(self.indices)) - set(self.to_delete)
            to_keep = numpy.array(list(to_keep))

            for count, temp_id in enumerate(to_keep):
                key_before = 'temp_' + str(temp_id)
                key_after  = 'temp_' + str(count)
                new_result['spiketimes'][key_after] = self.result['spiketimes'].pop(key_before)
                new_result['amplitudes'][key_after] = self.result['amplitudes'].pop(key_before)

            keys = ['spiketimes', 'amplitudes']

            if self.params.getboolean('fitting', 'collect_all'):
                keys += ['gspikes']
                new_result['gspikes'] = io.get_garbage(self.params)['gspikes']

            mydata = h5py.File(self.file_out_suff + '.result%s.hdf5' %self.ext_out, 'w', libver='latest')
            for key in keys:
                mydata.create_group(key)
                for temp in new_result[key].keys():
                    tmp_path = '%s/%s' %(key, temp)
                    mydata.create_dataset(tmp_path, data=new_result[key][temp])
            mydata.close()

            mydata  = h5py.File(self.file_out_suff + '.templates%s.hdf5' %self.ext_out, 'r+', libver='latest')
            version     = mydata.create_dataset('version', data=numpy.array([circus.__version__.encode('ascii', 'ignore')]))
            maxoverlaps = mydata.create_dataset('maxoverlap', shape=(len(to_keep), len(to_keep)), dtype=numpy.float32)
            maxlag      = mydata.create_dataset('maxlag', shape=(len(to_keep), len(to_keep)), dtype=numpy.int32)
            for c, i in enumerate(to_keep):
                maxoverlaps[c, :] = self.overlap[i, to_keep]*self.shape[0] * self.shape[1]
                maxlag[c, :]      = self.lag[i, to_keep]
            mydata.close()

            self.app.restoreOverrideCursor()

        sys.exit(0)