Source code for libertem.udf.sum

import numpy as np

from libertem.udf import UDF

[docs] class SumUDF(UDF): """ Sum up frames, preserving the signal dimension Parameters ---------- dtype : numpy.dtype, optional Preferred dtype for computation, default 'float32'. The actual dtype will be determined from this value and the dataset's dtype using :meth:`numpy.result_type`. See also :ref:`udf dtype`. Examples -------- >>> udf = SumUDF() >>> result = ctx.run_udf(dataset=dataset, udf=udf) >>> np.array(result["intensity"]).shape (32, 32) """ def __init__(self, dtype='float32'): super().__init__(dtype=dtype) def get_preferred_input_dtype(self): '' return self.params.dtype def get_backends(self): '' return self.BACKEND_ALL def get_result_buffers(self): '' return { 'intensity': self.buffer( kind='sig', dtype=self.meta.input_dtype, where='device' ) } def process_tile(self, tile): '' self.results.intensity[:] += self.forbuf( np.sum(tile, axis=0), self.results.intensity ) def merge(self, dest, src): '' dest.intensity[:] += src.intensity def merge_all(self, ordered_results): '' intensity_chunks = [b.intensity for b in ordered_results.values()] intensity_sum = np.stack(intensity_chunks, axis=0).sum(axis=0) return {'intensity': intensity_sum}