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36 lines
1.2 KiB
Python
36 lines
1.2 KiB
Python
import numpy as np
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from ria_toolkit_oss.data import Recording
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def qualify_slice_from_annotations(recording: Recording, slice_length: int):
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"""
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Slice a recording into many smaller recordings,
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discarding any slices which do not have annotations that apply to those samples.
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Used together with an annotation based qualifier.
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:param recording: The recording to slice.
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:type recording: Recording
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:param slice_length: The length in samples of a slice.
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:type slice_length: int"""
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if len(recording.annotations) == 0:
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print("Warning, no annotations.")
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annotation_mask = np.zeros(len(recording.data[0]))
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for annotation in recording.annotations:
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annotation_mask[annotation.sample_start : annotation.sample_start + annotation.sample_count] = 1
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output_recordings = []
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for i in range((len(recording.data[0]) // slice_length) - 1):
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start_index = slice_length * i
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end_index = slice_length * (i + 1)
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if 1 in annotation_mask[start_index:end_index]:
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sl = recording.data[:, start_index:end_index]
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output_recordings.append(Recording(data=sl, metadata=recording.metadata))
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return output_recordings
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