allensdk.brain_observatory.demixer module¶
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allensdk.brain_observatory.demixer.
demix_time_dep_masks
(raw_traces: numpy.ndarray, stack: numpy.ndarray, masks: numpy.ndarray, max_block_size: int = 1000) → Tuple[numpy.ndarray, list][source]¶ Demix traces of potentially overlapping masks extraced from a single 2p recording.
Parameters: - raw_traces – 2d array of traces for each mask, of dimensions (n, t), where t is the number of time points and n is the number of masks.
- stack – 3d array representing a 1p recording movie, of dimensions (t, H, W) or corresponding hdf5 dataset.
- masks – 3d array of binary roi masks, of shape (n, H, W), where n is the number of masks, and HW are the dimensions of an individual frame in the movie stack.
Max_block_size: int representing maximum number of movie frames to read at a time (-1 for full length t of stack) (the default is 1000)
Returns: Tuple of demixed traces and whether each frame was skipped in the demixing calculation.
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allensdk.brain_observatory.demixer.
find_negative_transients_threshold
(trace, window=500, length=10, std_devs=3)[source]¶
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allensdk.brain_observatory.demixer.
plot_negative_baselines
(raw_traces, demix_traces, mask_array, roi_ids_mask, plot_dir, ext='png')[source]¶
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allensdk.brain_observatory.demixer.
plot_negative_transients
(raw_traces, demix_traces, valid_roi, mask_array, roi_ids_mask, plot_dir, ext='png')[source]¶
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allensdk.brain_observatory.demixer.
plot_overlap_masks_lengthOne
(roi_ind, masks, savefile=None, weighted=False)[source]¶
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allensdk.brain_observatory.demixer.
plot_traces
(raw_trace, demix_trace, roi_id, roi_ind, save_file)[source]¶