allensdk.brain_observatory.behavior.session_apis.data_transforms.behavior_ophys_data_transforms module¶
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class
allensdk.brain_observatory.behavior.session_apis.data_transforms.behavior_ophys_data_transforms.
BehaviorOphysDataTransforms
(extractor: allensdk.brain_observatory.behavior.session_apis.abcs.data_extractor_base.behavior_ophys_data_extractor_base.BehaviorOphysDataExtractorBase, skip_eye_tracking: bool)[source]¶ Bases:
allensdk.brain_observatory.behavior.session_apis.data_transforms.behavior_data_transforms.BehaviorDataTransforms
,allensdk.brain_observatory.behavior.session_apis.abcs.session_base.behavior_ophys_base.BehaviorOphysBase
This class provides methods that transform data extracted from LIMS or JSON data sources into final data products necessary for populating a BehaviorOphysExperiment
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get_average_projection
(self, image_api=None)[source]¶ Get an image whose values are the average obtained values at each pixel of the ophys movie over time.
Returns: - allensdk.brain_observatory.behavior.image_api.Image:
Array-like interface to avg projection image data and metadata.
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get_cell_specimen_table
(self)[source]¶ Get a cell specimen dataframe containing ROI information about cells identified in an ophys experiment.
Returns: - pd.DataFrame
Cell ROI information organized into a dataframe. Index is the cell ROI IDs.
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get_corrected_fluorescence_traces
(self)[source]¶ Get motion-corrected fluorescence traces.
Returns: - pd.DataFrame
Motion-corrected fluorescence traces organized into a dataframe. Index is the cell ROI IDs.
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get_dff_traces
(self)[source]¶ Get a table of delta fluorescence over fluorescence traces.
Returns: - pd.DataFrame
The traces of dff (normalized fluorescence) organized into a dataframe. Index is the cell ROI IDs.
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get_events
(self, filter_scale: float = 2, filter_n_time_steps: int = 20) → pandas.core.frame.DataFrame[source]¶ Returns events in dataframe format
Parameters: - filter_scale: float
See filter_events_array for description
- filter_n_time_steps: int
See filter_events_array for description
- See behavior_ophys_experiment.events for return type
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get_eye_tracking
(self, z_threshold: float = 3.0, dilation_frames: int = 2) → Union[pandas.core.frame.DataFrame, NoneType][source]¶ Gets corneal, eye, and pupil ellipse fit data
Parameters: - z_threshold : float, optional
The z-threshold when determining which frames likely contain outliers for eye or pupil areas. Influences which frames are considered ‘likely blinks’. By default 3.0
- dilation_frames : int, optional
Determines the number of additional adjacent frames to mark as
‘likely_blink’, by default 2.
Returns:
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get_eye_tracking_rig_geometry
(self) → Union[dict, NoneType][source]¶ Get eye tracking rig metadata from behavior + ophys session.
Returns: - dict
Includes geometry of monitor, camera, LED
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get_max_projection
(self, image_api=None)[source]¶ Get an image whose values are the maximum obtained values at each pixel of the ophys movie over time.
Returns: - allensdk.brain_observatory.behavior.image_api.Image:
Array-like interface to max projection image data and metadata.
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get_metadata
(self) → allensdk.brain_observatory.behavior.metadata.behavior_ophys_metadata.BehaviorOphysMetadata[source]¶ Return metadata about the session. :rtype: BehaviorOphysMetadata
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get_motion_correction
(self)[source]¶ Get motion correction trace data.
Returns: - pd.DataFrame
A dataframe containing trace data used during motion correction computation.
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get_ophys_experiment_id
(self)[source]¶ Returns the ophys_experiment_id for the instantiated BehaviorOphys Session (or BehaviorOphys data fetcher) if applicable.
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get_ophys_session_id
(self)[source]¶ Returns the behavior + ophys_session_id associated with this experiment, if applicable.
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get_ophys_timestamps
(self)[source]¶ Get optical physiology frame timestamps.
Returns: - np.ndarray
Timestamps associated with frames captured by the microscope.
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get_rewards
(self)[source]¶ Get reward data from pkl file, based on pkl file timestamps (not sync file).
Returns: pd.DataFrame – A dataframe containing timestamps of delivered rewards.
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get_roi_masks_by_cell_roi_id
(self, cell_roi_ids: Union[int, Iterable[int], NoneType] = None)[source]¶ Obtains boolean masks indicating the location of one or more ROIs in this session.
Parameters: - cell_roi_ids : array-like of int, optional
ROI masks for these rois will be returned. The default behavior is to return masks for all rois.
Returns: - result : xr.DataArray
- dimensions are:
- roi_id : which roi is described by this mask?
- row : index within the underlying image
- column : index within the image
values are 1 where an ROI was present, otherwise 0.
Notes
This method helps Allen Institute scientists to look at sessions that have not yet had cell specimen ids assigned. You probably want to use get_roi_masks instead.
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