allensdk.core.brain_observatory_nwb_data_set module

class allensdk.core.brain_observatory_nwb_data_set.BrainObservatoryNwbDataSet(nwb_file)

Bases: object

FILE_METADATA_MAPPING = {'age': 'general/subject/age', 'device_string': 'general/devices/2-photon microscope', 'excitation_lambda': 'general/optophysiology/imaging_plane_1/excitation_lambda', 'experiment_container_id': 'general/experiment_container_id', 'fov': 'general/fov', 'generated_by': 'general/generated_by', 'genotype': 'general/subject/genotype', 'imaging_depth': 'general/optophysiology/imaging_plane_1/imaging depth', 'indicator': 'general/optophysiology/imaging_plane_1/indicator', 'ophys_experiment_id': 'general/session_id', 'session_start_time': 'session_start_time', 'session_type': 'general/session_type', 'sex': 'general/subject/sex', 'specimen_name': 'general/specimen_name', 'targeted_structure': 'general/optophysiology/imaging_plane_1/location'}

MOTION_CORRECTION_DATASETS = ['MotionCorrection/2p_image_series/xy_translations', 'MotionCorrection/2p_image_series/xy_translation']

PIPELINE_DATASET = 'brain_observatory_pipeline'

STIMULUS_TABLE_TYPES = {'abstract_feature_series': ['drifting_gratings', 'static_gratings'], 'indexed_time_series': ['natural_scenes', 'locally_sparse_noise', 'locally_sparse_noise_4deg', 'locally_sparse_noise_8deg'], 'repeated_indexed_time_series': ['natural_movie_one', 'natural_movie_two', 'natural_movie_three']}

SUPPORTED_PIPELINE_VERSION = '2.0'

get_cell_specimen_ids()

Returns an array of cell IDs for all cells in the file

Returns:

cell specimen IDs: list

get_cell_specimen_indices(cell_specimen_ids)

Given a list of cell specimen ids, return their index based on their order in this file.

Parameters:

cell_specimen_ids: list of cell specimen ids

get_corrected_fluorescence_traces(cell_specimen_ids=None)

Returns an array of demixed and neuropil-corrected fluorescence traces for all ROIs and the timestamps for each datapoint

Parameters:

cell_specimen_ids: list or array (optional)

List of cell IDs to return traces for. If this is None (default) then all are returned

Returns:

timestamps: 2D numpy array

Timestamp for each fluorescence sample

traces: 2D numpy array

Corrected fluorescence traces for each cell

get_demixed_traces(cell_specimen_ids=None)

Returns an array of demixed fluorescence traces for all ROIs and the timestamps for each datapoint

Parameters:

cell_specimen_ids: list or array (optional)

List of cell IDs to return traces for. If this is None (default) then all are returned

Returns:

timestamps: 2D numpy array

Timestamp for each fluorescence sample

traces: 2D numpy array

Demixed fluorescence traces for each cell

get_dff_traces(cell_specimen_ids=None)

Returns an array of dF/F traces for all ROIs and the timestamps for each datapoint

Parameters:

cell_specimen_ids: list or array (optional)

List of cell IDs to return data for. If this is None (default) then all are returned

Returns:

timestamps: 2D numpy array

Timestamp for each fluorescence sample

dF/F: 2D numpy array

dF/F values for each cell

get_fluorescence_timestamps()

Returns an array of timestamps in seconds for the fluorescence traces

get_fluorescence_traces(cell_specimen_ids=None)

Returns an array of fluorescence traces for all ROI and the timestamps for each datapoint

Parameters:

cell_specimen_ids: list or array (optional)

List of cell IDs to return traces for. If this is None (default) then all are returned

Returns:

timestamps: 2D numpy array

Timestamp for each fluorescence sample

traces: 2D numpy array

Fluorescence traces for each cell

get_locally_sparse_noise_stimulus_template(stimulus, mask_off_screen=True)

Return an array of the stimulus template for the specified stimulus.

Parameters:

stimulus: string

Which locally sparse noise stimulus to retrieve. Must be one of:

stimulus_info.LOCALLY_SPARSE_NOISE stimulus_info.LOCALLY_SPARSE_NOISE_4DEG stimulus_info.LOCALLY_SPARSE_NOISE_8DEG

mask_off_screen: boolean

Set off-screen regions of the stimulus to LocallySparseNoise.LSN_OFF_SCREEN.

Returns:

tuple: (template, off-screen mask)

get_max_projection()

Returns the maximum projection image for the 2P movie.

Returns:

max projection: np.ndarray

get_metadata()

Returns a dictionary of meta data associated with each experiment, including Cre line, specimen number, visual area imaged, imaging depth

Returns:

metadata: dictionary

get_motion_correction()

Returns a Panda DataFrame containing the x- and y- translation of each image used for image alignment

get_neuropil_r(cell_specimen_ids=None)

Returns a scalar value of r for neuropil correction of flourescence traces

Parameters:

cell_specimen_ids: list or array (optional)

List of cell IDs to return traces for. If this is None (default) then results for all are returned

Returns:

r: 1D numpy array, len(r)=len(cell_specimen_ids)

Scalar for neuropil subtraction for each cell

get_neuropil_traces(cell_specimen_ids=None)

Returns an array of neuropil fluorescence traces for all ROIs and the timestamps for each datapoint

Parameters:

cell_specimen_ids: list or array (optional)

List of cell IDs to return traces for. If this is None (default) then all are returned

Returns:

timestamps: 2D numpy array

Timestamp for each fluorescence sample

traces: 2D numpy array

Neuropil fluorescence traces for each cell

get_pupil_location(as_spherical=True)

Returns the x, y pupil location.

Parameters:

as_spherical : bool

Whether to return the location as spherical (default) or not. If true, the result is altitude and azimuth in degrees, otherwise it is x, y in centimeters. (0,0) is the center of the monitor.

Returns:

(timestamps, location)

Timestamps is an (Nx1) array of timestamps in seconds. Location is an (Nx2) array of spatial location.

get_pupil_size()

Returns the pupil area in pixels.

Returns:

(timestamps, areas)

Timestamps is an (Nx1) array of timestamps in seconds. Areas is an (Nx1) array of pupil areas in pixels.

get_roi_ids()

Returns an array of IDs for all ROIs in the file

Returns:

ROI IDs: list

get_roi_mask(cell_specimen_ids=None)

Returns an array of all the ROI masks

Parameters:

cell specimen IDs: list or array (optional)

List of cell IDs to return traces for. If this is None (default) then all are returned

Returns:

List of ROI_Mask objects

get_roi_mask_array(cell_specimen_ids=None)

Return a numpy array containing all of the ROI masks for requested cells. If cell_specimen_ids is omitted, return all masks.

Parameters:

cell_specimen_ids: list

List of cell specimen ids. Default None.

Returns:

np.ndarray: NxWxH array, where N is number of cells

get_running_speed()

Returns the mouse running speed in cm/s

get_session_type()

Returns the type of experimental session, presently one of the following: three_session_A, three_session_B, three_session_C

Returns:

session type: string

get_spontaneous_activity_stimulus_table(**kwargs)

Return the spontaneous activity stimulus table, if it exists.

Returns:

stimulus table: pd.DataFrame

get_stimulus(frame_ind)

get_stimulus_epoch_table()

Returns a pandas dataframe that summarizes the stimulus epoch duration for each acquisition time index in the experiment

Parameters:

None

Returns:

timestamps: 2D numpy array

Timestamp for each fluorescence sample

traces: 2D numpy array

Fluorescence traces for each cell

get_stimulus_table(stimulus_name)

Return a stimulus table given a stimulus name

Notes

For more information, see: http://help.brain-map.org/display/observatory/Documentation?preview=/10616846/10813485/VisualCoding_VisualStimuli.pdf

get_stimulus_template(**kwargs)

Return an array of the stimulus template for the specified stimulus.

Parameters:

stimulus_name: string

Must be one of the strings returned by list_stimuli().

Returns:

stimulus table: pd.DataFrame

list_stimuli()

Return a list of the stimuli presented in the experiment.

Returns:

stimuli: list of strings

number_of_cells

Number of cells in the experiment

save_analysis_arrays(*datasets)

save_analysis_dataframes(*tables)

stimulus_search

allensdk.core.brain_observatory_nwb_data_set.align_running_speed(dxcm, dxtime, timestamps)

If running speed timestamps differ from fluorescence timestamps, adjust by inserting NaNs to running speed.

Returns:

tuple: dxcm, dxtime

allensdk.core.brain_observatory_nwb_data_set.get_epoch_mask_list(st, threshold, max_cuts=2)

Convenience function to cut a stim table into multiple epochs

Parameters:

• st – input stimtable
• threshold – threshold on the max duration of a subepoch
• max_cuts – maximum number of allowed epochs to cut into

Returns:

epoch_mask_list, a list of indices that define the start and end of sub-epochs

allensdk.core.brain_observatory_nwb_data_set.make_display_mask(*args, **kwargs)

allensdk.core.brain_observatory_nwb_data_set.mask_stimulus_template(*args, **kwargs)

allensdk.core.brain_observatory_nwb_data_set.warp_stimulus_coords(*args, **kwargs)