pynwb.ophys module

class pynwb.ophys.OpticalChannel(name, description, emission_lambda)[source]

Bases: NWBContainer

An optical channel used to record from an imaging plane.

Parameters:

name (str) – the name of this electrode
description (str) – Any notes or comments about the channel.
emission_lambda (float) – Emission wavelength for channel, in nm.

property description: Any notes or comments about the channel.

property emission_lambda: Emission wavelength for channel, in nm.

namespace = 'core'

neurodata_type = 'OpticalChannel'

class pynwb.ophys.ImagingPlane(name, optical_channel, description=None, device=None, excitation_lambda=None, indicator=None, location=None, imaging_rate=None, manifold=None, conversion=1.0, unit='meters', reference_frame=None, origin_coords=None, origin_coords_unit='meters', grid_spacing=None, grid_spacing_unit='meters')[source]

Bases: NWBContainer

An imaging plane and its metadata.

Parameters:

name (str) – the name of this container
optical_channel (list or OpticalChannel) – One of possibly many groups storing channel-specific data.
description (str) – Description of this ImagingPlane.
device (Device) – the device that was used to record
excitation_lambda (float) – Excitation wavelength in nm.
indicator (str) – Calcium indicator
location (str) – Location of image plane.
imaging_rate (float) – Rate images are acquired, in Hz. If the corresponding TimeSeries is present, the rate should be stored there instead.
manifold (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator) – DEPRECATED - Physical position of each pixel. size=(“height”, “width”, “xyz”). Deprecated in favor of origin_coords and grid_spacing.
conversion (float) – DEPRECATED - Multiplier to get from stored values to specified unit (e.g., 1e-3 for millimeters) Deprecated in favor of origin_coords and grid_spacing.
unit (str) – DEPRECATED - Base unit that coordinates are stored in (e.g., Meters). Deprecated in favor of origin_coords_unit and grid_spacing_unit.
reference_frame (str) – Describes position and reference frame of manifold based on position of first element in manifold.
origin_coords (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator) – Physical location of the first element of the imaging plane (0, 0) for 2-D data or (0, 0, 0) for 3-D data. See also reference_frame for what the physical location is relative to (e.g., bregma).
origin_coords_unit (str) – Measurement units for origin_coords. The default value is ‘meters’.
grid_spacing (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator) – Space between pixels in (x, y) or voxels in (x, y, z) directions, in the specified unit. Assumes imaging plane is a regular grid. See also reference_frame to interpret the grid.
grid_spacing_unit (str) – Measurement units for grid_spacing. The default value is ‘meters’.

property conversion: DEPRECATED - Multiplier to get from stored values to specified unit (e.g., 1e-3 for millimeters) Deprecated in favor of origin_coords and grid_spacing.

property description: Description of this ImagingPlane.

property device: the device that was used to record

property excitation_lambda: Excitation wavelength in nm.

property grid_spacing: Space between pixels in (x, y) or voxels in (x, y, z) directions, in the specified unit. Assumes imaging plane is a regular grid. See also reference_frame to interpret the grid.

property grid_spacing_unit: Measurement units for grid_spacing. The default value is ‘meters’.

property imaging_rate: Rate images are acquired, in Hz. If the corresponding TimeSeries is present, the rate should be stored there instead.

property indicator: Calcium indicator

property location: Location of image plane.

property manifold: DEPRECATED - Physical position of each pixel. size=(“height”, “width”, “xyz”). Deprecated in favor of origin_coords and grid_spacing.

namespace = 'core'

neurodata_type = 'ImagingPlane'

property optical_channel: One of possibly many groups storing channel-specific data.

property origin_coords: Physical location of the first element of the imaging plane (0, 0) for 2-D data or (0, 0, 0) for 3-D data. See also reference_frame for what the physical location is relative to (e.g., bregma).

property origin_coords_unit: Measurement units for origin_coords. The default value is ‘meters’.

property reference_frame: Describes position and reference frame of manifold based on position of first element in manifold.

property unit: DEPRECATED - Base unit that coordinates are stored in (e.g., Meters). Deprecated in favor of origin_coords_unit and grid_spacing_unit.

class pynwb.ophys.OnePhotonSeries(name, imaging_plane, data=None, unit=None, format=None, pmt_gain=None, scan_line_rate=None, exposure_time=None, binning=None, power=None, intensity=None, external_file=None, starting_frame=None, bits_per_pixel=None, dimension=None, resolution=-1.0, conversion=1.0, timestamps=None, starting_time=None, rate=None, comments='no comments', description='no description', control=None, control_description=None, device=None, offset=0.0)[source]

Bases: ImageSeries

Image stack recorded over time from 1-photon microscope.

Parameters:

name (str) – The name of this TimeSeries dataset
imaging_plane (ImagingPlane) – Imaging plane class/pointer.
data (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator or DataIO or TimeSeries) – The data values. Can be 3D or 4D. The first dimension must be time (frame). The second and third dimensions represent x and y. The optional fourth dimension represents z. Either data or external_file must be specified (not None), but not both. If data is not specified, data will be set to an empty 3D array.
unit (str) – The unit of measurement of the image data, e.g., values between 0 and 255. Required when data is specified. If unit (and data) are not specified, then unit will be set to “unknown”.
format (str) – Format of image. Three types - 1) Image format; tiff, png, jpg, etc. 2) external 3) raw.
pmt_gain (float) – Photomultiplier gain.
scan_line_rate (float) – Lines imaged per second. This is also stored in /general/optophysiology but is kept here as it is useful information for analysis, and so good to be stored w/ the actual data.
exposure_time (float) – Exposure time of the sample; often the inverse of the frequency.
binning (int or uint) – Amount of pixels combined into ‘bins’; could be 1, 2, 4, 8, etc.
power (float) – Power of the excitation in mW, if known.
intensity (float) – Intensity of the excitation in mW/mm^2, if known.
external_file (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator or DataIO) – Path or URL to one or more external file(s). Field only present if format=external. Either external_file or data must be specified (not None), but not both.
starting_frame (Iterable) – Each entry is a frame number that corresponds to the first frame of each file listed in external_file within the full ImageSeries.
bits_per_pixel (int) – DEPRECATED: Number of bits per image pixel
dimension (Iterable) – Number of pixels on x, y, (and z) axes.
resolution (float) – The smallest meaningful difference (in specified unit) between values in data
conversion (float) – Scalar to multiply each element in data to convert it to the specified unit
timestamps (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator or DataIO or TimeSeries) – Timestamps for samples stored in data
starting_time (float) – The timestamp of the first sample
rate (float) – Sampling rate in Hz
comments (str) – Human-readable comments about this TimeSeries dataset
description (str) – Description of this TimeSeries dataset
control (Iterable) – Numerical labels that apply to each element in data
control_description (Iterable) – Description of each control value
device (Device) – Device used to capture the images/video.
offset (float) – Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.

property binning: Amount of pixels combined into ‘bins’; could be 1, 2, 4, 8, etc.

property exposure_time: Exposure time of the sample; often the inverse of the frequency.

property imaging_plane: Imaging plane class/pointer.

property intensity: Intensity of the excitation in mW/mm^2, if known.

namespace = 'core'

neurodata_type = 'OnePhotonSeries'

property pmt_gain: Photomultiplier gain.

property power: Power of the excitation in mW, if known.

property scan_line_rate: Lines imaged per second. This is also stored in /general/optophysiology but is kept here as it is useful information for analysis, and so good to be stored w/ the actual data.

class pynwb.ophys.TwoPhotonSeries(name, imaging_plane, data=None, unit=None, format=None, field_of_view=None, pmt_gain=None, scan_line_rate=None, external_file=None, starting_frame=None, bits_per_pixel=None, dimension=None, resolution=-1.0, conversion=1.0, timestamps=None, starting_time=None, rate=None, comments='no comments', description='no description', control=None, control_description=None, device=None, offset=0.0)[source]

Bases: ImageSeries

Image stack recorded over time from 2-photon microscope.

Parameters:

name (str) – The name of this TimeSeries dataset
imaging_plane (ImagingPlane) – Imaging plane class/pointer.
data (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator or DataIO or TimeSeries) – The data values. Can be 3D or 4D. The first dimension must be time (frame). The second and third dimensions represent x and y. The optional fourth dimension represents z. Either data or external_file must be specified (not None), but not both. If data is not specified, data will be set to an empty 3D array.
unit (str) – The unit of measurement of the image data, e.g., values between 0 and 255. Required when data is specified. If unit (and data) are not specified, then unit will be set to “unknown”.
format (str) – Format of image. Three types - 1) Image format; tiff, png, jpg, etc. 2) external 3) raw.
field_of_view (Iterable or TimeSeries) – Width, height and depth of image, or imaged area (meters).
pmt_gain (float) – Photomultiplier gain.
scan_line_rate (float) – Lines imaged per second. This is also stored in /general/optophysiology but is kept here as it is useful information for analysis, and so good to be stored w/ the actual data.
external_file (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator or DataIO) – Path or URL to one or more external file(s). Field only present if format=external. Either external_file or data must be specified (not None), but not both.
starting_frame (Iterable) – Each entry is a frame number that corresponds to the first frame of each file listed in external_file within the full ImageSeries.
bits_per_pixel (int) – DEPRECATED: Number of bits per image pixel
dimension (Iterable) – Number of pixels on x, y, (and z) axes.
resolution (float) – The smallest meaningful difference (in specified unit) between values in data
conversion (float) – Scalar to multiply each element in data to convert it to the specified unit
timestamps (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator or DataIO or TimeSeries) – Timestamps for samples stored in data
starting_time (float) – The timestamp of the first sample
rate (float) – Sampling rate in Hz
comments (str) – Human-readable comments about this TimeSeries dataset
description (str) – Description of this TimeSeries dataset
control (Iterable) – Numerical labels that apply to each element in data
control_description (Iterable) – Description of each control value
device (Device) – Device used to capture the images/video.
offset (float) – Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.

property field_of_view: Width, height and depth of image, or imaged area (meters).

property imaging_plane: Imaging plane class/pointer.

namespace = 'core'

neurodata_type = 'TwoPhotonSeries'

property pmt_gain: Photomultiplier gain.

property scan_line_rate: Lines imaged per second. This is also stored in /general/optophysiology but is kept here as it is useful information for analysis, and so good to be stored w/ the actual data.

class pynwb.ophys.CorrectedImageStack(corrected, original, xy_translation, name='CorrectedImageStack')[source]

Bases: NWBDataInterface

An image stack where all frames are shifted (registered) to a common coordinate system, to account for movement and drift between frames. Note: each frame at each point in time is assumed to be 2-D (has only x & y dimensions).

Parameters:

corrected (ImageSeries) – Image stack with frames shifted to the common coordinates. This must have the name “corrected”.
original (ImageSeries) – Link to image series that is being registered.
xy_translation (TimeSeries) – Stores the x,y delta necessary to align each frame to the common coordinates, for example, to align each frame to a reference image. This must have the name “xy_translation”.
name (str) – The name of this CorrectedImageStack container

property corrected: Image stack with frames shifted to the common coordinates. This must have the name “corrected”.

property original: Link to image series that is being registered.

property xy_translation: Stores the x,y delta necessary to align each frame to the common coordinates, for example, to align each frame to a reference image. This must have the name “xy_translation”.

namespace = 'core'

neurodata_type = 'CorrectedImageStack'

class pynwb.ophys.MotionCorrection(corrected_image_stacks={}, name='MotionCorrection')[source]

Bases: MultiContainerInterface

A collection of corrected images stacks.

Parameters:

corrected_image_stacks (list or tuple or dict or CorrectedImageStack) – CorrectedImageStack to store in this interface
name (str) – the name of this container

__getitem__(name=None)

Get a CorrectedImageStack from this MotionCorrection

Parameters:: name (str) – the name of the CorrectedImageStack
Returns:: the CorrectedImageStack with the given name
Return type:: CorrectedImageStack

add_corrected_image_stack(corrected_image_stacks)

Add one or multiple CorrectedImageStack objects to this MotionCorrection

Parameters:: corrected_image_stacks (list or tuple or dict or CorrectedImageStack) – one or multiple CorrectedImageStack objects to add to this MotionCorrection

property corrected_image_stacks: a dictionary containing the CorrectedImageStack in this MotionCorrection

create_corrected_image_stack(corrected, original, xy_translation, name='CorrectedImageStack')

Create a CorrectedImageStack object and add it to this MotionCorrection

Parameters:

corrected (ImageSeries) – Image stack with frames shifted to the common coordinates. This must have the name “corrected”.
original (ImageSeries) – Link to image series that is being registered.
xy_translation (TimeSeries) – Stores the x,y delta necessary to align each frame to the common coordinates, for example, to align each frame to a reference image. This must have the name “xy_translation”.
name (str) – The name of this CorrectedImageStack container

Returns:

the CorrectedImageStack object that was created

Return type:

CorrectedImageStack

get_corrected_image_stack(name=None)

Get a CorrectedImageStack from this MotionCorrection

Parameters:: name (str) – the name of the CorrectedImageStack
Returns:: the CorrectedImageStack with the given name
Return type:: CorrectedImageStack

namespace = 'core'

neurodata_type = 'MotionCorrection'

class pynwb.ophys.PlaneSegmentation(description, imaging_plane, name=None, reference_images=None, id=None, columns=None, colnames=None, target_tables=None, meanings_tables=None)[source]

Bases: DynamicTable

Stores pixels in an image that represent different regions of interest (ROIs) or masks. All segmentation for a given imaging plane is stored together, with storage for multiple imaging planes (masks) supported. Each ROI is stored in its own subgroup, with the ROI group containing both a 2D mask and a list of pixels that make up this mask. Segments can also be used for masking neuropil. If segmentation is allowed to change with time, a new imaging plane (or module) is required and ROI names should remain consistent between them.

Parameters:

description (str) – Description of image plane, recording wavelength, depth, etc.
imaging_plane (ImagingPlane) – the ImagingPlane this ROI applies to
name (str) – name of PlaneSegmentation.
reference_images (ImageSeries or list or dict or tuple) – One or more image stacks that the masks apply to (can be oneelement stack).
id (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator or DataIO or ElementIdentifiers) – the identifiers for this table
columns (tuple or list) – the columns in this table
colnames (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator) – the ordered names of the columns in this table. columns must also be provided.
target_tables (dict) – dict mapping DynamicTableRegion column name to the table that the DTR points to. The column is added to the table if it is not already present (i.e., when it is optional).
meanings_tables (tuple or list) – MeaningsTable objects that provide meanings for values in VectorData columns. Each MeaningsTable must have a name of “{column_name}_meanings” where column_name is the name of the target column in this DynamicTable. The target column must exist in this table.

property imaging_plane: the ImagingPlane this ROI applies to

property reference_images: One or more image stacks that the masks apply to (can be oneelement stack).

add_roi(pixel_mask=None, voxel_mask=None, image_mask=None, id=None)[source]

Add a Region Of Interest (ROI) data to this

Parameters:

pixel_mask (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator) – pixel mask for 2D ROIs: [(x1, y1, weight1), (x2, y2, weight2), …]
voxel_mask (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator) – voxel mask for 3D ROIs: [(x1, y1, z1, weight1), (x2, y2, z2, weight2), …]
image_mask (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator) – image with the same size of image where positive values mark this ROI
id (int) – the ID for the ROI

static pixel_to_image(pixel_mask)[source]: Converts a 2D pixel_mask of a ROI into an image_mask.

static image_to_pixel(image_mask)[source]: Converts an image_mask of a ROI into a pixel_mask

create_roi_table_region(description, region=slice(None, None, None), name='rois')[source]

Parameters:

description (str) – a brief description of what the region is
region (slice or list or tuple) – the indices of the table
name (str) – the name of the ROITableRegion

namespace = 'core'

neurodata_type = 'PlaneSegmentation'

class pynwb.ophys.ImageSegmentation(plane_segmentations={}, name='ImageSegmentation')[source]

Bases: MultiContainerInterface

Stores pixels in an image that represent different regions of interest (ROIs) or masks. All segmentation for a given imaging plane is stored together, with storage for multiple imaging planes (masks) supported. Each ROI is stored in its own subgroup, with the ROI group containing both a 2D mask and a list of pixels that make up this mask. Segments can also be used for masking neuropil. If segmentation is allowed to change with time, a new imaging plane (or module) is required and ROI names should remain consistent between them.

Parameters:

plane_segmentations (list or tuple or dict or PlaneSegmentation) – PlaneSegmentation to store in this interface
name (str) – the name of this container

add_segmentation(imaging_plane, description=None, name=None)[source]

Parameters:

imaging_plane (ImagingPlane) – the ImagingPlane this ROI applies to
description (str) – Description of image plane, recording wavelength, depth, etc.
name (str) – name of PlaneSegmentation.

__getitem__(name=None)

Get a PlaneSegmentation from this ImageSegmentation

Parameters:: name (str) – the name of the PlaneSegmentation
Returns:: the PlaneSegmentation with the given name
Return type:: PlaneSegmentation

add_plane_segmentation(plane_segmentations)

Add one or multiple PlaneSegmentation objects to this ImageSegmentation

Parameters:: plane_segmentations (list or tuple or dict or PlaneSegmentation) – one or multiple PlaneSegmentation objects to add to this ImageSegmentation

create_plane_segmentation(description, imaging_plane, name=None, reference_images=None, id=None, columns=None, colnames=None, target_tables=None, meanings_tables=None)

Create a PlaneSegmentation object and add it to this ImageSegmentation

Parameters:

description (str) – Description of image plane, recording wavelength, depth, etc.
imaging_plane (ImagingPlane) – the ImagingPlane this ROI applies to
name (str) – name of PlaneSegmentation.
reference_images (ImageSeries or list or dict or tuple) – One or more image stacks that the masks apply to (can be oneelement stack).
id (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator or DataIO or ElementIdentifiers) – the identifiers for this table
columns (tuple or list) – the columns in this table
colnames (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator) – the ordered names of the columns in this table. columns must also be provided.
target_tables (dict) – dict mapping DynamicTableRegion column name to the table that the DTR points to. The column is added to the table if it is not already present (i.e., when it is optional).
meanings_tables (tuple or list) – MeaningsTable objects that provide meanings for values in VectorData columns. Each MeaningsTable must have a name of “{column_name}_meanings” where column_name is the name of the target column in this DynamicTable. The target column must exist in this table.

Returns:

the PlaneSegmentation object that was created

Return type:

PlaneSegmentation

get_plane_segmentation(name=None)

Get a PlaneSegmentation from this ImageSegmentation

Parameters:: name (str) – the name of the PlaneSegmentation
Returns:: the PlaneSegmentation with the given name
Return type:: PlaneSegmentation

namespace = 'core'

neurodata_type = 'ImageSegmentation'

property plane_segmentations: a dictionary containing the PlaneSegmentation in this ImageSegmentation

class pynwb.ophys.RoiResponseSeries(name, data, unit, rois, resolution=-1.0, conversion=1.0, timestamps=None, starting_time=None, rate=None, comments='no comments', description='no description', control=None, control_description=None, offset=0.0)[source]

Bases: TimeSeries

ROI responses over an imaging plane. Each column in data should correspond to the signal from one ROI.

Parameters:

name (str) – The name of this TimeSeries dataset
data (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator or DataIO or TimeSeries) – The data values. May be 1D or 2D. The first dimension must be time. The optional second dimension represents ROIs
unit (str) – The base unit of measurement (should be SI unit)
rois (DynamicTableRegion) – a table region corresponding to the ROIs that were used to generate this data
resolution (float) – The smallest meaningful difference (in specified unit) between values in data
conversion (float) – Scalar to multiply each element in data to convert it to the specified unit
timestamps (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator or DataIO or TimeSeries) – Timestamps for samples stored in data
starting_time (float) – The timestamp of the first sample
rate (float) – Sampling rate in Hz
comments (str) – Human-readable comments about this TimeSeries dataset
description (str) – Description of this TimeSeries dataset
control (Iterable) – Numerical labels that apply to each element in data
control_description (Iterable) – Description of each control value
offset (float) – Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.

property rois: a table region corresponding to the ROIs that were used to generate this data

namespace = 'core'

neurodata_type = 'RoiResponseSeries'

class pynwb.ophys.DfOverF(roi_response_series={}, name='DfOverF')[source]

Bases: MultiContainerInterface

dF/F information about a region of interest (ROI). Storage hierarchy of dF/F should be the same as for segmentation (ie, same names for ROIs and for image planes).

Parameters:

roi_response_series (list or tuple or dict or RoiResponseSeries) – RoiResponseSeries to store in this interface
name (str) – the name of this container

__getitem__(name=None)

Get a RoiResponseSeries from this DfOverF

Parameters:: name (str) – the name of the RoiResponseSeries
Returns:: the RoiResponseSeries with the given name
Return type:: RoiResponseSeries

add_roi_response_series(roi_response_series)

Add one or multiple RoiResponseSeries objects to this DfOverF

Parameters:: roi_response_series (list or tuple or dict or RoiResponseSeries) – one or multiple RoiResponseSeries objects to add to this DfOverF

create_roi_response_series(name, data, unit, rois, resolution=-1.0, conversion=1.0, timestamps=None, starting_time=None, rate=None, comments='no comments', description='no description', control=None, control_description=None, offset=0.0)

Create a RoiResponseSeries object and add it to this DfOverF

Parameters:

name (str) – The name of this TimeSeries dataset
data (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator or DataIO or TimeSeries) – The data values. May be 1D or 2D. The first dimension must be time. The optional second dimension represents ROIs
unit (str) – The base unit of measurement (should be SI unit)
rois (DynamicTableRegion) – a table region corresponding to the ROIs that were used to generate this data
resolution (float) – The smallest meaningful difference (in specified unit) between values in data
conversion (float) – Scalar to multiply each element in data to convert it to the specified unit
timestamps (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator or DataIO or TimeSeries) – Timestamps for samples stored in data
starting_time (float) – The timestamp of the first sample
rate (float) – Sampling rate in Hz
comments (str) – Human-readable comments about this TimeSeries dataset
description (str) – Description of this TimeSeries dataset
control (Iterable) – Numerical labels that apply to each element in data
control_description (Iterable) – Description of each control value
offset (float) – Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.

Returns:

the RoiResponseSeries object that was created

Return type:

RoiResponseSeries

get_roi_response_series(name=None)

Get a RoiResponseSeries from this DfOverF

Parameters:: name (str) – the name of the RoiResponseSeries
Returns:: the RoiResponseSeries with the given name
Return type:: RoiResponseSeries

namespace = 'core'

neurodata_type = 'DfOverF'

property roi_response_series: a dictionary containing the RoiResponseSeries in this DfOverF

class pynwb.ophys.Fluorescence(roi_response_series={}, name='Fluorescence')[source]

Bases: MultiContainerInterface

Fluorescence information about a region of interest (ROI). Storage hierarchy of fluorescence should be the same as for segmentation (ie, same names for ROIs and for image planes).

Parameters:

roi_response_series (list or tuple or dict or RoiResponseSeries) – RoiResponseSeries to store in this interface
name (str) – the name of this container

__getitem__(name=None)

Get a RoiResponseSeries from this Fluorescence

Parameters:: name (str) – the name of the RoiResponseSeries
Returns:: the RoiResponseSeries with the given name
Return type:: RoiResponseSeries

add_roi_response_series(roi_response_series)

Add one or multiple RoiResponseSeries objects to this Fluorescence

Parameters:: roi_response_series (list or tuple or dict or RoiResponseSeries) – one or multiple RoiResponseSeries objects to add to this Fluorescence

create_roi_response_series(name, data, unit, rois, resolution=-1.0, conversion=1.0, timestamps=None, starting_time=None, rate=None, comments='no comments', description='no description', control=None, control_description=None, offset=0.0)

Create a RoiResponseSeries object and add it to this Fluorescence

Parameters:

name (str) – The name of this TimeSeries dataset
data (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator or DataIO or TimeSeries) – The data values. May be 1D or 2D. The first dimension must be time. The optional second dimension represents ROIs
unit (str) – The base unit of measurement (should be SI unit)
rois (DynamicTableRegion) – a table region corresponding to the ROIs that were used to generate this data
resolution (float) – The smallest meaningful difference (in specified unit) between values in data
conversion (float) – Scalar to multiply each element in data to convert it to the specified unit
timestamps (ndarray or list or tuple or Dataset or Array or StrDataset or HDMFDataset or AbstractDataChunkIterator or DataIO or TimeSeries) – Timestamps for samples stored in data
starting_time (float) – The timestamp of the first sample
rate (float) – Sampling rate in Hz
comments (str) – Human-readable comments about this TimeSeries dataset
description (str) – Description of this TimeSeries dataset
control (Iterable) – Numerical labels that apply to each element in data
control_description (Iterable) – Description of each control value
offset (float) – Scalar to add to each element in the data scaled by ‘conversion’ to finish converting it to the specified unit.

Returns:

the RoiResponseSeries object that was created

Return type:

RoiResponseSeries

get_roi_response_series(name=None)

Get a RoiResponseSeries from this Fluorescence

Parameters:: name (str) – the name of the RoiResponseSeries
Returns:: the RoiResponseSeries with the given name
Return type:: RoiResponseSeries

namespace = 'core'

neurodata_type = 'Fluorescence'

property roi_response_series: a dictionary containing the RoiResponseSeries in this Fluorescence