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Cnmfe

pynapple.io.cnmfe

⚠ DEPRECATED: This will be removed in version 1.0.0. Check nwbmatic or neuroconv instead.

Loaders for calcium imaging data with miniscope. Support CNMF-E in matlab, inscopix-cnmfe and minian.

CNMF_E

Bases: BaseLoader

Loader for data processed with matlab CNMF-E(https://github.com/zhoupc/CNMF_E). The path folder should contain a file ending in .mat when calling Source2d.save_neurons

Attributes:

Name Type Description
A ndarray

Spatial footprints
C TsdFrame

The calcium transients
sampling_rate float

Sampling rate of the data (default is 30 Hz).
Source code in pynapple/io/cnmfe.py 
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class CNMF_E(BaseLoader):
    """Loader for data processed with matlab CNMF-E(https://github.com/zhoupc/CNMF_E).
    The path folder should contain a file ending in .mat
    when calling Source2d.save_neurons

    Attributes
    ----------
    A : numpy.ndarray
        Spatial footprints
    C : TsdFrame
        The calcium transients
    sampling_rate : float
        Sampling rate of the data (default is 30 Hz).

    """

    def __init__(self, path):
        """

        Parameters
        ----------
        path : str
            The path to the data.
        """
        path = Path(path)
        self.basename = path.name

        super().__init__(path)

        self.load_cnmfe_nwb()

    def load_cnmfe_nwb(self):
        """
        Load the calcium transient and spatial footprint from nwb

        Parameters
        ----------
        path : str
            Path to the session
        """
        io = NWBHDF5IO(self.nwbfilepath, "r")
        nwbfile = io.read()

        if "ophys" in nwbfile.processing.keys():
            data = nwbfile.processing["ophys"]["Fluorescence"][
                "RoiResponseSeries"
            ].data[:]
            t = nwbfile.processing["ophys"]["Fluorescence"][
                "RoiResponseSeries"
            ].timestamps[:]
            self.C = nap.TsdFrame(t=t, d=data)
            self.A = nwbfile.processing["ophys"]["ImageSegmentation"][
                "PlaneSegmentation"
            ]["image_mask"].data[:]

            io.close()
            return True
        else:
            io.close()
            return False

load_data 

load_data()

Load NWB data saved with pynapple in the pynapplenwb folder

Parameters:

Name Type Description Default
path str

Path to the session folder

 required
Source code in pynapple/io/loader.py 
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def load_data(self):
    """
    Load NWB data saved with pynapple in the pynapplenwb folder

    Parameters
    ----------
    path : str
        Path to the session folder
    """

    io = NWBHDF5IO(self.nwbfilepath, "r+")
    nwbfile = io.read()

    position = {}
    acq_keys = nwbfile.acquisition.keys()
    if "CompassDirection" in acq_keys:
        compass = nwbfile.acquisition["CompassDirection"]
        for k in compass.spatial_series.keys():
            position[k] = pd.Series(
                index=compass.get_spatial_series(k).timestamps[:],
                data=compass.get_spatial_series(k).data[:],
            )
    if "Position" in acq_keys:
        tracking = nwbfile.acquisition["Position"]
        for k in tracking.spatial_series.keys():
            position[k] = pd.Series(
                index=tracking.get_spatial_series(k).timestamps[:],
                data=tracking.get_spatial_series(k).data[:],
            )
    if len(position):
        position = pd.DataFrame.from_dict(position)

        # retrieveing time support position if in epochs
        if "position_time_support" in nwbfile.intervals.keys():
            epochs = nwbfile.intervals["position_time_support"].to_dataframe()
            time_support = nap.IntervalSet(
                start=epochs["start_time"], end=epochs["stop_time"], time_units="s"
            )

        self.position = nap.TsdFrame(
            position, time_units="s", time_support=time_support
        )

    if nwbfile.epochs is not None:
        epochs = nwbfile.epochs.to_dataframe()
        # NWB is dumb and cannot take a single string for labels
        epochs["label"] = [epochs.loc[i, "tags"][0] for i in epochs.index]
        epochs = epochs.drop(labels="tags", axis=1)
        epochs = epochs.rename(columns={"start_time": "start", "stop_time": "end"})
        self.epochs = self._make_epochs(epochs)

        self.time_support = self._join_epochs(epochs, "s")

    io.close()

    return

save_nwb_intervals 

save_nwb_intervals(iset, name, description='')

Add epochs to the NWB file (e.g. ripples epochs) See pynwb.epoch.TimeIntervals

Parameters:

Name Type Description Default
iset IntervalSet

The intervalSet to save

 required
name str

The name in the nwb file

 required
Source code in pynapple/io/loader.py 
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def save_nwb_intervals(self, iset, name, description=""):
    """
    Add epochs to the NWB file (e.g. ripples epochs)
    See pynwb.epoch.TimeIntervals

    Parameters
    ----------
    iset : IntervalSet
        The intervalSet to save
    name : str
        The name in the nwb file
    """
    io = NWBHDF5IO(self.nwbfilepath, "r+")
    nwbfile = io.read()

    epochs = iset.as_units("s")
    time_intervals = TimeIntervals(name=name, description=description)
    for i in epochs.index:
        time_intervals.add_interval(
            start_time=epochs.loc[i, "start"],
            stop_time=epochs.loc[i, "end"],
            tags=str(i),
        )

    nwbfile.add_time_intervals(time_intervals)
    io.write(nwbfile)
    io.close()

    return

save_nwb_timeseries 

save_nwb_timeseries(tsd, name, description='')

Save timestamps in the NWB file (e.g. ripples time) with the time support. See pynwb.base.TimeSeries

Parameters:

Name Type Description Default
tsd TsdFrame

_

 required
name str

_

 required
description str

_

 ''
Source code in pynapple/io/loader.py 
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def save_nwb_timeseries(self, tsd, name, description=""):
    """
    Save timestamps in the NWB file (e.g. ripples time) with the time support.
    See pynwb.base.TimeSeries


    Parameters
    ----------
    tsd : TsdFrame
        _
    name : str
        _
    description : str, optional
        _
    """
    io = NWBHDF5IO(self.nwbfilepath, "r+")
    nwbfile = io.read()

    ts = TimeSeries(
        name=name,
        unit="s",
        data=tsd.values,
        timestamps=tsd.as_units("s").index.values,
    )

    time_support = TimeIntervals(
        name=name + "_timesupport", description="The time support of the object"
    )

    epochs = tsd.time_support.as_units("s")
    for i in epochs.index:
        time_support.add_interval(
            start_time=epochs.loc[i, "start"],
            stop_time=epochs.loc[i, "end"],
            tags=str(i),
        )
    nwbfile.add_time_intervals(time_support)
    nwbfile.add_acquisition(ts)
    io.write(nwbfile)
    io.close()

    return

load_nwb_intervals 

load_nwb_intervals(name)

Load epochs from the NWB file (e.g. 'ripples')

Parameters:

Name Type Description Default
name str

The name in the nwb file

 required
Source code in pynapple/io/loader.py 
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def load_nwb_intervals(self, name):
    """
    Load epochs from the NWB file (e.g. 'ripples')

    Parameters
    ----------
    name : str
        The name in the nwb file
    """
    io = NWBHDF5IO(self.nwbfilepath, "r")
    nwbfile = io.read()

    if name in nwbfile.intervals.keys():
        epochs = nwbfile.intervals[name].to_dataframe()
        isets = nap.IntervalSet(
            start=epochs["start_time"], end=epochs["stop_time"], time_units="s"
        )
        io.close()
        return isets
    else:
        io.close()
    return

load_nwb_timeseries 

load_nwb_timeseries(name)

Load timestamps in the NWB file (e.g. ripples time)

Parameters:

Name Type Description Default
name str

_

 required

Returns:

Type Description
Tsd

_
Source code in pynapple/io/loader.py 
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def load_nwb_timeseries(self, name):
    """
    Load timestamps in the NWB file (e.g. ripples time)

    Parameters
    ----------
    name : str
        _

    Returns
    -------
    Tsd
        _
    """
    io = NWBHDF5IO(self.nwbfilepath, "r")
    nwbfile = io.read()

    ts = nwbfile.acquisition[name]

    time_support = self.load_nwb_intervals(name + "_timesupport")

    tsd = nap.Tsd(
        t=ts.timestamps[:], d=ts.data[:], time_units="s", time_support=time_support
    )

    io.close()

    return tsd

__init__ 

__init__(path)

Parameters:

Name Type Description Default
path str

The path to the data.

 required
Source code in pynapple/io/cnmfe.py 
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def __init__(self, path):
    """

    Parameters
    ----------
    path : str
        The path to the data.
    """
    path = Path(path)
    self.basename = path.name

    super().__init__(path)

    self.load_cnmfe_nwb()

load_cnmfe_nwb 

load_cnmfe_nwb()

Load the calcium transient and spatial footprint from nwb

Parameters:

Name Type Description Default
path str

Path to the session

 required
Source code in pynapple/io/cnmfe.py 
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def load_cnmfe_nwb(self):
    """
    Load the calcium transient and spatial footprint from nwb

    Parameters
    ----------
    path : str
        Path to the session
    """
    io = NWBHDF5IO(self.nwbfilepath, "r")
    nwbfile = io.read()

    if "ophys" in nwbfile.processing.keys():
        data = nwbfile.processing["ophys"]["Fluorescence"][
            "RoiResponseSeries"
        ].data[:]
        t = nwbfile.processing["ophys"]["Fluorescence"][
            "RoiResponseSeries"
        ].timestamps[:]
        self.C = nap.TsdFrame(t=t, d=data)
        self.A = nwbfile.processing["ophys"]["ImageSegmentation"][
            "PlaneSegmentation"
        ]["image_mask"].data[:]

        io.close()
        return True
    else:
        io.close()
        return False

Minian

Bases: BaseLoader

Loader for data processed with Minian (https://github.com/denisecailab/minian). The path folder should contain a subfolder name minian.

Attributes:

Name Type Description
A ndarray

Spatial footprints
C TsdFrame

The calcium transients
sampling_rate float

Sampling rate of the data (default is 30 Hz).
Source code in pynapple/io/cnmfe.py 
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class Minian(BaseLoader):
    """Loader for data processed with Minian (https://github.com/denisecailab/minian).
    The path folder should contain a subfolder name minian.

    Attributes
    ----------
    A : numpy.ndarray
        Spatial footprints
    C : TsdFrame
        The calcium transients
    sampling_rate : float
        Sampling rate of the data (default is 30 Hz).

    """

    def __init__(self, path):
        """

        Parameters
        ----------
        path : str
            The path to the data.
        """
        path = Path(path)
        self.basename = path.name

        super().__init__(path)

        self.load_cnmfe_nwb()

    def load_cnmfe_nwb(self):
        """
        Load the calcium transient and spatial footprint from nwb

        Parameters
        ----------
        path : str
            Path to the session
        """
        io = NWBHDF5IO(self.nwbfilepath, "r")
        nwbfile = io.read()

        if "ophys" in nwbfile.processing.keys():
            data = nwbfile.processing["ophys"]["Fluorescence"][
                "RoiResponseSeries"
            ].data[:]
            t = nwbfile.processing["ophys"]["Fluorescence"][
                "RoiResponseSeries"
            ].timestamps[:]
            self.C = nap.TsdFrame(t=t, d=data)
            self.A = nwbfile.processing["ophys"]["ImageSegmentation"][
                "PlaneSegmentation"
            ]["image_mask"].data[:]

            io.close()
            return True
        else:
            io.close()
            return False

load_data 

load_data()

Load NWB data saved with pynapple in the pynapplenwb folder

Parameters:

Name Type Description Default
path str

Path to the session folder

 required
Source code in pynapple/io/loader.py 
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def load_data(self):
    """
    Load NWB data saved with pynapple in the pynapplenwb folder

    Parameters
    ----------
    path : str
        Path to the session folder
    """

    io = NWBHDF5IO(self.nwbfilepath, "r+")
    nwbfile = io.read()

    position = {}
    acq_keys = nwbfile.acquisition.keys()
    if "CompassDirection" in acq_keys:
        compass = nwbfile.acquisition["CompassDirection"]
        for k in compass.spatial_series.keys():
            position[k] = pd.Series(
                index=compass.get_spatial_series(k).timestamps[:],
                data=compass.get_spatial_series(k).data[:],
            )
    if "Position" in acq_keys:
        tracking = nwbfile.acquisition["Position"]
        for k in tracking.spatial_series.keys():
            position[k] = pd.Series(
                index=tracking.get_spatial_series(k).timestamps[:],
                data=tracking.get_spatial_series(k).data[:],
            )
    if len(position):
        position = pd.DataFrame.from_dict(position)

        # retrieveing time support position if in epochs
        if "position_time_support" in nwbfile.intervals.keys():
            epochs = nwbfile.intervals["position_time_support"].to_dataframe()
            time_support = nap.IntervalSet(
                start=epochs["start_time"], end=epochs["stop_time"], time_units="s"
            )

        self.position = nap.TsdFrame(
            position, time_units="s", time_support=time_support
        )

    if nwbfile.epochs is not None:
        epochs = nwbfile.epochs.to_dataframe()
        # NWB is dumb and cannot take a single string for labels
        epochs["label"] = [epochs.loc[i, "tags"][0] for i in epochs.index]
        epochs = epochs.drop(labels="tags", axis=1)
        epochs = epochs.rename(columns={"start_time": "start", "stop_time": "end"})
        self.epochs = self._make_epochs(epochs)

        self.time_support = self._join_epochs(epochs, "s")

    io.close()

    return

save_nwb_intervals 

save_nwb_intervals(iset, name, description='')

Add epochs to the NWB file (e.g. ripples epochs) See pynwb.epoch.TimeIntervals

Parameters:

Name Type Description Default
iset IntervalSet

The intervalSet to save

 required
name str

The name in the nwb file

 required
Source code in pynapple/io/loader.py 
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def save_nwb_intervals(self, iset, name, description=""):
    """
    Add epochs to the NWB file (e.g. ripples epochs)
    See pynwb.epoch.TimeIntervals

    Parameters
    ----------
    iset : IntervalSet
        The intervalSet to save
    name : str
        The name in the nwb file
    """
    io = NWBHDF5IO(self.nwbfilepath, "r+")
    nwbfile = io.read()

    epochs = iset.as_units("s")
    time_intervals = TimeIntervals(name=name, description=description)
    for i in epochs.index:
        time_intervals.add_interval(
            start_time=epochs.loc[i, "start"],
            stop_time=epochs.loc[i, "end"],
            tags=str(i),
        )

    nwbfile.add_time_intervals(time_intervals)
    io.write(nwbfile)
    io.close()

    return

save_nwb_timeseries 

save_nwb_timeseries(tsd, name, description='')

Save timestamps in the NWB file (e.g. ripples time) with the time support. See pynwb.base.TimeSeries

Parameters:

Name Type Description Default
tsd TsdFrame

_

 required
name str

_

 required
description str

_

 ''
Source code in pynapple/io/loader.py 
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def save_nwb_timeseries(self, tsd, name, description=""):
    """
    Save timestamps in the NWB file (e.g. ripples time) with the time support.
    See pynwb.base.TimeSeries


    Parameters
    ----------
    tsd : TsdFrame
        _
    name : str
        _
    description : str, optional
        _
    """
    io = NWBHDF5IO(self.nwbfilepath, "r+")
    nwbfile = io.read()

    ts = TimeSeries(
        name=name,
        unit="s",
        data=tsd.values,
        timestamps=tsd.as_units("s").index.values,
    )

    time_support = TimeIntervals(
        name=name + "_timesupport", description="The time support of the object"
    )

    epochs = tsd.time_support.as_units("s")
    for i in epochs.index:
        time_support.add_interval(
            start_time=epochs.loc[i, "start"],
            stop_time=epochs.loc[i, "end"],
            tags=str(i),
        )
    nwbfile.add_time_intervals(time_support)
    nwbfile.add_acquisition(ts)
    io.write(nwbfile)
    io.close()

    return

load_nwb_intervals 

load_nwb_intervals(name)

Load epochs from the NWB file (e.g. 'ripples')

Parameters:

Name Type Description Default
name str

The name in the nwb file

 required
Source code in pynapple/io/loader.py 
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def load_nwb_intervals(self, name):
    """
    Load epochs from the NWB file (e.g. 'ripples')

    Parameters
    ----------
    name : str
        The name in the nwb file
    """
    io = NWBHDF5IO(self.nwbfilepath, "r")
    nwbfile = io.read()

    if name in nwbfile.intervals.keys():
        epochs = nwbfile.intervals[name].to_dataframe()
        isets = nap.IntervalSet(
            start=epochs["start_time"], end=epochs["stop_time"], time_units="s"
        )
        io.close()
        return isets
    else:
        io.close()
    return

load_nwb_timeseries 

load_nwb_timeseries(name)

Load timestamps in the NWB file (e.g. ripples time)

Parameters:

Name Type Description Default
name str

_

 required

Returns:

Type Description
Tsd

_
Source code in pynapple/io/loader.py 
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def load_nwb_timeseries(self, name):
    """
    Load timestamps in the NWB file (e.g. ripples time)

    Parameters
    ----------
    name : str
        _

    Returns
    -------
    Tsd
        _
    """
    io = NWBHDF5IO(self.nwbfilepath, "r")
    nwbfile = io.read()

    ts = nwbfile.acquisition[name]

    time_support = self.load_nwb_intervals(name + "_timesupport")

    tsd = nap.Tsd(
        t=ts.timestamps[:], d=ts.data[:], time_units="s", time_support=time_support
    )

    io.close()

    return tsd

__init__ 

__init__(path)

Parameters:

Name Type Description Default
path str

The path to the data.

 required
Source code in pynapple/io/cnmfe.py 
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def __init__(self, path):
    """

    Parameters
    ----------
    path : str
        The path to the data.
    """
    path = Path(path)
    self.basename = path.name

    super().__init__(path)

    self.load_cnmfe_nwb()

load_cnmfe_nwb 

load_cnmfe_nwb()

Load the calcium transient and spatial footprint from nwb

Parameters:

Name Type Description Default
path str

Path to the session

 required
Source code in pynapple/io/cnmfe.py 
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def load_cnmfe_nwb(self):
    """
    Load the calcium transient and spatial footprint from nwb

    Parameters
    ----------
    path : str
        Path to the session
    """
    io = NWBHDF5IO(self.nwbfilepath, "r")
    nwbfile = io.read()

    if "ophys" in nwbfile.processing.keys():
        data = nwbfile.processing["ophys"]["Fluorescence"][
            "RoiResponseSeries"
        ].data[:]
        t = nwbfile.processing["ophys"]["Fluorescence"][
            "RoiResponseSeries"
        ].timestamps[:]
        self.C = nap.TsdFrame(t=t, d=data)
        self.A = nwbfile.processing["ophys"]["ImageSegmentation"][
            "PlaneSegmentation"
        ]["image_mask"].data[:]

        io.close()
        return True
    else:
        io.close()
        return False

InscopixCNMFE

Bases: BaseLoader

Loader for Inscopix-cnmfe (https://github.com/inscopix/inscopix-cnmfe). The folder should contain a file ending with '_traces.csv' and a tiff file for spatial footprints.

Attributes:

Name Type Description
A ndarray

The spatial footprints
C TsdFrame

The calcium transients
sampling_rate float

Sampling rate of the data (default is 30 Hz).
Source code in pynapple/io/cnmfe.py 
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class InscopixCNMFE(BaseLoader):
    """Loader for Inscopix-cnmfe (https://github.com/inscopix/inscopix-cnmfe).
    The folder should contain a file ending with '_traces.csv'
    and a tiff file for spatial footprints.

    Attributes
    ----------
    A : np.ndarray
        The spatial footprints
    C : TsdFrame
        The calcium transients
    sampling_rate : float
        Sampling rate of the data (default is 30 Hz).

    """

    def __init__(self, path):
        """

        Parameters
        ----------
        path : str
            The path to the data.
        """
        path = Path(path)
        self.basename = path.name

        super().__init__(path)

        self.load_cnmfe_nwb()

    def load_cnmfe_nwb(self):
        """
        Load the calcium transient and spatial footprint from nwb

        Parameters
        ----------
        path : str
            Path to the session
        """
        io = NWBHDF5IO(self.nwbfilepath, "r")
        nwbfile = io.read()

        if "ophys" in nwbfile.processing.keys():
            data = nwbfile.processing["ophys"]["Fluorescence"][
                "RoiResponseSeries"
            ].data[:]
            t = nwbfile.processing["ophys"]["Fluorescence"][
                "RoiResponseSeries"
            ].timestamps[:]
            self.C = nap.TsdFrame(t=t, d=data)
            self.A = nwbfile.processing["ophys"]["ImageSegmentation"][
                "PlaneSegmentation"
            ]["image_mask"].data[:]

            io.close()
            return True
        else:
            io.close()
            return False

load_data 

load_data()

Load NWB data saved with pynapple in the pynapplenwb folder

Parameters:

Name Type Description Default
path str

Path to the session folder

 required
Source code in pynapple/io/loader.py 
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def load_data(self):
    """
    Load NWB data saved with pynapple in the pynapplenwb folder

    Parameters
    ----------
    path : str
        Path to the session folder
    """

    io = NWBHDF5IO(self.nwbfilepath, "r+")
    nwbfile = io.read()

    position = {}
    acq_keys = nwbfile.acquisition.keys()
    if "CompassDirection" in acq_keys:
        compass = nwbfile.acquisition["CompassDirection"]
        for k in compass.spatial_series.keys():
            position[k] = pd.Series(
                index=compass.get_spatial_series(k).timestamps[:],
                data=compass.get_spatial_series(k).data[:],
            )
    if "Position" in acq_keys:
        tracking = nwbfile.acquisition["Position"]
        for k in tracking.spatial_series.keys():
            position[k] = pd.Series(
                index=tracking.get_spatial_series(k).timestamps[:],
                data=tracking.get_spatial_series(k).data[:],
            )
    if len(position):
        position = pd.DataFrame.from_dict(position)

        # retrieveing time support position if in epochs
        if "position_time_support" in nwbfile.intervals.keys():
            epochs = nwbfile.intervals["position_time_support"].to_dataframe()
            time_support = nap.IntervalSet(
                start=epochs["start_time"], end=epochs["stop_time"], time_units="s"
            )

        self.position = nap.TsdFrame(
            position, time_units="s", time_support=time_support
        )

    if nwbfile.epochs is not None:
        epochs = nwbfile.epochs.to_dataframe()
        # NWB is dumb and cannot take a single string for labels
        epochs["label"] = [epochs.loc[i, "tags"][0] for i in epochs.index]
        epochs = epochs.drop(labels="tags", axis=1)
        epochs = epochs.rename(columns={"start_time": "start", "stop_time": "end"})
        self.epochs = self._make_epochs(epochs)

        self.time_support = self._join_epochs(epochs, "s")

    io.close()

    return

save_nwb_intervals 

save_nwb_intervals(iset, name, description='')

Add epochs to the NWB file (e.g. ripples epochs) See pynwb.epoch.TimeIntervals

Parameters:

Name Type Description Default
iset IntervalSet

The intervalSet to save

 required
name str

The name in the nwb file

 required
Source code in pynapple/io/loader.py 
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def save_nwb_intervals(self, iset, name, description=""):
    """
    Add epochs to the NWB file (e.g. ripples epochs)
    See pynwb.epoch.TimeIntervals

    Parameters
    ----------
    iset : IntervalSet
        The intervalSet to save
    name : str
        The name in the nwb file
    """
    io = NWBHDF5IO(self.nwbfilepath, "r+")
    nwbfile = io.read()

    epochs = iset.as_units("s")
    time_intervals = TimeIntervals(name=name, description=description)
    for i in epochs.index:
        time_intervals.add_interval(
            start_time=epochs.loc[i, "start"],
            stop_time=epochs.loc[i, "end"],
            tags=str(i),
        )

    nwbfile.add_time_intervals(time_intervals)
    io.write(nwbfile)
    io.close()

    return

save_nwb_timeseries 

save_nwb_timeseries(tsd, name, description='')

Save timestamps in the NWB file (e.g. ripples time) with the time support. See pynwb.base.TimeSeries

Parameters:

Name Type Description Default
tsd TsdFrame

_

 required
name str

_

 required
description str

_

 ''
Source code in pynapple/io/loader.py 
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def save_nwb_timeseries(self, tsd, name, description=""):
    """
    Save timestamps in the NWB file (e.g. ripples time) with the time support.
    See pynwb.base.TimeSeries


    Parameters
    ----------
    tsd : TsdFrame
        _
    name : str
        _
    description : str, optional
        _
    """
    io = NWBHDF5IO(self.nwbfilepath, "r+")
    nwbfile = io.read()

    ts = TimeSeries(
        name=name,
        unit="s",
        data=tsd.values,
        timestamps=tsd.as_units("s").index.values,
    )

    time_support = TimeIntervals(
        name=name + "_timesupport", description="The time support of the object"
    )

    epochs = tsd.time_support.as_units("s")
    for i in epochs.index:
        time_support.add_interval(
            start_time=epochs.loc[i, "start"],
            stop_time=epochs.loc[i, "end"],
            tags=str(i),
        )
    nwbfile.add_time_intervals(time_support)
    nwbfile.add_acquisition(ts)
    io.write(nwbfile)
    io.close()

    return

load_nwb_intervals 

load_nwb_intervals(name)

Load epochs from the NWB file (e.g. 'ripples')

Parameters:

Name Type Description Default
name str

The name in the nwb file

 required
Source code in pynapple/io/loader.py 
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def load_nwb_intervals(self, name):
    """
    Load epochs from the NWB file (e.g. 'ripples')

    Parameters
    ----------
    name : str
        The name in the nwb file
    """
    io = NWBHDF5IO(self.nwbfilepath, "r")
    nwbfile = io.read()

    if name in nwbfile.intervals.keys():
        epochs = nwbfile.intervals[name].to_dataframe()
        isets = nap.IntervalSet(
            start=epochs["start_time"], end=epochs["stop_time"], time_units="s"
        )
        io.close()
        return isets
    else:
        io.close()
    return

load_nwb_timeseries 

load_nwb_timeseries(name)

Load timestamps in the NWB file (e.g. ripples time)

Parameters:

Name Type Description Default
name str

_

 required

Returns:

Type Description
Tsd

_
Source code in pynapple/io/loader.py 
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def load_nwb_timeseries(self, name):
    """
    Load timestamps in the NWB file (e.g. ripples time)

    Parameters
    ----------
    name : str
        _

    Returns
    -------
    Tsd
        _
    """
    io = NWBHDF5IO(self.nwbfilepath, "r")
    nwbfile = io.read()

    ts = nwbfile.acquisition[name]

    time_support = self.load_nwb_intervals(name + "_timesupport")

    tsd = nap.Tsd(
        t=ts.timestamps[:], d=ts.data[:], time_units="s", time_support=time_support
    )

    io.close()

    return tsd

__init__ 

__init__(path)

Parameters:

Name Type Description Default
path str

The path to the data.

 required
Source code in pynapple/io/cnmfe.py 
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def __init__(self, path):
    """

    Parameters
    ----------
    path : str
        The path to the data.
    """
    path = Path(path)
    self.basename = path.name

    super().__init__(path)

    self.load_cnmfe_nwb()

load_cnmfe_nwb 

load_cnmfe_nwb()

Load the calcium transient and spatial footprint from nwb

Parameters:

Name Type Description Default
path str

Path to the session

 required
Source code in pynapple/io/cnmfe.py 
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def load_cnmfe_nwb(self):
    """
    Load the calcium transient and spatial footprint from nwb

    Parameters
    ----------
    path : str
        Path to the session
    """
    io = NWBHDF5IO(self.nwbfilepath, "r")
    nwbfile = io.read()

    if "ophys" in nwbfile.processing.keys():
        data = nwbfile.processing["ophys"]["Fluorescence"][
            "RoiResponseSeries"
        ].data[:]
        t = nwbfile.processing["ophys"]["Fluorescence"][
            "RoiResponseSeries"
        ].timestamps[:]
        self.C = nap.TsdFrame(t=t, d=data)
        self.A = nwbfile.processing["ophys"]["ImageSegmentation"][
            "PlaneSegmentation"
        ]["image_mask"].data[:]

        io.close()
        return True
    else:
        io.close()
        return False