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common_interval.py

IntervalList

Bases: SpyglassMixin, Manual

Source code in src/spyglass/common/common_interval.py 
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@schema
class IntervalList(SpyglassMixin, dj.Manual):
    definition = """
    # Time intervals used for analysis
    -> Session
    interval_list_name: varchar(170)  # descriptive name of this interval list
    ---
    valid_times: longblob  # numpy array with start/end times for each interval
    pipeline = "": varchar(64)  # type of interval list
    """

    # See #630, #664. Excessive key length.

    @classmethod
    def insert_from_nwbfile(cls, nwbf: NWBFile, *, nwb_file_name: str):
        """Add each entry in the NWB file epochs table to the IntervalList.

        The interval list name for each epoch is set to the first tag for the
        epoch. If the epoch has no tags, then 'interval_x' will be used as the
        interval list name, where x is the index (0-indexed) of the epoch in the
        epochs table. The start time and stop time of the epoch are stored in
        the valid_times field as a numpy array of [start time, stop time] for
        each epoch.

        Parameters
        ----------
        nwbf : pynwb.NWBFile
            The source NWB file object.
        nwb_file_name : str
            The file name of the NWB file, used as a primary key to the Session
            table.
        """
        if nwbf.epochs is None:
            logger.info("No epochs found in NWB file.")
            return

        epochs = nwbf.epochs.to_dataframe()

        # Create a list of dictionaries to insert
        epoch_inserts = epochs.apply(
            lambda epoch_data: {
                "nwb_file_name": nwb_file_name,
                "interval_list_name": (
                    epoch_data.tags[0]
                    if epoch_data.tags
                    else f"interval_{epoch_data.name}"
                ),
                "valid_times": np.asarray(
                    [[epoch_data.start_time, epoch_data.stop_time]]
                ),
            },
            axis=1,
        ).tolist()

        cls.insert(epoch_inserts, skip_duplicates=True)

    def plot_intervals(self, figsize=(20, 5), return_fig=False):
        """Plot the intervals in the interval list."""
        interval_list = pd.DataFrame(self)
        fig, ax = plt.subplots(figsize=figsize)
        interval_count = 0
        for row in interval_list.itertuples(index=False):
            for interval in row.valid_times:
                ax.plot(interval, [interval_count, interval_count])
                ax.scatter(
                    interval,
                    [interval_count, interval_count],
                    alpha=0.8,
                    zorder=2,
                )
            interval_count += 1
        ax.set_yticks(np.arange(interval_list.shape[0]))
        ax.set_yticklabels(interval_list.interval_list_name)
        ax.set_xlabel("Time [s]")
        ax.grid(True)
        if return_fig:
            return fig

    def plot_epoch_pos_raw_intervals(self, figsize=(20, 5), return_fig=False):
        """Plot an epoch's position, raw data, and valid times intervals."""
        interval_list = pd.DataFrame(self)
        fig, ax = plt.subplots(figsize=(30, 3))

        raw_data_valid_times = interval_list.loc[
            interval_list.interval_list_name == "raw data valid times"
        ].valid_times
        interval_y = 1

        for interval in np.asarray(raw_data_valid_times)[0]:
            ax.plot(interval, [interval_y, interval_y])
            ax.scatter(interval, [interval_y, interval_y], alpha=0.8, zorder=2)

        epoch_valid_times = (
            interval_list.set_index("interval_list_name")
            .filter(regex=r"^[0-9]", axis=0)
            .valid_times
        )
        interval_y = 2
        for epoch, valid_times in zip(
            epoch_valid_times.index, epoch_valid_times
        ):
            for interval in valid_times:
                ax.plot(interval, [interval_y, interval_y])
                ax.scatter(
                    interval, [interval_y, interval_y], alpha=0.8, zorder=2
                )
                ax.text(
                    interval[0] + np.diff(interval)[0] / 2,
                    interval_y,
                    epoch,
                    ha="center",
                    va="bottom",
                )

        pos_valid_times = (
            interval_list.set_index("interval_list_name")
            .filter(regex=r"^pos \d+ valid times$", axis=0)
            .valid_times
        ).sort_index(key=lambda index: [int(name.split()[1]) for name in index])
        interval_y = 0
        for epoch, valid_times in zip(pos_valid_times.index, pos_valid_times):
            for interval in valid_times:
                ax.plot(interval, [interval_y, interval_y])
                ax.scatter(
                    interval, [interval_y, interval_y], alpha=0.8, zorder=2
                )
                ax.text(
                    interval[0] + np.diff(interval)[0] / 2,
                    interval_y,
                    epoch.replace(" valid times", ""),
                    ha="center",
                    va="bottom",
                )

        ax.set_ylim((-0.25, 2.25))
        ax.set_yticks(np.arange(3))
        ax.set_yticklabels(["pos valid times", "raw data valid times", "epoch"])
        ax.set_xlabel("Time [s]")
        ax.grid(True)
        if return_fig:
            return fig

    def nightly_cleanup(self, dry_run=True):
        """Clean up orphaned IntervalList entries."""
        orphans = self - get_child_tables(self)
        if dry_run:
            return orphans
        orphans.super_delete(warn=False)

insert_from_nwbfile(nwbf, *, nwb_file_name) classmethod

Add each entry in the NWB file epochs table to the IntervalList.

The interval list name for each epoch is set to the first tag for the epoch. If the epoch has no tags, then 'interval_x' will be used as the interval list name, where x is the index (0-indexed) of the epoch in the epochs table. The start time and stop time of the epoch are stored in the valid_times field as a numpy array of [start time, stop time] for each epoch.

Parameters:

Name Type Description Default
nwbf NWBFile

The source NWB file object.

 required
nwb_file_name str

The file name of the NWB file, used as a primary key to the Session table.

 required
Source code in src/spyglass/common/common_interval.py 
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@classmethod
def insert_from_nwbfile(cls, nwbf: NWBFile, *, nwb_file_name: str):
    """Add each entry in the NWB file epochs table to the IntervalList.

    The interval list name for each epoch is set to the first tag for the
    epoch. If the epoch has no tags, then 'interval_x' will be used as the
    interval list name, where x is the index (0-indexed) of the epoch in the
    epochs table. The start time and stop time of the epoch are stored in
    the valid_times field as a numpy array of [start time, stop time] for
    each epoch.

    Parameters
    ----------
    nwbf : pynwb.NWBFile
        The source NWB file object.
    nwb_file_name : str
        The file name of the NWB file, used as a primary key to the Session
        table.
    """
    if nwbf.epochs is None:
        logger.info("No epochs found in NWB file.")
        return

    epochs = nwbf.epochs.to_dataframe()

    # Create a list of dictionaries to insert
    epoch_inserts = epochs.apply(
        lambda epoch_data: {
            "nwb_file_name": nwb_file_name,
            "interval_list_name": (
                epoch_data.tags[0]
                if epoch_data.tags
                else f"interval_{epoch_data.name}"
            ),
            "valid_times": np.asarray(
                [[epoch_data.start_time, epoch_data.stop_time]]
            ),
        },
        axis=1,
    ).tolist()

    cls.insert(epoch_inserts, skip_duplicates=True)

plot_intervals(figsize=(20, 5), return_fig=False)

Plot the intervals in the interval list.

Source code in src/spyglass/common/common_interval.py 
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def plot_intervals(self, figsize=(20, 5), return_fig=False):
    """Plot the intervals in the interval list."""
    interval_list = pd.DataFrame(self)
    fig, ax = plt.subplots(figsize=figsize)
    interval_count = 0
    for row in interval_list.itertuples(index=False):
        for interval in row.valid_times:
            ax.plot(interval, [interval_count, interval_count])
            ax.scatter(
                interval,
                [interval_count, interval_count],
                alpha=0.8,
                zorder=2,
            )
        interval_count += 1
    ax.set_yticks(np.arange(interval_list.shape[0]))
    ax.set_yticklabels(interval_list.interval_list_name)
    ax.set_xlabel("Time [s]")
    ax.grid(True)
    if return_fig:
        return fig

plot_epoch_pos_raw_intervals(figsize=(20, 5), return_fig=False)

Plot an epoch's position, raw data, and valid times intervals.

Source code in src/spyglass/common/common_interval.py 
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def plot_epoch_pos_raw_intervals(self, figsize=(20, 5), return_fig=False):
    """Plot an epoch's position, raw data, and valid times intervals."""
    interval_list = pd.DataFrame(self)
    fig, ax = plt.subplots(figsize=(30, 3))

    raw_data_valid_times = interval_list.loc[
        interval_list.interval_list_name == "raw data valid times"
    ].valid_times
    interval_y = 1

    for interval in np.asarray(raw_data_valid_times)[0]:
        ax.plot(interval, [interval_y, interval_y])
        ax.scatter(interval, [interval_y, interval_y], alpha=0.8, zorder=2)

    epoch_valid_times = (
        interval_list.set_index("interval_list_name")
        .filter(regex=r"^[0-9]", axis=0)
        .valid_times
    )
    interval_y = 2
    for epoch, valid_times in zip(
        epoch_valid_times.index, epoch_valid_times
    ):
        for interval in valid_times:
            ax.plot(interval, [interval_y, interval_y])
            ax.scatter(
                interval, [interval_y, interval_y], alpha=0.8, zorder=2
            )
            ax.text(
                interval[0] + np.diff(interval)[0] / 2,
                interval_y,
                epoch,
                ha="center",
                va="bottom",
            )

    pos_valid_times = (
        interval_list.set_index("interval_list_name")
        .filter(regex=r"^pos \d+ valid times$", axis=0)
        .valid_times
    ).sort_index(key=lambda index: [int(name.split()[1]) for name in index])
    interval_y = 0
    for epoch, valid_times in zip(pos_valid_times.index, pos_valid_times):
        for interval in valid_times:
            ax.plot(interval, [interval_y, interval_y])
            ax.scatter(
                interval, [interval_y, interval_y], alpha=0.8, zorder=2
            )
            ax.text(
                interval[0] + np.diff(interval)[0] / 2,
                interval_y,
                epoch.replace(" valid times", ""),
                ha="center",
                va="bottom",
            )

    ax.set_ylim((-0.25, 2.25))
    ax.set_yticks(np.arange(3))
    ax.set_yticklabels(["pos valid times", "raw data valid times", "epoch"])
    ax.set_xlabel("Time [s]")
    ax.grid(True)
    if return_fig:
        return fig

nightly_cleanup(dry_run=True)

Clean up orphaned IntervalList entries.

Source code in src/spyglass/common/common_interval.py 
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def nightly_cleanup(self, dry_run=True):
    """Clean up orphaned IntervalList entries."""
    orphans = self - get_child_tables(self)
    if dry_run:
        return orphans
    orphans.super_delete(warn=False)

intervals_by_length(interval_list, min_length=0.0, max_length=10000000000.0)

Select intervals of certain lengths from an interval list.

Parameters:

Name Type Description Default
interval_list array_like

Each element is (start time, stop time), i.e. an interval in seconds.

 required
min_length float

Minimum interval length in seconds. Defaults to 0.0.

 0.0
max_length float

Maximum interval length in seconds. Defaults to 1e10.

 10000000000.0
Source code in src/spyglass/common/common_interval.py 
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def intervals_by_length(interval_list, min_length=0.0, max_length=1e10):
    """Select intervals of certain lengths from an interval list.

    Parameters
    ----------
    interval_list : array_like
        Each element is (start time, stop time), i.e. an interval in seconds.
    min_length : float, optional
        Minimum interval length in seconds. Defaults to 0.0.
    max_length : float, optional
        Maximum interval length in seconds. Defaults to 1e10.
    """
    lengths = np.ravel(np.diff(interval_list))
    return interval_list[
        np.logical_and(lengths > min_length, lengths < max_length)
    ]

interval_list_contains_ind(interval_list, timestamps)

Find indices of list of timestamps contained in an interval list.

Parameters:

Name Type Description Default
interval_list array_like

Each element is (start time, stop time), i.e. an interval in seconds.

 required
timestamps array_like
required
Source code in src/spyglass/common/common_interval.py 
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def interval_list_contains_ind(interval_list, timestamps):
    """Find indices of list of timestamps contained in an interval list.

    Parameters
    ----------
    interval_list : array_like
        Each element is (start time, stop time), i.e. an interval in seconds.
    timestamps : array_like
    """
    ind = []
    for interval in interval_list:
        ind += np.ravel(
            np.argwhere(
                np.logical_and(
                    timestamps >= interval[0], timestamps <= interval[1]
                )
            )
        ).tolist()
    return np.asarray(ind)

interval_list_contains(interval_list, timestamps)

Find timestamps that are contained in an interval list.

Parameters:

Name Type Description Default
interval_list array_like

Each element is (start time, stop time), i.e. an interval in seconds.

 required
timestamps array_like
required
Source code in src/spyglass/common/common_interval.py 
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def interval_list_contains(interval_list, timestamps):
    """Find timestamps that are contained in an interval list.

    Parameters
    ----------
    interval_list : array_like
        Each element is (start time, stop time), i.e. an interval in seconds.
    timestamps : array_like
    """
    ind = []
    for interval in interval_list:
        ind += np.ravel(
            np.argwhere(
                np.logical_and(
                    timestamps >= interval[0], timestamps <= interval[1]
                )
            )
        ).tolist()
    return timestamps[ind]

interval_list_excludes_ind(interval_list, timestamps)

Find indices of timestamps that are not contained in an interval list.

Parameters:

Name Type Description Default
interval_list array_like

Each element is (start time, stop time), i.e. an interval in seconds.

 required
timestamps array_like
required
Source code in src/spyglass/common/common_interval.py 
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def interval_list_excludes_ind(interval_list, timestamps):
    """Find indices of timestamps that are not contained in an interval list.

    Parameters
    ----------
    interval_list : array_like
        Each element is (start time, stop time), i.e. an interval in seconds.
    timestamps : array_like
    """

    contained_inds = interval_list_contains_ind(interval_list, timestamps)
    return np.setdiff1d(np.arange(len(timestamps)), contained_inds)

interval_list_excludes(interval_list, timestamps)

Find timestamps that are not contained in an interval list.

Parameters:

Name Type Description Default
interval_list array_like

Each element is (start time, stop time), i.e. an interval in seconds.

 required
timestamps array_like
required
Source code in src/spyglass/common/common_interval.py 
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def interval_list_excludes(interval_list, timestamps):
    """Find timestamps that are not contained in an interval list.

    Parameters
    ----------
    interval_list : array_like
        Each element is (start time, stop time), i.e. an interval in seconds.
    timestamps : array_like
    """
    contained_times = interval_list_contains(interval_list, timestamps)
    return np.setdiff1d(timestamps, contained_times)

consolidate_intervals(interval_list)

Consolidate overlapping intervals in an interval list.

Source code in src/spyglass/common/common_interval.py 
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def consolidate_intervals(interval_list):
    """Consolidate overlapping intervals in an interval list."""
    if interval_list.ndim == 1:
        interval_list = np.expand_dims(interval_list, 0)
    else:
        interval_list = interval_list[np.argsort(interval_list[:, 0])]
        interval_list = reduce(_union_concat, interval_list)
        # the following check is needed in the case where the interval list is a
        # single element (behavior of reduce)
        if interval_list.ndim == 1:
            interval_list = np.expand_dims(interval_list, 0)
    return interval_list

interval_list_intersect(interval_list1, interval_list2, min_length=0)

Finds the intersections between two interval lists

Each interval is (start time, stop time)

Parameters:

Name Type Description Default
interval_list1 np.array, (N,2) where N = number of intervals
required
interval_list2 np.array, (N,2) where N = number of intervals
required
min_length float, optional.

Minimum length of intervals to include, default 0

 0

Returns:

Name Type Description
interval_list (array, (N, 2))
Source code in src/spyglass/common/common_interval.py 
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def interval_list_intersect(interval_list1, interval_list2, min_length=0):
    """Finds the intersections between two interval lists

    Each interval is (start time, stop time)

    Parameters
    ----------
    interval_list1 : np.array, (N,2) where N = number of intervals
    interval_list2 : np.array, (N,2) where N = number of intervals
    min_length : float, optional.
        Minimum length of intervals to include, default 0

    Returns
    -------
    interval_list: np.array, (N,2)
    """

    # Consolidate interval lists to disjoint int'ls by sorting & applying union
    interval_list1 = consolidate_intervals(interval_list1)
    interval_list2 = consolidate_intervals(interval_list2)

    # then do pairwise comparison and collect intersections
    intersecting_intervals = [
        _intersection(interval2, interval1)
        for interval2 in interval_list2
        for interval1 in interval_list1
        if _intersection(interval2, interval1) is not None
    ]

    # if no intersection, then return an empty list
    if not intersecting_intervals:
        return []

    intersecting_intervals = np.asarray(intersecting_intervals)
    intersecting_intervals = intersecting_intervals[
        np.argsort(intersecting_intervals[:, 0])
    ]

    return intervals_by_length(intersecting_intervals, min_length=min_length)

union_adjacent_index(interval1, interval2)

Union index-adjacent intervals. If not adjacent, just concatenate.

e.g. [a,b] and [b+1, c] is converted to [a,c]

Parameters:

Name Type Description Default
interval1 array
required
interval2 array
required
Source code in src/spyglass/common/common_interval.py 
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def union_adjacent_index(interval1, interval2):
    """Union index-adjacent intervals. If not adjacent, just concatenate.

    e.g. [a,b] and [b+1, c] is converted to [a,c]

    Parameters
    ----------
    interval1 : np.array
    interval2 : np.array
    """
    interval1 = np.atleast_2d(interval1)
    interval2 = np.atleast_2d(interval2)

    if (
        interval1[-1][1] + 1 == interval2[0][0]
        or interval2[0][1] + 1 == interval1[-1][0]
    ):
        x = np.array(
            [
                [
                    np.min([interval1[-1][0], interval2[0][0]]),
                    np.max([interval1[-1][1], interval2[0][1]]),
                ]
            ]
        )
        return np.concatenate((interval1[:-1], x), axis=0)
    else:
        return np.concatenate((interval1, interval2), axis=0)

interval_list_union(interval_list1, interval_list2, min_length=0.0, max_length=10000000000.0)

Finds the union (all times in one or both) for two interval lists

Parameters:

Name Type Description Default
interval_list1 ndarray

The first interval list [start, stop]

 required
interval_list2 ndarray

The second interval list [start, stop]

 required
min_length float

Minimum length of interval for inclusion in output, default 0.0

 0.0
max_length float

Maximum length of interval for inclusion in output, default 1e10

 10000000000.0

Returns:

Type Description
ndarray

Array of intervals [start, stop]
Source code in src/spyglass/common/common_interval.py 
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def interval_list_union(
    interval_list1: np.ndarray,
    interval_list2: np.ndarray,
    min_length: float = 0.0,
    max_length: float = 1e10,
) -> np.ndarray:
    """Finds the union (all times in one or both) for two interval lists

    Parameters
    ----------
    interval_list1 : np.ndarray
        The first interval list [start, stop]
    interval_list2 : np.ndarray
        The second interval list [start, stop]
    min_length : float, optional
        Minimum length of interval for inclusion in output, default 0.0
    max_length : float, optional
        Maximum length of interval for inclusion in output, default 1e10

    Returns
    -------
    np.ndarray
        Array of intervals [start, stop]
    """

    il1, il1_start_end = _parallel_union(interval_list1)
    il2, il2_start_end = _parallel_union(interval_list2)

    # Concatenate the two lists so we can resort the intervals and apply the
    # same sorting to the start-end arrays
    combined_intervals = np.concatenate((il1, il2))
    ss = np.concatenate((il1_start_end, il2_start_end))
    sort_ind = np.argsort(combined_intervals)
    combined_intervals = combined_intervals[sort_ind]

    # a cumulative sum of 1 indicates the beginning of a joint interval; a
    # cumulative sum of 0 indicates the end
    union_starts = np.ravel(np.array(np.where(np.cumsum(ss[sort_ind]) == 1)))
    union_stops = np.ravel(np.array(np.where(np.cumsum(ss[sort_ind]) == 0)))
    union = [
        [combined_intervals[start], combined_intervals[stop]]
        for start, stop in zip(union_starts, union_stops)
    ]

    return np.asarray(union)

interval_list_censor(interval_list, timestamps)

Returns new interval list that starts/ends at first/last timestamp

Parameters:

Name Type Description Default
interval_list numpy array of intervals [start, stop]

interval list from IntervalList valid times

 required
timestamps numpy array or list
required

Returns:

Type Description
interval_list (numpy array of intervals [start, stop])
Source code in src/spyglass/common/common_interval.py 
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def interval_list_censor(interval_list, timestamps):
    """Returns new interval list that starts/ends at first/last timestamp

    Parameters
    ----------
    interval_list : numpy array of intervals [start, stop]
        interval list from IntervalList valid times
    timestamps : numpy array or list

    Returns
    -------
    interval_list (numpy array of intervals [start, stop])
    """
    # check that all timestamps are in the interval list
    if len(interval_list_contains_ind(interval_list, timestamps)) != len(
        timestamps
    ):
        raise ValueError("Interval_list must contain all timestamps")

    timestamps_interval = np.asarray([[timestamps[0], timestamps[-1]]])
    return interval_list_intersect(interval_list, timestamps_interval)

interval_from_inds(list_frames)

Converts a list of indices to a list of intervals.

e.g. [2,3,4,6,7,8,9,10] -> [[2,4],[6,10]]

Parameters:

Name Type Description Default
list_frames array_like of int
required
Source code in src/spyglass/common/common_interval.py 
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def interval_from_inds(list_frames):
    """Converts a list of indices to a list of intervals.

    e.g. [2,3,4,6,7,8,9,10] -> [[2,4],[6,10]]

    Parameters
    ----------
    list_frames : array_like of int
    """
    list_frames = np.unique(list_frames)
    interval_list = []
    for key, group in itertools.groupby(
        enumerate(list_frames), lambda t: t[1] - t[0]
    ):
        group = list(group)
        interval_list.append([group[0][1], group[-1][1]])
    return np.asarray(interval_list)

interval_set_difference_inds(intervals1, intervals2)

e.g. intervals1 = [(0, 5), (8, 10)] intervals2 = [(1, 2), (3, 4), (6, 9)]

result = [(0, 1), (4, 5), (9, 10)]

Parameters:

Name Type Description Default
intervals1 _type_

description

 required
intervals2 _type_

description

 required

Returns:

Type Description
_type_

description
Source code in src/spyglass/common/common_interval.py 
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def interval_set_difference_inds(intervals1, intervals2):
    """
    e.g.
    intervals1 = [(0, 5), (8, 10)]
    intervals2 = [(1, 2), (3, 4), (6, 9)]

    result = [(0, 1), (4, 5), (9, 10)]

    Parameters
    ----------
    intervals1 : _type_
        _description_
    intervals2 : _type_
        _description_

    Returns
    -------
    _type_
        _description_
    """
    result = []
    i = j = 0
    while i < len(intervals1) and j < len(intervals2):
        if intervals1[i][1] <= intervals2[j][0]:
            result.append(intervals1[i])
            i += 1
        elif intervals2[j][1] <= intervals1[i][0]:
            j += 1
        else:
            if intervals1[i][0] < intervals2[j][0]:
                result.append((intervals1[i][0], intervals2[j][0]))
            if intervals1[i][1] > intervals2[j][1]:
                intervals1[i] = (intervals2[j][1], intervals1[i][1])
                j += 1
            else:
                i += 1
    result += intervals1[i:]
    return result

interval_list_complement(intervals1, intervals2, min_length=0.0)

Finds intervals in intervals1 that are not in intervals2

Parameters:

Name Type Description Default
min_length float

Minimum interval length in seconds. Defaults to 0.0.

 0.0
Source code in src/spyglass/common/common_interval.py 
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def interval_list_complement(intervals1, intervals2, min_length=0.0):
    """
    Finds intervals in intervals1 that are not in intervals2

    Parameters
    ----------
    min_length : float, optional
        Minimum interval length in seconds. Defaults to 0.0.
    """

    result = []

    for start1, end1 in intervals1:
        subtracted = [(start1, end1)]

        for start2, end2 in intervals2:
            new_subtracted = []

            for s, e in subtracted:
                if start2 <= s and e <= end2:
                    continue

                if e <= start2 or end2 <= s:
                    new_subtracted.append((s, e))
                    continue

                if start2 > s:
                    new_subtracted.append((s, start2))

                if end2 < e:
                    new_subtracted.append((end2, e))

            subtracted = new_subtracted

        result.extend(subtracted)

    return intervals_by_length(
        np.asarray(result), min_length=min_length, max_length=1e100
    )