interpolate_intervals#

pypillometry.interpolate_intervals(intervals, eyes=[], variables=[], method='linear', margin=(-20, 20), store_as_suffix=None, policy='default')#

Pipeline step for interpolate_intervals() (d | pp.interpolate_intervals(...)).

Interpolate data within specified intervals.

This function replaces data within the specified intervals with interpolated values based on boundary points outside each interval. The interpolated samples get the "interpolated" layer (see get_interpolated()), so they are used under the default mask policy and masked under the "strict" one (see mask()). Intervals without usable boundary points on both sides are skipped with a warning.

Parameters:

  • intervals (Intervals, Epochs, list of tuple or dict) –

    Either:

    • A single Intervals (or Epochs) object or a list of (start, end) tuples (in ms, or with units): applied to all specified eyes/variables

    • A dict of Intervals (or Epochs): keys like “left_pupil”, “right_x”, etc. When dict is provided, eyes and variables are ignored.

  • eyes (str or list of str, optional) – eye(s) to interpolate; if empty, all available eyes. Ignored if intervals is a dict.

  • variables (str or list of str, optional) – variable(s) to interpolate; if empty, all available variables. Ignored if intervals is a dict.

  • method (str, default "linear") – Interpolation method. Options: “linear”, “nearest”, “zero”, “slinear”, “quadratic”, “cubic”, “previous”, “next”. Passed to scipy.interpolate.interp1d.

  • margin (tuple, default (-20, 20)) – Time window (in ms) before and after the interval to collect boundary points for interpolation, relative to the start and end of each interval: points are taken from start + margin[0] to the start and from the end to end + margin[1], so margin[0] must be <= 0 and margin[1] >= 0. Samples that are unusable under policy (masked or NaN) are not used. For higher-order methods like “cubic” or “quadratic”, more boundary points from this margin are used to fit the interpolation curve.

  • store_as_suffix (str or None, default None) – If None, replace the original data. If a string, store interpolated data in a new variable with this suffix (e.g., “_interp” creates “left_pupil_interp”).

  • policy (str, MaskPolicy or list of str) – mask policy that decides which boundary points are usable (see mask()); default "default"

  • inplace (bool or None, optional) – if True, make change in-place and return the object; if False, make and return copy before making changes; if None, use the object-level setting (specified in the constructor)

Return type:

EyeData

Returns:

The object with interpolated data (self or a copy, depending on inplace).

See also

mask_intervals

Apply intervals as masks without interpolation

get_blinks

Retrieve stored blink intervals

Examples

Interpolate blinks for left eye pupil data:

>>> import pypillometry as pp
>>> d = pp.get_example_data("rlmw_002_short").pupil.blinks_detect()
>>> blinks = d.get_blinks(eyes="left", variables="pupil")["left_pupil"]
>>> d1 = d.interpolate_intervals(blinks, eyes=["left"], variables=["pupil"],
...                              inplace=False)

Interpolate using a dict of intervals:

>>> blinks = d.get_blinks()  # returns dict
>>> d2 = d.interpolate_intervals(blinks, inplace=False)

Store interpolated data in a new variable:

>>> d3 = d.interpolate_intervals(blinks, store_as_suffix="_interp",
...                              inplace=False)
>>> "left_pupil_interp" in d3.data
True

Use cubic interpolation with wider margin:

>>> d4 = d.interpolate_intervals(blinks, method="cubic", margin=(-50, 50),
...                              inplace=False)