Package index

Remove observations of poor quality

These functions ensure that your data is ready for analysis.

filter_na_confidence()

Filter low-confidence values in a dataset

filter_na_speed()

Filter values by speed threshold

filter_na_roi()

Filter coordinates outside a region of interest (ROI)

filter_na_range()

Filter values outside a range to NA

Interpolate over missing values

These functions ensure that your data is ready for analysis.

replace_na()

Replace Missing Values Using Various Methods

replace_na_linear()

Replace Missing Values Using Linear Interpolation

replace_na_locf()

Replace Missing Values Using Last Observation Carried Forward

replace_na_spline()

Replace Missing Values Using Spline Interpolation

replace_na_stine()

Replace Missing Values Using Stineman Interpolation

replace_na_value()

Replace Missing Values with a Constant Value

Smoothing/filtering functions

These functions ensure that your data is ready for analysis.

filter_aniframe() experimental

Smooth Movement Data

filter_lowpass()

Apply Butterworth Lowpass Filter to Signal

filter_highpass()

Apply Butterworth Highpass Filter to Signal

filter_lowpass_fft()

Apply FFT-based Lowpass Filter to Signal

filter_highpass_fft()

Apply FFT-based Highpass Filter to Signal

filter_kalman()

Kalman Filter for Regular Time Series

filter_kalman_irregular()

Kalman Filter for Irregular Time Series with Optional Resampling

filter_rollmean()

Apply Rolling Mean Filter

filter_rollmedian()

Apply Rolling Median Filter

filter_sgolay()

Apply Savitzky-Golay Filter to Movement Data

Other functions

These functions ensure that your data is ready for analysis.

find_peaks()

Find Peaks in Time Series Data

find_troughs()

Find Troughs in Time Series Data