Package index • aniprocess

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)

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