Plot a given trajectory under all available filters
plot_filter_graphs.RdThis function loads a CSV containing tracking data. Given a particular body-part, axis, and level of smoothing, the function plots the trajectory of the body-part along that axis.
Usage
plot_filter_graphs(
csv_or_path,
p_cutoff,
reference_distance = NA,
manual_scale_factor = NA,
fps = 2000,
fixed_baseline = 1,
y_threshold = 0.1,
savgol_window_length = 25,
savgol_filter_smoothing_multiplier = 3,
median_window_length = 25,
average_window_length = 25,
body_part = "center",
axis = "y"
)Arguments
- csv_or_path
Either a csv loaded as an R object, or the full path to that CSV.
- p_cutoff
The confidence value at which all tracked points below this threshold are replaced by linear interpolation between two higher-confidence points.
- reference_distance
The 'real-world-length' between your reference objects (can be in mm, cm, etc). If you indicate a
manual_scale_factor, this setting will be overrided by that factor.- manual_scale_factor
The 'real-world-length' to pixel conversion factor (i.e. millimeters/pixel). If you are using two reference points, you can ignore this parameter.
- fps
The frames per second of your CSV.
- fixed_baseline
The height (in units of choice) above the lowest y-axis position of the paw, used to determine the baseline for activity. the
y_thresholdparameter is used to set a baseline for this level of activity.- y_threshold
The threshold (in units of choice) above the fixed baseline at which the start and end time-points of activity are determined.
- savgol_window_length
The rolling window length of Savitzky-Golay filter smoothing to apply to your tracking trajectory.
- median_window_length
The rolling window length of median filter smoothing to apply to your tracking trajectory.
- average_window_length
The rolling window length of average filter smoothing to apply to your tracking trajectory.
- body_part
The body_part you wish to plot.
- axis
The axis you wish to plot.