What should we include in our summary statistics? Should we always provide both central estimates and uncertainty estimates? Here's a list of potential ideas.
Also, I think it would make sense to have the ability to generate different summaries that require different information, something along the lines of:
Kinematics (single individual, doesn't care about absolute position)
Criteria: Single individual, independent of external world
Kinematics for all keypoints individually
Kinematics relative to other keypoints
Navigation
Criteria: Relative to external object
Types of external objects:
Arena/enclosure
Distance to walls
Distance to nearest corner
Zone (make some defaults for square and round arenas)
Heading relative to nearest wall
Object
Distance to object
Heading relative to object
Social
Criteria: Relative to other individual
Keypoint-pairs of interests (one on self, one on other individual)
Distance between keypoints
Whole-individual
Relative speed
Relative heading
Minimum distance between any two keypoints
For position, pose and social, we need to think of a good way of making a general solution that handles relational information.
Kinematics
Translation
[ ] distance Distance covered since last timepoint
I think it's worth considering whether these should all be possible to use. E.g. velocities will necessarily not follow a Gaussian, so median + a measure of dispersion (MAD or some range) will likely always be preferable.
Central tendency (CT)
[ ] Mean
[ ] Median
[ ] Mode
Dispersion (D)
[ ] SD
[ ] MAD
Other
[ ] Total / sum
Movement metrics
Translation
[ ] distance, total
[ ] v_translation, CT + D
[ ] a_translation, CT + D
Rotation
[ ] rotation, total
[ ] v_rotation, CT + D
[ ] a_rotation, CT + D
Combinations
There are a bunch of measures that basically describe the path straightness, which have gathered interest in relation to search/movement patterns in particular (random walks, Levy walks, etc.). Different authors use different terms for them (path straightness, sinuosity, tortuosity), so I think it's best to pinpoint the first paper to describe each metric and use the author and year as their name.
[ ] total_distance / shortest line between beginning and end
[ ] shortest line between beginning and end / total_distance
[ ] 1 - (shortest line between beginning and end / total_distance)
[ ] CT + D of something that's calculated for each frame
Other?
Are there other things I've missed that would be of interest?
Also happy to think of relational summaries (e.g. distance between two individuals or an individual and an object, or time inside ROI, distance between keypoints), but maybe that would best be its own function.
What should we include in our summary statistics? Should we always provide both central estimates and uncertainty estimates? Here's a list of potential ideas.
Also, I think it would make sense to have the ability to generate different summaries that require different information, something along the lines of:
For position, pose and social, we need to think of a good way of making a general solution that handles relational information.
Kinematics
Translation
distanceDistance covered since last timepoints_translationInstantaneous translational speedv_translationInstantaneous translational velocity (can be different froms_translationwhen you have a heading too)a_translationInstantaneous translational accelerationRotation
headingHeading of animal (or vector between two keypoints)directionDirection of movement since last timepointrotationChange of direction since last timepoints_rotationInstantaneous rotational speedv_rotationInstantaneous rotational velocitya_rotationInstantaneous rotational accelerationSummary statistics
See e.g. Joo et al (2019) for a wide range of possibilities. Also in the MARS paper https://elifesciences.org/articles/63720.
Statistical measures
I think it's worth considering whether these should all be possible to use. E.g. velocities will necessarily not follow a Gaussian, so median + a measure of dispersion (MAD or some range) will likely always be preferable.
Movement metrics
Translation
distance, totalv_translation, CT + Da_translation, CT + DRotation
rotation, totalv_rotation, CT + Da_rotation, CT + DCombinations
There are a bunch of measures that basically describe the path straightness, which have gathered interest in relation to search/movement patterns in particular (random walks, Levy walks, etc.). Different authors use different terms for them (path straightness, sinuosity, tortuosity), so I think it's best to pinpoint the first paper to describe each metric and use the author and year as their name.
total_distance/ shortest line between beginning and endtotal_distancetotal_distance)Other?
Are there other things I've missed that would be of interest? Also happy to think of relational summaries (e.g. distance between two individuals or an individual and an object, or time inside ROI, distance between keypoints), but maybe that would best be its own function.