This will first calculate the geodesic distance of each cell to the waypoint. This distance is used as a weight
project_waypoints(
trajectory,
space,
waypoints = select_waypoints(trajectory),
trajectory_projection_sd = sum(trajectory$milestone_network$length) * 0.05
)A matrix in which the waypoints (rows) were projected into a new space defined by the same number of dimensions (columns) as in the space argument
The trajectory as created by infer_trajectory() or add_trajectory()
A matrix with cells in rows and different dimensions in the columns. This is typically an expression matrix or a dimensionality reduction
A set of waypoints, which can be created by select_waypoints(). It is a list containing:
waypoints: a dataframe containing in the very least the waypoint_id
milestone_percentages: the positions of waypoints withing the trajectory
geodesic_distances: matrix with precalculated geodesic distances between waypoints (rows) and cells (columns), optional
The standard deviation of the gaussian kernel