Function reference • flapper

All functions
`ac()`	The acoustic-container (AC) algorithm
`acdc()`	The acoustic-container depth-contour (ACDC) algorithm
`acdc_access_dat()` `acdc_access_timesteps()` `acdc_access_maps()`	Short-cuts to elements of an `"acdc_record"` object
`acdc_animate_record()`	Create a html animation of the AC/DC algorithm(s)
`acdc_archive-class`	"acdc-archive" class
`acdc_plot_record()`	Plot time-specific maps from the AC/DC algorithm(s)
`acdc_plot_trace()`	Plot AC* container dynamics
`acdc_record-class`	"acdc_record" class
`acdc_simplify()`	Simplify the outputs of the AC/DC algorithms
`acs_setup_containers()`	Setup the detection containers required for the AC* algorithm(s)
`acs_setup_detection_kernels()`	Setup detection probability kernels for the AC* algorithm(s)
`acs_setup_mobility()`	Examine the constant `mobility' assumption of the AC* algorithm(s)
`assemble_sentinel_counts()`	Assemble counts of transmissions/detections from sentinel tags
`buffer_and_crop()`	Buffer and crop a spatial object
`cells_from_val()`	Obtain a RasterLayer or the cells of RasterLayer that are equal to or lie within a range of specified values
`cl_lapply()` `cl_check()` `cl_cores()` `cl_chunks()` `cl_export()` `cl_stop()`	Parallelisation helpers
`coa()`	The centres of activity (COA) algorithm
`coa_setup_delta_t()`	Suggest time intervals over which to calculate centres of activity
`crop_from_click()`	Interactively crop a `raster`
`dat_acdc`	Example ACDC algorithm output
`dat_acoustics`	Example passive acoustic telemetry detections dataset
`dat_archival`	Example archival dataset
`dat_coast`	The coastline around the MEFS Firth of Lorn acoustic array
`dat_containers`	Example detection containers from `acs_setup_containers`
`dat_dc`	Example DC algorithm output
`dat_dcpf_histories`	Example DCPF algorithm output: particle histories
`dat_dcpf_paths`	Example DCPF algorithm output: reconstructed paths
`dat_gebco`	The bathymetry around the MEFS Firth of Lorn acoustic array
`dat_ids`	Example tagged individuals dataset
`dat_moorings`	Example passive acoustic telemetry receiver moorings dataset
`dat_sentinel`	Example sentinel tag range testing dataset
`dc()`	The depth-contour (DC) algorithm
`dcq()`	The `quick' depth-contour (DCQ) algorithm
`dist_btw_clicks()`	Calculate the distance between sequential mouse clicks on a map
`dist_btw_points_3d()`	Calculate the Euclidean distance(s) between points in three-dimensional space.
`dist_btw_receivers()`	Compute Euclidean distances between receivers
`dist_over_surface()`	Calculate the total distance of a path over a three-dimensional surface
`eval_by_kud()`	Evaluate movement path estimates using kernel utilisation distributions
`flapper-tips-parallel`	Parallelisation in `flapper`
`flapper`	`flapper`: Routines for the analysis of passive acoustic telemetry data
`flapper_run_parallel` `flapper_run_slow`	Global example controls
`get_detection_area_sum()`	Calculate the total area sampled by acoustic receivers
`get_detection_area_ts()`	Calculate the area sampled by receivers through time
`get_detection_clumps()`	Get detection clumps
`get_detection_containers()`	Define detection containers around receivers
`get_detection_containers_envir()`	Sample environmental conditions around receivers
`get_detection_containers_overlap()`	Get detection container overlaps
`get_detection_days()`	Calculate detection days
`get_detection_overlaps()`	Get `overlapping' detections
`get_detection_pr()`	A detection probability function based on distance
`get_hr_prop()` `get_hr_core()` `get_hr_home()` `get_hr_full()`	Get animal `home ranges'
`get_id_rec_overlap()`	Calculate the overlap between individuals' time at liberty and receivers' operational periods
`get_intersection()`	Spatial intersections with one or more geometries
`get_mvt_mobility_from_acoustics()` `get_mvt_mobility_from_archival()`	Estimate individual swimming speeds from acoustic and archival data
`get_mvt_resting()`	Identify resting behaviour within depth time series
`get_n_operational_ts()`	Calculate the number of operational units through time
`get_residents()`	Identify `resident' individuals in a passive acoustic telemetry array
`invert_poly()`	Invert a (spatial) polygon
`kud_around_coastline()` `kud_around_coastline_fast()`	Process a kernel utilisation distribution around a barrier
`kud_habitat()`	Define a `habitat' grid for kernel smoothing
`lcp_comp()`	Compare Euclidean and shortest distances
`lcp_costs()`	Calculate the distances between connected cells in a Raster*
`lcp_from_point()`	Create a Raster* of the least-cost distances around a point
`lcp_graph_surface()`	Construct a graph for least-cost paths analysis of movement from a point on a Raster*
`lcp_interp()`	Interpolate shortest (least-cost) paths between locations along a movement path
`lcp_over_surface()`	Calculate shortest path(s) and/or distance(s) over a surface between origin and destination coordinates
`make_df_detections()`	Convert a detection matrix into a dataframe
`make_matrix_cooccurence()`	Compute a detection history similarity matrix
`make_matrix_detections()`	Matricise detection time series
`make_matrix_ids()`	Matricise individual deployment time series
`make_matrix_receivers()`	Matricise receiver deployment time series
`mask_io()`	Implement `mask` using the inside or outside of the mask
`pf()`	The particle filtering routine
`pf_access_history()`	Access the `history' element of a `pf_archive-class` object
`pf_access_history_files()`	List `history' files from a PF algorithm
`pf_access_particles_unique()`	Access the cells sampled by PF
`pf_animate_history()`	Create a html animation of the PF algorithm(s)
`pf_archive-class`	"pf_archive" class
`pf_kud()`	Smooth POU maps
`pf_kud_1()` `pf_kud_2()`	(Experimental) Alternative kernel smoothing routines for particles or paths from a PF algorithm
`pf_loglik()`	Calculate the log-probability of movement paths from a PF algorithm
`pf_path-class`	"pf" class
`pf_plot_1d()`	Plot one-dimensional depth time series from a PF algorithm
`pf_plot_2d()`	Map two-dimensional paths from a PF algorithm
`pf_plot_3d()`	Map three-dimensional paths from a PF algorithm
`pf_plot_history()`	Plot particle histories from a PF algorithm
`pf_plot_map()`	Plot `probability of use' from a PF algorithm
`pf_setup_movement_pr()`	A simple movement model dependent on distance
`pf_setup_optimisers()`	Optimisation settings for `pf`
`pf_setup_record()`	List `record' files from an AC/DC algorithm for PF
`pf_simplify()`	Convert particle histories from `pf` into movement paths
`process_false_detections_sf()`	Pass putative false detections through a spatial filter
`process_quality_check()`	Basic quality checks of passive acoustic telemetry datasets
`process_receiver_id()`	Add unique receiver IDs to passive acoustic telemetry time series
`process_surface()`	Process a Raster* by aggregation and quantify the error induced by this process
`query_open_topo()`	Query the Open Topo Data API for elevation data
`segments_cross_barrier()`	Determine if Euclidean path segments cross a barrier
`sim_array()`	Simulate (marine) monitoring arrays
`sim_detections()`	Simulate detections
`sim_path_*`	Functions for the simulation of movement paths
`sim_path_ou_1()`	Simulate discrete-time movement paths under a Ornstein-Uhlenbeck process (1)
`sim_path_sa()` `sim_steps()` `sim_angles()`	Simulate discrete-time movement paths from step lengths and turning angles
`sim_surface()`	Populate a raster with simulated values
`split_raster_equally()`	Split a raster into equal-area parts
`update_extent()`	Shrink or expand an `extent` object
`xy_from_click()`	Get location coordinates from mouse click(s)

Reference

All functions