These functions load example outputs from key patter
functions. They are included in the package to streamline function examples and tests.
Source
For full details on the algorithm parameters used to generate these datasets, see https://github.com/edwardlavender/patter/blob/main/data-raw/003-add-data-algorithms.R.
Value
The functions return a dataset or a character
string that defines the path to a dataset. See the corresponding function documentation for full details.
Details
dat_path()
reads an example output fromsim_path_walk()
;dat_coa()
reads an example output fromcoa()
;dat_pff()
reads an example output from a forward run ofpf_filter()
;dat_pfb()
reads an example output from a backward run ofpf_filter()
;dat_tff()
reads an example output frompf_smoother_two_filter()
;
See also
Particle filters and smoothers sample states (particles) that represent the possible locations of an individual through time, accounting for all data and the individual's movement.
To simulate artificial datasets, see
sim_*()
functions (especiallysim_path_walk()
,sim_array()
andsim_observations()
).To assemble real-world datasets for the filter, see
assemble
_*()
functions.pf_filter()
runs the filter:To run particle smoothing, use
pf_smoother_two_filter()
.To map emergent patterns of space use, use a
map_*()
function (such asmap_pou()
,map_dens()
andmap_hr()
).
Examples
# Load inbuilt datasets
dat_path() |> summary()
#> path_id timestep timestamp map_value
#> Min. :1 Min. : 1.00 Min. :2016-01-01 00:00:00 Min. : 5.661
#> 1st Qu.:1 1st Qu.: 90.75 1st Qu.:2016-01-01 02:59:30 1st Qu.: 27.332
#> Median :1 Median :180.50 Median :2016-01-01 05:59:00 Median : 47.209
#> Mean :1 Mean :180.50 Mean :2016-01-01 05:59:00 Mean : 73.360
#> 3rd Qu.:1 3rd Qu.:270.25 3rd Qu.:2016-01-01 08:58:30 3rd Qu.:116.657
#> Max. :1 Max. :360.00 Max. :2016-01-01 11:58:00 Max. :196.003
#> x y
#> Min. :706015 Min. :6259156
#> 1st Qu.:707440 1st Qu.:6261930
#> Median :710191 Median :6263235
#> Mean :709700 Mean :6263451
#> 3rd Qu.:711246 3rd Qu.:6265161
#> Max. :711852 Max. :6267903
dat_coa() |> summary()
#> timestep timestamp map_value x
#> Min. :1.00 Min. :2016-01-01 00:00:00 Min. : 24.39 Min. :706900
#> 1st Qu.:2.25 1st Qu.:2016-01-01 02:30:00 1st Qu.: 31.60 1st Qu.:708216
#> Median :3.50 Median :2016-01-01 05:00:00 Median : 52.49 Median :710228
#> Mean :3.50 Mean :2016-01-01 05:00:00 Mean : 83.81 Mean :709568
#> 3rd Qu.:4.75 3rd Qu.:2016-01-01 07:30:00 3rd Qu.:134.28 3rd Qu.:711013
#> Max. :6.00 Max. :2016-01-01 10:00:00 Max. :187.29 Max. :711229
#> y
#> Min. :6259666
#> 1st Qu.:6262546
#> Median :6263398
#> Mean :6263395
#> 3rd Qu.:6264844
#> Max. :6266321
dat_pff() |> summary()
#> Length Class Mode
#> states 6 data.table list
#> diagnostics 4 data.table list
#> callstats 7 data.table list
dat_pfb() |> summary()
#> Length Class Mode
#> states 6 data.table list
#> diagnostics 4 data.table list
#> callstats 7 data.table list
dat_tff() |> summary()
#> Length Class Mode
#> states 6 data.table list
#> diagnostics 4 data.table list
#> callstats 7 data.table list