Provides access simplified distribution of ecopmo forecasts forecasts for Calanus finmarchicus.
remotes::install_github("BigelowLab/calfinforecast")
Each day the repository and package are refreshed using…
$ Rscript /mnt/s1/projects/ecocast/corecode/R/ecopmo_forecast/calfinforecast/inst/scripts/copy_forecast.R
This copies the most recent forecasts (-5 days to +10 days, although that will vary by available forecast data.) Makes a copy of the most recent configuration list, saves both a time-faceted forecast plot as well as per day forecast plots.
Data are stored within the package, so we provide function to easily read these data.
Read the raw forecast data as raster,
library(calfinforecast)
x = read_raster()
x## stars object with 3 dimensions and 1 attribute
## attribute(s), summary of first 1e+05 cells:
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## q050 0.0003209292 0.009350357 0.02676463 0.08899682 0.1295596 0.8283182 34222
## dimension(s):
## from to offset delta refsys point x/y
## x 1 415 -77.04 0.08333 WGS 84 FALSE [x]
## y 1 261 56.71 -0.08333 WGS 84 FALSE [y]
## time 1 13 2026-07-17 1 days Date NA
Read in the convenience spatial bounding box.
bb = get_bb(reg = "gom")
bb## xmin ymin xmax ymax
## -72 39 -63 46
The configuration list may provide important contextual information.
cfg = read_config()
str(cfg)## List of 10
## $ species : chr "calfin"
## $ longname : chr "Calanus finmarchicus"
## $ version : chr "v1.01"
## $ class : chr "right whale prey"
## $ note : chr "same as v0/1.00 but using 90th percentile of abudnance as threshold"
## $ verbose : logi TRUE
## $ training_data :List of 5
## ..$ species : chr "calfin"
## ..$ species_data :List of 4
## .. ..$ ecomon_column: NULL
## .. ..$ alt_source : chr "function"
## .. ..$ function : chr "read_merged"
## .. ..$ threshold :List of 2
## .. .. ..$ pre : num 39725
## .. .. ..$ post: NULL
## ..$ classification:List of 3
## .. ..$ name : chr "patch"
## .. ..$ levels: int [1:2] 1 0
## .. ..$ labels: chr [1:2] "1" "0"
## ..$ coper_data :List of 6
## .. ..$ vars_static: chr "deptho"
## .. ..$ reg_phys : chr "chfc"
## .. ..$ vars_phys : chr [1:6] "temp_bot" "mlotst_mld" "sal_sur" "temp_sur" ...
## .. ..$ reg_bgc : chr "world"
## .. ..$ vars_bgc : NULL
## .. ..$ vars_time : chr [1:2] "day_length" "ddx_day_length"
## ..$ split :List of 3
## .. ..$ func : chr "rsample::mc_cv"
## .. ..$ prop : num 0.75
## .. ..$ times: int 25
## $ model :List of 3
## ..$ seed : num 799
## ..$ model :List of 9
## .. ..$ name : chr "Boosted Regression Tree"
## .. ..$ engine : chr "xgboost"
## .. ..$ trees : num 500
## .. ..$ learn_rate : num 0.1
## .. ..$ tree_depth : num 4
## .. ..$ mtry : num 5
## .. ..$ min_n : num 10
## .. ..$ nthread : num 4
## .. ..$ engine_version: chr "3.2.1.1"
## ..$ transformations: chr [1:2] "step_log_bathy" "step_normalize_numeric"
## $ predict :List of 1
## ..$ quantiles: num [1:7] 0 0.05 0.25 0.5 0.75 0.95 1
## $ suggested_threshold:List of 2
## ..$ quantile : num 0.5
## ..$ threshold: num 0.283
Graphics can be composed of one time-facted plot or a collection of per-day plots.
gg1 = plot_forecast(x, wrap = TRUE, crop = get_bb(reg = "gom"))
gg1
Alternatively
we can retrieve a listing with one graphic per day.
gg2 = plot_forecast(x, wrap = FALSE, crop = get_bb(reg = "gom"))
gg2[[6]]
Each of these is rendered as a PNG. You can list them…
list_images("wrapped") |>
basename()## [1] "wrapped.png"
list_images("daily") |>
basename()## [1] "2026-07-17.png" "2026-07-18.png" "2026-07-19.png" "2026-07-20.png"
## [5] "2026-07-21.png" "2026-07-22.png" "2026-07-23.png" "2026-07-24.png"
## [9] "2026-07-25.png" "2026-07-26.png" "2026-07-27.png" "2026-07-28.png"
## [13] "2026-07-29.png"
You can download the raw data using this command, and then read it in as a stars object.
ok = download.file("https://github.com/BigelowLab/calfinforecast/raw/refs/heads/main/inst/extdata/data.Rds", "data.Rds")
x = readRDS("data.Rds")
x## stars object with 3 dimensions and 1 attribute
## attribute(s), summary of first 1e+05 cells:
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## q050 0.0003209292 0.009350357 0.02676463 0.08899682 0.1295596 0.8283182 34222
## dimension(s):
## from to offset delta refsys point x/y
## x 1 415 -77.04 0.08333 WGS 84 FALSE [x]
## y 1 261 56.71 -0.08333 WGS 84 FALSE [y]
## time 1 13 2026-07-17 1 days Date NA