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Point to the new PortalPredictions, portal-forecasts
Portal-forecasts is a revised version of portalPredictions Portal-forecasts contains forecasts as zipped files
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|---|---|---|
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@@ -19,3 +19,4 @@ testing_dir/* | |
| /Meta/ | ||
| inst/app/models.knit.md | ||
| *.DS_Store* | ||
| .Rproj.user | ||
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| Package: portalcasting | ||
| Title: Model and Forecast Portal Rodent Dynamics | ||
| Version: 0.60.1 | ||
| Version: 0.60.2 | ||
| Authors@R: c( | ||
| person(c("Juniper", "L."), "Simonis", | ||
| email = "[email protected]", role = c("aut", "cre"), | ||
|
|
@@ -21,7 +21,7 @@ Authors@R: c( | |
| comment = c(ORCID = "0000-0001-6728-7745")), | ||
| person(c("S. K.", "Morgan"), "Ernest", role = c("aut"), | ||
| comment = c(ORCID = "0000-0002-6026-8530"))) | ||
| Description: Create a directory, populate it with data, build models, forecast rodent populations, and visualize the results. The user can spin-up a local lightweight sandbox or full-scale production environment from the same code underlying the continuously deployed Portal Predictions Project continuous integration system <https://github.com/weecology/portalpredictions> and website <https://portal.naturecast.org>. | ||
| Description: Create a directory, populate it with data, build models, forecast rodent populations, and visualize the results. The user can spin-up a local lightweight sandbox or full-scale production environment from the same code underlying the continuously deployed Portal Predictions Project continuous integration system <https://github.com/weecology/portal-forecasts> and website <https://portal.naturecast.org>. | ||
| URL: https://weecology.github.io/portalcasting/, https://github.com/weecology/portalcasting | ||
| BugReports: https://github.com/weecology/portalcasting/issues | ||
| Depends: | ||
|
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@@ -48,7 +48,9 @@ Imports: | |
| shiny, | ||
| stats, | ||
| viridis, | ||
| yaml | ||
| yaml, | ||
| utils, | ||
| zipR | ||
| Suggests: | ||
| pkgdown, | ||
| testthat | ||
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|
||
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| @@ -0,0 +1,91 @@ | ||
| #' unZip and zip forecasts by forecast date | ||
| #' | ||
| #' @param type either zip or unzip | ||
| #' @param forecast_path location of forecast directory | ||
| #' @param date forecaset date to use while zipping | ||
| #' | ||
| #' @export | ||
| #' | ||
| zip_unzip <- | ||
| function(type = NULL, | ||
| forecast_path = "forecasts/", | ||
| date = NULL) { | ||
| print("Preparing forecasts files") | ||
| proj_path <- forecast_path | ||
| forecasts_metadata = paste0(proj_path, "/forecasts_metadata.csv") | ||
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| proj_path <- normalizePath(proj_path, mustWork = FALSE) | ||
| forecasts_metadata <- | ||
| normalizePath(forecasts_metadata, mustWork = FALSE) | ||
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| metadata <- read.csv(forecasts_metadata) | ||
| unique_dates <- unique(metadata$forecast_date) | ||
| unique_dates = sort(unique_dates) | ||
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| if (type == "zip") { | ||
| csv_file <- "_forecast_table.csv" | ||
| yaml_file <- "_metadata.yaml" | ||
| json_file <- "_model_forecast.json" | ||
| if (!is.null(date)) { | ||
| unique_dates = c(date) | ||
| print(paste0("Zipping forecasts files for ", date)) | ||
| } | ||
| for (forecast_day in unique_dates) { | ||
| id_date_files <- c() | ||
| zipfile <- | ||
| paste0(proj_path, "/forecast_id_", forecast_day, ".zip") | ||
| # Get all the values of that particular day in a data frame | ||
| newdata <- | ||
| subset(metadata, | ||
| forecast_date == forecast_day, | ||
| select = c(forecast_id, forecast_date)) | ||
| # for each forecast_id get 3 files | ||
| All_ids <- newdata$forecast_id | ||
| for (id in All_ids) { | ||
| csv_file_path = paste0(proj_path, "forecast_id_", id, csv_file) | ||
| yaml_file_path = paste0(proj_path, "forecast_id_", id, yaml_file) | ||
| json_file_path = paste0(proj_path, "forecast_id_", id, json_file) | ||
| id_date_files <- | ||
| c(id_date_files, | ||
| csv_file_path, | ||
| yaml_file_path, | ||
| json_file_path) | ||
| } | ||
| zipfile <- normalizePath(zipfile, mustWork = FALSE) | ||
| # First remove old zip file if exists | ||
| unlink(zipfile) | ||
| # zip all id_date_files | ||
| zipr(zipfile, id_date_files, compression_level = 9) | ||
| unlink(id_date_files) | ||
| } | ||
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| # Zip forecasts_evaluations.csv | ||
| id_date_files <- | ||
| c(paste0(proj_path, "/forecasts_evaluations.csv")) | ||
| id_date_files <- normalizePath(id_date_files, mustWork = FALSE) | ||
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| zipfile <- paste0(proj_path, "/forecasts_evaluations.zip") | ||
| zipfile <- normalizePath(zipfile, mustWork = FALSE) | ||
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| zipr(zipfile, id_date_files, compression_level = 9) | ||
| } | ||
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| if (type == "unzip") { | ||
| print("Unzipping forecasts files") | ||
| # unzip files basing on unique_dates | ||
| for (forecast_day in unique_dates) { | ||
| zipfile <- paste0(proj_path, "/forecast_id_", forecast_day, ".zip") | ||
| zipfile <- normalizePath(zipfile, mustWork = FALSE) | ||
| if (file.exists(zipfile)) { | ||
| unzip(zipfile, exdir = proj_path) | ||
| unlink(zipfile) | ||
| } | ||
| } | ||
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| # Unzip forecasts_evaluations.csv | ||
| eval_zip <- paste0(proj_path, "/forecasts_evaluations.zip") | ||
| eval_zip <- normalizePath(eval_zip, mustWork = FALSE) | ||
| utils::unzip(eval_zip, exdir = proj_path) | ||
| unlink(eval_zip) | ||
| } | ||
| } |
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