diff --git a/.env b/.env
index f90c73a..be0f06b 100644
Binary files a/.env and b/.env differ
diff --git a/.gitignore b/.gitignore
index f38b151..ddcd55a 100644
--- a/.gitignore
+++ b/.gitignore
@@ -21,5 +21,6 @@ data/**/*.tif
data/elevation/*
data/slope_aspect/*
data/soil/*
-
+notes/*
+*.token
diff --git a/R/AWS_get_folder.R b/R/AWS_get_folder.R
index bd2521c..8d44fd7 100644
--- a/R/AWS_get_folder.R
+++ b/R/AWS_get_folder.R
@@ -1,31 +1,21 @@
-#' Download files from an AWS S3 bucket to a local folder
+#' AWS S3 Bucket File Retrieval
#'
-#' This function downloads files from a specified S3 bucket and prefix to a local folder.
-#' It only downloads files that are not already present in the local folder.
-#' Additionally, it ensures that AWS credentials and region are set in the environment.
+#' The function retrieves files stored in an AWS S3 bucket to a local folder and removes faulty parquet files.
#'
-#' @author Nathan Layman
+#' @author Nathan C. Layman
#'
-#' @param local_folder Character. The path to the local folder where files should be downloaded and the AWS prefix
-#' @param ...
+#' @param local_folder A string representing the local folder where the files will be downloaded
+#' @param ... additional arguments not used by this function, included for generic function compatibility
#'
-#' @return A list of files downloaded from AWS
-#'
-#' @note
-#' The AWS environment variables `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, `AWS_REGION`, and `AWS_BUCKET_ID`
-#' must be set correctly in order to access the S3 bucket. If any of these are missing, the function will stop with an error.
-#' Files in the S3 bucket will be deleted if they cannot be successfully read as parquet files.
+#' @return A vector of strings representing the paths of the downloaded files. If no files are found, NULL is returned.
#'
+#' @note This function requires the AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, and AWS_REGION environment variables to be set.
+#' Access AWS S3 bucket contents, download files locally, clean faulty data, and return the list of downloaded files.
#'
#' @examples
-#' \dontrun{
-#' # Ensure the AWS environment variables are set in your system or .env file:
-#' # AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION, and AWS_BUCKET_ID
+#' # Ensure to set AWS environment variables (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION)
+#' AWS_get_folder(local_folder = "./data")
#'
-#' # Download files from an S3 bucket folder to a local directory
-#' downloaded_files <- AWS_get_folder("my/local/folder")
-#' }
-#'
#' @export
AWS_get_folder <- function(local_folder, ...) {
@@ -108,32 +98,29 @@ AWS_get_folder <- function(local_folder, ...) {
}
-#' Upload and Sync Files with AWS S3
+#' Upload Transformed Files to AWS
#'
-#' This function synchronizes a local folder with an AWS S3 bucket. It checks for AWS credentials,
-#' lists existing files in the S3 bucket, and compares them with the local files to upload new files
-#' or remove files that are no longer needed.
-#'
-#' @author Nathan Layman
+#' This function uploads transformed files to AWS given a list of files and a target local folder. It supports continuation token for handling large quantities of files. It also checks for existing files on AWS and in local folder before upload, providing informative messages about the uploading process.
#'
-#' @param transformed_file_list A character vector of file paths that should be present on AWS S3.
-#' @param local_folder A character string specifying the path to the local folder to be synced with AWS S3.
+#' @author Nathan C. Layman
#'
-#' @examples
-#' \dontrun{
-#' AWS_put_files(transformed_file_list = c("file1.parquet", "file2.parquet"),
-#' local_folder = "path/to/local/folder")
-#' }
+#' @param transformed_file_list A character vector of filenames that have been transformed and are to be uploaded to AWS S3. Filenames should be base names, not full paths.
+#' @param local_folder A character string indicating the local directory that contains the transformed files to be uploaded to AWS S3.
+#' @param ... Additional arguments not used by this function.
+#'
+#' @return A character vector of messages indicating the outcomes of trying to upload each file in the transformed_file_list to AWS.
+#'
+#' @note The function uses AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, and AWS_REGION environment variables to access AWS. These should be set prior to running this function.
#'
-#' @return A list of actions taken
+#' @examples
+#' AWS_put_files(transformed_file_list = c("file1.csv", "file2.csv"),
+#' local_folder = "./transformed_data")
#'
#' @export
AWS_put_files <- function(transformed_file_list,
local_folder,
...) {
- transformed_file_list <- basename(transformed_file_list |> unlist())
-
# Check if AWS credentials and region are set in the environment
if (any(Sys.getenv(c("AWS_ACCESS_KEY_ID", "AWS_SECRET_ACCESS_KEY", "AWS_REGION")) == "")) {
msg <- paste(
@@ -166,10 +153,10 @@ AWS_put_files <- function(transformed_file_list,
}
# Get files in local folder
- local_folder_files <- list.files(path = local_folder, recursive = TRUE)
+ local_folder_files <- list.files(path = local_folder, recursive = TRUE, full.names = T)
# Collect outcomes
- outcome <- c()
+ outcomes <- c()
# Walk through local_folder_files
for(file in local_folder_files) {
@@ -177,36 +164,33 @@ AWS_put_files <- function(transformed_file_list,
# Is the file in the transformed_file_list?
if(file %in% transformed_file_list) {
- # Is the file already on AWS?
- if(file %in% s3_files) {
-
- outcome <- c(outcome, glue::glue("{file} already present on AWS"))
-
- } else {
-
- outcome <- c(outcome, glue::glue("Uploading {file} to AWS"))
-
- # Put the file on S3
- s3_upload <- s3$put_object(
- Body = file.path(local_folder, file),
- Bucket = Sys.getenv("AWS_BUCKET_ID"),
- Key = file.path(local_folder, file))
- }
+ # Put the file on S3
+ s3_upload <- s3$put_object(
+ Body = file,
+ Bucket = Sys.getenv("AWS_BUCKET_ID"),
+ Key = file)
+
+ outcome <- glue::glue("Uploading {file} to AWS")
+
} else {
# Remove the file from AWS if it's present in the folder and on AWS
# but not in the list of successfully transformed files. This file is
# not relevant to the pipeline
- if(file.path(local_folder, file) %in% s3_files) {
+ if(file %in% s3_files) {
- outcome <- c(outcome, glue::glue("Cleaning up dangling file {file} from AWS"))
+ outcome <- glue::glue("Cleaning up dangling file {file} from AWS")
# Remove the file from AWS
s3_delete_receipt <- s3$delete_object(
- Bucket = Sys.getenv("AWS_BUCKET_ID"),
+ Bucket = Sys.getenv("AWS_BUCKET_ID"),
Key = file.path(local_folder, file))
+ } else {
+ next
}
}
+ message(outcome)
+ outcomes <- c(outcomes, outcome)
}
outcome
diff --git a/R/calculate_forecasts_anomalies.R b/R/calculate_forecasts_anomalies.R
index 4ce7e49..e53843e 100644
--- a/R/calculate_forecasts_anomalies.R
+++ b/R/calculate_forecasts_anomalies.R
@@ -65,15 +65,32 @@ calculate_forecasts_anomalies <- function(ecmwf_forecasts_transformed,
# contributions of March and April.
# An easier way to do this is to just make a list of every day from start to
- # start + 30 - 1. Figure out the month and join to forecast month from
+ # start + 30 - 1. Figure out the year nad month and join to forecast month from
# ecmwf_forecasts_transformed. That way we could do all the things at once.
# Then group by x, y, and summarize average of data columns. Map over each
# lead interval and done. A benefit of this approach is that it makes
# comparing to historical means easy. Just find the historical means for each
# day then left join that in by month as well.
- forecasts_transformed_dataset <- arrow::open_dataset(ecmwf_forecasts_transformed) |>
- filter(base_date == floor_date(model_dates_selected, unit = "month"))
+ # Updated notes after discussion with Noam
+ # We want current date, current ndvi, forecast amount in days, forecast weather, forecast outbreak history (check this), and all the static layers. So we don't want wide weather forecast but long.
+
+ # Get a tibble of all the dates in the anomaly forecast range for the given lead interval
+ model_dates <- tibble(date = seq(from = model_dates_selected + lead_interval_start,
+ to = model_dates_selected + lead_interval_end - 1, by = 1)) |>
+ mutate(doy = as.integer(lubridate::yday(date)), # Calculate day of year
+ month = as.integer(lubridate::month(date)), # Extract month
+ year = as.integer(lubridate::year(date))) # Extract year
+
+ # Get the relevant forecast data. From the most recent base_date that came
+ # before the model_date selected.
+ forecasts_transformed_dataset <- arrow::open_dataset(ecmwf_forecasts_transformed) |> filter(base_date <= model_dates_selected)
+ relevant_base_date <- forecasts_transformed_dataset |>
+ select(base_date) |>
+ distinct() |>
+ arrange(base_date) |>
+ pull(base_date, as_vector = TRUE)
+ forecasts_transformed_dataset <- forecasts_transformed_dataset |> filter(base_date == relevant_base_date)
historical_means <- arrow::open_dataset(weather_historical_means)
@@ -85,51 +102,59 @@ calculate_forecasts_anomalies <- function(ecmwf_forecasts_transformed,
message(glue::glue("Processing forecast interval {lead_interval_start}-{lead_interval_end} days out"))
# Get a tibble of all the dates in the anomaly forecast range for the given lead interval
- model_dates <- tibble(date = seq(from = model_dates_selected + lead_interval_start, to = model_dates_selected + lead_interval_end - 1, by = 1)) |>
- mutate(doy = as.integer(lubridate::yday(date)), # Calculate day of year
- month = month(date), # Extract month
- year = year(date), # Extract year
- lead_interval_start = lead_interval_start, # Store lead interval duration
+ forecast_anomaly <- model_dates |>
+ mutate(lead_interval_start = lead_interval_start, # Store lead interval duration
lead_interval_end = lead_interval_end) # Store lead interval duration
# Join historical means based on day of year (doy)
- model_dates <- historical_means |> filter(doy >= min(model_dates$doy)) |>
- right_join(model_dates, by = c("doy"))
+ forecast_anomaly <- historical_means |> filter(doy >= min(model_dates$doy)) |>
+ right_join(model_dates, by = c("doy")) |> relocate(-matches("precipitation|temperature|humidity"))
# Join in forecast data based on x, y, month, and year.
# The historical data and forecast data _should_ have the same column
# names so differentiate with a suffix
- model_dates <- model_dates |>
+ forecast_anomaly <- forecast_anomaly |>
left_join(forecasts_transformed_dataset, by = c("x", "y", "month", "year"), suffix = c("_historical", "_forecast"))
+
# Summarize by calculating the mean for each variable type (temperature, precipitation, relative_humidity)
# and across both historical data and forecast data over the days in the model_dates range
- model_dates <- model_dates |>
+ forecast_anomaly <- forecast_anomaly |>
group_by(x, y, lead_interval_start, lead_interval_end) |>
summarize(across(matches("temperature|precipitation|relative_humidity"), ~mean(.x)), .groups = "drop")
+
# Calculate temperature anomalies
- model_dates <- model_dates |>
+ forecast_anomaly <- forecast_anomaly |>
mutate(anomaly_forecast_temperature = temperature_forecast - temperature_historical,
anomaly_forecast_scaled_temperature = anomaly_forecast_temperature / temperature_sd_historical)
# Calculate precipitation anomalies
- model_dates <- model_dates |>
+ forecast_anomaly <- forecast_anomaly |>
mutate(anomaly_forecast_precipitation = precipitation_forecast - precipitation_historical,
anomaly_forecast_scaled_precipitation = anomaly_forecast_precipitation / precipitation_sd_historical)
# Calculate relative_humidity anomalies
- model_dates <- model_dates |>
+ forecast_anomaly <- forecast_anomaly |>
mutate(anomaly_forecast_relative_humidity = relative_humidity_forecast - relative_humidity_historical,
anomaly_forecast_scaled_relative_humidity = anomaly_forecast_relative_humidity / relative_humidity_sd_historical)
# Clean up intermediate columns
- model_dates |>
+ forecast_anomaly |>
mutate(date = model_dates_selected) |>
- select(x, y, date, 'lead_interval_start', 'lead_interval_end', starts_with("anomaly")) |>
+ select(x, y, date, doy, month, year, 'lead_interval_start', 'lead_interval_end', starts_with("anomaly")) |>
collect()
})
+ # Change forecast lead and start to just forecast weather column and forecast days. Include zero here. I don't think NASA weather is necessary then.
+ forecasts_anomalies <- forecasts_anomalies |>
+ select(-lead_interval_start) # |>
+ # pivot_wider(
+ # names_from = lead_interval_end,
+ # values_from = contains("anomaly"),
+ # names_sep = "_"
+ # )
+
# Write output to a parquet file
arrow::write_parquet(forecasts_anomalies, save_filename, compression = "gzip", compression_level = 5)
diff --git a/R/calculate_ndvi_anomalies.R b/R/calculate_ndvi_anomalies.R
index bd5ac37..a6ce8f9 100644
--- a/R/calculate_ndvi_anomalies.R
+++ b/R/calculate_ndvi_anomalies.R
@@ -64,7 +64,10 @@ calculate_ndvi_anomalies <- function(sentinel_ndvi_transformed,
# Remove intermediate columns
ndvi_transformed_dataset <- ndvi_transformed_dataset |>
- select(x, y, date, starts_with("anomaly"))
+ mutate(doy = as.integer(lubridate::yday(date)), # Calculate day of year
+ month = as.integer(lubridate::month(date)), # Extract month
+ year = as.integer(lubridate::year(date))) |> # Extract year
+ select(x, y, date, doy, month, year, starts_with("anomaly"))
# Save as parquet
arrow::write_parquet(ndvi_transformed_dataset, save_filename, compression = "gzip", compression_level = 5)
diff --git a/R/calculate_weather_anomalies.R b/R/calculate_weather_anomalies.R
index c7cad2a..a3c5af0 100644
--- a/R/calculate_weather_anomalies.R
+++ b/R/calculate_weather_anomalies.R
@@ -77,7 +77,10 @@ calculate_weather_anomalies <- function(nasa_weather_transformed,
# Remove intermediate columns
weather_transformed_dataset <- weather_transformed_dataset |>
- select(x, y, date, starts_with("anomaly"))
+ mutate(doy = as.integer(lubridate::yday(date)), # Calculate day of year
+ month = as.integer(lubridate::month(date)), # Extract month
+ year = as.integer(lubridate::year(date))) |> # Extract year
+ select(x, y, date, doy, month, year, starts_with("anomaly"))
# Save as parquet
arrow::write_parquet(weather_transformed_dataset, save_filename, compression = "gzip", compression_level = 5)
diff --git a/R/download_sentinel_ndvi.R b/R/download_sentinel_ndvi.R
index 498b6d6..b1fcdc9 100644
--- a/R/download_sentinel_ndvi.R
+++ b/R/download_sentinel_ndvi.R
@@ -22,26 +22,40 @@
#'
#' @export
download_sentinel_ndvi <- function(sentinel_ndvi_api_parameters,
- raw_filename) {
+ raw_filename,
+ sentinel_ndvi_token_file = "sentinel.token") {
product_id <- sentinel_ndvi_api_parameters$id
message(paste0("Downloading ", raw_filename))
- auth <- httr::POST("https://identity.dataspace.copernicus.eu/auth/realms/CDSE/protocol/openid-connect/token",
- body = list(
- grant_type = "password",
- username = Sys.getenv("COPERNICUS_USERNAME"),
- password = Sys.getenv("COPERNICUS_PASSWORD"),
- client_id = "cdse-public"),
- encode = "form")
+ # Read in sentinel token
+ sentinel_ndvi_token <- readLines(sentinel_ndvi_token_file)
url <- glue::glue('https://zipper.dataspace.copernicus.eu/odata/v1/Products({product_id})/$value')
- response <- httr::GET(url, httr::add_headers(Authorization = paste("Bearer", httr::content(auth)$access_token)),
- httr::write_disk(raw_filename, overwrite = TRUE))
+ i <- 0
+ response <- list()
+ response$status_code <- 401
+
+ while(response$status_code != 200 && i < 6) {
+ response <- httr::GET(url, httr::add_headers(Authorization = paste("Bearer", sentinel_ndvi_token)),
+ httr::write_disk(raw_filename, overwrite = TRUE))
+ httr::message_for_status(response)
+ if(response$status_code == 401) {
+ get_sentinel_ndvi_token(filename = sentinel_ndvi_token_file)
+ sentinel_ndvi_token <- readLines(sentinel_ndvi_token_file)
+ }
+ Sys.sleep(ifelse(2^i>60, 60, 2^i))
+ }
+
+ httr::stop_for_status(response)
# Remove old nc file if it exists
- file.remove(paste0(tools::file_path_sans_ext(raw_filename), ".nc"))
+ # Construct the file path of the .nc file
+ nc_file <- paste0(tools::file_path_sans_ext(raw_filename), ".nc")
+ if (file.exists(nc_file)) {
+ file.remove(nc_file)
+ }
# Unzip the new download and rename
unzip(raw_filename,
diff --git a/R/get_outbreak_distance_matrix.R b/R/get_outbreak_distance_matrix.R
index 12fc724..98370a4 100644
--- a/R/get_outbreak_distance_matrix.R
+++ b/R/get_outbreak_distance_matrix.R
@@ -1,27 +1,26 @@
-#' Calculate Outbreak Distance Matrix
+#' Compute the Outbreak Distance Matrix
#'
-#' This function calculates a distance matrix for outbreaks based on given parameters. The function takes
-#' outbreak data, a raster template, a distance in kilometers, and a beta distribution values as arguments.
-#' It then calculates the distance values, applies conditions, and returns a matrix of distances.
+#' This function computes the geographical distance between outbreak locations and
+#' raster grid cells, transforming these distances into a connectivity matrix.
#'
#' @author Nathan C. Layman
#'
-#' @param wahis_outbreaks Dataframe containing outbreak data.
-#' @param wahis_raster_template A raster template for structuring the data.
-#' @param within_km The maximum distance in kilometers to be considered for the matrix. Default is 500.
-#' @param beta_dist A value defining beta distribution. Default is 0.01.
+#' @param wahis_outbreaks A dataframe of outbreak locations with columns 'longitude' and 'latitude'.
+#' @param wahis_raster_template A raster template on which the function calculates distances.
+#' @param within_km Numeric, the radius within which to calculate distances. Defaults to 500.
+#' @param beta_dist Numeric, a coefficient used to transform distances into a connectivity matrix. Defaults to 0.01.
#'
-#' @return A matrix containing calculated distance values based on outbreak data.
+#' @return A matrix with rows representing grid cells and columns representing outbreak locations,
+#' where each cell's value is a transformed measure of its distance from the outbreak.
#'
-#' @note This function calculates distance values based on vincenty measure, applies conditions, and returns a
-#' matrix of distances. If the distance is larger than a given threshold, it is set as NA. Distance values are then adjusted
-#' based on a beta distribution, and NA values are set as 0.
+#' @note Distances are calculated with the Vincenty measure,
+#' transformed using an exponential decay function, and outside of the specified radius are set to zero.
#'
#' @examples
-#' get_outbreak_distance_matrix(wahis_outbreaks = outbreak_data,
+#' get_outbreak_distance_matrix(wahis_outbreaks = wahis_df,
#' wahis_raster_template = raster_template,
-#' within_km = 100,
-#' beta_dist = 0.05)
+#' within_km = 500,
+#' beta_dist = 0.01)
#'
#' @export
get_outbreak_distance_matrix <- function(wahis_outbreaks, wahis_raster_template, within_km = 500, beta_dist = 0.01) {
@@ -46,4 +45,4 @@ get_outbreak_distance_matrix <- function(wahis_outbreaks, wahis_raster_template,
dist_mat[is.na(dist_mat)] <- 0
dist_mat
-}
\ No newline at end of file
+}
diff --git a/R/get_outbreak_history.R b/R/get_outbreak_history.R
index 2aeb22a..344a061 100644
--- a/R/get_outbreak_history.R
+++ b/R/get_outbreak_history.R
@@ -5,7 +5,7 @@
#'
#' @author Nathan C. Layman
#'
-#' @param dates_df A dataframe of the dates for which the outbreak history is to be calculated
+#' @param wahis_outbreak_dates A dataframe of the dates for which the outbreak history is to be calculated
#' @param wahis_outbreaks The outbreak naming convention
#' @param wahis_distance_matrix The inter locality distance matrix
#' @param wahis_raster_template The template for the raster mapping
@@ -24,7 +24,7 @@
#' FALSE, it simply returns the filepath of the existing file.
#'
#' @examples
-#' get_daily_outbreak_history(dates_df = dates,
+#' get_daily_outbreak_history(wahis_outbreak_dates = dates,
#' wahis_outbreaks = outbreaks,
#' wahis_distance_matrix = distance_matrix,
#' wahis_raster_template = raster_template,
@@ -33,7 +33,7 @@
#' beta_time = 0.5, max_years = 10, recent = 3/12, overwrite = FALSE)
#'
#' @export
-get_daily_outbreak_history <- function(dates_df,
+get_daily_outbreak_history <- function(wahis_outbreak_dates,
wahis_outbreaks,
wahis_distance_matrix,
wahis_raster_template,
@@ -45,10 +45,11 @@ get_daily_outbreak_history <- function(dates_df,
overwrite = FALSE,
...) {
- # Ensure only one year in dates provided
- year <- unique(dates_df$year)
- stopifnot(length(year) == 1)
+ year <- wahis_outbreak_dates$year |> unique()
+ month <- wahis_outbreak_dates$month |> unique()
+ stopifnot(length(year) == 1)
+ stopifnot(length(month) == 1)
# Create directory if it does not yet exist
dir.create(output_dir, recursive = TRUE, showWarnings = FALSE)
@@ -59,7 +60,7 @@ get_daily_outbreak_history <- function(dates_df,
error_safe_read_parquet <- possibly(arrow::open_dataset, NULL)
# Check if output file already exists and can be loaded
- outbreak_history_filename <- file.path(output_dir, glue::glue("{tools::file_path_sans_ext(output_filename)}_{year}.{tools::file_ext(output_filename)}"))
+ outbreak_history_filename <- file.path(output_dir, glue::glue("{tools::file_path_sans_ext(output_filename)}_{year}_{month}.{tools::file_ext(output_filename)}"))
# Check if outbreak_history file exist and can be read and that we don't want to overwrite them.
if(!is.null(error_safe_read_parquet(outbreak_history_filename)) & !overwrite & year != year(Sys.time())) {
@@ -68,7 +69,7 @@ get_daily_outbreak_history <- function(dates_df,
}
# This is the computationally intensive step get_outbreak_history()
- daily_outbreak_history <- map_dfr(dates_df$date, ~get_outbreak_history(date = .x,
+ daily_outbreak_history <- map_dfr(wahis_outbreak_dates$date, ~get_outbreak_history(date = .x,
wahis_outbreaks,
wahis_distance_matrix,
wahis_raster_template,
@@ -81,15 +82,20 @@ get_daily_outbreak_history <- function(dates_df,
recent_xy <- as.data.frame(daily_recent_outbreak_history, xy = TRUE) |>
as_tibble() |>
- pivot_longer(-c(x,y), names_to = "date", values_to = "weight") |>
- mutate(time_frame = "recent")
+ pivot_longer(-c(x,y), names_to = "date", values_to = "outbreak_history_weight_recent")
old_xy <- as.data.frame(daily_old_outbreak_history, xy = TRUE) |>
as_tibble() |>
- pivot_longer(-c(x,y), names_to = "date", values_to = "weight") |>
- mutate(time_frame = "old")
+ pivot_longer(-c(x,y), names_to = "date", values_to = "outbreak_history_weight_old")
+
+ outbreak_history <- inner_join(recent_xy, old_xy) |>
+ mutate(date = as.Date(date),
+ doy = as.integer(lubridate::yday(date)),
+ month = as.integer(lubridate::month(date)),
+ year = as.integer(lubridate::year(date))) |>
+ relocate(-contains("weight"))
- arrow::write_parquet(bind_rows(recent_xy, old_xy), outbreak_history_filename, compression = "gzip", compression_level = 5)
+ arrow::write_parquet(outbreak_history, outbreak_history_filename, compression = "gzip", compression_level = 5)
return(outbreak_history_filename)
diff --git a/R/get_outbreak_history_animation.R b/R/get_outbreak_history_animation.R
index 4713f3e..b0c13d8 100644
--- a/R/get_outbreak_history_animation.R
+++ b/R/get_outbreak_history_animation.R
@@ -34,7 +34,7 @@ get_outbreak_history_animation <- function(wahis_outbreak_history,
# Load the data
outbreak_history_dataset <- arrow::open_dataset(wahis_outbreak_history)
- # Fastest way to use parquet files is to do as many opperations before collect or pull
+ # Fastest way to use parquet files is to do as many operations before collect or pull
min_weight <- outbreak_history_dataset |>
summarise(min_weight = min(weight, na.rm = TRUE)) |>
pull(min_weight, as_vector = TRUE)
diff --git a/R/get_sentinel_ndvi_token.R b/R/get_sentinel_ndvi_token.R
new file mode 100644
index 0000000..becd60d
--- /dev/null
+++ b/R/get_sentinel_ndvi_token.R
@@ -0,0 +1,16 @@
+get_sentinel_ndvi_token <- function(filename = "sentinel.token") {
+ auth <- httr::POST("https://identity.dataspace.copernicus.eu/auth/realms/CDSE/protocol/openid-connect/token",
+ body = list(
+ grant_type = "password",
+ username = Sys.getenv("COPERNICUS_USERNAME"),
+ password = Sys.getenv("COPERNICUS_PASSWORD"),
+ client_id = "cdse-public"),
+ encode = "form")
+
+ sentinel_ndvi_token <- httr::content(auth)$access_token
+
+ # Write to a file
+ writeLines(sentinel_ndvi_token, filename)
+
+ filename
+}
diff --git a/R/set_ecmwf_api_parameter.R b/R/set_ecmwf_api_parameter.R
index 7b6d64e..4663f4d 100644
--- a/R/set_ecmwf_api_parameter.R
+++ b/R/set_ecmwf_api_parameter.R
@@ -1,18 +1,66 @@
-#' .. content for \description{} (no empty lines) ..
+#' Set ECMWF API Parameter for Climate Data Retrieval
#'
-#' .. content for \details{} ..
+#' This function sets parameters needed for the retrieval of climate data from the European
+#' Centre for Medium-range Weather Forecasts (ECMWF) API based on the user's requirements.
+#' It is used internally by other functions to fetch and process the data.
#'
-#' @title
-
-#' @return
-#' @author Emma Mendelsohn
-#' @export
-set_ecmwf_api_parameter <- function(years = 2005:2018,
+#' @author Emma Mendelsohn and Nathan Layman
+#'
+#' @param start_year The year from which to start the retrieval of the climate data, default is 2005.
+#' @param bbox_coords The bounding box coordinates for the location for which the data are to be retrieved.
+#' @param variables The variables to retrieve from the API; default are '2m_dewpoint_temperature', '2m_temperature', and 'total_precipitation'.
+#' @param product_types The type of data product to retrieve; default are 'monthly_mean', 'monthly_maximum', 'monthly_minimum', 'monthly_standard_deviation'.
+#' @param leadtime_months The lead times in months for which the forecasts are made; default are '1', '2', '3', '4', '5', '6'.
+#'
+#' @return A tibble containing the set parameters.
+#'
+#' @note This function is used internally and does not directly communicate with the ECMWF API.
+#'
+#' @examples
+#' set_ecmwf_api_parameter(start_year = 2010,
+#' bbox_coords = c(50.8503, 4.3517),
+#' variables = c("2m_temperature", "total_precipitation"),
+#' product_types = c("monthly_mean", "monthly_maximum"),
+#' leadtime_months = c("1", "2", "3"))
+#'
+set_ecmwf_api_parameter <- function(start_year = 2005,
bbox_coords = continent_bounding_box,
variables = c("2m_dewpoint_temperature", "2m_temperature", "total_precipitation"),
product_types = c("monthly_mean", "monthly_maximum", "monthly_minimum", "monthly_standard_deviation"),
leadtime_months = c("1", "2", "3", "4", "5", "6")) {
+
+ # API details from:
+ # https://confluence.ecmwf.int/display/CKB/How+to+use+the+CDS+interactive+forms+and+CDS+API+for+seasonal+forecast+datasets
+
+ # Originating centre: Select the name of the institution the forecasting system of your interest originates from.
+ #
+ # System: Select the version of the forecasting system. This is a numeric label and the available values are different for the different "originating centres". Note that for a given start date you could find more than one system available for a single "originating centre".
+ # Please note that you must pair up your forecasts with the relevant hindcasts by using the same "system" for both of them. A full description of the use of the system keyword is available from the "Documentation" tab.
+ #
+ # Variable: Select the parameter(s) you are interested in.
+ #
+ # Product type: Select the monthly product you are interested in.
+ # Note that the products under the category "Individual members" consist of all available individual ensemble members, while those in the category "Ensemble" have a single value for each forecast system ensemble.
+ #
+ # Year: Select the year of the initialization date of the model run(s) you are interested in.
+ # Note that years in both the hindcast period and real-time forecasts are shown here together. You can find more details about hindcast and forecast years availability in the Start dates available in the CDS per forecast system page.
+ #
+ # Please note that you must use the hindcast data in order to make a meaningful use of the forecast data. And remember you must pair forecasts and hindcasts up by using the same "system" for both of them.
+ #
+ # Month: Select the month of the initialization date of the model run(s) you are interested in.
+ # Note that in the current setup all monthly products are encoded using as nominal start date the 1st of each month, regardless of the real initialization date. You can find more information about how nominal start dates are assigned in the "Documentation" tab.
+ #
+ # Leadtime month: Select the lead time(s) you are interested in. This is the time, in months, from the initialization date.
+ # Note that the convention used for labelling the data implies that leadtime_month=1 is the first complete calendar month after the initialization date. In the current setup of all datasets that means that for a forecast initialised on the 1st of November, leadtime_month=1 is November.
+ #
+ # Geographical area: You can select a global field ("whole available area") or a regional subselection by providing the latitude and longitude of its corners.
+ #
+ # Data format: You can select the data format for your data retrieval.
+ # Currently, GRIB format is used to store C3S seasonal forecast datasets data files.
+ # An experimental netCDF conversion can be also accessed. You can find some related information in the "Documentation" tab.
+
+
# Setup spatial bounds
# N, W, S, E
spatial_bounds <- c("N" = unname(bbox_coords["ymax"]),
@@ -22,16 +70,19 @@ set_ecmwf_api_parameter <- function(years = 2005:2018,
# Up till last month.
# dates <- seq.Date(ymd("2017-9-01"), floor_date(today() - months(1), "month"), by = "month")
- dates <- seq.Date(lubridate::ymd(min(years), truncated = 2L), floor_date(today() - months(1), "month"), by = "month")
+ dates <- seq.Date(lubridate::ymd(start_year, truncated = 2L), floor_date(today() - months(1), "month"), by = "month")
seasonal_forecast_parameters <- tibble(year = year(dates), month = month(dates))
message(glue::glue("Preparing to fetch ecmwf {product_types}"))
+ # 2m_temperature (monthly mean) is the average 2-meter air temperature over the calendar month.
+ # 2m_dewpoint_temperature is the average dew point temperature over the same period.
+ # total_precipitation is typically the total accumulation for the month (not an average). Check metadata to confirm, as some datasets might report mean daily precipitation rates.
+
seasonal_forecast_parameters |>
mutate(spatial_bounds = list(spatial_bounds)) |>
mutate(variables = list(variables)) |>
mutate(product_types = list(product_types)) |>
mutate(leadtime_months = list(leadtime_months))
-
-}
\ No newline at end of file
+}
diff --git a/R/transform_ecmwf_forecasts.R b/R/transform_ecmwf_forecasts.R
index 1d4c985..45b51ff 100644
--- a/R/transform_ecmwf_forecasts.R
+++ b/R/transform_ecmwf_forecasts.R
@@ -41,7 +41,13 @@ transform_ecmwf_forecasts <- function(ecmwf_forecasts_api_parameters,
# re-run it.
error_safe_read_parquet <- possibly(arrow::open_dataset, NULL)
- if(!is.null(error_safe_read_parquet(transformed_file)) && year < year(Sys.time()) && !overwrite) {
+ # Re-run current forecasts as they may change
+ current_year <- as.numeric(format(Sys.Date(), "%Y"))
+ current_month <- as.numeric(format(Sys.Date(), "%m"))
+
+ if (!is.null(error_safe_read_parquet(transformed_file)) &&
+ (year < current_year || (year == current_year && month < current_month)) &&
+ !overwrite) {
message(glue::glue("{transformed_file} is already present and can be read."))
return(transformed_file)
}
@@ -70,8 +76,8 @@ transform_ecmwf_forecasts <- function(ecmwf_forecasts_api_parameters,
product_type = product_type,
variable = variable,
year = year,
- month = month,
- leadtime_month = unlist(ecmwf_forecasts_api_parameters$leadtime_months),
+ month = month, # The current month
+ leadtime_month = unlist(ecmwf_forecasts_api_parameters$leadtime_months), # What will the weather be X months from the current month?
area = round(unlist(ecmwf_forecasts_api_parameters$spatial_bounds), 1),
format = "grib",
dataset_short_name = "seasonal-monthly-single-levels",
@@ -112,15 +118,25 @@ transform_ecmwf_forecasts <- function(ecmwf_forecasts_api_parameters,
message(glue::glue("ecmwf_seasonal_forecast_{month}_{year} metadata successfully read."))
+ # The base date for an ECMWF forecast is the time when the forecast was initialized
+ # or made. For example, a forecast with a base date of Wed 1 Nov 2024 18 UTC (T+6) s
+ # means that the forecast was made at 18 UTC on Wednesday, November 1, 2024
+ # And lead month is the month average for that many months out with a lead month
+ # of 1 being the month that includes the base_date which _should_ always be on the
+ # first of the month. So base date 01-01-2005 1 lead month is the monthly average
+ # forecast for January 2005.
+
# 1. Convert kelvin to celsius (note these columns are mislabeled as C as provided by ecmwf)
- # 2. Fix total_precipitation metadata and convert units from m/second to mm/day.
+ # 2. Fix total_precipitation metadata and convert units from m/second to mm/day.
+ # Note the variable name is total_precipitation but it is really *mean total precipitation rate*
# 3. Correct precip sd
grib_data <- grib_data |> mutate(mean = ifelse(units == "C", mean - 273.15, ((mean > 0) * 8.64e+7 * mean)),
sd = ifelse(units == "", ((sd > 0) * 8.64e+7 * sd), sd),
var_id = ifelse(units == "", "tprate", var_id),
units = ifelse(units == "", "mm/day", units),
- month = month(forecast_end_date - 1),
- year = year(forecast_end_date - 1),
+ month = as.integer(lubridate::month(base_date)), # Base month
+ year = as.integer(lubridate::year(base_date)), # Base year
+ lead_month = as.integer(lubridate::month(forecast_end_date - 1)),
variable = fct_recode(variable,
dewpoint = "2m_dewpoint_temperature",
temperature = "2m_temperature",
@@ -128,9 +144,10 @@ transform_ecmwf_forecasts <- function(ecmwf_forecasts_api_parameters,
# Calculate relative humidity from temperature and dewpoint temperature
grib_data <- grib_data |>
- select(x, y, base_date, month, year, mean, sd, variable) |>
- pivot_wider(names_from = variable, values_from = c(mean, sd), names_glue = "{variable}_{.value}") |> # Reshape to make it easier to calculate composition values
+ select(x, y, base_date, month, year, lead_months, mean, sd, variable) |>
+ pivot_wider(names_from = variable, values_from = c(mean, sd), names_glue = "{variable}_{.value}") |> # Reshape to make it easier to calculate composite values like relative humidity
mutate(
+
# Calculate saturation and actual vapor pressures
saturation_vapor_pressure = exp((17.625 * temperature_mean) / (243.04 + temperature_mean)),
actual_vapor_pressure = exp((17.625 * dewpoint_mean) / (243.04 + dewpoint_mean)),
@@ -139,7 +156,7 @@ transform_ecmwf_forecasts <- function(ecmwf_forecasts_api_parameters,
relative_humidity_mean = 100 * actual_vapor_pressure / saturation_vapor_pressure,
# Calculate partial derivatives of RH with respect to temperature and dewpoint temperature
- # Used for propogation of error to get sd of rh from sd of temperature and dewpoint
+ # Used for propagation of error to get sd of rh from sd of temperature and dewpoint
dRH_dT = -relative_humidity_mean * (17.625 * 243.04) / ((243.04 + temperature_mean)^2),
dRH_dTd = relative_humidity_mean * (17.625 * 243.04) / ((243.04 + dewpoint_mean)^2),
diff --git a/R/transform_modis_ndvi.R b/R/transform_modis_ndvi.R
index 65259fc..5f0d3af 100644
--- a/R/transform_modis_ndvi.R
+++ b/R/transform_modis_ndvi.R
@@ -84,9 +84,9 @@ transform_modis_ndvi <- function(modis_ndvi_token,
mutate(days_count = as.integer(end_date - start_date) + 1) |>
uncount(days_count, .id = "step") |> # This is a pretty cool trick. Very fast.
mutate(date = start_date + step - 1,
- doy = lubridate::yday(date),
- month = lubridate::month(date),
- year = lubridate::year(date),
+ doy = as.integer(lubridate::yday(date)),
+ month = as.integer(lubridate::month(date)),
+ year = as.integer(lubridate::year(date)),
source = "modis")
# Save transformed rast as parquet
diff --git a/R/transform_sentinel_ndvi.R b/R/transform_sentinel_ndvi.R
index 9a426e9..25917fb 100644
--- a/R/transform_sentinel_ndvi.R
+++ b/R/transform_sentinel_ndvi.R
@@ -28,6 +28,7 @@
transform_sentinel_ndvi <- function(sentinel_ndvi_api_parameters,
continent_raster_template,
sentinel_ndvi_transformed_directory,
+ sentinel_ndvi_token_file = "sentinel.token",
overwrite = FALSE,
...) {
@@ -44,11 +45,8 @@ transform_sentinel_ndvi <- function(sentinel_ndvi_api_parameters,
# Extract start and end dates from the raw downloaded file name
# naming conventions
# https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-3-synergy/naming-conventions
- filename_dates <- regmatches(basename(raw_filename), gregexpr("\\d{8}", basename(raw_filename))) |>
- unlist() |>
- map_vec(~as.Date(.x, format = "%Y%m%d"))
- start_date <- min(filename_dates)
- end_date <- max(filename_dates)
+ start_date <- sentinel_ndvi_api_parameters$properties$startDate |> as.Date()
+ end_date <- sentinel_ndvi_api_parameters$properties$completionDate |> as.Date()
sentinel_ndvi_filename <- file.path(sentinel_ndvi_transformed_directory, glue::glue("transformed_sentinel_NDVI_{start_date}_to_{end_date}.gz.parquet"))
@@ -59,7 +57,7 @@ transform_sentinel_ndvi <- function(sentinel_ndvi_api_parameters,
}
# Download raw data
- sentinel_ndvi_downloaded <- download_sentinel_ndvi(sentinel_ndvi_api_parameters, raw_filename)
+ sentinel_ndvi_downloaded <- download_sentinel_ndvi(sentinel_ndvi_api_parameters, raw_filename, sentinel_ndvi_token_file)
message(paste0("Transforming ", raw_filename))
@@ -77,9 +75,9 @@ transform_sentinel_ndvi <- function(sentinel_ndvi_api_parameters,
days_count = as.integer(end_date - start_date) + 1) |>
uncount(days_count, .id = "step") |> # This is a pretty cool trick. Very fast.
mutate(date = start_date + step - 1,
- doy = lubridate::yday(date),
- month = lubridate::month(date),
- year = lubridate::year(date),
+ doy = as.integer(lubridate::yday(date)),
+ month = as.integer(lubridate::month(date)),
+ year = as.integer(lubridate::year(date)),
source = "sentinel") |>
select(-start_date, -end_date, -step)
diff --git a/README.html b/README.html
index 2947189..006d469 100644
--- a/README.html
+++ b/README.html
@@ -642,240 +642,228 @@
Repository Structure
mermaid.js
syntax and should display as a graph on GitHub.
It can also be viewed by pasting the code into https://mermaid.live.)
-
Warning messages: 1: package ‘rmarkdown’ was built under R version
-4.3.3 2: package ‘paws’ was built under R version 4.3.3 3: package
-‘terra’ was built under R version 4.3.3
+Warning messages: 1: package ‘targets’ was built under R version
+4.3.3 2: package ‘rmarkdown’ was built under R version 4.3.3 3: package
+‘paws’ was built under R version 4.3.3 4: package ‘terra’ was built
+under R version 4.3.3
graph LR
subgraph Project Workflow
subgraph Graph
direction LR
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- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> xbd6b5d8fe3154d5a["weather_historical_means"]:::queued
- x021b0407fd88c849(["lead_intervals"]):::skipped --> xbd6b5d8fe3154d5a["weather_historical_means"]:::queued
- x0548e231345702f7["nasa_weather_transformed"]:::queued --> xbd6b5d8fe3154d5a["weather_historical_means"]:::queued
- x711dc87df29f0a9c(["nasa_weather_transformed_directory"]):::skipped --> xbd6b5d8fe3154d5a["weather_historical_means"]:::queued
- xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued --> xbd6b5d8fe3154d5a["weather_historical_means"]:::queued
- x4407a62768444c3e(["weather_historical_means_directory"]):::skipped --> xbd6b5d8fe3154d5a["weather_historical_means"]:::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
+ x0548e231345702f7["nasa_weather_transformed"]:::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
+ x0df1395319c2f010(["weather_anomalies_AWS"]):::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
+ xf94f7486eed9869c(["weather_anomalies_directory"]):::completed --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
+ xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
+ xb06c08f4a8f21445(["lag_intervals"]):::completed --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
+ x0548e231345702f7["nasa_weather_transformed"]:::queued --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
+ xf94f7486eed9869c(["weather_anomalies_directory"]):::completed --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
+ xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
x049b29595ee19108(["aspect_AWS"]):::queued --> x155e2f0b29a20e05(["aspect_preprocessed"]):::queued
- x42a5375a64b48216(["aspect_directory"]):::skipped --> x155e2f0b29a20e05(["aspect_preprocessed"]):::queued
- x213d1d2657d00cd0(["aspect_urls"]):::skipped --> x155e2f0b29a20e05(["aspect_preprocessed"]):::queued
+ x42a5375a64b48216(["aspect_directory"]):::completed --> x155e2f0b29a20e05(["aspect_preprocessed"]):::queued
+ x213d1d2657d00cd0(["aspect_urls"]):::completed --> x155e2f0b29a20e05(["aspect_preprocessed"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> x155e2f0b29a20e05(["aspect_preprocessed"]):::queued
- x1f222a4448edddc4(["days_of_year"]):::skipped --> x44345ceb9b3d4a81["ndvi_historical_means"]:::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> x44345ceb9b3d4a81["ndvi_historical_means"]:::queued
- x92b237aaa434cba4(["ndvi_date_lookup"]):::queued --> x44345ceb9b3d4a81["ndvi_historical_means"]:::queued
- x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued --> x44345ceb9b3d4a81["ndvi_historical_means"]:::queued
- x7fef416d6ce259f3(["ndvi_historical_means_directory"]):::skipped --> x44345ceb9b3d4a81["ndvi_historical_means"]:::queued
- xe8b8ca5535fe5f2a(["bioclim_directory"]):::skipped --> xe2930fde1049416f(["bioclim_AWS"]):::queued
+ x27dbf0f2484063f3["wahis_outbreak_history"]:::queued --> x53890e32519c2cdc(["wahis_outbreak_history_AWS_upload"]):::queued
+ x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::completed --> x53890e32519c2cdc(["wahis_outbreak_history_AWS_upload"]):::queued
+ x659aa62eded9787b(["wahis_outbreaks"]):::queued --> xa33032ce29b67c7f(["wahis_distance_matrix"]):::queued
+ x39ef63e4c3553f78(["wahis_raster_template"]):::queued --> xa33032ce29b67c7f(["wahis_distance_matrix"]):::queued
+ x2b83f10567783884(["wahis_rvf_outbreaks_preprocessed"]):::queued --> x50043477563454fd(["wahis_outbreak_dates"]):::queued
+ xe8b8ca5535fe5f2a(["bioclim_directory"]):::completed --> xe2930fde1049416f(["bioclim_AWS"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> xe2930fde1049416f(["bioclim_AWS"]):::queued
- xa33032ce29b67c7f(["wahis_distance_matrix"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
- x50043477563454fd(["wahis_outbreak_dates"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
- xcc02e30ec90a7edd(["wahis_outbreak_history_directory"]):::skipped --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
- x659aa62eded9787b(["wahis_outbreaks"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
- x39ef63e4c3553f78(["wahis_raster_template"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x955e49f3e0c22510(["landcover_AWS"]):::queued
- x8894af119fe2eaa1(["landcover_directory"]):::skipped --> x955e49f3e0c22510(["landcover_AWS"]):::queued
- x42a5375a64b48216(["aspect_directory"]):::skipped --> x7039ba6fde7353f3(["soil_preprocessed_AWS_upload"]):::queued
- xd70b16641fa1b4ef(["soil_preprocessed"]):::queued --> x7039ba6fde7353f3(["soil_preprocessed_AWS_upload"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
- xa9eddcdb0d1f1d02(["get_sentinel_ndvi_AWS"]):::queued --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
- x6e1924e349d8e6e8(["sentinel_ndvi_api_parameters"]):::skipped --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
- x3ea733d22e9c32e7(["sentinel_ndvi_transformed_directory"]):::skipped --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
- xe3c4533ec81ef618(["continent_polygon"]):::skipped --> xba6244832b5285ba(["continent_raster_template"]):::queued
- x97fc33c6215703a3(["rsa_polygon"]):::skipped --> x8367f94bdb991b08(["rsa_polygon_spatial_weights"]):::queued
- x4847fdb918188b25(["country_polygons"]):::skipped --> x53c4b2fb80542353(["country_bounding_boxes"]):::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> xf9b79e824823a870["ndvi_anomalies"]:::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
- x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
- xe2329877730e44b5(["ndvi_anomalies_directory"]):::skipped --> xf9b79e824823a870["ndvi_anomalies"]:::queued
- x92b237aaa434cba4(["ndvi_date_lookup"]):::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
- x44345ceb9b3d4a81["ndvi_historical_means"]:::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
- x3ea733d22e9c32e7(["sentinel_ndvi_transformed_directory"]):::skipped --> xa9eddcdb0d1f1d02(["get_sentinel_ndvi_AWS"]):::queued
- x53c4b2fb80542353(["country_bounding_boxes"]):::queued --> xc54ffbea58c4afd9(["nasa_weather_coordinates"]):::queued
- xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued --> x705cc9e765652376(["forecasts_anomalies_validate_AWS_upload"]):::queued
- x309ea01959a83a5a(["forecasts_validate_directory"]):::skipped --> x705cc9e765652376(["forecasts_anomalies_validate_AWS_upload"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> x5130788afbe32544["modis_ndvi_transformed"]:::queued
- xcfc776190ac6b73c(["modis_ndvi_bundle_request"]):::queued --> x5130788afbe32544["modis_ndvi_transformed"]:::queued
+ xb64343d9bc0ef12e(["modis_ndvi_requests"]):::queued --> x5130788afbe32544["modis_ndvi_transformed"]:::queued
x3f3ba2f9e89a9591(["modis_ndvi_token"]):::completed --> x5130788afbe32544["modis_ndvi_transformed"]:::queued
xf36f13d6d1345340(["modis_ndvi_transformed_AWS"]):::queued --> x5130788afbe32544["modis_ndvi_transformed"]:::queued
xdc843e2504e22144(["modis_ndvi_transformed_directory"]):::skipped --> x5130788afbe32544["modis_ndvi_transformed"]:::queued
- x44345ceb9b3d4a81["ndvi_historical_means"]:::queued --> x1be60916d37ebe0f(["ndvi_historical_means_AWS_upload"]):::queued
- x7fef416d6ce259f3(["ndvi_historical_means_directory"]):::skipped --> x1be60916d37ebe0f(["ndvi_historical_means_AWS_upload"]):::queued
+ x9c9060069417a49a(["wahis_rvf_outbreaks_raw"]):::completed --> x2b83f10567783884(["wahis_rvf_outbreaks_preprocessed"]):::queued
+ x2e80ddc3dafd7312(["augmented_data_directory"]):::completed --> x67bf5d7b4af55c88(["augmented_data_AWS"]):::queued
+ x482d364fd551ff53(["augmented_data_sources"]):::queued --> x67bf5d7b4af55c88(["augmented_data_AWS"]):::queued
+ x27dbf0f2484063f3["wahis_outbreak_history"]:::queued --> x16e1cc582647deec["wahis_outbreak_history_animations"]:::queued
+ x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::completed --> x16e1cc582647deec["wahis_outbreak_history_animations"]:::queued
+ xa33032ce29b67c7f(["wahis_distance_matrix"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
+ x50043477563454fd(["wahis_outbreak_dates"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
+ xcc02e30ec90a7edd(["wahis_outbreak_history_directory"]):::completed --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
+ x659aa62eded9787b(["wahis_outbreaks"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
+ x39ef63e4c3553f78(["wahis_raster_template"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
+ x16e1cc582647deec["wahis_outbreak_history_animations"]:::queued --> x3a8830b5def8250b(["wahis_outbreak_history_animations_AWS_upload"]):::queued
+ x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::completed --> x3a8830b5def8250b(["wahis_outbreak_history_animations_AWS_upload"]):::queued
+ x01b9e03cb52b7b05["weather_anomalies"]:::queued --> xc567f473073bf453(["weather_anomalies_AWS_upload"]):::queued
+ xf94f7486eed9869c(["weather_anomalies_directory"]):::completed --> xc567f473073bf453(["weather_anomalies_AWS_upload"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> xdecc37cc7e708cec(["landcover_preprocessed"]):::queued
x955e49f3e0c22510(["landcover_AWS"]):::queued --> xdecc37cc7e708cec(["landcover_preprocessed"]):::queued
- x8894af119fe2eaa1(["landcover_directory"]):::skipped --> xdecc37cc7e708cec(["landcover_preprocessed"]):::queued
- x684d7fe78b0e841d(["landcover_types"]):::skipped --> xdecc37cc7e708cec(["landcover_preprocessed"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x32725338020380f8(["get_ecmwf_forecasts_AWS"]):::queued
- x73599238bfebd1c5(["ecmwf_forecasts_api_parameters"]):::queued --> x32725338020380f8(["get_ecmwf_forecasts_AWS"]):::queued
- x16ce463b7b647c1e(["ecmwf_forecasts_transformed_directory"]):::skipped --> x32725338020380f8(["get_ecmwf_forecasts_AWS"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x0dffb1605751d1b1(["elevation_preprocessed"]):::queued
- x98b1351d966647f6(["elevation_AWS"]):::queued --> x0dffb1605751d1b1(["elevation_preprocessed"]):::queued
- x0381132b9136146c(["elevation_directory"]):::skipped --> x0dffb1605751d1b1(["elevation_preprocessed"]):::queued
- x5130788afbe32544["modis_ndvi_transformed"]:::queued --> xe90a7836ba709288(["modis_ndvi_transformed_AWS_upload"]):::queued
- xdc843e2504e22144(["modis_ndvi_transformed_directory"]):::skipped --> xe90a7836ba709288(["modis_ndvi_transformed_AWS_upload"]):::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
- x0548e231345702f7["nasa_weather_transformed"]:::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
- x711dc87df29f0a9c(["nasa_weather_transformed_directory"]):::skipped --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
- x0df1395319c2f010(["weather_anomalies_AWS"]):::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
- xf94f7486eed9869c(["weather_anomalies_directory"]):::skipped --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
- xbd6b5d8fe3154d5a["weather_historical_means"]:::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
- xe8b8ca5535fe5f2a(["bioclim_directory"]):::skipped --> xe4be5b46895c0f8c(["bioclim_preprocessed_AWS_upload"]):::queued
- x1c7b6e6a1c101e59(["bioclim_preprocessed"]):::queued --> xe4be5b46895c0f8c(["bioclim_preprocessed_AWS_upload"]):::queued
- x680f7450837c9229["forecasts_anomalies"]:::queued --> xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued
- xcc18535b953bde28(["forecasts_anomalies_validate_AWS"]):::queued --> xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued
- x309ea01959a83a5a(["forecasts_validate_directory"]):::skipped --> xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued
- x021b0407fd88c849(["lead_intervals"]):::skipped --> xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued
- x0548e231345702f7["nasa_weather_transformed"]:::queued --> xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued
- xbd6b5d8fe3154d5a["weather_historical_means"]:::queued --> xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued
- x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
- x8ff15aa322c64802(["forecasts_anomalies_directory"]):::skipped --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
- x021b0407fd88c849(["lead_intervals"]):::skipped --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
- xbd6b5d8fe3154d5a["weather_historical_means"]:::queued --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
- x1f222a4448edddc4(["days_of_year"]):::skipped --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
- x021b0407fd88c849(["lead_intervals"]):::skipped --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
- x0548e231345702f7["nasa_weather_transformed"]:::queued --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
- x4407a62768444c3e(["weather_historical_means_directory"]):::skipped --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
- x6bae1f342f811d0b(["wahis_rvf_controls_raw"]):::skipped --> x2668bdb7843be979(["wahis_rvf_controls_preprocessed"]):::queued
- x165085d61327782d(["slope_directory"]):::skipped --> x5aa9efa15ecd03d0(["slope_preprocessed_AWS_upload"]):::queued
- x680370f9b58b9f6d(["slope_preprocessed"]):::queued --> x5aa9efa15ecd03d0(["slope_preprocessed_AWS_upload"]):::queued
- xdc843e2504e22144(["modis_ndvi_transformed_directory"]):::skipped --> x24983cd244fff5db(["modis_ndvi_bundle_request_file"]):::queued
- xb49d77ffc5b097ae(["continent_bounding_box"]):::queued --> x73599238bfebd1c5(["ecmwf_forecasts_api_parameters"]):::queued
- x680f7450837c9229["forecasts_anomalies"]:::queued --> x72d065c3b2ed1267(["forecasts_anomalies_AWS_upload"]):::queued
- x8ff15aa322c64802(["forecasts_anomalies_directory"]):::skipped --> x72d065c3b2ed1267(["forecasts_anomalies_AWS_upload"]):::queued
- xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued --> x6db823df8cb78984(["sentinel_ndvi_transformed_AWS_upload"]):::queued
- x3ea733d22e9c32e7(["sentinel_ndvi_transformed_directory"]):::skipped --> x6db823df8cb78984(["sentinel_ndvi_transformed_AWS_upload"]):::queued
+ x8894af119fe2eaa1(["landcover_directory"]):::completed --> xdecc37cc7e708cec(["landcover_preprocessed"]):::queued
+ x684d7fe78b0e841d(["landcover_types"]):::completed --> xdecc37cc7e708cec(["landcover_preprocessed"]):::queued
+ xe8b8ca5535fe5f2a(["bioclim_directory"]):::completed --> xb22e604d282eb0d4(["ta"]):::queued
+ x1c7b6e6a1c101e59(["bioclim_preprocessed"]):::queued --> xb22e604d282eb0d4(["ta"]):::queued
+ x4847fdb918188b25(["country_polygons"]):::completed --> x53c4b2fb80542353(["country_bounding_boxes"]):::queued
+ x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued --> xe017ffc3bafa162a(["ecmwf_forecasts_transformed_AWS_upload"]):::queued
+ x16ce463b7b647c1e(["ecmwf_forecasts_transformed_directory"]):::completed --> xe017ffc3bafa162a(["ecmwf_forecasts_transformed_AWS_upload"]):::queued
+ x53c4b2fb80542353(["country_bounding_boxes"]):::queued --> xc54ffbea58c4afd9(["nasa_weather_coordinates"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> xd70b16641fa1b4ef(["soil_preprocessed"]):::queued
x4110b36142c7dd5b(["soil_AWS"]):::queued --> xd70b16641fa1b4ef(["soil_preprocessed"]):::queued
- x9c14f0532ee1f83c(["soil_directory"]):::skipped --> xd70b16641fa1b4ef(["soil_preprocessed"]):::queued
- xe8b8ca5535fe5f2a(["bioclim_directory"]):::skipped --> x1c7b6e6a1c101e59(["bioclim_preprocessed"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x1c7b6e6a1c101e59(["bioclim_preprocessed"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x71c93c84792ad529(["glw_AWS"]):::queued
- x5448b80c3909d641(["glw_directory"]):::skipped --> x71c93c84792ad529(["glw_AWS"]):::queued
- x42a5375a64b48216(["aspect_directory"]):::skipped --> x890a8fc59a28f6b2(["slope_AWS"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x890a8fc59a28f6b2(["slope_AWS"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x680370f9b58b9f6d(["slope_preprocessed"]):::queued
- x890a8fc59a28f6b2(["slope_AWS"]):::queued --> x680370f9b58b9f6d(["slope_preprocessed"]):::queued
- x165085d61327782d(["slope_directory"]):::skipped --> x680370f9b58b9f6d(["slope_preprocessed"]):::queued
- x1ef0d1881ff89dbd(["slope_urls"]):::skipped --> x680370f9b58b9f6d(["slope_preprocessed"]):::queued
+ x9c14f0532ee1f83c(["soil_directory"]):::completed --> xd70b16641fa1b4ef(["soil_preprocessed"]):::queued
+ xe3c4533ec81ef618(["continent_polygon"]):::skipped --> x73599238bfebd1c5(["ecmwf_forecasts_api_parameters"]):::queued
+ x42a5375a64b48216(["aspect_directory"]):::completed --> xfe5a910dc093a019(["aspect_preprocessed_AWS_upload"]):::queued
+ x155e2f0b29a20e05(["aspect_preprocessed"]):::queued --> xfe5a910dc093a019(["aspect_preprocessed_AWS_upload"]):::queued
+ xe3c4533ec81ef618(["continent_polygon"]):::skipped --> x39ef63e4c3553f78(["wahis_raster_template"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> xf36f13d6d1345340(["modis_ndvi_transformed_AWS"]):::queued
- xcfc776190ac6b73c(["modis_ndvi_bundle_request"]):::queued --> xf36f13d6d1345340(["modis_ndvi_transformed_AWS"]):::queued
+ xcfc776190ac6b73c["modis_ndvi_bundle_request"]:::queued --> xf36f13d6d1345340(["modis_ndvi_transformed_AWS"]):::queued
x3f3ba2f9e89a9591(["modis_ndvi_token"]):::completed --> xf36f13d6d1345340(["modis_ndvi_transformed_AWS"]):::queued
xdc843e2504e22144(["modis_ndvi_transformed_directory"]):::skipped --> xf36f13d6d1345340(["modis_ndvi_transformed_AWS"]):::queued
- x2b83f10567783884(["wahis_rvf_outbreaks_preprocessed"]):::queued --> x50043477563454fd(["wahis_outbreak_dates"]):::queued
+ x42a5375a64b48216(["aspect_directory"]):::completed --> x890a8fc59a28f6b2(["slope_AWS"]):::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x890a8fc59a28f6b2(["slope_AWS"]):::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x955e49f3e0c22510(["landcover_AWS"]):::queued
+ x8894af119fe2eaa1(["landcover_directory"]):::completed --> x955e49f3e0c22510(["landcover_AWS"]):::queued
+ xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued --> x6db823df8cb78984(["sentinel_ndvi_transformed_AWS_upload"]):::queued
+ x3ea733d22e9c32e7(["sentinel_ndvi_transformed_directory"]):::completed --> x6db823df8cb78984(["sentinel_ndvi_transformed_AWS_upload"]):::queued
+ x0381132b9136146c(["elevation_directory"]):::completed --> xd9f5e6274aef515b(["elevation_preprocessed_AWS_upload"]):::queued
+ x0dffb1605751d1b1(["elevation_preprocessed"]):::queued --> xd9f5e6274aef515b(["elevation_preprocessed_AWS_upload"]):::queued
+ x0548e231345702f7["nasa_weather_transformed"]:::queued --> xddb5620937cdbc01(["nasa_weather_transformed_AWS_upload"]):::queued
+ x711dc87df29f0a9c(["nasa_weather_transformed_directory"]):::completed --> xddb5620937cdbc01(["nasa_weather_transformed_AWS_upload"]):::queued
+ x67bf5d7b4af55c88(["augmented_data_AWS"]):::queued --> xcc8316047ac6de28(["augmented_data"]):::queued
+ x2e80ddc3dafd7312(["augmented_data_directory"]):::completed --> xcc8316047ac6de28(["augmented_data"]):::queued
+ x482d364fd551ff53(["augmented_data_sources"]):::queued --> xcc8316047ac6de28(["augmented_data"]):::queued
+ x1f222a4448edddc4(["days_of_year"]):::completed --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
+ xb06c08f4a8f21445(["lag_intervals"]):::completed --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
+ x021b0407fd88c849(["lead_intervals"]):::completed --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
+ x0548e231345702f7["nasa_weather_transformed"]:::queued --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
+ x4407a62768444c3e(["weather_historical_means_directory"]):::completed --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
+ x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued --> x1be60916d37ebe0f(["ndvi_historical_means_AWS_upload"]):::queued
+ x7fef416d6ce259f3(["ndvi_historical_means_directory"]):::completed --> x1be60916d37ebe0f(["ndvi_historical_means_AWS_upload"]):::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
+ x5130788afbe32544["modis_ndvi_transformed"]:::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
+ x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
+ xe2329877730e44b5(["ndvi_anomalies_directory"]):::completed --> xf9b79e824823a870["ndvi_anomalies"]:::queued
+ x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
+ xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
+ x5130788afbe32544["modis_ndvi_transformed"]:::queued --> x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued
+ x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued --> x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued
+ x7fef416d6ce259f3(["ndvi_historical_means_directory"]):::completed --> x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued
+ xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued --> x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued
+ xcfc776190ac6b73c["modis_ndvi_bundle_request"]:::queued --> xb64343d9bc0ef12e(["modis_ndvi_requests"]):::queued
+ xa5bc51cd67d5e6c0["modis_ndvi_task_id_continent"]:::queued --> xcfc776190ac6b73c["modis_ndvi_bundle_request"]:::queued
+ x3f3ba2f9e89a9591(["modis_ndvi_token"]):::completed --> xcfc776190ac6b73c["modis_ndvi_bundle_request"]:::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x0dffb1605751d1b1(["elevation_preprocessed"]):::queued
+ x98b1351d966647f6(["elevation_AWS"]):::queued --> x0dffb1605751d1b1(["elevation_preprocessed"]):::queued
+ x0381132b9136146c(["elevation_directory"]):::completed --> x0dffb1605751d1b1(["elevation_preprocessed"]):::queued
+ xe3c4533ec81ef618(["continent_polygon"]):::skipped --> xba6244832b5285ba(["continent_raster_template"]):::queued
+ x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued --> x680f7450837c9229["forecasts_anomalies"]:::queued
+ x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued --> x680f7450837c9229["forecasts_anomalies"]:::queued
+ x8ff15aa322c64802(["forecasts_anomalies_directory"]):::completed --> x680f7450837c9229["forecasts_anomalies"]:::queued
+ x021b0407fd88c849(["lead_intervals"]):::completed --> x680f7450837c9229["forecasts_anomalies"]:::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> x680f7450837c9229["forecasts_anomalies"]:::queued
+ xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued --> x680f7450837c9229["forecasts_anomalies"]:::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x98b1351d966647f6(["elevation_AWS"]):::queued
+ x0381132b9136146c(["elevation_directory"]):::completed --> x98b1351d966647f6(["elevation_AWS"]):::queued
+ x5130788afbe32544["modis_ndvi_transformed"]:::queued --> xe90a7836ba709288(["modis_ndvi_transformed_AWS_upload"]):::queued
+ xdc843e2504e22144(["modis_ndvi_transformed_directory"]):::skipped --> xe90a7836ba709288(["modis_ndvi_transformed_AWS_upload"]):::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
+ xa9eddcdb0d1f1d02(["get_sentinel_ndvi_AWS"]):::queued --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
+ x6e1924e349d8e6e8(["sentinel_ndvi_api_parameters"]):::completed --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
+ x3ea733d22e9c32e7(["sentinel_ndvi_transformed_directory"]):::completed --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
+ x30a742f54b518a5f(["augmented_data_rsa_directory"]):::completed --> x62efb3d9001cb58b(["augmented_data_rsa_AWS"]):::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> x62efb3d9001cb58b(["augmented_data_rsa_AWS"]):::queued
+ xf9b79e824823a870["ndvi_anomalies"]:::queued --> x62efb3d9001cb58b(["augmented_data_rsa_AWS"]):::queued
+ x01b9e03cb52b7b05["weather_anomalies"]:::queued --> x62efb3d9001cb58b(["augmented_data_rsa_AWS"]):::queued
+ xcc8316047ac6de28(["augmented_data"]):::queued --> xcfd8f1e8f3ea9117["aggregated_data_rsa"]:::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> xcfd8f1e8f3ea9117["aggregated_data_rsa"]:::queued
+ x97fc33c6215703a3(["rsa_polygon"]):::completed --> xcfd8f1e8f3ea9117["aggregated_data_rsa"]:::queued
xa33032ce29b67c7f(["wahis_distance_matrix"]):::queued --> x27dbf0f2484063f3["wahis_outbreak_history"]:::queued
x50043477563454fd(["wahis_outbreak_dates"]):::queued --> x27dbf0f2484063f3["wahis_outbreak_history"]:::queued
x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued --> x27dbf0f2484063f3["wahis_outbreak_history"]:::queued
- xcc02e30ec90a7edd(["wahis_outbreak_history_directory"]):::skipped --> x27dbf0f2484063f3["wahis_outbreak_history"]:::queued
+ xcc02e30ec90a7edd(["wahis_outbreak_history_directory"]):::completed --> x27dbf0f2484063f3["wahis_outbreak_history"]:::queued
x659aa62eded9787b(["wahis_outbreaks"]):::queued --> x27dbf0f2484063f3["wahis_outbreak_history"]:::queued
x39ef63e4c3553f78(["wahis_raster_template"]):::queued --> x27dbf0f2484063f3["wahis_outbreak_history"]:::queued
- xe3c4533ec81ef618(["continent_polygon"]):::skipped --> xb49d77ffc5b097ae(["continent_bounding_box"]):::queued
- x50d291d42ebde68c(["combined_anomalies_directory"]):::skipped --> x439c9f5bc1e96cd5(["combined_anomalies_AWS"]):::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> x439c9f5bc1e96cd5(["combined_anomalies_AWS"]):::queued
- xf9b79e824823a870["ndvi_anomalies"]:::queued --> x439c9f5bc1e96cd5(["combined_anomalies_AWS"]):::queued
- x01b9e03cb52b7b05["weather_anomalies"]:::queued --> x439c9f5bc1e96cd5(["combined_anomalies_AWS"]):::queued
+ x2b83f10567783884(["wahis_rvf_outbreaks_preprocessed"]):::queued --> x659aa62eded9787b(["wahis_outbreaks"]):::queued
+ x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
+ x8ff15aa322c64802(["forecasts_anomalies_directory"]):::completed --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
+ x021b0407fd88c849(["lead_intervals"]):::completed --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
+ xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
+ x9c14f0532ee1f83c(["soil_directory"]):::completed --> x7039ba6fde7353f3(["soil_preprocessed_AWS_upload"]):::queued
+ xd70b16641fa1b4ef(["soil_preprocessed"]):::queued --> x7039ba6fde7353f3(["soil_preprocessed_AWS_upload"]):::queued
+ xe3c4533ec81ef618(["continent_polygon"]):::skipped --> xa5bc51cd67d5e6c0["modis_ndvi_task_id_continent"]:::queued
+ x3f3ba2f9e89a9591(["modis_ndvi_token"]):::completed --> xa5bc51cd67d5e6c0["modis_ndvi_task_id_continent"]:::queued
+ xdc843e2504e22144(["modis_ndvi_transformed_directory"]):::skipped --> xa5bc51cd67d5e6c0["modis_ndvi_task_id_continent"]:::queued
+ xb406dc4c2762194f(["modis_task_end_dates"]):::queued --> xa5bc51cd67d5e6c0["modis_ndvi_task_id_continent"]:::queued
+ x155e2f0b29a20e05(["aspect_preprocessed"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x1c7b6e6a1c101e59(["bioclim_preprocessed"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x0dffb1605751d1b1(["elevation_preprocessed"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x680f7450837c9229["forecasts_anomalies"]:::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x82990a83bfa4db45(["glw_preprocessed"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ xdecc37cc7e708cec(["landcover_preprocessed"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ xf9b79e824823a870["ndvi_anomalies"]:::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x680370f9b58b9f6d(["slope_preprocessed"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ xd70b16641fa1b4ef(["soil_preprocessed"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x27dbf0f2484063f3["wahis_outbreak_history"]:::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x01b9e03cb52b7b05["weather_anomalies"]:::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ xb06c08f4a8f21445(["lag_intervals"]):::completed --> x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued
+ xe2329877730e44b5(["ndvi_anomalies_directory"]):::completed --> x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued
+ x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued --> x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued
+ x3ea733d22e9c32e7(["sentinel_ndvi_transformed_directory"]):::completed --> xa9eddcdb0d1f1d02(["get_sentinel_ndvi_AWS"]):::queued
+ x0548e231345702f7["nasa_weather_transformed"]:::queued --> xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued
+ xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued --> xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued
+ x4407a62768444c3e(["weather_historical_means_directory"]):::completed --> xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued
xf9b79e824823a870["ndvi_anomalies"]:::queued --> x144f59a0db036a4b(["ndvi_anomalies_AWS_upload"]):::queued
- xe2329877730e44b5(["ndvi_anomalies_directory"]):::skipped --> x144f59a0db036a4b(["ndvi_anomalies_AWS_upload"]):::queued
- x680f7450837c9229["forecasts_anomalies"]:::queued --> xcc18535b953bde28(["forecasts_anomalies_validate_AWS"]):::queued
- x309ea01959a83a5a(["forecasts_validate_directory"]):::skipped --> xcc18535b953bde28(["forecasts_anomalies_validate_AWS"]):::queued
- x021b0407fd88c849(["lead_intervals"]):::skipped --> xcc18535b953bde28(["forecasts_anomalies_validate_AWS"]):::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> xcc18535b953bde28(["forecasts_anomalies_validate_AWS"]):::queued
- x0548e231345702f7["nasa_weather_transformed"]:::queued --> xcc18535b953bde28(["forecasts_anomalies_validate_AWS"]):::queued
- xbd6b5d8fe3154d5a["weather_historical_means"]:::queued --> xcc18535b953bde28(["forecasts_anomalies_validate_AWS"]):::queued
- x27dbf0f2484063f3["wahis_outbreak_history"]:::queued --> x53890e32519c2cdc(["wahis_outbreak_history_AWS_upload"]):::queued
- x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::skipped --> x53890e32519c2cdc(["wahis_outbreak_history_AWS_upload"]):::queued
+ xe2329877730e44b5(["ndvi_anomalies_directory"]):::completed --> x144f59a0db036a4b(["ndvi_anomalies_AWS_upload"]):::queued
+ x8894af119fe2eaa1(["landcover_directory"]):::completed --> xbc982b2f29054bd9(["landcover_preprocessed_AWS_upload"]):::queued
+ xdecc37cc7e708cec(["landcover_preprocessed"]):::queued --> xbc982b2f29054bd9(["landcover_preprocessed_AWS_upload"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> x0548e231345702f7["nasa_weather_transformed"]:::queued
x84fbc80b775022e1(["nasa_weather_AWS"]):::queued --> x0548e231345702f7["nasa_weather_transformed"]:::queued
xc54ffbea58c4afd9(["nasa_weather_coordinates"]):::queued --> x0548e231345702f7["nasa_weather_transformed"]:::queued
- x711dc87df29f0a9c(["nasa_weather_transformed_directory"]):::skipped --> x0548e231345702f7["nasa_weather_transformed"]:::queued
- x0c2748f0f39a3907(["nasa_weather_years"]):::skipped --> x0548e231345702f7["nasa_weather_transformed"]:::queued
- x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued --> xe017ffc3bafa162a(["ecmwf_forecasts_transformed_AWS_upload"]):::queued
- x16ce463b7b647c1e(["ecmwf_forecasts_transformed_directory"]):::skipped --> xe017ffc3bafa162a(["ecmwf_forecasts_transformed_AWS_upload"]):::queued
- x2b83f10567783884(["wahis_rvf_outbreaks_preprocessed"]):::queued --> x659aa62eded9787b(["wahis_outbreaks"]):::queued
- xb49d77ffc5b097ae(["continent_bounding_box"]):::queued --> xa5bc51cd67d5e6c0(["modis_ndvi_task_id_continent"]):::queued
- x3f3ba2f9e89a9591(["modis_ndvi_token"]):::completed --> xa5bc51cd67d5e6c0(["modis_ndvi_task_id_continent"]):::queued
- x16e1cc582647deec["wahis_outbreak_history_animations"]:::queued --> x3a8830b5def8250b(["wahis_outbreak_history_animations_AWS_upload"]):::queued
- x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::skipped --> x3a8830b5def8250b(["wahis_outbreak_history_animations_AWS_upload"]):::queued
- x5448b80c3909d641(["glw_directory"]):::skipped --> x01e625a4f1dd2c42(["glw_preprocessed_AWS_upload"]):::queued
- x82990a83bfa4db45(["glw_preprocessed"]):::queued --> x01e625a4f1dd2c42(["glw_preprocessed_AWS_upload"]):::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> xcfd8f1e8f3ea9117["aggregated_data_rsa"]:::queued
- x97fc33c6215703a3(["rsa_polygon"]):::skipped --> xcfd8f1e8f3ea9117["aggregated_data_rsa"]:::queued
- x1f222a4448edddc4(["days_of_year"]):::skipped --> x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued
- x92b237aaa434cba4(["ndvi_date_lookup"]):::queued --> x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued
- x7fef416d6ce259f3(["ndvi_historical_means_directory"]):::skipped --> x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued
- x5130788afbe32544["modis_ndvi_transformed"]:::queued --> x92b237aaa434cba4(["ndvi_date_lookup"]):::queued
- xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued --> x92b237aaa434cba4(["ndvi_date_lookup"]):::queued
- x659aa62eded9787b(["wahis_outbreaks"]):::queued --> xa33032ce29b67c7f(["wahis_distance_matrix"]):::queued
- x39ef63e4c3553f78(["wahis_raster_template"]):::queued --> xa33032ce29b67c7f(["wahis_distance_matrix"]):::queued
- x27dbf0f2484063f3["wahis_outbreak_history"]:::queued --> x16e1cc582647deec["wahis_outbreak_history_animations"]:::queued
- x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::skipped --> x16e1cc582647deec["wahis_outbreak_history_animations"]:::queued
- x27dbf0f2484063f3["wahis_outbreak_history"]:::queued --> x2b50e7687b4412ab(["wahis_outbreak_history_animations_AWS"]):::queued
- x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::skipped --> x2b50e7687b4412ab(["wahis_outbreak_history_animations_AWS"]):::queued
- x8894af119fe2eaa1(["landcover_directory"]):::skipped --> xbc982b2f29054bd9(["landcover_preprocessed_AWS_upload"]):::queued
- xdecc37cc7e708cec(["landcover_preprocessed"]):::queued --> xbc982b2f29054bd9(["landcover_preprocessed_AWS_upload"]):::queued
- x42a5375a64b48216(["aspect_directory"]):::skipped --> xfe5a910dc093a019(["aspect_preprocessed_AWS_upload"]):::queued
- x155e2f0b29a20e05(["aspect_preprocessed"]):::queued --> xfe5a910dc093a019(["aspect_preprocessed_AWS_upload"]):::queued
- x439c9f5bc1e96cd5(["combined_anomalies_AWS"]):::queued --> xfde5ff2681c50d89(["combined_anomalies"]):::queued
- x50d291d42ebde68c(["combined_anomalies_directory"]):::skipped --> xfde5ff2681c50d89(["combined_anomalies"]):::queued
- x680f7450837c9229["forecasts_anomalies"]:::queued --> xfde5ff2681c50d89(["combined_anomalies"]):::queued
- xf9b79e824823a870["ndvi_anomalies"]:::queued --> xfde5ff2681c50d89(["combined_anomalies"]):::queued
- x01b9e03cb52b7b05["weather_anomalies"]:::queued --> xfde5ff2681c50d89(["combined_anomalies"]):::queued
- x42a5375a64b48216(["aspect_directory"]):::skipped --> x049b29595ee19108(["aspect_AWS"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x049b29595ee19108(["aspect_AWS"]):::queued
- x9c9060069417a49a(["wahis_rvf_outbreaks_raw"]):::skipped --> x2b83f10567783884(["wahis_rvf_outbreaks_preprocessed"]):::queued
- xfde5ff2681c50d89(["combined_anomalies"]):::queued --> xba5d6169ff0233fa(["combined_anomalies_AWS_upload"]):::queued
- x50d291d42ebde68c(["combined_anomalies_directory"]):::skipped --> xba5d6169ff0233fa(["combined_anomalies_AWS_upload"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x82990a83bfa4db45(["glw_preprocessed"]):::queued
- x71c93c84792ad529(["glw_AWS"]):::queued --> x82990a83bfa4db45(["glw_preprocessed"]):::queued
- x5448b80c3909d641(["glw_directory"]):::skipped --> x82990a83bfa4db45(["glw_preprocessed"]):::queued
- x4d4a15b2f0f1851f(["glw_urls"]):::skipped --> x82990a83bfa4db45(["glw_preprocessed"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x98b1351d966647f6(["elevation_AWS"]):::queued
- x0381132b9136146c(["elevation_directory"]):::skipped --> x98b1351d966647f6(["elevation_AWS"]):::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> xc61c34839fb8c873(["model_dates_selected"]):::queued
- x01b9e03cb52b7b05["weather_anomalies"]:::queued --> xc567f473073bf453(["weather_anomalies_AWS_upload"]):::queued
- xf94f7486eed9869c(["weather_anomalies_directory"]):::skipped --> xc567f473073bf453(["weather_anomalies_AWS_upload"]):::queued
- xbd6b5d8fe3154d5a["weather_historical_means"]:::queued --> xf8b72b30842f6a3c(["weather_historical_means_AWS_upload"]):::queued
- x4407a62768444c3e(["weather_historical_means_directory"]):::skipped --> xf8b72b30842f6a3c(["weather_historical_means_AWS_upload"]):::queued
+ x711dc87df29f0a9c(["nasa_weather_transformed_directory"]):::completed --> x0548e231345702f7["nasa_weather_transformed"]:::queued
+ x0c2748f0f39a3907(["nasa_weather_years"]):::queued --> x0548e231345702f7["nasa_weather_transformed"]:::queued
+ xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued --> xf8b72b30842f6a3c(["weather_historical_means_AWS_upload"]):::queued
+ x4407a62768444c3e(["weather_historical_means_directory"]):::completed --> xf8b72b30842f6a3c(["weather_historical_means_AWS_upload"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> x84fbc80b775022e1(["nasa_weather_AWS"]):::queued
xc54ffbea58c4afd9(["nasa_weather_coordinates"]):::queued --> x84fbc80b775022e1(["nasa_weather_AWS"]):::queued
- x711dc87df29f0a9c(["nasa_weather_transformed_directory"]):::skipped --> x84fbc80b775022e1(["nasa_weather_AWS"]):::queued
- x0c2748f0f39a3907(["nasa_weather_years"]):::skipped --> x84fbc80b775022e1(["nasa_weather_AWS"]):::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
- x0548e231345702f7["nasa_weather_transformed"]:::queued --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
- xf94f7486eed9869c(["weather_anomalies_directory"]):::skipped --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
- xbd6b5d8fe3154d5a["weather_historical_means"]:::queued --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
- x30a742f54b518a5f(["augmented_data_rsa_directory"]):::skipped --> x30a742f54b518a5f(["augmented_data_rsa_directory"]):::skipped
- xdc94d22b863438a5(["nasa_weather_variables"]):::skipped --> xdc94d22b863438a5(["nasa_weather_variables"]):::skipped
+ x711dc87df29f0a9c(["nasa_weather_transformed_directory"]):::completed --> x84fbc80b775022e1(["nasa_weather_AWS"]):::queued
+ x0c2748f0f39a3907(["nasa_weather_years"]):::queued --> x84fbc80b775022e1(["nasa_weather_AWS"]):::queued
+ xcc8316047ac6de28(["augmented_data"]):::queued --> x3130c5a4e0174582(["augmented_data_AWS_upload"]):::queued
+ x2e80ddc3dafd7312(["augmented_data_directory"]):::completed --> x3130c5a4e0174582(["augmented_data_AWS_upload"]):::queued
+ xe8b8ca5535fe5f2a(["bioclim_directory"]):::completed --> x1c7b6e6a1c101e59(["bioclim_preprocessed"]):::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x1c7b6e6a1c101e59(["bioclim_preprocessed"]):::queued
+ x5448b80c3909d641(["glw_directory"]):::completed --> x01e625a4f1dd2c42(["glw_preprocessed_AWS_upload"]):::queued
+ x82990a83bfa4db45(["glw_preprocessed"]):::queued --> x01e625a4f1dd2c42(["glw_preprocessed_AWS_upload"]):::queued
+ xdc94d22b863438a5(["nasa_weather_variables"]):::queued --> xdc94d22b863438a5(["nasa_weather_variables"]):::queued
end
linkStyle 0 stroke-width:0px;
Many of the computational steps can be time consuming and either
diff --git a/README.md b/README.md
index 37cf92e..fae51eb 100644
--- a/README.md
+++ b/README.md
@@ -51,242 +51,230 @@ across the continent.
syntax and should display as a graph on GitHub. It can also be viewed
by pasting the code into .)
-Warning messages: 1: package ‘rmarkdown’ was built under R version 4.3.3
-2: package ‘paws’ was built under R version 4.3.3 3: package ‘terra’ was
-built under R version 4.3.3
+Warning messages: 1: package ‘targets’ was built under R version 4.3.3
+2: package ‘rmarkdown’ was built under R version 4.3.3 3: package ‘paws’
+was built under R version 4.3.3 4: package ‘terra’ was built under R
+version 4.3.3
``` mermaid
graph LR
subgraph Project Workflow
subgraph Graph
direction LR
- x5130788afbe32544["modis_ndvi_transformed"]:::queued --> xddb5620937cdbc01(["nasa_weather_transformed_AWS_upload"]):::queued
- xdc843e2504e22144(["modis_ndvi_transformed_directory"]):::skipped --> xddb5620937cdbc01(["nasa_weather_transformed_AWS_upload"]):::queued
+ x97fc33c6215703a3(["rsa_polygon"]):::completed --> x8367f94bdb991b08(["rsa_polygon_spatial_weights"]):::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x71c93c84792ad529(["glw_AWS"]):::queued
+ x5448b80c3909d641(["glw_directory"]):::completed --> x71c93c84792ad529(["glw_AWS"]):::queued
+ x27dbf0f2484063f3["wahis_outbreak_history"]:::queued --> x2b50e7687b4412ab(["wahis_outbreak_history_animations_AWS"]):::queued
+ x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::completed --> x2b50e7687b4412ab(["wahis_outbreak_history_animations_AWS"]):::queued
+ x5130788afbe32544["modis_ndvi_transformed"]:::queued --> x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued
+ x7fef416d6ce259f3(["ndvi_historical_means_directory"]):::completed --> x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued
+ xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued --> x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x4110b36142c7dd5b(["soil_AWS"]):::queued
+ x9c14f0532ee1f83c(["soil_directory"]):::completed --> x4110b36142c7dd5b(["soil_AWS"]):::queued
+ x680f7450837c9229["forecasts_anomalies"]:::queued --> x72d065c3b2ed1267(["forecasts_anomalies_AWS_upload"]):::queued
+ x8ff15aa322c64802(["forecasts_anomalies_directory"]):::completed --> x72d065c3b2ed1267(["forecasts_anomalies_AWS_upload"]):::queued
+ xb06c08f4a8f21445(["lag_intervals"]):::completed --> xc61c34839fb8c873(["model_dates_selected"]):::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x680370f9b58b9f6d(["slope_preprocessed"]):::queued
+ x890a8fc59a28f6b2(["slope_AWS"]):::queued --> x680370f9b58b9f6d(["slope_preprocessed"]):::queued
+ x165085d61327782d(["slope_directory"]):::completed --> x680370f9b58b9f6d(["slope_preprocessed"]):::queued
+ x1ef0d1881ff89dbd(["slope_urls"]):::completed --> x680370f9b58b9f6d(["slope_preprocessed"]):::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x82990a83bfa4db45(["glw_preprocessed"]):::queued
+ x71c93c84792ad529(["glw_AWS"]):::queued --> x82990a83bfa4db45(["glw_preprocessed"]):::queued
+ x5448b80c3909d641(["glw_directory"]):::completed --> x82990a83bfa4db45(["glw_preprocessed"]):::queued
+ x4d4a15b2f0f1851f(["glw_urls"]):::completed --> x82990a83bfa4db45(["glw_preprocessed"]):::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x32725338020380f8(["get_ecmwf_forecasts_AWS"]):::queued
+ x73599238bfebd1c5(["ecmwf_forecasts_api_parameters"]):::queued --> x32725338020380f8(["get_ecmwf_forecasts_AWS"]):::queued
+ x16ce463b7b647c1e(["ecmwf_forecasts_transformed_directory"]):::completed --> x32725338020380f8(["get_ecmwf_forecasts_AWS"]):::queued
+ x42a5375a64b48216(["aspect_directory"]):::completed --> x049b29595ee19108(["aspect_AWS"]):::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x049b29595ee19108(["aspect_AWS"]):::queued
+ x165085d61327782d(["slope_directory"]):::completed --> x5aa9efa15ecd03d0(["slope_preprocessed_AWS_upload"]):::queued
+ x680370f9b58b9f6d(["slope_preprocessed"]):::queued --> x5aa9efa15ecd03d0(["slope_preprocessed_AWS_upload"]):::queued
+ x6bae1f342f811d0b(["wahis_rvf_controls_raw"]):::completed --> x2668bdb7843be979(["wahis_rvf_controls_preprocessed"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued
x73599238bfebd1c5(["ecmwf_forecasts_api_parameters"]):::queued --> x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued
- x16ce463b7b647c1e(["ecmwf_forecasts_transformed_directory"]):::skipped --> x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued
+ x16ce463b7b647c1e(["ecmwf_forecasts_transformed_directory"]):::completed --> x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued
x32725338020380f8(["get_ecmwf_forecasts_AWS"]):::queued --> x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued
- x0381132b9136146c(["elevation_directory"]):::skipped --> xd9f5e6274aef515b(["elevation_preprocessed_AWS_upload"]):::queued
- x0dffb1605751d1b1(["elevation_preprocessed"]):::queued --> xd9f5e6274aef515b(["elevation_preprocessed_AWS_upload"]):::queued
- x24983cd244fff5db(["modis_ndvi_bundle_request_file"]):::queued --> xcfc776190ac6b73c(["modis_ndvi_bundle_request"]):::queued
- xa5bc51cd67d5e6c0(["modis_ndvi_task_id_continent"]):::queued --> xcfc776190ac6b73c(["modis_ndvi_bundle_request"]):::queued
- x3f3ba2f9e89a9591(["modis_ndvi_token"]):::completed --> xcfc776190ac6b73c(["modis_ndvi_bundle_request"]):::queued
- xe3c4533ec81ef618(["continent_polygon"]):::skipped --> x39ef63e4c3553f78(["wahis_raster_template"]):::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued
- xe2329877730e44b5(["ndvi_anomalies_directory"]):::skipped --> x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued
- x92b237aaa434cba4(["ndvi_date_lookup"]):::queued --> x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued
- x44345ceb9b3d4a81["ndvi_historical_means"]:::queued --> x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x4110b36142c7dd5b(["soil_AWS"]):::queued
- x9c14f0532ee1f83c(["soil_directory"]):::skipped --> x4110b36142c7dd5b(["soil_AWS"]):::queued
- x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued --> x680f7450837c9229["forecasts_anomalies"]:::queued
- x16ce463b7b647c1e(["ecmwf_forecasts_transformed_directory"]):::skipped --> x680f7450837c9229["forecasts_anomalies"]:::queued
- x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued --> x680f7450837c9229["forecasts_anomalies"]:::queued
- x8ff15aa322c64802(["forecasts_anomalies_directory"]):::skipped --> x680f7450837c9229["forecasts_anomalies"]:::queued
- x021b0407fd88c849(["lead_intervals"]):::skipped --> x680f7450837c9229["forecasts_anomalies"]:::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> x680f7450837c9229["forecasts_anomalies"]:::queued
- xbd6b5d8fe3154d5a["weather_historical_means"]:::queued --> x680f7450837c9229["forecasts_anomalies"]:::queued
- x1f222a4448edddc4(["days_of_year"]):::skipped --> xbd6b5d8fe3154d5a["weather_historical_means"]:::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> xbd6b5d8fe3154d5a["weather_historical_means"]:::queued
- x021b0407fd88c849(["lead_intervals"]):::skipped --> xbd6b5d8fe3154d5a["weather_historical_means"]:::queued
- x0548e231345702f7["nasa_weather_transformed"]:::queued --> xbd6b5d8fe3154d5a["weather_historical_means"]:::queued
- x711dc87df29f0a9c(["nasa_weather_transformed_directory"]):::skipped --> xbd6b5d8fe3154d5a["weather_historical_means"]:::queued
- xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued --> xbd6b5d8fe3154d5a["weather_historical_means"]:::queued
- x4407a62768444c3e(["weather_historical_means_directory"]):::skipped --> xbd6b5d8fe3154d5a["weather_historical_means"]:::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
+ x0548e231345702f7["nasa_weather_transformed"]:::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
+ x0df1395319c2f010(["weather_anomalies_AWS"]):::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
+ xf94f7486eed9869c(["weather_anomalies_directory"]):::completed --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
+ xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
+ xb06c08f4a8f21445(["lag_intervals"]):::completed --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
+ x0548e231345702f7["nasa_weather_transformed"]:::queued --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
+ xf94f7486eed9869c(["weather_anomalies_directory"]):::completed --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
+ xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
x049b29595ee19108(["aspect_AWS"]):::queued --> x155e2f0b29a20e05(["aspect_preprocessed"]):::queued
- x42a5375a64b48216(["aspect_directory"]):::skipped --> x155e2f0b29a20e05(["aspect_preprocessed"]):::queued
- x213d1d2657d00cd0(["aspect_urls"]):::skipped --> x155e2f0b29a20e05(["aspect_preprocessed"]):::queued
+ x42a5375a64b48216(["aspect_directory"]):::completed --> x155e2f0b29a20e05(["aspect_preprocessed"]):::queued
+ x213d1d2657d00cd0(["aspect_urls"]):::completed --> x155e2f0b29a20e05(["aspect_preprocessed"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> x155e2f0b29a20e05(["aspect_preprocessed"]):::queued
- x1f222a4448edddc4(["days_of_year"]):::skipped --> x44345ceb9b3d4a81["ndvi_historical_means"]:::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> x44345ceb9b3d4a81["ndvi_historical_means"]:::queued
- x92b237aaa434cba4(["ndvi_date_lookup"]):::queued --> x44345ceb9b3d4a81["ndvi_historical_means"]:::queued
- x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued --> x44345ceb9b3d4a81["ndvi_historical_means"]:::queued
- x7fef416d6ce259f3(["ndvi_historical_means_directory"]):::skipped --> x44345ceb9b3d4a81["ndvi_historical_means"]:::queued
- xe8b8ca5535fe5f2a(["bioclim_directory"]):::skipped --> xe2930fde1049416f(["bioclim_AWS"]):::queued
+ x27dbf0f2484063f3["wahis_outbreak_history"]:::queued --> x53890e32519c2cdc(["wahis_outbreak_history_AWS_upload"]):::queued
+ x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::completed --> x53890e32519c2cdc(["wahis_outbreak_history_AWS_upload"]):::queued
+ x659aa62eded9787b(["wahis_outbreaks"]):::queued --> xa33032ce29b67c7f(["wahis_distance_matrix"]):::queued
+ x39ef63e4c3553f78(["wahis_raster_template"]):::queued --> xa33032ce29b67c7f(["wahis_distance_matrix"]):::queued
+ x2b83f10567783884(["wahis_rvf_outbreaks_preprocessed"]):::queued --> x50043477563454fd(["wahis_outbreak_dates"]):::queued
+ xe8b8ca5535fe5f2a(["bioclim_directory"]):::completed --> xe2930fde1049416f(["bioclim_AWS"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> xe2930fde1049416f(["bioclim_AWS"]):::queued
- xa33032ce29b67c7f(["wahis_distance_matrix"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
- x50043477563454fd(["wahis_outbreak_dates"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
- xcc02e30ec90a7edd(["wahis_outbreak_history_directory"]):::skipped --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
- x659aa62eded9787b(["wahis_outbreaks"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
- x39ef63e4c3553f78(["wahis_raster_template"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x955e49f3e0c22510(["landcover_AWS"]):::queued
- x8894af119fe2eaa1(["landcover_directory"]):::skipped --> x955e49f3e0c22510(["landcover_AWS"]):::queued
- x42a5375a64b48216(["aspect_directory"]):::skipped --> x7039ba6fde7353f3(["soil_preprocessed_AWS_upload"]):::queued
- xd70b16641fa1b4ef(["soil_preprocessed"]):::queued --> x7039ba6fde7353f3(["soil_preprocessed_AWS_upload"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
- xa9eddcdb0d1f1d02(["get_sentinel_ndvi_AWS"]):::queued --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
- x6e1924e349d8e6e8(["sentinel_ndvi_api_parameters"]):::skipped --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
- x3ea733d22e9c32e7(["sentinel_ndvi_transformed_directory"]):::skipped --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
- xe3c4533ec81ef618(["continent_polygon"]):::skipped --> xba6244832b5285ba(["continent_raster_template"]):::queued
- x97fc33c6215703a3(["rsa_polygon"]):::skipped --> x8367f94bdb991b08(["rsa_polygon_spatial_weights"]):::queued
- x4847fdb918188b25(["country_polygons"]):::skipped --> x53c4b2fb80542353(["country_bounding_boxes"]):::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> xf9b79e824823a870["ndvi_anomalies"]:::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
- x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
- xe2329877730e44b5(["ndvi_anomalies_directory"]):::skipped --> xf9b79e824823a870["ndvi_anomalies"]:::queued
- x92b237aaa434cba4(["ndvi_date_lookup"]):::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
- x44345ceb9b3d4a81["ndvi_historical_means"]:::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
- x3ea733d22e9c32e7(["sentinel_ndvi_transformed_directory"]):::skipped --> xa9eddcdb0d1f1d02(["get_sentinel_ndvi_AWS"]):::queued
- x53c4b2fb80542353(["country_bounding_boxes"]):::queued --> xc54ffbea58c4afd9(["nasa_weather_coordinates"]):::queued
- xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued --> x705cc9e765652376(["forecasts_anomalies_validate_AWS_upload"]):::queued
- x309ea01959a83a5a(["forecasts_validate_directory"]):::skipped --> x705cc9e765652376(["forecasts_anomalies_validate_AWS_upload"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> x5130788afbe32544["modis_ndvi_transformed"]:::queued
- xcfc776190ac6b73c(["modis_ndvi_bundle_request"]):::queued --> x5130788afbe32544["modis_ndvi_transformed"]:::queued
+ xb64343d9bc0ef12e(["modis_ndvi_requests"]):::queued --> x5130788afbe32544["modis_ndvi_transformed"]:::queued
x3f3ba2f9e89a9591(["modis_ndvi_token"]):::completed --> x5130788afbe32544["modis_ndvi_transformed"]:::queued
xf36f13d6d1345340(["modis_ndvi_transformed_AWS"]):::queued --> x5130788afbe32544["modis_ndvi_transformed"]:::queued
xdc843e2504e22144(["modis_ndvi_transformed_directory"]):::skipped --> x5130788afbe32544["modis_ndvi_transformed"]:::queued
- x44345ceb9b3d4a81["ndvi_historical_means"]:::queued --> x1be60916d37ebe0f(["ndvi_historical_means_AWS_upload"]):::queued
- x7fef416d6ce259f3(["ndvi_historical_means_directory"]):::skipped --> x1be60916d37ebe0f(["ndvi_historical_means_AWS_upload"]):::queued
+ x9c9060069417a49a(["wahis_rvf_outbreaks_raw"]):::completed --> x2b83f10567783884(["wahis_rvf_outbreaks_preprocessed"]):::queued
+ x2e80ddc3dafd7312(["augmented_data_directory"]):::completed --> x67bf5d7b4af55c88(["augmented_data_AWS"]):::queued
+ x482d364fd551ff53(["augmented_data_sources"]):::queued --> x67bf5d7b4af55c88(["augmented_data_AWS"]):::queued
+ x27dbf0f2484063f3["wahis_outbreak_history"]:::queued --> x16e1cc582647deec["wahis_outbreak_history_animations"]:::queued
+ x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::completed --> x16e1cc582647deec["wahis_outbreak_history_animations"]:::queued
+ xa33032ce29b67c7f(["wahis_distance_matrix"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
+ x50043477563454fd(["wahis_outbreak_dates"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
+ xcc02e30ec90a7edd(["wahis_outbreak_history_directory"]):::completed --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
+ x659aa62eded9787b(["wahis_outbreaks"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
+ x39ef63e4c3553f78(["wahis_raster_template"]):::queued --> x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued
+ x16e1cc582647deec["wahis_outbreak_history_animations"]:::queued --> x3a8830b5def8250b(["wahis_outbreak_history_animations_AWS_upload"]):::queued
+ x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::completed --> x3a8830b5def8250b(["wahis_outbreak_history_animations_AWS_upload"]):::queued
+ x01b9e03cb52b7b05["weather_anomalies"]:::queued --> xc567f473073bf453(["weather_anomalies_AWS_upload"]):::queued
+ xf94f7486eed9869c(["weather_anomalies_directory"]):::completed --> xc567f473073bf453(["weather_anomalies_AWS_upload"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> xdecc37cc7e708cec(["landcover_preprocessed"]):::queued
x955e49f3e0c22510(["landcover_AWS"]):::queued --> xdecc37cc7e708cec(["landcover_preprocessed"]):::queued
- x8894af119fe2eaa1(["landcover_directory"]):::skipped --> xdecc37cc7e708cec(["landcover_preprocessed"]):::queued
- x684d7fe78b0e841d(["landcover_types"]):::skipped --> xdecc37cc7e708cec(["landcover_preprocessed"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x32725338020380f8(["get_ecmwf_forecasts_AWS"]):::queued
- x73599238bfebd1c5(["ecmwf_forecasts_api_parameters"]):::queued --> x32725338020380f8(["get_ecmwf_forecasts_AWS"]):::queued
- x16ce463b7b647c1e(["ecmwf_forecasts_transformed_directory"]):::skipped --> x32725338020380f8(["get_ecmwf_forecasts_AWS"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x0dffb1605751d1b1(["elevation_preprocessed"]):::queued
- x98b1351d966647f6(["elevation_AWS"]):::queued --> x0dffb1605751d1b1(["elevation_preprocessed"]):::queued
- x0381132b9136146c(["elevation_directory"]):::skipped --> x0dffb1605751d1b1(["elevation_preprocessed"]):::queued
- x5130788afbe32544["modis_ndvi_transformed"]:::queued --> xe90a7836ba709288(["modis_ndvi_transformed_AWS_upload"]):::queued
- xdc843e2504e22144(["modis_ndvi_transformed_directory"]):::skipped --> xe90a7836ba709288(["modis_ndvi_transformed_AWS_upload"]):::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
- x0548e231345702f7["nasa_weather_transformed"]:::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
- x711dc87df29f0a9c(["nasa_weather_transformed_directory"]):::skipped --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
- x0df1395319c2f010(["weather_anomalies_AWS"]):::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
- xf94f7486eed9869c(["weather_anomalies_directory"]):::skipped --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
- xbd6b5d8fe3154d5a["weather_historical_means"]:::queued --> x01b9e03cb52b7b05["weather_anomalies"]:::queued
- xe8b8ca5535fe5f2a(["bioclim_directory"]):::skipped --> xe4be5b46895c0f8c(["bioclim_preprocessed_AWS_upload"]):::queued
- x1c7b6e6a1c101e59(["bioclim_preprocessed"]):::queued --> xe4be5b46895c0f8c(["bioclim_preprocessed_AWS_upload"]):::queued
- x680f7450837c9229["forecasts_anomalies"]:::queued --> xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued
- xcc18535b953bde28(["forecasts_anomalies_validate_AWS"]):::queued --> xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued
- x309ea01959a83a5a(["forecasts_validate_directory"]):::skipped --> xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued
- x021b0407fd88c849(["lead_intervals"]):::skipped --> xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued
- x0548e231345702f7["nasa_weather_transformed"]:::queued --> xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued
- xbd6b5d8fe3154d5a["weather_historical_means"]:::queued --> xa72a356ab8b0f2e4["forecasts_anomalies_validate"]:::queued
- x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
- x8ff15aa322c64802(["forecasts_anomalies_directory"]):::skipped --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
- x021b0407fd88c849(["lead_intervals"]):::skipped --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
- xbd6b5d8fe3154d5a["weather_historical_means"]:::queued --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
- x1f222a4448edddc4(["days_of_year"]):::skipped --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
- x021b0407fd88c849(["lead_intervals"]):::skipped --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
- x0548e231345702f7["nasa_weather_transformed"]:::queued --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
- x4407a62768444c3e(["weather_historical_means_directory"]):::skipped --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
- x6bae1f342f811d0b(["wahis_rvf_controls_raw"]):::skipped --> x2668bdb7843be979(["wahis_rvf_controls_preprocessed"]):::queued
- x165085d61327782d(["slope_directory"]):::skipped --> x5aa9efa15ecd03d0(["slope_preprocessed_AWS_upload"]):::queued
- x680370f9b58b9f6d(["slope_preprocessed"]):::queued --> x5aa9efa15ecd03d0(["slope_preprocessed_AWS_upload"]):::queued
- xdc843e2504e22144(["modis_ndvi_transformed_directory"]):::skipped --> x24983cd244fff5db(["modis_ndvi_bundle_request_file"]):::queued
- xb49d77ffc5b097ae(["continent_bounding_box"]):::queued --> x73599238bfebd1c5(["ecmwf_forecasts_api_parameters"]):::queued
- x680f7450837c9229["forecasts_anomalies"]:::queued --> x72d065c3b2ed1267(["forecasts_anomalies_AWS_upload"]):::queued
- x8ff15aa322c64802(["forecasts_anomalies_directory"]):::skipped --> x72d065c3b2ed1267(["forecasts_anomalies_AWS_upload"]):::queued
- xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued --> x6db823df8cb78984(["sentinel_ndvi_transformed_AWS_upload"]):::queued
- x3ea733d22e9c32e7(["sentinel_ndvi_transformed_directory"]):::skipped --> x6db823df8cb78984(["sentinel_ndvi_transformed_AWS_upload"]):::queued
+ x8894af119fe2eaa1(["landcover_directory"]):::completed --> xdecc37cc7e708cec(["landcover_preprocessed"]):::queued
+ x684d7fe78b0e841d(["landcover_types"]):::completed --> xdecc37cc7e708cec(["landcover_preprocessed"]):::queued
+ xe8b8ca5535fe5f2a(["bioclim_directory"]):::completed --> xb22e604d282eb0d4(["ta"]):::queued
+ x1c7b6e6a1c101e59(["bioclim_preprocessed"]):::queued --> xb22e604d282eb0d4(["ta"]):::queued
+ x4847fdb918188b25(["country_polygons"]):::completed --> x53c4b2fb80542353(["country_bounding_boxes"]):::queued
+ x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued --> xe017ffc3bafa162a(["ecmwf_forecasts_transformed_AWS_upload"]):::queued
+ x16ce463b7b647c1e(["ecmwf_forecasts_transformed_directory"]):::completed --> xe017ffc3bafa162a(["ecmwf_forecasts_transformed_AWS_upload"]):::queued
+ x53c4b2fb80542353(["country_bounding_boxes"]):::queued --> xc54ffbea58c4afd9(["nasa_weather_coordinates"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> xd70b16641fa1b4ef(["soil_preprocessed"]):::queued
x4110b36142c7dd5b(["soil_AWS"]):::queued --> xd70b16641fa1b4ef(["soil_preprocessed"]):::queued
- x9c14f0532ee1f83c(["soil_directory"]):::skipped --> xd70b16641fa1b4ef(["soil_preprocessed"]):::queued
- xe8b8ca5535fe5f2a(["bioclim_directory"]):::skipped --> x1c7b6e6a1c101e59(["bioclim_preprocessed"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x1c7b6e6a1c101e59(["bioclim_preprocessed"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x71c93c84792ad529(["glw_AWS"]):::queued
- x5448b80c3909d641(["glw_directory"]):::skipped --> x71c93c84792ad529(["glw_AWS"]):::queued
- x42a5375a64b48216(["aspect_directory"]):::skipped --> x890a8fc59a28f6b2(["slope_AWS"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x890a8fc59a28f6b2(["slope_AWS"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x680370f9b58b9f6d(["slope_preprocessed"]):::queued
- x890a8fc59a28f6b2(["slope_AWS"]):::queued --> x680370f9b58b9f6d(["slope_preprocessed"]):::queued
- x165085d61327782d(["slope_directory"]):::skipped --> x680370f9b58b9f6d(["slope_preprocessed"]):::queued
- x1ef0d1881ff89dbd(["slope_urls"]):::skipped --> x680370f9b58b9f6d(["slope_preprocessed"]):::queued
+ x9c14f0532ee1f83c(["soil_directory"]):::completed --> xd70b16641fa1b4ef(["soil_preprocessed"]):::queued
+ xe3c4533ec81ef618(["continent_polygon"]):::skipped --> x73599238bfebd1c5(["ecmwf_forecasts_api_parameters"]):::queued
+ x42a5375a64b48216(["aspect_directory"]):::completed --> xfe5a910dc093a019(["aspect_preprocessed_AWS_upload"]):::queued
+ x155e2f0b29a20e05(["aspect_preprocessed"]):::queued --> xfe5a910dc093a019(["aspect_preprocessed_AWS_upload"]):::queued
+ xe3c4533ec81ef618(["continent_polygon"]):::skipped --> x39ef63e4c3553f78(["wahis_raster_template"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> xf36f13d6d1345340(["modis_ndvi_transformed_AWS"]):::queued
- xcfc776190ac6b73c(["modis_ndvi_bundle_request"]):::queued --> xf36f13d6d1345340(["modis_ndvi_transformed_AWS"]):::queued
+ xcfc776190ac6b73c["modis_ndvi_bundle_request"]:::queued --> xf36f13d6d1345340(["modis_ndvi_transformed_AWS"]):::queued
x3f3ba2f9e89a9591(["modis_ndvi_token"]):::completed --> xf36f13d6d1345340(["modis_ndvi_transformed_AWS"]):::queued
xdc843e2504e22144(["modis_ndvi_transformed_directory"]):::skipped --> xf36f13d6d1345340(["modis_ndvi_transformed_AWS"]):::queued
- x2b83f10567783884(["wahis_rvf_outbreaks_preprocessed"]):::queued --> x50043477563454fd(["wahis_outbreak_dates"]):::queued
+ x42a5375a64b48216(["aspect_directory"]):::completed --> x890a8fc59a28f6b2(["slope_AWS"]):::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x890a8fc59a28f6b2(["slope_AWS"]):::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x955e49f3e0c22510(["landcover_AWS"]):::queued
+ x8894af119fe2eaa1(["landcover_directory"]):::completed --> x955e49f3e0c22510(["landcover_AWS"]):::queued
+ xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued --> x6db823df8cb78984(["sentinel_ndvi_transformed_AWS_upload"]):::queued
+ x3ea733d22e9c32e7(["sentinel_ndvi_transformed_directory"]):::completed --> x6db823df8cb78984(["sentinel_ndvi_transformed_AWS_upload"]):::queued
+ x0381132b9136146c(["elevation_directory"]):::completed --> xd9f5e6274aef515b(["elevation_preprocessed_AWS_upload"]):::queued
+ x0dffb1605751d1b1(["elevation_preprocessed"]):::queued --> xd9f5e6274aef515b(["elevation_preprocessed_AWS_upload"]):::queued
+ x0548e231345702f7["nasa_weather_transformed"]:::queued --> xddb5620937cdbc01(["nasa_weather_transformed_AWS_upload"]):::queued
+ x711dc87df29f0a9c(["nasa_weather_transformed_directory"]):::completed --> xddb5620937cdbc01(["nasa_weather_transformed_AWS_upload"]):::queued
+ x67bf5d7b4af55c88(["augmented_data_AWS"]):::queued --> xcc8316047ac6de28(["augmented_data"]):::queued
+ x2e80ddc3dafd7312(["augmented_data_directory"]):::completed --> xcc8316047ac6de28(["augmented_data"]):::queued
+ x482d364fd551ff53(["augmented_data_sources"]):::queued --> xcc8316047ac6de28(["augmented_data"]):::queued
+ x1f222a4448edddc4(["days_of_year"]):::completed --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
+ xb06c08f4a8f21445(["lag_intervals"]):::completed --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
+ x021b0407fd88c849(["lead_intervals"]):::completed --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
+ x0548e231345702f7["nasa_weather_transformed"]:::queued --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
+ x4407a62768444c3e(["weather_historical_means_directory"]):::completed --> xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued
+ x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued --> x1be60916d37ebe0f(["ndvi_historical_means_AWS_upload"]):::queued
+ x7fef416d6ce259f3(["ndvi_historical_means_directory"]):::completed --> x1be60916d37ebe0f(["ndvi_historical_means_AWS_upload"]):::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
+ x5130788afbe32544["modis_ndvi_transformed"]:::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
+ x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
+ xe2329877730e44b5(["ndvi_anomalies_directory"]):::completed --> xf9b79e824823a870["ndvi_anomalies"]:::queued
+ x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
+ xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued --> xf9b79e824823a870["ndvi_anomalies"]:::queued
+ x5130788afbe32544["modis_ndvi_transformed"]:::queued --> x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued
+ x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued --> x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued
+ x7fef416d6ce259f3(["ndvi_historical_means_directory"]):::completed --> x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued
+ xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued --> x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued
+ xcfc776190ac6b73c["modis_ndvi_bundle_request"]:::queued --> xb64343d9bc0ef12e(["modis_ndvi_requests"]):::queued
+ xa5bc51cd67d5e6c0["modis_ndvi_task_id_continent"]:::queued --> xcfc776190ac6b73c["modis_ndvi_bundle_request"]:::queued
+ x3f3ba2f9e89a9591(["modis_ndvi_token"]):::completed --> xcfc776190ac6b73c["modis_ndvi_bundle_request"]:::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x0dffb1605751d1b1(["elevation_preprocessed"]):::queued
+ x98b1351d966647f6(["elevation_AWS"]):::queued --> x0dffb1605751d1b1(["elevation_preprocessed"]):::queued
+ x0381132b9136146c(["elevation_directory"]):::completed --> x0dffb1605751d1b1(["elevation_preprocessed"]):::queued
+ xe3c4533ec81ef618(["continent_polygon"]):::skipped --> xba6244832b5285ba(["continent_raster_template"]):::queued
+ x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued --> x680f7450837c9229["forecasts_anomalies"]:::queued
+ x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued --> x680f7450837c9229["forecasts_anomalies"]:::queued
+ x8ff15aa322c64802(["forecasts_anomalies_directory"]):::completed --> x680f7450837c9229["forecasts_anomalies"]:::queued
+ x021b0407fd88c849(["lead_intervals"]):::completed --> x680f7450837c9229["forecasts_anomalies"]:::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> x680f7450837c9229["forecasts_anomalies"]:::queued
+ xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued --> x680f7450837c9229["forecasts_anomalies"]:::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x98b1351d966647f6(["elevation_AWS"]):::queued
+ x0381132b9136146c(["elevation_directory"]):::completed --> x98b1351d966647f6(["elevation_AWS"]):::queued
+ x5130788afbe32544["modis_ndvi_transformed"]:::queued --> xe90a7836ba709288(["modis_ndvi_transformed_AWS_upload"]):::queued
+ xdc843e2504e22144(["modis_ndvi_transformed_directory"]):::skipped --> xe90a7836ba709288(["modis_ndvi_transformed_AWS_upload"]):::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
+ xa9eddcdb0d1f1d02(["get_sentinel_ndvi_AWS"]):::queued --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
+ x6e1924e349d8e6e8(["sentinel_ndvi_api_parameters"]):::completed --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
+ x3ea733d22e9c32e7(["sentinel_ndvi_transformed_directory"]):::completed --> xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued
+ x30a742f54b518a5f(["augmented_data_rsa_directory"]):::completed --> x62efb3d9001cb58b(["augmented_data_rsa_AWS"]):::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> x62efb3d9001cb58b(["augmented_data_rsa_AWS"]):::queued
+ xf9b79e824823a870["ndvi_anomalies"]:::queued --> x62efb3d9001cb58b(["augmented_data_rsa_AWS"]):::queued
+ x01b9e03cb52b7b05["weather_anomalies"]:::queued --> x62efb3d9001cb58b(["augmented_data_rsa_AWS"]):::queued
+ xcc8316047ac6de28(["augmented_data"]):::queued --> xcfd8f1e8f3ea9117["aggregated_data_rsa"]:::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> xcfd8f1e8f3ea9117["aggregated_data_rsa"]:::queued
+ x97fc33c6215703a3(["rsa_polygon"]):::completed --> xcfd8f1e8f3ea9117["aggregated_data_rsa"]:::queued
xa33032ce29b67c7f(["wahis_distance_matrix"]):::queued --> x27dbf0f2484063f3["wahis_outbreak_history"]:::queued
x50043477563454fd(["wahis_outbreak_dates"]):::queued --> x27dbf0f2484063f3["wahis_outbreak_history"]:::queued
x200daf9f58e96ac5(["wahis_outbreak_history_AWS"]):::queued --> x27dbf0f2484063f3["wahis_outbreak_history"]:::queued
- xcc02e30ec90a7edd(["wahis_outbreak_history_directory"]):::skipped --> x27dbf0f2484063f3["wahis_outbreak_history"]:::queued
+ xcc02e30ec90a7edd(["wahis_outbreak_history_directory"]):::completed --> x27dbf0f2484063f3["wahis_outbreak_history"]:::queued
x659aa62eded9787b(["wahis_outbreaks"]):::queued --> x27dbf0f2484063f3["wahis_outbreak_history"]:::queued
x39ef63e4c3553f78(["wahis_raster_template"]):::queued --> x27dbf0f2484063f3["wahis_outbreak_history"]:::queued
- xe3c4533ec81ef618(["continent_polygon"]):::skipped --> xb49d77ffc5b097ae(["continent_bounding_box"]):::queued
- x50d291d42ebde68c(["combined_anomalies_directory"]):::skipped --> x439c9f5bc1e96cd5(["combined_anomalies_AWS"]):::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> x439c9f5bc1e96cd5(["combined_anomalies_AWS"]):::queued
- xf9b79e824823a870["ndvi_anomalies"]:::queued --> x439c9f5bc1e96cd5(["combined_anomalies_AWS"]):::queued
- x01b9e03cb52b7b05["weather_anomalies"]:::queued --> x439c9f5bc1e96cd5(["combined_anomalies_AWS"]):::queued
+ x2b83f10567783884(["wahis_rvf_outbreaks_preprocessed"]):::queued --> x659aa62eded9787b(["wahis_outbreaks"]):::queued
+ x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
+ x8ff15aa322c64802(["forecasts_anomalies_directory"]):::completed --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
+ x021b0407fd88c849(["lead_intervals"]):::completed --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
+ xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued --> x259885b5bdbd7dfc(["forecasts_anomalies_AWS"]):::queued
+ x9c14f0532ee1f83c(["soil_directory"]):::completed --> x7039ba6fde7353f3(["soil_preprocessed_AWS_upload"]):::queued
+ xd70b16641fa1b4ef(["soil_preprocessed"]):::queued --> x7039ba6fde7353f3(["soil_preprocessed_AWS_upload"]):::queued
+ xe3c4533ec81ef618(["continent_polygon"]):::skipped --> xa5bc51cd67d5e6c0["modis_ndvi_task_id_continent"]:::queued
+ x3f3ba2f9e89a9591(["modis_ndvi_token"]):::completed --> xa5bc51cd67d5e6c0["modis_ndvi_task_id_continent"]:::queued
+ xdc843e2504e22144(["modis_ndvi_transformed_directory"]):::skipped --> xa5bc51cd67d5e6c0["modis_ndvi_task_id_continent"]:::queued
+ xb406dc4c2762194f(["modis_task_end_dates"]):::queued --> xa5bc51cd67d5e6c0["modis_ndvi_task_id_continent"]:::queued
+ x155e2f0b29a20e05(["aspect_preprocessed"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x1c7b6e6a1c101e59(["bioclim_preprocessed"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x0dffb1605751d1b1(["elevation_preprocessed"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x680f7450837c9229["forecasts_anomalies"]:::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x82990a83bfa4db45(["glw_preprocessed"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ xdecc37cc7e708cec(["landcover_preprocessed"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ xf9b79e824823a870["ndvi_anomalies"]:::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x680370f9b58b9f6d(["slope_preprocessed"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ xd70b16641fa1b4ef(["soil_preprocessed"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x27dbf0f2484063f3["wahis_outbreak_history"]:::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ x01b9e03cb52b7b05["weather_anomalies"]:::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued --> x482d364fd551ff53(["augmented_data_sources"]):::queued
+ xb06c08f4a8f21445(["lag_intervals"]):::completed --> x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued
+ xc61c34839fb8c873(["model_dates_selected"]):::queued --> x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued
+ xe2329877730e44b5(["ndvi_anomalies_directory"]):::completed --> x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued
+ x44345ceb9b3d4a81(["ndvi_historical_means"]):::queued --> x8d58a79e9d066b5d(["ndvi_anomalies_AWS"]):::queued
+ x3ea733d22e9c32e7(["sentinel_ndvi_transformed_directory"]):::completed --> xa9eddcdb0d1f1d02(["get_sentinel_ndvi_AWS"]):::queued
+ x0548e231345702f7["nasa_weather_transformed"]:::queued --> xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued
+ xce069f3121e32dfb(["weather_historical_means_AWS"]):::queued --> xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued
+ x4407a62768444c3e(["weather_historical_means_directory"]):::completed --> xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued
xf9b79e824823a870["ndvi_anomalies"]:::queued --> x144f59a0db036a4b(["ndvi_anomalies_AWS_upload"]):::queued
- xe2329877730e44b5(["ndvi_anomalies_directory"]):::skipped --> x144f59a0db036a4b(["ndvi_anomalies_AWS_upload"]):::queued
- x680f7450837c9229["forecasts_anomalies"]:::queued --> xcc18535b953bde28(["forecasts_anomalies_validate_AWS"]):::queued
- x309ea01959a83a5a(["forecasts_validate_directory"]):::skipped --> xcc18535b953bde28(["forecasts_anomalies_validate_AWS"]):::queued
- x021b0407fd88c849(["lead_intervals"]):::skipped --> xcc18535b953bde28(["forecasts_anomalies_validate_AWS"]):::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> xcc18535b953bde28(["forecasts_anomalies_validate_AWS"]):::queued
- x0548e231345702f7["nasa_weather_transformed"]:::queued --> xcc18535b953bde28(["forecasts_anomalies_validate_AWS"]):::queued
- xbd6b5d8fe3154d5a["weather_historical_means"]:::queued --> xcc18535b953bde28(["forecasts_anomalies_validate_AWS"]):::queued
- x27dbf0f2484063f3["wahis_outbreak_history"]:::queued --> x53890e32519c2cdc(["wahis_outbreak_history_AWS_upload"]):::queued
- x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::skipped --> x53890e32519c2cdc(["wahis_outbreak_history_AWS_upload"]):::queued
+ xe2329877730e44b5(["ndvi_anomalies_directory"]):::completed --> x144f59a0db036a4b(["ndvi_anomalies_AWS_upload"]):::queued
+ x8894af119fe2eaa1(["landcover_directory"]):::completed --> xbc982b2f29054bd9(["landcover_preprocessed_AWS_upload"]):::queued
+ xdecc37cc7e708cec(["landcover_preprocessed"]):::queued --> xbc982b2f29054bd9(["landcover_preprocessed_AWS_upload"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> x0548e231345702f7["nasa_weather_transformed"]:::queued
x84fbc80b775022e1(["nasa_weather_AWS"]):::queued --> x0548e231345702f7["nasa_weather_transformed"]:::queued
xc54ffbea58c4afd9(["nasa_weather_coordinates"]):::queued --> x0548e231345702f7["nasa_weather_transformed"]:::queued
- x711dc87df29f0a9c(["nasa_weather_transformed_directory"]):::skipped --> x0548e231345702f7["nasa_weather_transformed"]:::queued
- x0c2748f0f39a3907(["nasa_weather_years"]):::skipped --> x0548e231345702f7["nasa_weather_transformed"]:::queued
- x3b5d33025a7856bb["ecmwf_forecasts_transformed"]:::queued --> xe017ffc3bafa162a(["ecmwf_forecasts_transformed_AWS_upload"]):::queued
- x16ce463b7b647c1e(["ecmwf_forecasts_transformed_directory"]):::skipped --> xe017ffc3bafa162a(["ecmwf_forecasts_transformed_AWS_upload"]):::queued
- x2b83f10567783884(["wahis_rvf_outbreaks_preprocessed"]):::queued --> x659aa62eded9787b(["wahis_outbreaks"]):::queued
- xb49d77ffc5b097ae(["continent_bounding_box"]):::queued --> xa5bc51cd67d5e6c0(["modis_ndvi_task_id_continent"]):::queued
- x3f3ba2f9e89a9591(["modis_ndvi_token"]):::completed --> xa5bc51cd67d5e6c0(["modis_ndvi_task_id_continent"]):::queued
- x16e1cc582647deec["wahis_outbreak_history_animations"]:::queued --> x3a8830b5def8250b(["wahis_outbreak_history_animations_AWS_upload"]):::queued
- x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::skipped --> x3a8830b5def8250b(["wahis_outbreak_history_animations_AWS_upload"]):::queued
- x5448b80c3909d641(["glw_directory"]):::skipped --> x01e625a4f1dd2c42(["glw_preprocessed_AWS_upload"]):::queued
- x82990a83bfa4db45(["glw_preprocessed"]):::queued --> x01e625a4f1dd2c42(["glw_preprocessed_AWS_upload"]):::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> xcfd8f1e8f3ea9117["aggregated_data_rsa"]:::queued
- x97fc33c6215703a3(["rsa_polygon"]):::skipped --> xcfd8f1e8f3ea9117["aggregated_data_rsa"]:::queued
- x1f222a4448edddc4(["days_of_year"]):::skipped --> x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued
- x92b237aaa434cba4(["ndvi_date_lookup"]):::queued --> x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued
- x7fef416d6ce259f3(["ndvi_historical_means_directory"]):::skipped --> x42d785b9e0106385(["ndvi_historical_means_AWS"]):::queued
- x5130788afbe32544["modis_ndvi_transformed"]:::queued --> x92b237aaa434cba4(["ndvi_date_lookup"]):::queued
- xa4eb23442420052a["sentinel_ndvi_transformed"]:::queued --> x92b237aaa434cba4(["ndvi_date_lookup"]):::queued
- x659aa62eded9787b(["wahis_outbreaks"]):::queued --> xa33032ce29b67c7f(["wahis_distance_matrix"]):::queued
- x39ef63e4c3553f78(["wahis_raster_template"]):::queued --> xa33032ce29b67c7f(["wahis_distance_matrix"]):::queued
- x27dbf0f2484063f3["wahis_outbreak_history"]:::queued --> x16e1cc582647deec["wahis_outbreak_history_animations"]:::queued
- x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::skipped --> x16e1cc582647deec["wahis_outbreak_history_animations"]:::queued
- x27dbf0f2484063f3["wahis_outbreak_history"]:::queued --> x2b50e7687b4412ab(["wahis_outbreak_history_animations_AWS"]):::queued
- x338ce62055c4090f(["wahis_outbreak_history_animations_directory"]):::skipped --> x2b50e7687b4412ab(["wahis_outbreak_history_animations_AWS"]):::queued
- x8894af119fe2eaa1(["landcover_directory"]):::skipped --> xbc982b2f29054bd9(["landcover_preprocessed_AWS_upload"]):::queued
- xdecc37cc7e708cec(["landcover_preprocessed"]):::queued --> xbc982b2f29054bd9(["landcover_preprocessed_AWS_upload"]):::queued
- x42a5375a64b48216(["aspect_directory"]):::skipped --> xfe5a910dc093a019(["aspect_preprocessed_AWS_upload"]):::queued
- x155e2f0b29a20e05(["aspect_preprocessed"]):::queued --> xfe5a910dc093a019(["aspect_preprocessed_AWS_upload"]):::queued
- x439c9f5bc1e96cd5(["combined_anomalies_AWS"]):::queued --> xfde5ff2681c50d89(["combined_anomalies"]):::queued
- x50d291d42ebde68c(["combined_anomalies_directory"]):::skipped --> xfde5ff2681c50d89(["combined_anomalies"]):::queued
- x680f7450837c9229["forecasts_anomalies"]:::queued --> xfde5ff2681c50d89(["combined_anomalies"]):::queued
- xf9b79e824823a870["ndvi_anomalies"]:::queued --> xfde5ff2681c50d89(["combined_anomalies"]):::queued
- x01b9e03cb52b7b05["weather_anomalies"]:::queued --> xfde5ff2681c50d89(["combined_anomalies"]):::queued
- x42a5375a64b48216(["aspect_directory"]):::skipped --> x049b29595ee19108(["aspect_AWS"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x049b29595ee19108(["aspect_AWS"]):::queued
- x9c9060069417a49a(["wahis_rvf_outbreaks_raw"]):::skipped --> x2b83f10567783884(["wahis_rvf_outbreaks_preprocessed"]):::queued
- xfde5ff2681c50d89(["combined_anomalies"]):::queued --> xba5d6169ff0233fa(["combined_anomalies_AWS_upload"]):::queued
- x50d291d42ebde68c(["combined_anomalies_directory"]):::skipped --> xba5d6169ff0233fa(["combined_anomalies_AWS_upload"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x82990a83bfa4db45(["glw_preprocessed"]):::queued
- x71c93c84792ad529(["glw_AWS"]):::queued --> x82990a83bfa4db45(["glw_preprocessed"]):::queued
- x5448b80c3909d641(["glw_directory"]):::skipped --> x82990a83bfa4db45(["glw_preprocessed"]):::queued
- x4d4a15b2f0f1851f(["glw_urls"]):::skipped --> x82990a83bfa4db45(["glw_preprocessed"]):::queued
- xba6244832b5285ba(["continent_raster_template"]):::queued --> x98b1351d966647f6(["elevation_AWS"]):::queued
- x0381132b9136146c(["elevation_directory"]):::skipped --> x98b1351d966647f6(["elevation_AWS"]):::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> xc61c34839fb8c873(["model_dates_selected"]):::queued
- x01b9e03cb52b7b05["weather_anomalies"]:::queued --> xc567f473073bf453(["weather_anomalies_AWS_upload"]):::queued
- xf94f7486eed9869c(["weather_anomalies_directory"]):::skipped --> xc567f473073bf453(["weather_anomalies_AWS_upload"]):::queued
- xbd6b5d8fe3154d5a["weather_historical_means"]:::queued --> xf8b72b30842f6a3c(["weather_historical_means_AWS_upload"]):::queued
- x4407a62768444c3e(["weather_historical_means_directory"]):::skipped --> xf8b72b30842f6a3c(["weather_historical_means_AWS_upload"]):::queued
+ x711dc87df29f0a9c(["nasa_weather_transformed_directory"]):::completed --> x0548e231345702f7["nasa_weather_transformed"]:::queued
+ x0c2748f0f39a3907(["nasa_weather_years"]):::queued --> x0548e231345702f7["nasa_weather_transformed"]:::queued
+ xbd6b5d8fe3154d5a(["weather_historical_means"]):::queued --> xf8b72b30842f6a3c(["weather_historical_means_AWS_upload"]):::queued
+ x4407a62768444c3e(["weather_historical_means_directory"]):::completed --> xf8b72b30842f6a3c(["weather_historical_means_AWS_upload"]):::queued
xba6244832b5285ba(["continent_raster_template"]):::queued --> x84fbc80b775022e1(["nasa_weather_AWS"]):::queued
xc54ffbea58c4afd9(["nasa_weather_coordinates"]):::queued --> x84fbc80b775022e1(["nasa_weather_AWS"]):::queued
- x711dc87df29f0a9c(["nasa_weather_transformed_directory"]):::skipped --> x84fbc80b775022e1(["nasa_weather_AWS"]):::queued
- x0c2748f0f39a3907(["nasa_weather_years"]):::skipped --> x84fbc80b775022e1(["nasa_weather_AWS"]):::queued
- xb06c08f4a8f21445(["lag_intervals"]):::skipped --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
- xc61c34839fb8c873(["model_dates_selected"]):::queued --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
- x0548e231345702f7["nasa_weather_transformed"]:::queued --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
- xf94f7486eed9869c(["weather_anomalies_directory"]):::skipped --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
- xbd6b5d8fe3154d5a["weather_historical_means"]:::queued --> x0df1395319c2f010(["weather_anomalies_AWS"]):::queued
- x30a742f54b518a5f(["augmented_data_rsa_directory"]):::skipped --> x30a742f54b518a5f(["augmented_data_rsa_directory"]):::skipped
- xdc94d22b863438a5(["nasa_weather_variables"]):::skipped --> xdc94d22b863438a5(["nasa_weather_variables"]):::skipped
+ x711dc87df29f0a9c(["nasa_weather_transformed_directory"]):::completed --> x84fbc80b775022e1(["nasa_weather_AWS"]):::queued
+ x0c2748f0f39a3907(["nasa_weather_years"]):::queued --> x84fbc80b775022e1(["nasa_weather_AWS"]):::queued
+ xcc8316047ac6de28(["augmented_data"]):::queued --> x3130c5a4e0174582(["augmented_data_AWS_upload"]):::queued
+ x2e80ddc3dafd7312(["augmented_data_directory"]):::completed --> x3130c5a4e0174582(["augmented_data_AWS_upload"]):::queued
+ xe8b8ca5535fe5f2a(["bioclim_directory"]):::completed --> x1c7b6e6a1c101e59(["bioclim_preprocessed"]):::queued
+ xba6244832b5285ba(["continent_raster_template"]):::queued --> x1c7b6e6a1c101e59(["bioclim_preprocessed"]):::queued
+ x5448b80c3909d641(["glw_directory"]):::completed --> x01e625a4f1dd2c42(["glw_preprocessed_AWS_upload"]):::queued
+ x82990a83bfa4db45(["glw_preprocessed"]):::queued --> x01e625a4f1dd2c42(["glw_preprocessed_AWS_upload"]):::queued
+ xdc94d22b863438a5(["nasa_weather_variables"]):::queued --> xdc94d22b863438a5(["nasa_weather_variables"]):::queued
end
linkStyle 0 stroke-width:0px;
```
diff --git a/_targets.R b/_targets.R
index 3a2b12c..68d8ff0 100644
--- a/_targets.R
+++ b/_targets.R
@@ -25,7 +25,8 @@ source("_targets_settings.R")
# If the file can be successfully downloaded and opened with arrow it will move
# on to the next task unless the OVERWRITE_X_DATA environment flag is set to TRUE
# in the .env file. In that case, the target will always download and process
-# data directly from the primary source.
+# data directly from the primary source. The pipeline will still run even if
+# the AWS targets fail.
# Static Data Download ----------------------------------------------------
# These data sources don't change with time.
@@ -70,8 +71,7 @@ static_targets <- tar_plan(
tar_target(soil_preprocessed_AWS_upload, AWS_put_files(soil_preprocessed,
soil_directory),
- error = "null",
- cue = tar_cue("always")), # Continue the pipeline even on error
+ error = "null"), # Continue the pipeline even on error
# ASPECT -------------------------------------------------
tar_target(aspect_urls, c("aspect_zero" = "https://www.fao.org/fileadmin/user_upload/soils/HWSD%20Viewer/GloAspectClN_30as.rar",
@@ -86,7 +86,8 @@ static_targets <- tar_plan(
# If so download from AWS instead of primary source
tar_target(aspect_AWS, AWS_get_folder(aspect_directory,
continent_raster_template),
- error = "null"), # Enforce Dependency
+ error = "null",
+ cue = tar_cue("always")), # Enforce Dependency
tar_target(aspect_preprocessed, get_remote_rasters(urls = aspect_urls,
output_dir = aspect_directory,
@@ -120,7 +121,8 @@ static_targets <- tar_plan(
# If so download from AWS instead of primary source
tar_target(slope_AWS, AWS_get_folder(aspect_directory,
continent_raster_template), # Enforce Dependency
- error = "null"), # Continue the pipeline even on error
+ error = "null",
+ cue = tar_cue("always")), # Continue the pipeline even on error
tar_target(slope_preprocessed, get_remote_rasters(urls = slope_urls,
output_dir = slope_directory,
@@ -150,7 +152,8 @@ static_targets <- tar_plan(
# If so download from AWS instead of primary source
tar_target(glw_AWS, AWS_get_folder(glw_directory,
continent_raster_template), # Enforce Dependency
- error = "null"), # Continue the pipeline even on error
+ error = "null",
+ cue = tar_cue("always")), # Continue the pipeline even on error
tar_target(glw_preprocessed,
preprocess_glw_data(glw_directory,
@@ -173,7 +176,8 @@ tar_target(elevation_directory,
# If so download from AWS instead of primary source
tar_target(elevation_AWS, AWS_get_folder(elevation_directory,
continent_raster_template), # Enforce Dependency
- error = "null"), # Continue the pipeline even on error
+ error = "null",
+ cue = tar_cue("always")), # Continue the pipeline even on error
tar_target(elevation_preprocessed,
get_elevation_data(output_dir = elevation_directory,
@@ -196,7 +200,8 @@ tar_target(bioclim_directory,
# If so download from AWS instead of primary source
tar_target(bioclim_AWS, AWS_get_folder(bioclim_directory,
continent_raster_template), # Enforce Dependency
- error = "null"), # Continue the pipeline even on error
+ error = "null",
+ cue = tar_cue("always")), # Continue the pipeline even on error
tar_target(bioclim_preprocessed,
get_bioclim_data(output_dir = bioclim_directory,
@@ -206,7 +211,7 @@ tar_target(bioclim_preprocessed,
format = "file",
repository = "local"),
-tar_target(ta, AWS_put_files(bioclim_preprocessed,
+tar_target(bioclim_preprocessed_AWS_upload, AWS_put_files(bioclim_preprocessed,
bioclim_directory),
error = "null"), # Continue the pipeline even on error
@@ -220,7 +225,8 @@ tar_target(landcover_directory,
# If so download from AWS instead of primary source
tar_target(landcover_AWS, AWS_get_folder(landcover_directory,
continent_raster_template), # Enforce Dependency
- error = "null"), # Continue the pipeline even on error
+ error = "null",
+ cue = tar_cue("always")), # Continue the pipeline even on error
tar_target(landcover_preprocessed,
get_landcover_data(output_dir = landcover_directory,
@@ -255,7 +261,7 @@ dynamic_targets <- tar_plan(
by = "day"),
year = year(date),
month = month(date)) |>
- group_by(year) |>
+ group_by(month, year) |>
tar_group(),
iteration = "group"),
@@ -289,10 +295,11 @@ dynamic_targets <- tar_plan(
wahis_outbreaks, # Enforce Dependency
wahis_distance_matrix, # Enforce Dependency
wahis_raster_template), # Enforce Dependency
- error = "null"), # Continue the pipeline even on error
+ error = "null",
+ cue = tar_cue("always")), # Continue the pipeline even on error
# Dynamic branch over year batch over day otherwise too many branches.
- tar_target(wahis_outbreak_history, get_daily_outbreak_history(dates_df = wahis_outbreak_dates,
+ tar_target(wahis_outbreak_history, get_daily_outbreak_history(wahis_outbreak_dates,
wahis_outbreaks,
wahis_distance_matrix,
wahis_raster_template,
@@ -315,26 +322,29 @@ dynamic_targets <- tar_plan(
wahis_outbreak_history_animations_directory),
error = "null"), # Continue the pipeline even on error
- # Check if preprocessed wahis_outbreak_history data already exists on AWS and can be loaded.
- # If so download from AWS instead of primary source
- tar_target(wahis_outbreak_history_animations_AWS, AWS_get_folder(wahis_outbreak_history_animations_directory,
- wahis_outbreak_history), # Enforce Dependency
- error = "null"), # Continue the pipeline even on error
+ # NCL: Note need to refactor to account for switching to wide format wahis_outbreak_history
- # Animate a SpatRaster stack where each layer is a date.
- # gganimate took 20 minutes per file.
- # just saving all the frames as separate pngs
- # and combining with gifski took 50 minutes for all of them.
- tar_target(wahis_outbreak_history_animations, get_outbreak_history_animation(wahis_outbreak_history,
- wahis_outbreak_history_animations_directory,
- overwrite = as.logical(Sys.getenv("OVERWRITE_OUTBREAK_HISTORY", unset = "FALSE"))), # Just included to enforce dependency with wahis_outbreak_history
- pattern = map(wahis_outbreak_history),
- error = "null",
- repository = "local"),
-
- tar_target(wahis_outbreak_history_animations_AWS_upload, AWS_put_files(wahis_outbreak_history_animations,
- wahis_outbreak_history_animations_directory),
- error = "null"), # Continue the pipeline even on error
+ # # Check if preprocessed wahis_outbreak_history data already exists on AWS and can be loaded.
+ # # If so download from AWS instead of primary source
+ # tar_target(wahis_outbreak_history_animations_AWS, AWS_get_folder(wahis_outbreak_history_animations_directory,
+ # wahis_outbreak_history), # Enforce Dependency
+ # error = "null",
+ # cue = tar_cue("always")), # Continue the pipeline even on error
+ #
+ # # Animate a SpatRaster stack where each layer is a date.
+ # # gganimate took 20 minutes per file.
+ # # just saving all the frames as separate pngs
+ # # and combining with gifski took 50 minutes for all of them.
+ # tar_target(wahis_outbreak_history_animations, get_outbreak_history_animation(wahis_outbreak_history,
+ # wahis_outbreak_history_animations_directory,
+ # overwrite = as.logical(Sys.getenv("OVERWRITE_OUTBREAK_HISTORY", unset = "FALSE"))), # Just included to enforce dependency with wahis_outbreak_history
+ # pattern = map(wahis_outbreak_history),
+ # error = "null",
+ # repository = "local"),
+ #
+ # tar_target(wahis_outbreak_history_animations_AWS_upload, AWS_put_files(wahis_outbreak_history_animations,
+ # wahis_outbreak_history_animations_directory),
+ # error = "null"), # Continue the pipeline even on error
# SENTINEL NDVI -----------------------------------------------------------
# 2018-present
@@ -343,7 +353,11 @@ dynamic_targets <- tar_plan(
create_data_directory(directory_path = "data/sentinel_ndvi_transformed")),
tar_target(get_sentinel_ndvi_AWS, AWS_get_folder(sentinel_ndvi_transformed_directory),
- error = "null"),
+ error = "null",
+ cue = tar_cue("always")),
+
+ # Should last 10 minutes. If it fails renew the token and try again.
+ tar_target(sentinel_ndvi_token_file, get_sentinel_ndvi_token(), cue = tar_cue("always")),
# get API parameters
tar_target(sentinel_ndvi_api_parameters, get_sentinel_ndvi_api_parameters()),
@@ -356,6 +370,7 @@ dynamic_targets <- tar_plan(
transform_sentinel_ndvi(sentinel_ndvi_api_parameters,
continent_raster_template,
sentinel_ndvi_transformed_directory,
+ sentinel_ndvi_token_file,
overwrite = as.logical(Sys.getenv("OVERWRITE_SENTINEL_NDVI", unset = "FALSE")),
get_sentinel_ndvi_AWS),
pattern = map(sentinel_ndvi_api_parameters),
@@ -370,7 +385,8 @@ dynamic_targets <- tar_plan(
# MODIS NDVI -----------------------------------------------------------
# 2005-present
# this satellite will be retired soon, so we should use sentinel for present dates
- # 16 day period
+ # ~10 day period. Note the period of sentinel data does not match modis.
+ # Some interpolation would be useful. Currently using step function.
tar_target(modis_ndvi_transformed_directory,
create_data_directory(directory_path = "data/modis_ndvi_transformed")),
@@ -449,10 +465,9 @@ dynamic_targets <- tar_plan(
error = "null"), # Repository local means it isn't stored on AWS just yet.
# Put modis_ndvi_transformed files on AWS
- tar_target(modis_ndvi_transformed_AWS_upload, AWS_put_files(transformed_file_list = modis_ndvi_transformed,
- local_folder = modis_ndvi_transformed_directory),
- error = "null",
- cue = tar_cue("always")),
+ tar_target(modis_ndvi_transformed_AWS_upload, AWS_put_files(modis_ndvi_transformed,
+ modis_ndvi_transformed_directory),
+ error = "null"),
# NASA POWER recorded weather -----------------------------------------------------------
# RH2M MERRA-2 Relative Humidity at 2 Meters (%) ;
@@ -472,7 +487,8 @@ dynamic_targets <- tar_plan(
nasa_weather_coordinates, # Enforce Dependency
nasa_weather_years, # Enforce Dependency
continent_raster_template),
- error = "null"), # Enforce Dependency
+ error = "null",
+ cue = tar_cue("always")), # Enforce Dependency
# Process the weather data
tar_target(nasa_weather_transformed, transform_nasa_weather(nasa_weather_coordinates,
@@ -498,19 +514,22 @@ dynamic_targets <- tar_plan(
create_data_directory(directory_path = "data/ecmwf_forecasts_transformed")),
# set branching for ecmwf download
- tar_target(ecmwf_forecasts_api_parameters, set_ecmwf_api_parameter(years = 2005:2024,
+ # Note: Neet to auto update years here.
+ tar_target(ecmwf_forecasts_api_parameters, set_ecmwf_api_parameter(start_year = 2005,
bbox_coords = sf::st_bbox(continent_polygon),
variables = c("2m_dewpoint_temperature", "2m_temperature", "total_precipitation"),
# product_types = c("monthly_mean", "monthly_maximum", "monthly_minimum", "monthly_standard_deviation"),
product_types = c("monthly_mean"),
- leadtime_months = c("1", "2", "3", "4", "5", "6"))),
+ leadtime_months = c("1", "2", "3", "4", "5", "6")),
+ cue = tar_cue("always")),
# Check if ecmwf files already exists on AWS and can be loaded
# The only important one is the directory. The others are there to enforce dependencies.
tar_target(get_ecmwf_forecasts_AWS, AWS_get_folder(ecmwf_forecasts_transformed_directory,
ecmwf_forecasts_api_parameters, # Enforce Dependency
continent_raster_template),
- error = "null"), # Enforce Dependency
+ error = "null",
+ cue = tar_cue("never")), # Enforce Dependency
# Download ecmwf forecasts, project to the template and save as arrow dataset
# Note: This target takes a while (mostly because the ECMWF API is slow)
@@ -527,7 +546,8 @@ dynamic_targets <- tar_plan(
pattern = map(ecmwf_forecasts_api_parameters),
error = "null",
format = "file",
- repository = "local"),
+ repository = "local",
+ cue = tar_cue("always")),
# Next step put modis_ndvi_transformed files on AWS.
tar_target(ecmwf_forecasts_transformed_AWS_upload, AWS_put_files(ecmwf_forecasts_transformed,
@@ -564,7 +584,9 @@ data_targets <- tar_plan(
days_of_year, # Enforce dependency
lag_intervals, # Enforce dependency
lead_intervals, # Enforce dependency
- nasa_weather_transformed)), # Enforce dependency
+ nasa_weather_transformed),
+ error = "null",
+ cue = tar_cue("always")), # Enforce dependency
tar_target(weather_historical_means, calculate_weather_historical_means(nasa_weather_transformed,
weather_historical_means_directory,
@@ -574,7 +596,8 @@ data_targets <- tar_plan(
# Next step put weather_historical_means files on AWS.
tar_target(weather_historical_means_AWS_upload, AWS_put_files(weather_historical_means,
- weather_historical_means_directory)),
+ weather_historical_means_directory),
+ error = "null"),
tar_target(weather_anomalies_directory,
create_data_directory(directory_path = "data/weather_anomalies")),
@@ -585,7 +608,9 @@ data_targets <- tar_plan(
weather_historical_means, # Enforce dependency
model_dates_selected, # Enforce dependency
lag_intervals, # Enforce dependency
- nasa_weather_transformed)), # Enforce dependency
+ nasa_weather_transformed),
+ error = "null",
+ cue = tar_cue("always")), # Enforce dependency
# Weather anomalies are deviations from the historical mean
tar_target(weather_anomalies, calculate_weather_anomalies(nasa_weather_transformed,
@@ -601,7 +626,8 @@ data_targets <- tar_plan(
# Next step put weather_historical_means files on AWS.
tar_target(weather_anomalies_AWS_upload, AWS_put_files(weather_anomalies,
- weather_anomalies_directory)),
+ weather_anomalies_directory),
+ error = "null"),
# forecast weather anomalies ----------------------------------------------------------------------
@@ -614,7 +640,9 @@ data_targets <- tar_plan(
weather_historical_means, # Enforce dependency
model_dates_selected, # Enforce dependency
lead_intervals, # Enforce dependency
- ecmwf_forecasts_transformed)), # Enforce dependency
+ ecmwf_forecasts_transformed),
+ error = "null",
+ cue = tar_cue("always")), # Enforce dependency
# Calculate the scaled and unscaled difference between the forecast mean and the
# historical mean across different lead intervals. The lead intervals reflect
@@ -645,7 +673,8 @@ data_targets <- tar_plan(
# Next step put weather_historical_means files on AWS.
tar_target(forecasts_anomalies_AWS_upload, AWS_put_files(forecasts_anomalies,
- forecasts_anomalies_directory)),
+ forecasts_anomalies_directory),
+ error = "null"),
tar_target(ndvi_historical_means_directory,
create_data_directory(directory_path = "data/ndvi_historical_means")),
@@ -654,7 +683,9 @@ data_targets <- tar_plan(
# The only important one is the directory. The others are there to enforce dependencies.
tar_target(ndvi_historical_means_AWS, AWS_get_folder(ndvi_historical_means_directory,
sentinel_ndvi_transformed, # Enforce dependency
- modis_ndvi_transformed)), # Enforce dependency
+ modis_ndvi_transformed),
+ error = "null",
+ cue = tar_cue("always")), # Enforce dependency
tar_target(ndvi_historical_means, calculate_ndvi_historical_means(sentinel_ndvi_transformed,
modis_ndvi_transformed,
@@ -666,7 +697,8 @@ data_targets <- tar_plan(
# Next step put ndvi_historical_means files on AWS.
tar_target(ndvi_historical_means_AWS_upload, AWS_put_files(ndvi_historical_means,
- ndvi_historical_means_directory)),
+ ndvi_historical_means_directory),
+ error = "null"),
tar_target(ndvi_anomalies_directory,
@@ -677,7 +709,9 @@ data_targets <- tar_plan(
tar_target(ndvi_anomalies_AWS, AWS_get_folder(ndvi_anomalies_directory,
ndvi_historical_means, # Enforce dependency
model_dates_selected, # Enforce dependency
- lag_intervals)), # Enforce dependency
+ lag_intervals),
+ error = "null",
+ cue = tar_cue("always")), # Enforce dependency
tar_target(ndvi_anomalies, calculate_ndvi_anomalies(sentinel_ndvi_transformed,
modis_ndvi_transformed,
@@ -693,74 +727,88 @@ data_targets <- tar_plan(
# Next step put ndvi_historical_means files on AWS.
tar_target(ndvi_anomalies_AWS_upload, AWS_put_files(ndvi_anomalies,
- ndvi_anomalies_directory)),
+ ndvi_anomalies_directory),
+ error = "null"),
- # Combine all static and dynamic data layers by date
- tar_target(augmented_data_directory,
+ tar_target(augmented_data_directory,
create_data_directory(directory_path = "data/augmented_data")),
- # This is where we set up what predictive layers go into the model
- # This doesn't need to be a list that's just for clarity it will
- # all be unlisted.
- tar_target(augmented_data_sources, list(outbreak_layers = wahis_outbreak_history,
- static_layers = c(soil_preprocessed,
- aspect_preprocessed,
- slope_preprocessed,
- glw_preprocessed,
- elevation_preprocessed,
- bioclim_preprocessed,
- landcover_preprocessed),
- dynamic_layers = c(weather_historical_means,
- ndvi_historical_means,
- ecmwf_forecasts_transformed, # data_date: timestamp[us, tz=UTC]
- weather_anomalies, # date: day32[day] 2005-04-14 2017-09-01
- forecasts_anomalies, # date: date32[day]
- ndvi_anomalies)), # date: date32[day]
- repository = "local"),
-
# Check if ndvi_anomalies_AWS parquet files already exists on AWS and can be loaded
# The only important one is the directory. The others are there to enforce dependencies.
tar_target(augmented_data_AWS, AWS_get_folder(augmented_data_directory,
- augmented_data_sources)), # Enforce dependency
-
- # Are we missing anything? Does ecmwf_forecasts_transformed serve as forecast_means?
- tar_target(augmented_data, augment_data(augmented_data_sources, # A list of source files to join and hive partition by date
- augmented_data_directory,
- augmented_data_AWS), # Enforce dependency
- format = "file",
- repository = "local"), # Enforce dependency
-
+ augmented_data_sources),
+ error = "null",
+ cue = tar_cue("always")), # Enforce dependency
+
+ # Combine all static and dynamic data layers by x, y, date, or doy
+ # Partition to complete dataset out into separate parquet files by year.
+ tar_target(augmented_data, list(response = rvf_outbreaks,
+ outbreak_history_layers = wahis_outbreak_history, # Good to join
+ static_layers = c(soil_preprocessed, # Good to join
+ aspect_preprocessed, # Good to join
+ slope_preprocessed, # Good to join
+ glw_preprocessed, # Good to join
+ elevation_preprocessed, # Good to join
+ bioclim_preprocessed, # Good to join
+ landcover_preprocessed), # Good to join
+ dynamic_layers = c(weather_historical_means, # Good to join
+ ndvi_historical_means, # Good to join
+ ecmwf_forecasts_transformed, # Good to join
+ weather_anomalies, # Good to join
+ forecasts_anomalies, # Need to add month and year as integer for partitioning
+ ndvi_anomalies)) |> ## Good to join
+ unlist() |>
+ arrow::open_dataset(unify_schemas = T) |>
+ arrow::write_dataset(partitioning = c("year", "month")),
+ repository = "local"),
+
# Next step put combined_anomalies files on AWS.
tar_target(augmented_data_AWS_upload, AWS_put_files(augmented_data,
- augmented_data_directory)),
-
+ augmented_data_directory),
+ error = "null"),
+
)
# Model -----------------------------------------------------------
model_targets <- tar_plan(
# RSA --------------------------------------------------
- tar_target(augmented_data_rsa_directory,
+ tar_target(augmented_data_rsa_directory,
create_data_directory(directory_path = "data/augmented_data_rsa")),
- # Check if combined_anomalies parquet files already exists on AWS and can be loaded
- # The only important one is the directory. The others are there to enforce dependencies.
- tar_target(augmented_data_rsa_AWS, AWS_get_folder(augmented_data_rsa_directory,
- weather_anomalies, # Enforce dependency
- ndvi_anomalies, # Enforce dependency
- model_dates_selected)), # Enforce dependency
-
- tar_target(aggregated_data_rsa,
- aggregate_augmented_data_by_adm(augmented_data,
- rsa_polygon,
- model_dates_selected),
- pattern = model_dates_selected),
-
- tar_target(rsa_polygon_spatial_weights, rsa_polygon |>
- mutate(area = sf::st_area(rsa_polygon)) |>
- as_tibble() |>
- select(shapeName, area)),
-
+ # # Switch to parquet based to save memory. Arrow left joins automatically.
+ # tar_target(model_data,
+ # left_join(aggregated_data_rsa,
+ # rvf_outbreaks,
+ # by = join_by(date, shapeName)) |>
+ # mutate(outbreak_30 = factor(replace_na(outbreak_30, FALSE))) |>
+ # left_join(rsa_polygon_spatial_weights, by = "shapeName") |>
+ # mutate(area = as.numeric(area))
+ # ),
+ #
+ # tar_target(training_data, training(model_data_split)),
+ # tar_target(holdout_data, testing(model_data_split)),
+
+ # # Check if combined_anomalies parquet files already exists on AWS and can be loaded
+ # # The only important one is the directory. The others are there to enforce dependencies.
+ # tar_target(augmented_data_rsa_AWS, AWS_get_folder(augmented_data_rsa_directory,
+ # weather_anomalies, # Enforce dependency
+ # ndvi_anomalies, # Enforce dependency
+ # model_dates_selected),
+ # error = "null",
+ # cue = tar_cue("always")), # Enforce dependency
+ #
+ # tar_target(aggregated_data_rsa,
+ # aggregate_augmented_data_by_adm(augmented_data,
+ # rsa_polygon,
+ # model_dates_selected),
+ # pattern = model_dates_selected),
+ #
+ # tar_target(rsa_polygon_spatial_weights, rsa_polygon |>
+ # mutate(area = sf::st_area(rsa_polygon)) |>
+ # as_tibble() |>
+ # select(shapeName, area)),
+
# # Switch to parquet based to save memory. Arrow left joins automatically.
# tar_target(model_data,
# left_join(aggregated_data_rsa,
diff --git a/_targets/meta/meta b/_targets/meta/meta
index 21d8ef2..2854ea9 100644
--- a/_targets/meta/meta
+++ b/_targets/meta/meta
@@ -1,128 +1,2468 @@
name|type|data|command|depend|seed|path|time|size|bytes|format|repository|iteration|parent|children|seconds|warnings|error
-tar_get_error|function|3c106aa142d6c9a9|||||||||||||||
-plot_targets|object|718ad17f619b9b2f|||||||||||||||
-report_targets|object|718ad17f619b9b2f|||||||||||||||
-download_modis_ndvi_delete|function|33709e5ea023c37c|||||||||||||||
-create_data_directory|function|90b18168daa27c11|||||||||||||||
-download_sentinel_ndvi|function|a56efa4dcafa639f|||||||||||||||
-transform_raster|function|0dc0c7d04248eec3|||||||||||||||
-create_country_polygons|function|d55b8c17ed672bf5|||||||||||||||
-set_ecmwf_api_parameter|function|ee3123dfaf994abc|||||||||||||||
+.Random.seed|object|062e61dbd8cf8f38|||||||||||||||
+aggregate_augmented_data_by_adm|function|2315722e5d2c9d69|||||||||||||||
+aggregated_data_rsa_cfa46357c5422e85|branch||7d01190fb5774477|82a53e13ddf3fb76|-529501474||t20048.2062256452s||0|qs|local|vector|aggregated_data_rsa||0.021||error in evaluating the argument x in selecting a method for function rast Failed to evaluate glue component augmented_dataCaused by error object augmented_data not found
+all_targets|function|43c15cf82d6b2a67|||||||||||||||
+aspect_AWS|stem|b09b8987c98d79b4|b38a981c8eabaac2|42aea4b6492310fb|2125538909||t20050.759422922s|0f5cc5be67b9db73|64|qs|local|vector|||0.313||
+aspect_directory|stem|9b8f594a9bd72a99|cff4cd549009b055|b4f5e9cdfa77e842|1585684056||t20047.8627788173s|3a092808d479a224|95|qs|local|vector|||0||
+aspect_preprocessed|stem|89e31b186303895d|b6996887bdfccb13|5d1c7e1742508c74|229226648|data/aspect_dataset/aspect.parquet|t20042.4663729884s|4ebb4d8eecfc783c|64917|file|local|vector|||0.006||
+aspect_preprocessed_AWS_upload|stem|121efa4c6f7e2603|f7e09b62977fc232|426ea4a10683c4b1|722026177||t20048.8843393371s|fe51d37b9c2ffbfd|161|qs|local|vector|||0.266||
+aspect_urls|stem|5883c2a2433de9ef|c2b161a9d51b1b18|2c530c1562a7fbd1|1401931808||t20047.8632723072s|cb5de256bff6bdf1|247|qs|local|vector|||0||
+augment_data|function|9c3d1e9c896537cd|||||||||||||||
+augment_data_old|function|06b3311d36ec63f5|||||||||||||||
+augmented_data|stem||f662570cee2d5283|d93e6eac71d70db3|-1997977228||t20048.04801025s||0|file|local|vector|||0.135||Cannot infer type from vector
+augmented_data_AWS|stem|b09b8987c98d79b4|39fd08b3192fc454|110feb5df64fc261|2085879239||t20050.7593061053s|0f5cc5be67b9db73|64|qs|local|vector|||0.356||
+augmented_data_directory|stem|3d86af701215c317|858fb51c9865890d|b4f5e9cdfa77e842|383321186||t20047.8634252608s|3a092808d479a224|95|qs|local|vector|||0.001||
+augmented_data_rsa_AWS|stem|b09b8987c98d79b4|1569834ee48af1ee|9826c8d2bf996e07|547378159||t20048.2054687969s|0f5cc5be67b9db73|64|qs|local|vector|||0.085||
+augmented_data_rsa_directory|stem|7865699f763a7f87|a0ed825ffed31382|b4f5e9cdfa77e842|1824665238||t20047.8627761219s|271db55f47f9100d|99|qs|local|vector|||0||
+augmented_data_sources|stem|0dcd7047e21e19f6|fe8597089e64d3cc|d7ecdef2c15b8092|-288201153||t20048.0400481564s||18898|qs|local|vector|||0.011||x is not a character vector
+aws_bucket|object|db87ce1c67408764|||||||||||||||
+AWS_get_folder|function|55fffed1bc2bedc5|||||||||||||||
+AWS_put_files|function|1511387f13a5426c|||||||||||||||
+aws_s3_upload_single_type|function|1a54b513a98e58f9|||||||||||||||
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+bioclim_preprocessed_AWS_upload|stem|4dce0db8ccbfff07|59e1fa988ffcf045|09cf826a0ed5c4ac|1756197124||t20048.8827946266s|5b53d96c56a085a8|163|qs|local|vector|||11.734||
+calculate_forecasts_anomalies|function|0d7ab8b116ec8db8|||||||||||||||
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+calculate_ndvi_historical_means|function|49c00f2659c9949b|||||||||||||||
+calculate_weather_anomalies|function|358d9e3de595a55e|||||||||||||||
calculate_weather_historical_means|function|ae3f281d755ccc1a|||||||||||||||
-documentation_targets|object|9ec6e3a264cd940b|||||||||||||||
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-delete_appears_task|function|51491fbb0277962e|||||||||||||||
-get_task_status_overview|function|b020881e0d2956c8|||||||||||||||
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+create_africa_polygon|function|cf9eeb8e3a6dd8ad|||||||||||||||
+create_country_polygons|function|d55b8c17ed672bf5|||||||||||||||
+create_data_directory|function|90b18168daa27c11|||||||||||||||
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create_raster_template_plot|function|756a38df4230b5db|||||||||||||||
-get_outbreak_distance_matrix|function|f385d13a21259a5a|||||||||||||||
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+delete_all_current_tasks|function|e0c0c08646308a1f|||||||||||||||
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+documentation_targets|object|0c4b888b73fc526f|||||||||||||||
+download_ecmwf_forecasts|function|23bba2002bf634d7|||||||||||||||
+download_modis_ndvi|function|1984481a2abc5759|||||||||||||||
+download_modis_ndvi_delete|function|33709e5ea023c37c|||||||||||||||
download_nasa_weather|function|f7dea44b09e73ce8|||||||||||||||
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+forecasts_anomalies_09a22e34546c46e0|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-140233188||t20049.27746851s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_09ce4264d3f535fa|branch|ceb97159a6d5f675|8ffd0455e647df1a|e3af31abed045e90|1980135505|data/forecast_anomalies/forecast_anomaly_2024-05-23.gz.parquet|t20047.6663892537s|f7dc8d141d446ccf|41343531|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_0b6bb234a2809878|branch|4950ff4ee672485b|8ffd0455e647df1a|e3af31abed045e90|-112224694|data/forecast_anomalies/forecast_anomaly_2015-12-20.gz.parquet|t20047.3792055183s|e70172e471b54d99|41474424|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_0bfd046ace736196|branch|eb1053629d79b4b8|8ffd0455e647df1a|e3af31abed045e90|-784234104|data/forecast_anomalies/forecast_anomaly_2019-05-02.gz.parquet|t20047.6436443103s|2fff7be5357ddbce|41363699|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_0c197fe44f1dad66|branch|a53fab995061b59b|8ffd0455e647df1a|e3af31abed045e90|-436278737|data/forecast_anomalies/forecast_anomaly_2015-03-22.gz.parquet|t20047.3760542354s|2cdc0229be3e0c44|41273368|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_0dea7c20a99fa348|branch|f39b627c0336ef98|8ffd0455e647df1a|e3af31abed045e90|-1044748241|data/forecast_anomalies/forecast_anomaly_2015-10-30.gz.parquet|t20047.3786383554s|e50eaf7b8b5a2a86|41404621|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_0ed933f48083dbeb|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-2101426356||t20049.2771649486s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_0ef75a2bf3d23976|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1169027264||t20049.2775158361s||0|null|local|vector|forecasts_anomalies||0.214||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_0f1202f3de705729|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1292369967||t20049.2771459338s||0|null|local|vector|forecasts_anomalies||0.191||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_0fdb98600d48188c|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-554657325||t20049.2774310863s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_10c9d4c62121166f|branch|51d3b0c3ef244d51|8ffd0455e647df1a|e3af31abed045e90|1400289701|data/forecast_anomalies/forecast_anomaly_2023-01-17.gz.parquet|t20047.6606260111s|03e5afdfbe8689a2|41294331|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_10cd279a895686b6|branch|bf71404ae98d183f|8ffd0455e647df1a|e3af31abed045e90|-654637087|data/forecast_anomalies/forecast_anomaly_2018-08-25.gz.parquet|t20047.6403657171s|3350367682252024|41297678|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_11133626cfd1583d|branch|acc7edb31d839aac|8ffd0455e647df1a|e3af31abed045e90|1789775895|data/forecast_anomalies/forecast_anomaly_2014-06-23.gz.parquet|t20047.3729752456s|172bff3f7e7a63b7|41350778|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_1147f1a515cb0a5b|branch|4e56c5b4ad6fcc88|8ffd0455e647df1a|e3af31abed045e90|-936471768|data/forecast_anomalies/forecast_anomaly_2016-07-13.gz.parquet|t20047.3821969304s|9a7953ef27f237c1|41310341|file|local|vector|forecasts_anomalies||0.004||
+forecasts_anomalies_11b1dae52df4d884|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-507421836||t20049.2773364017s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_11e206b5136011d0|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|501903183||t20049.2773224221s||0|null|local|vector|forecasts_anomalies||0.188||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_1212b768e4d2ff90|branch|0038b92a226cc355|8ffd0455e647df1a|e3af31abed045e90|-1509011656|data/forecast_anomalies/forecast_anomaly_2014-11-29.gz.parquet|t20047.3747888613s|5be149aeb00d1e00|41392582|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_124d450a43ea6e3c|branch|24a97b3f71535930|8ffd0455e647df1a|e3af31abed045e90|-704393800|data/forecast_anomalies/forecast_anomaly_2018-08-01.gz.parquet|t20047.640231407s|0b53dd4186343665|41272967|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_1296973a508f23d9|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-2116135546||t20049.2771131424s||0|null|local|vector|forecasts_anomalies||0.187||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_12a3606478cf5824|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-631375908||t20050.7619007149s||0|null|local|vector|forecasts_anomalies||0.317||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_1347fa03690bb780|branch|2cd78d74a294b59c|8ffd0455e647df1a|e3af31abed045e90|1813044025|data/forecast_anomalies/forecast_anomaly_2020-06-28.gz.parquet|t20047.6491635735s|c1917c6636126b11|41370325|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_14b5f13bda5a95d7|branch|63e66923ca0ae0c7|8ffd0455e647df1a|e3af31abed045e90|1158244526|data/forecast_anomalies/forecast_anomaly_2016-04-24.gz.parquet|t20047.3809792252s|205a0568d3ea78a0|41369633|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_150b2bb9ec7026f2|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-706360534||t20050.7616258445s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_152f11bf39d506f4|branch|e12c5261e8529a45|8ffd0455e647df1a|e3af31abed045e90|-1863999022|data/forecast_anomalies/forecast_anomaly_2014-07-05.gz.parquet|t20047.3732922142s|f1c4297961805d65|41355644|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_15d4d2acdabd783f|branch|497fe329bc9c8a34|8ffd0455e647df1a|e3af31abed045e90|-1333979126|data/forecast_anomalies/forecast_anomaly_2018-06-06.gz.parquet|t20047.6396265274s|9ffcf48c0c00d89b|41346796|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_16defa32d5300763|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|220501143||t20050.761910437s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_16e503fe66b15a5f|branch|c564d0ae25b91435|8ffd0455e647df1a|e3af31abed045e90|1595942870|data/forecast_anomalies/forecast_anomaly_2015-12-24.gz.parquet|t20047.3793704665s|af2d9af138b7b2e0|41471020|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_17079f4f721514e6|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1394840310||t20049.2770233174s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_17dc5b4af3befd1b|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|202869778||t20050.761781648s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_18f1f84e36c62a10|branch|6e0d8a221e9d5f55|8ffd0455e647df1a|e3af31abed045e90|1549349647|data/forecast_anomalies/forecast_anomaly_2023-04-12.gz.parquet|t20047.6618797312s|30833822e86d232e|41369980|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_1963a8ce15fbff4a|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-497595131||t20050.7618899414s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_1a5c4bd26a24a552|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|863735601||t20049.2771556886s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_1a8a75db8357ed58|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-2136332856||t20049.2775676149s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_1b7edf214a9d6df5|branch|119ac8d6a6a916a2|8ffd0455e647df1a|e3af31abed045e90|-835817903|data/forecast_anomalies/forecast_anomaly_2023-02-07.gz.parquet|t20047.6611396352s|589f89c84415e500|41349344|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_1c4b156d96430f87|branch|52549a07e041a4e8|8ffd0455e647df1a|e3af31abed045e90|1606853612|data/forecast_anomalies/forecast_anomaly_2020-08-10.gz.parquet|t20047.6497079278s|efdca083cb260369|41373030|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_1ca4fc885c189d61|branch|e195357bd3e98b78|8ffd0455e647df1a|e3af31abed045e90|386326501|data/forecast_anomalies/forecast_anomaly_2020-03-22.gz.parquet|t20047.6478228827s|ff1d89ef6ef9b3a1|41360454|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_1cfa98b128eaf944|branch|481f034ba3d8d3d7|8ffd0455e647df1a|e3af31abed045e90|-864677043|data/forecast_anomalies/forecast_anomaly_2022-09-04.gz.parquet|t20047.6589005589s|a3b37ad7c0312133|41255411|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_1d6a8fb14e19f443|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1312695596||t20049.2774924007s||0|null|local|vector|forecasts_anomalies||0.216||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_1e9d02d062f0cf56|branch|a03f7c7155a248ee|8ffd0455e647df1a|e3af31abed045e90|1537533659|data/forecast_anomalies/forecast_anomaly_2018-07-28.gz.parquet|t20047.639895643s|4724fb8af6172fd9|41298533|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_1f95e17000998fc9|branch|6fac2b3aaf9a3eff|8ffd0455e647df1a|e3af31abed045e90|-1549955658|data/forecast_anomalies/forecast_anomaly_2018-06-11.gz.parquet|t20047.6397641803s|615c44769df5150a|41353213|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_2224065c4fd154e2|branch|294ffb98ecfcf75a|8ffd0455e647df1a|e3af31abed045e90|395630009|data/forecast_anomalies/forecast_anomaly_2024-11-03.gz.parquet|t20047.6682319252s|bf78d9fa54295a26|100420|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_2227ca7e27efbe22|branch|f88e02cff3291cba|8ffd0455e647df1a|e3af31abed045e90|435195993|data/forecast_anomalies/forecast_anomaly_2023-08-28.gz.parquet|t20047.6632971005s|4042f397bd15ecdb|41393815|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_22376479c4db62d1|branch|e9cde5bd84820d7f|8ffd0455e647df1a|e3af31abed045e90|-390902050|data/forecast_anomalies/forecast_anomaly_2015-09-03.gz.parquet|t20047.3781966502s|2020ff605430cb3f|41295878|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_22a7fe52b1ba399e|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-145536215||t20049.2770753895s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_22e2fbe9b70db179|branch|d5070a96e49ee6ae|8ffd0455e647df1a|e3af31abed045e90|-203395445|data/forecast_anomalies/forecast_anomaly_2014-09-08.gz.parquet|t20047.373891802s|8341f3df083ec92f|41337556|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_22fff3f4152e743c|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|462718869||t20049.2774593097s||0|null|local|vector|forecasts_anomalies||0.189||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_230b15e1a5a62aa5|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|2128644645||t20049.2774264608s||0|null|local|vector|forecasts_anomalies||0.226||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_2391cfa78cc2c05a|branch|de2d0e202845fa11|8ffd0455e647df1a|e3af31abed045e90|-1067828069|data/forecast_anomalies/forecast_anomaly_2020-01-30.gz.parquet|t20047.6471297996s|5473073684223197|41399458|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_23d13314b30414eb|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-868516606||t20049.2769809836s||0|null|local|vector|forecasts_anomalies||0.319||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_2455e2c77482686f|branch|20f37a91db74ca5e|8ffd0455e647df1a|e3af31abed045e90|-2091310141|data/forecast_anomalies/forecast_anomaly_2022-05-19.gz.parquet|t20047.6579125884s|bb954f3d01105498|41280327|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_24bdc2c2f0add2ed|branch|d0d258fc0be6cf30|8ffd0455e647df1a|e3af31abed045e90|-1796955733|data/forecast_anomalies/forecast_anomaly_2017-08-03.gz.parquet|t20047.6357010318s|ad8063830bcf34cb|41290746|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_24f122ec8fdadf19|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|790510691||t20049.277255026s||0|null|local|vector|forecasts_anomalies||0.214||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_26d9eee4f3ba3dc0|branch|4ebff59eda6b0809|8ffd0455e647df1a|e3af31abed045e90|-244209087|data/forecast_anomalies/forecast_anomaly_2015-08-15.gz.parquet|t20047.3779177732s|d1cd66da93d577e8|41346646|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_27cf5045ae0b1928|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|707998370||t20049.2773505955s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_286d5f7365dd3e1d|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|158506339||t20049.2773787812s||0|null|local|vector|forecasts_anomalies||0.189||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_2ab0d6962b637f81|branch|0e176a881daaee8e|8ffd0455e647df1a|e3af31abed045e90|506976080|data/forecast_anomalies/forecast_anomaly_2015-05-21.gz.parquet|t20047.3770846329s|da4fae13a5cebc22|41319249|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_2b0d70ad7e579747|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-285585047||t20050.7618760614s||0|null|local|vector|forecasts_anomalies||0.187||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_2b363b2699b3b64e|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-78473617||t20050.7616166779s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_2bfbcc090ea86dd0|branch|1bfa57b56a724f38|8ffd0455e647df1a|e3af31abed045e90|-1145687811|data/forecast_anomalies/forecast_anomaly_2019-12-07.gz.parquet|t20047.6467193308s|712cffd404f38043|41373775|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_2c0c5b41df6982f6|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1058574186||t20049.2771510253s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_2e07e440381bf3ad|branch|c253ab23cb4d829b|8ffd0455e647df1a|e3af31abed045e90|-963487804|data/forecast_anomalies/forecast_anomaly_2020-08-25.gz.parquet|t20047.6499189135s|bccf655761b65020|41395077|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_2ed56f4f3a7e3652|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|692782280||t20049.2774119534s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_2fc03dd07fdb69c6|branch|017f81b063badbc6|8ffd0455e647df1a|e3af31abed045e90|1161021610|data/forecast_anomalies/forecast_anomaly_2017-10-11.gz.parquet|t20047.6365292383s|f2edf6e6cf7757bf|41354360|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_30932890cf93ae83|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1413108499||t20049.2769902858s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_30e37a399584cf02|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-909082718||t20049.2770279309s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_311873790d6f26ec|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-37338070||t20050.7618141054s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_3124c8fc177f702c|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-209107262||t20049.2774545236s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_312b7c73b7001076|branch|e32ae45c375b9ce4|8ffd0455e647df1a|e3af31abed045e90|-510688790|data/forecast_anomalies/forecast_anomaly_2018-01-24.gz.parquet|t20047.6376469403s|a697cee641e541df|41310928|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_3160919350c0e01b|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|897518010||t20050.761621295s||0|null|local|vector|forecasts_anomalies||0.191||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_31ed9b04e4e3eafd|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1148501578||t20049.2774780882s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_31ff1f428a3b30db|branch|589698ce4c88bde6|8ffd0455e647df1a|e3af31abed045e90|-339887307|data/forecast_anomalies/forecast_anomaly_2020-11-08.gz.parquet|t20047.6511479845s|4ba9a0d1efe52d8e|41409404|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_32ba2742f89ca6b6|branch|3ff93a61ce38ae0f|8ffd0455e647df1a|e3af31abed045e90|1242162888|data/forecast_anomalies/forecast_anomaly_2021-01-31.gz.parquet|t20047.6516715426s|62001773c729c30f|41314019|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_32cc4efb38c4d02d|branch|5e50f383411088a1|8ffd0455e647df1a|e3af31abed045e90|867889856|data/forecast_anomalies/forecast_anomaly_2015-06-26.gz.parquet|t20047.3772984878s|ab3e8f0d161050f2|41352758|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_3380d4d68c673dfa|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|231805552||t20049.277131962s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_33c3577052454b5f|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-2128868597||t20049.277160332s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_33c9c5062cc712fd|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-754506174||t20049.2770371924s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_3441a3f49aee95ac|branch|c5277decee08e23b|8ffd0455e647df1a|e3af31abed045e90|-574395970|data/forecast_anomalies/forecast_anomaly_2014-12-10.gz.parquet|t20047.3751011269s|9d02221a7dc024fa|41390888|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_3441aa0c2a69495c|branch|ba372d8850797bca|8ffd0455e647df1a|e3af31abed045e90|1131376297|data/forecast_anomalies/forecast_anomaly_2021-07-16.gz.parquet|t20047.6545400194s|cb38930a391984f0|41372431|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_3478379847d98b24|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-2111594134||t20049.277245365s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_34d50a243cd1e35b|branch|825744b8cc17fb1a|8ffd0455e647df1a|e3af31abed045e90|1711019887|data/forecast_anomalies/forecast_anomaly_2018-04-30.gz.parquet|t20047.63922353s|550ff447186725d8|41394471|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_34fb553d5388b666|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1161402873||t20049.2772643017s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_36e98a5d5306660c|branch|d4c8d73a7f69b0ed|8ffd0455e647df1a|e3af31abed045e90|1087048439|data/forecast_anomalies/forecast_anomaly_2021-11-26.gz.parquet|t20047.6559041343s|6b785e204d81f1c0|41368986|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_3767bc89703ac188|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|297434581||t20049.2772171385s||0|null|local|vector|forecasts_anomalies||0.187||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_37a1da467a8b2b52|branch|d1ad967b3439cb16|8ffd0455e647df1a|e3af31abed045e90|393022588|data/forecast_anomalies/forecast_anomaly_2023-03-29.gz.parquet|t20047.6612946073s|bd96d36317d8f242|41347900|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_388d8dd843ffa409|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|2081021899||t20049.2771366541s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_38c79201a1082875|branch|69309dcb61865ef8|8ffd0455e647df1a|e3af31abed045e90|-1048538827|data/forecast_anomalies/forecast_anomaly_2016-12-03.gz.parquet|t20047.6324815555s|9ad0e39953ff0dc0|41419712|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_39274e5501ddcc81|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1157310477||t20050.761937959s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_39572e646d0f947c|branch|d553f4d8242f9789|8ffd0455e647df1a|e3af31abed045e90|-138265181|data/forecast_anomalies/forecast_anomaly_2016-01-12.gz.parquet|t20047.3796885822s|0e5be3217d98dac2|41420351|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_3a0bd4dd35a77864|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-816096244||t20050.7618806563s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_3a31545b92636f3d|branch|08cf5292b06b44d8|8ffd0455e647df1a|e3af31abed045e90|-1484491676|data/forecast_anomalies/forecast_anomaly_2017-11-26.gz.parquet|t20047.6370014683s|c734886225998066|41331507|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_3a679629046ab976|branch|35ae1622b380aaf4|8ffd0455e647df1a|e3af31abed045e90|246113429|data/forecast_anomalies/forecast_anomaly_2019-10-06.gz.parquet|t20047.6458296408s|31ecb6aa8c2c67e3|41308951|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_3acf0bc0bbe3ab55|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-808925842||t20050.76197505s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_3d03bb2b741663e5|branch|c3f208a0e85f8cbe|8ffd0455e647df1a|e3af31abed045e90|1952356919|data/forecast_anomalies/forecast_anomaly_2019-03-09.gz.parquet|t20047.6426158381s|19ec650f5bd034ee|41334238|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_3d1939f0d4893dcb|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-2100172513||t20049.277534826s||0|null|local|vector|forecasts_anomalies||0.215||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_3f71916275841a14|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1354427285||t20049.2775251809s||0|null|local|vector|forecasts_anomalies||0.188||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_4098e03a89b70fb6|branch|28d51f26729000a0|8ffd0455e647df1a|e3af31abed045e90|-545999145|data/forecast_anomalies/forecast_anomaly_2023-07-04.gz.parquet|t20047.6629519304s|8076eba03115389f|41394594|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_40a69473a1de8360|branch|f4169351363be8e2|8ffd0455e647df1a|e3af31abed045e90|677832548|data/forecast_anomalies/forecast_anomaly_2017-11-21.gz.parquet|t20047.6367649077s|7374e2423d45c32c|41335347|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_4152e5c16c41491d|branch|ba612b99399870a6|8ffd0455e647df1a|e3af31abed045e90|-159584066|data/forecast_anomalies/forecast_anomaly_2019-02-21.gz.parquet|t20047.6422424658s|03c8707ff555163b|41380190|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_417f557a93a30f49|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1423862450||t20049.2771177719s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_41c6767b85dba4a0|branch|d49d2c2885057a26|8ffd0455e647df1a|e3af31abed045e90|1360822623|data/forecast_anomalies/forecast_anomaly_2019-12-15.gz.parquet|t20047.6464746505s|12941a4c79f2ccfa|41361107|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_423225928384a482|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|560875784||t20050.761947661s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_424d7fc2ce2ad9a0|branch|15b9d23d857bfaf0|8ffd0455e647df1a|e3af31abed045e90|-489432323|data/forecast_anomalies/forecast_anomaly_2017-05-10.gz.parquet|t20047.6343103051s|4ea238a36eb0ed14|41414562|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_43385c0754db2936|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1661623904||t20049.277032612s||0|null|local|vector|forecasts_anomalies||0.188||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_454c0b19ed3460d9|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1416411298||t20049.2773838s||0|null|local|vector|forecasts_anomalies||0.216||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_45c41e2d9edf6a0f|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1999551225||t20049.2775298222s||0|null|local|vector|forecasts_anomalies||0.189||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_45c5467a0c18bddb|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1746033906||t20050.7619241397s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_4723b413befbf330|branch|d26e6854cf7f7f27|8ffd0455e647df1a|e3af31abed045e90|-122801859|data/forecast_anomalies/forecast_anomaly_2020-03-25.gz.parquet|t20047.6480502051s|90897f0478317a05|41375097|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_47957bbdd449deca|branch|aa1c31d6e63eeb3b|8ffd0455e647df1a|e3af31abed045e90|1758790765|data/forecast_anomalies/forecast_anomaly_2019-02-17.gz.parquet|t20047.6423905748s|ada2c223a2ffc2d2|41390774|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_47a8f81e53baacf4|branch|156064a273c57e80|8ffd0455e647df1a|e3af31abed045e90|707259376|data/forecast_anomalies/forecast_anomaly_2024-11-14.gz.parquet|t20047.6683370555s|9450f432162775e4|99579|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_47d9714962c074c2|branch|a4e952f88a0b8927|8ffd0455e647df1a|e3af31abed045e90|2075959165|data/forecast_anomalies/forecast_anomaly_2016-09-13.gz.parquet|t20047.6315680356s|0716943b634038e0|41398046|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_47fbf41e582cb026|branch|b5000c1e07d57f0b|8ffd0455e647df1a|e3af31abed045e90|1311733413|data/forecast_anomalies/forecast_anomaly_2019-04-22.gz.parquet|t20047.6430640733s|8a8339abad85f43d|41364950|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_485e23e212ea358e|branch|0a2019a8fa54f5f8|8ffd0455e647df1a|e3af31abed045e90|654172612|data/forecast_anomalies/forecast_anomaly_2014-06-26.gz.parquet|t20047.3728442138s|76e4c1c032f43af8|41357575|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_48f1e9192ec8b84e|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|34797075||t20049.2774403285s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_494a65edfa3455be|branch|bd870aed3abbc4ba|8ffd0455e647df1a|e3af31abed045e90|-184906217|data/forecast_anomalies/forecast_anomaly_2014-07-30.gz.parquet|t20047.3731084974s|fb3ab1cb62e1886e|41273823|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_4b899179b2681877|branch|ac5b87f1bf664894|8ffd0455e647df1a|e3af31abed045e90|1184401752|data/forecast_anomalies/forecast_anomaly_2021-08-01.gz.parquet|t20047.6547473126s|5da4ba8df754a1f7|41314591|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_4bae79c2ccb98cfb|branch|8393de53e7dc0bb8|8ffd0455e647df1a|e3af31abed045e90|753358740|data/forecast_anomalies/forecast_anomaly_2019-11-07.gz.parquet|t20047.6460008187s|22626ee44f5cad22|41372895|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_4c2d825f8f56e0d7|branch|7334288f687c89f3|8ffd0455e647df1a|e3af31abed045e90|1983403135|data/forecast_anomalies/forecast_anomaly_2016-10-14.gz.parquet|t20047.6317271902s|67467047890d59c3|41396161|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_4ca218bfffb6c9f2|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-435740072||t20050.7619196183s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_4d1eb460f614eee9|branch|405739debf880847|8ffd0455e647df1a|e3af31abed045e90|358011850|data/forecast_anomalies/forecast_anomaly_2021-11-20.gz.parquet|t20047.6557535525s|42981043b24907bd|41334005|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_4e801bda3b1b7dfb|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-671115347||t20050.7618853904s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_4eae4a13809577eb|branch|b8eb4c0e69aa30bd|8ffd0455e647df1a|e3af31abed045e90|2065740775|data/forecast_anomalies/forecast_anomaly_2015-08-23.gz.parquet|t20047.3780569302s|c54ca163c199842e|41339236|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_4f1a55152a8a9fb9|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|702938377||t20049.2774449078s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_514b99f656ef5dfa|branch|67db3e0aa8931fa6|8ffd0455e647df1a|e3af31abed045e90|-1049097614|data/forecast_anomalies/forecast_anomaly_2024-01-03.gz.parquet|t20047.6648205034s|89db187210096ce0|41371448|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_525239c738b72403|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1530460563||t20049.2774827575s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_527d71579c8cffa9|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|645553686||t20049.2775533748s||0|null|local|vector|forecasts_anomalies||0.187||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_52b9fde42a5dc6e4|branch|3e284d9b906c1663|8ffd0455e647df1a|e3af31abed045e90|-1588957311|data/forecast_anomalies/forecast_anomaly_2016-07-30.gz.parquet|t20047.3819819674s|8f6bc5ebb394224e|41349819|file|local|vector|forecasts_anomalies||0.004||
+forecasts_anomalies_546bdd4a8bfd4d62|branch|c2f4882548cca514|8ffd0455e647df1a|e3af31abed045e90|202783991|data/forecast_anomalies/forecast_anomaly_2023-09-03.gz.parquet|t20047.6635611711s|48867b6f7114f57b|41395136|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_55371f417017d362|branch|768c6d00902ef959|8ffd0455e647df1a|e3af31abed045e90|1065731735|data/forecast_anomalies/forecast_anomaly_2020-06-01.gz.parquet|t20047.6489272242s|fd9568697584c5b8|41353599|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_55c247a84a537799|branch|631414c219af7f45|8ffd0455e647df1a|e3af31abed045e90|1231109555|data/forecast_anomalies/forecast_anomaly_2024-07-16.gz.parquet|t20047.6669673529s|1231ed28053ff75f|41439186|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_567ca18935d300dd|branch|7733cea989218453|8ffd0455e647df1a|e3af31abed045e90|-319605938|data/forecast_anomalies/forecast_anomaly_2016-05-13.gz.parquet|t20047.38142355s|d5f4845eb694cada|41402303|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_56b67d6e232523a9|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1576168470||t20049.2772689152s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_56e375b9e4f4dae1|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1823468896||t20050.7619894211s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_571e6c945dd76d08|branch|dbe43e15a80214fd|8ffd0455e647df1a|e3af31abed045e90|1013722387|data/forecast_anomalies/forecast_anomaly_2016-10-21.gz.parquet|t20047.6318714816s|5f4dfbf8b33ce805|41404179|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_574fc12a6ded6a41|branch|476a8d1e33980c70|8ffd0455e647df1a|e3af31abed045e90|1589986197|data/forecast_anomalies/forecast_anomaly_2017-07-16.gz.parquet|t20047.6352455947s|6472c979853e937a|41338904|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_57750e9dad6ee3e1|branch|84206591d6363dca|8ffd0455e647df1a|e3af31abed045e90|-2064412225|data/forecast_anomalies/forecast_anomaly_2016-02-19.gz.parquet|t20047.3801484266s|3b5cd4fb5db5b8a5|41392445|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_57ce3f53364aab0d|branch|7b52f0b1f4988105|8ffd0455e647df1a|e3af31abed045e90|967735747|data/forecast_anomalies/forecast_anomaly_2016-06-08.gz.parquet|t20047.3817731367s|e9e3500180a656f5|41381230|file|local|vector|forecasts_anomalies||0.004||
+forecasts_anomalies_586a211d594cb553|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1860585111||t20049.2773598785s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_58c8e7a0ae2a83d9|branch|6f6e58954ac2e21f|8ffd0455e647df1a|e3af31abed045e90|539135682|data/forecast_anomalies/forecast_anomaly_2021-09-02.gz.parquet|t20047.6551694814s|36da71cf9b4534a2|41243558|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_599a5596055f2c3f|branch|6c8d0d826dfcc947|8ffd0455e647df1a|e3af31abed045e90|812642028|data/forecast_anomalies/forecast_anomaly_2018-02-27.gz.parquet|t20047.6383312303s|7b6fba285ba7a3e8|41302788|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_59c5dcf889e626b1|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|728803624||t20050.7619802256s||0|null|local|vector|forecasts_anomalies||0.226||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_5a2a5f767c11c0b0|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|591789750||t20050.7618278455s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_5b0cd52bf0f4afd3|branch|f4909ef83a291682|8ffd0455e647df1a|e3af31abed045e90|1182837051|data/forecast_anomalies/forecast_anomaly_2024-08-02.gz.parquet|t20047.6672965955s|be096bb457658a23|41378853|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_5b7e8520afe2cd94|branch|a2aae82669c3494e|8ffd0455e647df1a|e3af31abed045e90|2043183568|data/forecast_anomalies/forecast_anomaly_2023-12-14.gz.parquet|t20047.6646671131s|9bdb2c51c6483fb9|41385078|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_5bf7caaa11d8f471|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1000229782||t20050.7618605924s||0|null|local|vector|forecasts_anomalies||0.191||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_5c26ac46815bca4d|branch|d8682408d09b916e|8ffd0455e647df1a|e3af31abed045e90|690350433|data/forecast_anomalies/forecast_anomaly_2024-10-23.gz.parquet|t20047.6681259806s|0f15212c07f60e75|41467249|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_5c52265634a41613|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1043980046||t20049.277563006s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_5cf753cd77fb29e4|branch|3562e389797666e4|8ffd0455e647df1a|e3af31abed045e90|-1226032723|data/forecast_anomalies/forecast_anomaly_2016-03-03.gz.parquet|t20047.3805323689s|bb27cdf4d408600c|41373752|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_5d58c3a7c217c822|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1848666835||t20049.2770514407s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_5dbb3417c6508ea1|branch|8c37aec387b4bf9d|8ffd0455e647df1a|e3af31abed045e90|1341335947|data/forecast_anomalies/forecast_anomaly_2014-08-26.gz.parquet|t20047.3736774668s|8a53e86683e65331|41261260|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_5defab566f775ab9|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-630664049||t20049.2774167056s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_629aff36a80bd877|branch|542c5ca360cb7c94|8ffd0455e647df1a|e3af31abed045e90|1802893854|data/forecast_anomalies/forecast_anomaly_2015-05-28.gz.parquet|t20047.3768707062s|a733709458ae4b64|41349479|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_62f48adff866bf98|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|277107155||t20049.2769652248s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_63006c29d6e9cbdf|branch|831f974e06be2d79|8ffd0455e647df1a|e3af31abed045e90|811289729|data/forecast_anomalies/forecast_anomaly_2015-11-23.gz.parquet|t20047.3787952002s|8865e7bf65472e67|41395325|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_63cfd81955d62696|branch|cb713e92ea24f05b|8ffd0455e647df1a|e3af31abed045e90|967468360|data/forecast_anomalies/forecast_anomaly_2023-11-03.gz.parquet|t20047.6643536699s|a283a7e0cb1d4c67|41354920|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_63ea6a0e61a0b01b|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1042382557||t20050.7616685795s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_64ab7074c2cfaae1|branch|01eac94ba83d545d|8ffd0455e647df1a|e3af31abed045e90|214162368|data/forecast_anomalies/forecast_anomaly_2024-01-24.gz.parquet|t20047.6650497129s|620b92a2c442a442|41427813|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_64bcace81dbfe5e5|branch|bd457b891b54555d|8ffd0455e647df1a|e3af31abed045e90|-841005604|data/forecast_anomalies/forecast_anomaly_2021-07-03.gz.parquet|t20047.6543146096s|4f785ec4d5308ab6|41345283|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_64f01d85cb90109f|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|753173684||t20050.7617349753s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_653139e816d8af51|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1343608250||t20049.2774356399s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_6576345f18f461e8|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1589169879||t20050.7615776657s||0|null|local|vector|forecasts_anomalies||0.181||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_65dfa4923a2f2f7b|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|938919694||t20049.2774073828s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_662395a4a42e8c2e|branch|3a9036f07f58f30c|8ffd0455e647df1a|e3af31abed045e90|2030209106|data/forecast_anomalies/forecast_anomaly_2024-04-27.gz.parquet|t20047.6659528206s|f00dbb5a5373d747|41350855|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_66d212cdab25c9a1|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|560611772||t20049.2771839192s||0|null|local|vector|forecasts_anomalies||0.187||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_6734a44247f58947|branch|c96bfdb184d3b1e4|8ffd0455e647df1a|e3af31abed045e90|-1695057585|data/forecast_anomalies/forecast_anomaly_2015-02-06.gz.parquet|t20047.3756850272s|71ecddb90791265a|41322946|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_67bb413e86d81214|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1877089502||t20049.2769605437s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_6852861d95e01992|branch|7e97e6661f805631|8ffd0455e647df1a|e3af31abed045e90|-1557741203|data/forecast_anomalies/forecast_anomaly_2017-02-24.gz.parquet|t20047.6332500461s|af1554b74db6fbef|41377527|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_6950a825b2487020|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-957256818||t20049.2771746394s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_69a12f644f14e702|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-383079679||t20050.7616731927s||0|null|local|vector|forecasts_anomalies||0.187||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_6a2183180632f7b0|branch|57358f6fd757037a|8ffd0455e647df1a|e3af31abed045e90|-1435725677|data/forecast_anomalies/forecast_anomaly_2024-12-27.gz.parquet|t20047.668552841s|633be13d4efd9137|99954|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_6a23f174f1cf3859|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|841405221||t20050.7616402332s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_6a330ad318946ba0|branch|4d3d8f602e8f7c8f|8ffd0455e647df1a|e3af31abed045e90|-991439996|data/forecast_anomalies/forecast_anomaly_2022-12-30.gz.parquet|t20047.6604719723s|637191323c1390c7|41357474|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_6a5992c64ded77b1|branch|db39a22ff142aba7|8ffd0455e647df1a|e3af31abed045e90|-1768681274|data/forecast_anomalies/forecast_anomaly_2015-10-16.gz.parquet|t20047.3784908207s|ece62bfece54ed04|41387353|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_6a85cd474d26a7c8|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-469975758||t20049.277070765s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_6b5f9c7f857d73a1|branch|9e758c25771ff2fb|8ffd0455e647df1a|e3af31abed045e90|499318668|data/forecast_anomalies/forecast_anomaly_2015-03-17.gz.parquet|t20047.3762829564s|d8da63a93dd60223|41261492|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_6b74f884dd6fb5d8|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1400680834||t20050.7617861479s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_6b86701a648b627a|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-522567185||t20050.7618945823s||0|null|local|vector|forecasts_anomalies||0.188||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_6b91a5a9da16936b|branch|b141f5b1a589db75|8ffd0455e647df1a|e3af31abed045e90|819797170|data/forecast_anomalies/forecast_anomaly_2018-09-06.gz.parquet|t20047.6408117743s|1044a897badbff93|41307844|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_6c5cb6ddcfbb7544|branch|a963e932dd43aa13|8ffd0455e647df1a|e3af31abed045e90|1050838052|data/forecast_anomalies/forecast_anomaly_2019-09-07.gz.parquet|t20047.6451445707s|b2d1a80e0e3d3f83|41283432|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_6ccd889c61a8a4a7|branch|0f97b549e8032af9|8ffd0455e647df1a|e3af31abed045e90|992720281|data/forecast_anomalies/forecast_anomaly_2017-03-19.gz.parquet|t20047.6337083168s|579151da3a8f5eab|41374420|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_6ccea29cb2449bb6|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-683138460||t20049.2773977687s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_6d06d26f52ba874b|branch|1af7926fd45f7749|8ffd0455e647df1a|e3af31abed045e90|1914004307|data/forecast_anomalies/forecast_anomaly_2020-02-06.gz.parquet|t20047.6475942155s|1468352419b1eb4b|41432533|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_6d5d9d48a549206c|branch|c5e5774f4c22e8b9|8ffd0455e647df1a|e3af31abed045e90|-700550233|data/forecast_anomalies/forecast_anomaly_2021-05-10.gz.parquet|t20047.6536733694s|e06ff9fa04626002|41404275|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_6d60dcd9dbc2e309|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-838354956||t20050.7619052487s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_6d6363e8164c224e|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|122776316||t20050.7616640238s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_6e05856e2f3420bd|branch|987fa5948be74cf4|8ffd0455e647df1a|e3af31abed045e90|-1762742661|data/forecast_anomalies/forecast_anomaly_2018-05-22.gz.parquet|t20047.639357793s|4e9ebcc63c7ac971|41348631|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_6e4fe7f885523be6|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1296863587||t20049.2774638875s||0|null|local|vector|forecasts_anomalies||0.181||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_6e89ffa245ca7a0b|branch|30ddbc3e59d15ccd|8ffd0455e647df1a|e3af31abed045e90|-1062674145|data/forecast_anomalies/forecast_anomaly_2017-06-02.gz.parquet|t20047.6346773369s|42d5784358e69e85|41366633|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_6f0c902e15b8271f|branch|314c807ccc6474f4|8ffd0455e647df1a|e3af31abed045e90|1336538658|data/forecast_anomalies/forecast_anomaly_2020-10-12.gz.parquet|t20047.6508452267s|0d68c25d29b317af|41406256|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_6f300f5f7daa8568|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1090267349||t20050.7619149423s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_6f3cd13daa2c1695|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|565884346||t20050.7615875076s||0|null|local|vector|forecasts_anomalies||0.231||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_6f76fa27f795938f|branch|591235b74c497c32|8ffd0455e647df1a|e3af31abed045e90|250833572|data/forecast_anomalies/forecast_anomaly_2021-09-29.gz.parquet|t20047.6553111846s|29b074f131bb35e3|41371628|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_6f86b27a85609625|branch|971d41596f4c223b|8ffd0455e647df1a|e3af31abed045e90|-1712675951|data/forecast_anomalies/forecast_anomaly_2014-08-23.gz.parquet|t20047.3734673935s|994387b1cefc13ce|41257889|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_6f96c4c66e825275|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|307362521||t20049.2771699227s||0|null|local|vector|forecasts_anomalies||0.216||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_6fc028010d574957|branch|c1de63410722ef82|8ffd0455e647df1a|e3af31abed045e90|-2120903422|data/forecast_anomalies/forecast_anomaly_2020-09-06.gz.parquet|t20047.6503640945s|b2c692626ad4cae2|41347858|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_708dcbedae06221f|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1300817913||t20050.7619287678s||0|null|local|vector|forecasts_anomalies||0.188||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_71046703e23b6e1b|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1501795527||t20049.2773081337s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_712d52f5cc65bb61|branch|0e8287bb633a648c|8ffd0455e647df1a|e3af31abed045e90|1309508952|data/forecast_anomalies/forecast_anomaly_2018-02-19.gz.parquet|t20047.6381083782s|53d9f94ac8590c2d|41265808|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_713dd80035089c64|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1790166896||t20050.7619614302s||0|null|local|vector|forecasts_anomalies||0.19||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_71b0f042227450ae|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1580276073||t20050.7617724731s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_723c32e2c1b7d4ed|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-460578764||t20049.2772407747s||0|null|local|vector|forecasts_anomalies||0.2||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_72476f1be18e2667|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1449349789||t20049.2773648761s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_73002d61d3eaa2cb|branch|a4b770c20ddb169d|8ffd0455e647df1a|e3af31abed045e90|299929460|data/forecast_anomalies/forecast_anomaly_2016-03-27.gz.parquet|t20047.3803037507s|c83d6d90667d5f3f|41361341|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_730228bad97eed3e|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|40067949||t20049.276955962s||0|null|local|vector|forecasts_anomalies||0.215||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_7318bf6ba979e583|branch|351a6bdef0de72f3|8ffd0455e647df1a|e3af31abed045e90|755895191|data/forecast_anomalies/forecast_anomaly_2018-03-17.gz.parquet|t20047.6385552504s|347aa015f4717e3c|41257674|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_732a4434c06ebb92|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1018070847||t20049.2771084882s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_737b5c1cbc933577|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|247133467||t20049.2774499585s||0|null|local|vector|forecasts_anomalies||0.216||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_7492d2983a0d27d5|branch|89cd2fb9861f8d0d|8ffd0455e647df1a|e3af31abed045e90|-9521828|data/forecast_anomalies/forecast_anomaly_2024-03-23.gz.parquet|t20047.6656625249s|707f31bcf9ed4811|41315862|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_74df73eb571e3c41|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1658299546||t20049.2773270532s||0|null|local|vector|forecasts_anomalies||0.189||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_74fe4b13c11f1c9a|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1512472308||t20050.7616918531s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_7520c798ddbc6ad9|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-173953736||t20050.761592187s||0|null|local|vector|forecasts_anomalies||0.187||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_75d42e23a57f79c1|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|64796286||t20050.7616587865s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_764a8a09fe18f470|branch|83a29bc31ca8d729|8ffd0455e647df1a|e3af31abed045e90|-324245702|data/forecast_anomalies/forecast_anomaly_2018-10-10.gz.parquet|t20047.6409700351s|cbc0ed27630de929|41386617|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_77b03c45c9ccd15f|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|893587852||t20050.7616779659s||0|null|local|vector|forecasts_anomalies||0.187||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_785ecdfc38bf3b9d|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1483143777||t20049.2774212635s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_78bb9a4a1e078d9d|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|654213819||t20049.2772989067s||0|null|local|vector|forecasts_anomalies||0.22||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_79890cf2f279c9a1|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-373270481||t20050.7618559899s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_7a2bdf2d2c8eb4c7|branch|242f18bd520f0015|8ffd0455e647df1a|e3af31abed045e90|1323984932|data/forecast_anomalies/forecast_anomaly_2016-02-01.gz.parquet|t20047.379920231s|ea0a71c06f1673f1|41385840|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_7a9adc15e099b22a|branch|e7f27a98e341dbb0|8ffd0455e647df1a|e3af31abed045e90|422643611|data/forecast_anomalies/forecast_anomaly_2022-02-05.gz.parquet|t20047.6568952601s|c814d3156f688aa5|41371301|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_7c78fb07f951416c|branch|2f646c1cf0a39b8f|8ffd0455e647df1a|e3af31abed045e90|1310665194|data/forecast_anomalies/forecast_anomaly_2015-06-25.gz.parquet|t20047.3775072113s|40823a34511a9257|41356616|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_7f30e82c07e49223|branch|cbe81aa1bf983730|8ffd0455e647df1a|e3af31abed045e90|651967872|data/forecast_anomalies/forecast_anomaly_2014-10-27.gz.parquet|t20047.3743281373s|d3cac915bec2306a|41361763|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_80eaf89cae56eab9|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|667649255||t20050.7618050271s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_80f49079e8b431bc|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|243925044||t20049.277303561s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_816c4e52e62e45e0|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1097753931||t20050.7616825635s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_816fe8c74cbd66a0|branch|47e6f9621cc6525b|8ffd0455e647df1a|e3af31abed045e90|870067024|data/forecast_anomalies/forecast_anomaly_2014-10-02.gz.parquet|t20047.3744729608s|56fcb10dec76ed22|41305466|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_81bdb68e802fefc8|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-969953186||t20049.2772596704s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_81d63bc039effa18|branch|fc8e2d6c7cba99e9|8ffd0455e647df1a|e3af31abed045e90|-500647557|data/forecast_anomalies/forecast_anomaly_2024-06-14.gz.parquet|t20047.6667556853s|23afa59422e6d3fc|41409397|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_829d2947bce17031|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|295276901||t20050.7619939256s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_82bfe9e3641c785a|branch|4b5ac77c1a524f0d|8ffd0455e647df1a|e3af31abed045e90|-122491507|data/forecast_anomalies/forecast_anomaly_2017-09-18.gz.parquet|t20047.636072161s|891cdc7ddb4498cb|41338211|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_82d6939b7df2d1af|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1111336640||t20049.2773884584s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_82d96bf3c8a9d513|branch|d16458cf390d89ab|8ffd0455e647df1a|e3af31abed045e90|-1897510593|data/forecast_anomalies/forecast_anomaly_2014-09-16.gz.parquet|t20047.3741074094s|8cd8629639f60dea|41339448|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_82e39c1ec7f7486c|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1342556572||t20049.2770091503s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_84fed4685f9fafd3|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1051828536||t20050.7617628348s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_850d1e2bc400e6d4|branch|b0b4a7c09cb88c8f|8ffd0455e647df1a|e3af31abed045e90|-2096704686|data/forecast_anomalies/forecast_anomaly_2016-12-19.gz.parquet|t20047.6327144348s|60274a70f193a540|41391341|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_857780ed6c632fe7|branch|f440b510d2650e38|8ffd0455e647df1a|e3af31abed045e90|72127021|data/forecast_anomalies/forecast_anomaly_2022-10-03.gz.parquet|t20047.6593289922s|a094afdd7e953fe8|41323228|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_8702e6c8ace1ae51|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|446577729||t20049.2769698013s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_87416bd4ce591501|branch|c963e7ec1bc9c161|8ffd0455e647df1a|e3af31abed045e90|-1956257859|data/forecast_anomalies/forecast_anomaly_2015-09-06.gz.parquet|t20047.3783448422s|0bacb0f38e867996|41348407|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_879a7d0ad17bf653|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|588322635||t20049.2773317305s||0|null|local|vector|forecasts_anomalies||0.189||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_8890da29fb50342e|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|178464440||t20050.7616448192s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_88e170ee0990afdf|branch|52a9cb82b355c9b4|8ffd0455e647df1a|e3af31abed045e90|872521378|data/forecast_anomalies/forecast_anomaly_2022-07-26.gz.parquet|t20047.6585066989s|b87e255b0801d2d3|41284098|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_8935c5d050b1610f|branch|3ccd633f73148525|8ffd0455e647df1a|e3af31abed045e90|-1298393224|data/forecast_anomalies/forecast_anomaly_2015-11-20.gz.parquet|t20047.3789561422s|c793167c201c01ff|41398981|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_896a4c05ff8a5a49|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1427724776||t20050.7619567789s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_8a1268137c436bd7|branch|33eb2614c027b245|8ffd0455e647df1a|e3af31abed045e90|-1620812593|data/forecast_anomalies/forecast_anomaly_2022-11-27.gz.parquet|t20047.6600055457s|176d0e58d5c40c55|41372491|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_8bad23692ce5aa14|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|111596554||t20049.2771934864s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_8c4d1b61c0223b6e|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|631017312||t20050.7618003759s||0|null|local|vector|forecasts_anomalies||0.228||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_8d4154fab290bb73|branch|791dd883f2850040|8ffd0455e647df1a|e3af31abed045e90|-387747099|data/forecast_anomalies/forecast_anomaly_2024-02-17.gz.parquet|t20047.6654352622s|1fbe53df4f5a35f1|41309537|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_8d5eb23c14fbfe15|branch|baf6439cc0e65eda|8ffd0455e647df1a|e3af31abed045e90|-1097318349|data/forecast_anomalies/forecast_anomaly_2023-07-08.gz.parquet|t20047.6631642769s|2cbca4cf0091eeec|41378193|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_8f45721225f672f3|branch|bcf55440edae7870|8ffd0455e647df1a|e3af31abed045e90|220719188|data/forecast_anomalies/forecast_anomaly_2019-06-16.gz.parquet|t20047.6438599235s|52d88a72280d49fa|41337013|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_910112e5e3b8c07f|branch|55217f2001492797|8ffd0455e647df1a|e3af31abed045e90|1306796296|data/forecast_anomalies/forecast_anomaly_2023-09-20.gz.parquet|t20047.663701015s|58ebc02809bceac8|41377954|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_91c07f1bbb6ee2e0|branch|48e22bf8dbb61035|8ffd0455e647df1a|e3af31abed045e90|-72192188|data/forecast_anomalies/forecast_anomaly_2015-07-24.gz.parquet|t20047.3776370934s|c56a1b2dcab5947d|41328623|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_928638d3a04731c9|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1646009639||t20049.2775205354s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_9332746df6125be0|branch|0d1addf4b2cf6547|8ffd0455e647df1a|e3af31abed045e90|1192010461|data/forecast_anomalies/forecast_anomaly_2020-04-11.gz.parquet|t20047.6484982934s|c135008ffbcde51f|41416967|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_9378be60de454e12|branch|041c733e25460d86|8ffd0455e647df1a|e3af31abed045e90|-1706399729|data/forecast_anomalies/forecast_anomaly_2020-12-19.gz.parquet|t20047.6513038663s|1987b5bbc4063b04|41356619|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_93ae17f782dbab1b|branch|ae9b263379373777|8ffd0455e647df1a|e3af31abed045e90|1516598266|data/forecast_anomalies/forecast_anomaly_2023-08-24.gz.parquet|t20047.663430528s|c605fcafd5aff1e7|41389981|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_93b92a161e45fa8b|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|270587606||t20049.2772734892s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_94084e71681d1d05|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1704554678||t20049.2772500103s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_94bee36003178e5c|branch|eae9a4386a357419|8ffd0455e647df1a|e3af31abed045e90|26073409|data/forecast_anomalies/forecast_anomaly_2024-07-15.gz.parquet|t20047.6671078716s|02453e6a8091a36c|41419158|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_94d6f3b6efa9ea50|branch|fee1953abbb2f439|8ffd0455e647df1a|e3af31abed045e90|-1379059692|data/forecast_anomalies/forecast_anomaly_2022-05-18.gz.parquet|t20047.6577751427s|fc3129e768bebc28|41305565|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_95732b8c45057104|branch|390136d9959cab9f|8ffd0455e647df1a|e3af31abed045e90|687315570|data/forecast_anomalies/forecast_anomaly_2019-10-11.gz.parquet|t20047.6455956838s|29b19414e6f2771d|41303078|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_957fbc596de0c900|branch|aa1e1cc1a8b1deb2|8ffd0455e647df1a|e3af31abed045e90|-1749346974|data/forecast_anomalies/forecast_anomaly_2017-03-28.gz.parquet|t20047.6338563361s|e24e03e91f7070b4|41402524|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_95c6d4091ebecf96|branch|6ac0fe66ccbae7fe|8ffd0455e647df1a|e3af31abed045e90|-1590309159|data/forecast_anomalies/forecast_anomaly_2023-04-24.gz.parquet|t20047.6616621663s|776f8f4b56ba2355|41349685|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_964e15f837f46cbf|branch|b33595a4ae708807|8ffd0455e647df1a|e3af31abed045e90|2022919265|data/forecast_anomalies/forecast_anomaly_2024-09-28.gz.parquet|t20047.6676154216s|27a89f1f526cb19a|41497194|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_96e5384e649fba97|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-586783761||t20049.277289282s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_99170826f9c2aa83|branch|39987186745fef1b|8ffd0455e647df1a|e3af31abed045e90|563502843|data/forecast_anomalies/forecast_anomaly_2017-04-27.gz.parquet|t20047.6341614003s|8e2a1e1231a3621b|41422043|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_99704bc4f46cb74f|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-131089942||t20049.2770943071s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_9a5f0ebac7f97265|branch|cd0396660feb4d23|8ffd0455e647df1a|e3af31abed045e90|-314266371|data/forecast_anomalies/forecast_anomaly_2020-04-23.gz.parquet|t20047.6482742797s|dbec1bd4080e1267|41389946|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_9b2ca550184dea2d|branch|8ea89bcddc41a518|8ffd0455e647df1a|e3af31abed045e90|683459179|data/forecast_anomalies/forecast_anomaly_2018-12-16.gz.parquet|t20047.6417807773s|a09756237b8f305d|41348207|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_9be5cdaba1f122bf|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-402525999||t20050.7616356558s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_9bea1c51f8401092|branch|b6879d4b7c90d95c|8ffd0455e647df1a|e3af31abed045e90|-501730805|data/forecast_anomalies/forecast_anomaly_2023-05-16.gz.parquet|t20047.6620968157s|da5ee066571c810b|41388356|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_9bf618874a549ae0|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1094167190||t20049.2769745017s||0|null|local|vector|forecasts_anomalies||0.189||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_9c23ef4c80d34607|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|652769420||t20049.2771412062s||0|null|local|vector|forecasts_anomalies||0.181||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_9d9cf9ecd3975ffc|branch|ba906ecd22cfb785|8ffd0455e647df1a|e3af31abed045e90|-100096957|data/forecast_anomalies/forecast_anomaly_2020-05-08.gz.parquet|t20047.6486445471s|99ecd75a00b29ee9|41409173|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_9de42571df7b57f4|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-772191727||t20050.7619334084s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_9df6a86fe9f2c923|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-233415883||t20050.7617019039s||0|null|local|vector|forecasts_anomalies||0.19||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_9f3b3e9dcb1af744|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-365040246||t20049.2773460403s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_9f894021f7ca7e1a|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-642361747||t20049.2770800863s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_9fd8414b061d8281|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|570664982||t20049.2771792771s||0|null|local|vector|forecasts_anomalies||0.19||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_a00106affa9e3dc5|branch|7833fbdcafe6a3b1|8ffd0455e647df1a|e3af31abed045e90|-1447410101|data/forecast_anomalies/forecast_anomaly_2017-05-17.gz.parquet|t20047.6344577959s|e296fd341737aa11|41372974|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_a0912cc7cd030e82|branch|ca37c0268d765da7|8ffd0455e647df1a|e3af31abed045e90|297554252|data/forecast_anomalies/forecast_anomaly_2018-12-18.gz.parquet|t20047.6416194494s|530e6542030ba946|41358408|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_a0bd67ef9723e49c|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1524658877||t20050.7615684173s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_a144387b640cc49d|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|123928949||t20049.2770183441s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_a15ef440f8c9e775|branch|f1926d46831ff9ec|8ffd0455e647df1a|e3af31abed045e90|1179674245|data/forecast_anomalies/forecast_anomaly_2016-04-04.gz.parquet|t20047.3807599098s|6c15c5bcdcd8a508|41386749|file|local|vector|forecasts_anomalies||0.004||
+forecasts_anomalies_a189b5f751e204c1|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1659302930||t20050.7616120897s||0|null|local|vector|forecasts_anomalies||0.181||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_a19de4e10c48b7d5|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1855291180||t20050.7618095299s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_a2b6e2b88316397f|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1414771796||t20049.2773413639s||0|null|local|vector|forecasts_anomalies||0.213||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_a34ab094992747f7|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-887098308||t20049.2769855853s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_a421a6b92684f0e8|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1250907951||t20049.2770606981s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_a45a894380811aa4|branch|18a1d6f134c4c1de|8ffd0455e647df1a|e3af31abed045e90|-767554195|data/forecast_anomalies/forecast_anomaly_2017-06-18.gz.parquet|t20047.6348247378s|a8b411c32a039d74|41351109|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_a57ca26541e15701|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|242674536||t20050.7619659602s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_a63bb8b8d94f953f|branch|828be28329b7660f|8ffd0455e647df1a|e3af31abed045e90|1432670713|data/forecast_anomalies/forecast_anomaly_2014-12-29.gz.parquet|t20047.3749426089s|cf62a207d865548d|41365536|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_a68eecc618a51175|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1854735893||t20050.7616075907s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_a6a5d2b276768ef2|branch|24560398b74631ce|8ffd0455e647df1a|e3af31abed045e90|264890642|data/forecast_anomalies/forecast_anomaly_2020-07-17.gz.parquet|t20047.6494931452s|366be45a51e649a6|41330256|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_a841f7d740fd9af6|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|938332072||t20049.2773173691s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_a8507259409852b5|branch|4d9392c47265ee80|8ffd0455e647df1a|e3af31abed045e90|-676630341|data/forecast_anomalies/forecast_anomaly_2017-09-11.gz.parquet|t20047.6359260669s|1ee851f4b31cea66|41335383|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_a8a04d56fb06b537|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|474760429||t20050.7617907486s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_a8dac3ade4d4511b|branch|dc32807aacbc719c|8ffd0455e647df1a|e3af31abed045e90|-514052489|data/forecast_anomalies/forecast_anomaly_2016-11-14.gz.parquet|t20047.6322428151s|90c458446ea7b7c3|41402294|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_a8f08c46e2b225ae|branch|2037d536e9f39224|8ffd0455e647df1a|e3af31abed045e90|827820366|data/forecast_anomalies/forecast_anomaly_2017-01-30.gz.parquet|t20047.6331014224s|c38ab0af9452b97b|41397743|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_a90b1768be5eddcd|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1929148373||t20050.7619705198s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_a9d20d693f16ef4b|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-876955647||t20049.2775109101s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_aa646932557ed9a1|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-834136885||t20050.7619522649s||0|null|local|vector|forecasts_anomalies||0.19||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_aaab6802e16873c9|branch|84a106d2bb118393|8ffd0455e647df1a|e3af31abed045e90|1552400817|data/forecast_anomalies/forecast_anomaly_2024-09-17.gz.parquet|t20047.6677900268s|7a334e393f87e7d2|41430266|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_aaebd69104cdfbde|branch|2d171942f3ba24b1|8ffd0455e647df1a|e3af31abed045e90|1890128237|data/forecast_anomalies/forecast_anomaly_2021-03-18.gz.parquet|t20047.6528006834s|1b142d05ae9a9a03|41311415|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_ab213f3d345938bf|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1441089309||t20049.2775722395s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_ac0ca45e51cf55fb|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1820083543||t20049.2773127966s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_ac4b00661d3ae6c3|branch|488aa2123385009d|8ffd0455e647df1a|e3af31abed045e90|724394285|data/forecast_anomalies/forecast_anomaly_2016-01-08.gz.parquet|t20047.3795312418s|d1b0679f3cbb5ae3|41436270|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_acdcd1471cfb0a2b|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1158134862||t20049.2770850799s||0|null|local|vector|forecasts_anomalies||0.213||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_ad4eb0861a156ed2|branch|af7ee8697736db6f|8ffd0455e647df1a|e3af31abed045e90|1220029269|data/forecast_anomalies/forecast_anomaly_2015-07-19.gz.parquet|t20047.3777773792s|b0d0a6fb08e03cfe|41305787|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_adec5907cb62d51c|branch|cbdb9c83f6fa3af7|8ffd0455e647df1a|e3af31abed045e90|-1722533512|data/forecast_anomalies/forecast_anomaly_2023-01-16.gz.parquet|t20047.6607815877s|a0abd31412efcd36|41304414|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_aecce4309368201f|branch|e87ca1d802adb46a|8ffd0455e647df1a|e3af31abed045e90|908496847|data/forecast_anomalies/forecast_anomaly_2024-05-18.gz.parquet|t20047.6662432411s|5abf6b89440a0cb1|41338783|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_af8a7e1a8fca6d9e|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-488718397||t20049.2770560752s||0|null|local|vector|forecasts_anomalies||0.187||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_af93a83c00da6d09|branch|4f5f8aca785d60e1|8ffd0455e647df1a|e3af31abed045e90|-1706292107|data/forecast_anomalies/forecast_anomaly_2021-06-22.gz.parquet|t20047.6541050131s|73fe1ccbb83488b4|41349522|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_AWS|stem|b09b8987c98d79b4|db1836602de7f0a9|8fe91b6c38b0f333|1100283252||t20050.7615404647s|0f5cc5be67b9db73|64|qs|local|vector|||0.179||
+forecasts_anomalies_AWS_upload|stem|dc5cc3acafa31d79|1b776da7e4f73b83|981d080206e012f5|-1334965273||t20048.2054641174s|2cbdbb0ff1663637|187|qs|local|vector|||0.203||
+forecasts_anomalies_b039a2cc90e8e3b9|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1768509185||t20050.7618375834s||0|null|local|vector|forecasts_anomalies||0.233||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_b07ffc4bac7381fc|branch|77ed210bd7808a31|8ffd0455e647df1a|e3af31abed045e90|-2091167264|data/forecast_anomalies/forecast_anomaly_2023-10-06.gz.parquet|t20047.6638506931s|b0da9b9440ba8ca6|41403101|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_b1271f7d31ee80d6|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1770741803||t20050.7616542078s||0|null|local|vector|forecasts_anomalies||0.187||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_b194099bbc7d88de|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1118714883||t20049.277279998s||0|null|local|vector|forecasts_anomalies||0.31||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_b1b31d822283394a|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1091816769||t20049.2774873921s||0|null|local|vector|forecasts_anomalies||0.181||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_b32bf0fa1161ae65|branch|6f51c41a99d756f5|8ffd0455e647df1a|e3af31abed045e90|2007243356|data/forecast_anomalies/forecast_anomaly_2017-12-05.gz.parquet|t20047.6372430479s|6398806dfcdd0de4|41356692|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_b3fabe8e96c35cb7|branch|6d051356ed3d9b08|8ffd0455e647df1a|e3af31abed045e90|-586119076|data/forecast_anomalies/forecast_anomaly_2016-08-09.gz.parquet|t20047.3823462464s|e879936fdd8a29ce|41388718|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_b40f95a8c5abc719|branch|3c9c3cfebf0ba6e8|8ffd0455e647df1a|e3af31abed045e90|1388903037|data/forecast_anomalies/forecast_anomaly_2017-07-02.gz.parquet|t20047.6350365269s|d351d013ae7395c0|41328285|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_b4f5cd1dcf18b1cc|branch|feb6ed1d07344ea2|8ffd0455e647df1a|e3af31abed045e90|1662330102|data/forecast_anomalies/forecast_anomaly_2016-08-21.gz.parquet|t20047.3825652639s|1634a2e7c0e490ab|41397433|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_b56a10378f5cff9d|branch|a6a90bfcbc71e42b|8ffd0455e647df1a|e3af31abed045e90|197150657|data/forecast_anomalies/forecast_anomaly_2018-07-09.gz.parquet|t20047.6400241471s|85a34faacd281001|41295761|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_b6c58b2a663d3ebf|branch|23e428254983d406|8ffd0455e647df1a|e3af31abed045e90|447963433|data/forecast_anomalies/forecast_anomaly_2020-02-22.gz.parquet|t20047.6473576592s|3a1929dc7f2c8053|41396022|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_b71dd1b5c97bfbd8|branch|90456fa4a5239143|8ffd0455e647df1a|e3af31abed045e90|593516455|data/forecast_anomalies/forecast_anomaly_2018-11-16.gz.parquet|t20047.6414498662s|32ea7d770f67b3b7|41343809|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_b76569fef69b3038|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1546301020||t20050.7617443459s||0|null|local|vector|forecasts_anomalies||0.192||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_b87752da4d9934c2|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|868976055||t20049.277212457s||0|null|local|vector|forecasts_anomalies||0.212||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_b8e10e360941c022|branch|aca4d10458c40b46|8ffd0455e647df1a|e3af31abed045e90|-281835850|data/forecast_anomalies/forecast_anomaly_2021-01-17.gz.parquet|t20047.6519021981s|20582157eb26dc21|41257110|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_b98a4fa6bb67e307|branch|1a73fd2fe63a57d1|8ffd0455e647df1a|e3af31abed045e90|-525805321|data/forecast_anomalies/forecast_anomaly_2022-03-12.gz.parquet|t20047.6571908394s|475844114f01bfe8|41338834|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_b9a06c65d1ffe416|branch|b651f5269a9272c7|8ffd0455e647df1a|e3af31abed045e90|-1286702948|data/forecast_anomalies/forecast_anomaly_2024-02-04.gz.parquet|t20047.6652809887s|8116b775d44733be|41378301|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_ba24b3e42a507116|branch|d8a06c88bbbc1b92|8ffd0455e647df1a|e3af31abed045e90|-950942730|data/forecast_anomalies/forecast_anomaly_2023-06-14.gz.parquet|t20047.6625238538s|4966e51c9efe652c|41409933|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_ba28d271be8d01a6|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|286843320||t20049.2769999034s||0|null|local|vector|forecasts_anomalies||0.214||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_bb1e9cc23deb21c1|branch|cae700cf1eb19ebf|8ffd0455e647df1a|e3af31abed045e90|-1873476983|data/forecast_anomalies/forecast_anomaly_2019-07-23.gz.parquet|t20047.644496373s|0b2aa4b505cbcd55|41342422|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_bc94ea53d791545c|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1455653785||t20049.2775441055s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_bcb90fcde640ab9d|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1221136689||t20050.7615823303s||0|null|local|vector|forecasts_anomalies||0.188||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_bcd035c8a9686780|branch|8ceef8555280c0bd|8ffd0455e647df1a|e3af31abed045e90|-366196861|data/forecast_anomalies/forecast_anomaly_2019-06-04.gz.parquet|t20047.6440702522s|9fc6473ee88e80fd|41345064|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_bf643212ca3a8424|branch|d3fccfa197d2628f|8ffd0455e647df1a|e3af31abed045e90|-607884678|data/forecast_anomalies/forecast_anomaly_2023-10-15.gz.parquet|t20047.6640001027s|e0169d6747d04232|41415044|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_c007368cf3f53264|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1716157847||t20049.2773741459s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_c00cbe38a9352e9a|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1216481361||t20049.2771035733s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_c15e74f265a0bff9|branch|e1fcf15156643f91|8ffd0455e647df1a|e3af31abed045e90|759758093|data/forecast_anomalies/forecast_anomaly_2023-02-15.gz.parquet|t20047.660926961s|3d0e20326810e9c8|41302085|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_c2819c33458c5c79|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1095673576||t20049.2774970231s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_c2a1a59c4811ccc7|branch|555d675d4bc0def9|8ffd0455e647df1a|e3af31abed045e90|1831132445|data/forecast_anomalies/forecast_anomaly_2016-06-26.gz.parquet|t20047.3815581958s|74689f31686b33e8|41369915|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_c3d3cd51b7c90790|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1090322152||t20049.277539416s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_c3eaa215ba6ce5fc|branch|30a0edb7eedb99bb|8ffd0455e647df1a|e3af31abed045e90|1127622085|data/forecast_anomalies/forecast_anomaly_2021-05-14.gz.parquet|t20047.6534539736s|f3f97e3b09adf33c|41377188|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_c45e4a018eabde46|branch|3cce36cfb5ccc4be|8ffd0455e647df1a|e3af31abed045e90|-449909826|data/forecast_anomalies/forecast_anomaly_2020-01-28.gz.parquet|t20047.6469668781s|514fda2f21042e6e|41395324|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_c51b1a50fab354c4|branch|c0a62a3acda6f067|8ffd0455e647df1a|e3af31abed045e90|-760558152|data/forecast_anomalies/forecast_anomaly_2017-01-12.gz.parquet|t20047.6329504385s|4ac868a4b5f4e01f|41404095|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_c55cf431118c1114|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1265853905||t20050.7615968289s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_c56b76614492ea13|branch|3095eb9fc79b6487|8ffd0455e647df1a|e3af31abed045e90|-1967991910|data/forecast_anomalies/forecast_anomaly_2019-01-23.gz.parquet|t20047.6419305336s|b1a92c6671fdf701|41349013|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_c6132bc72df645fd|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1325601384||t20050.7618468023s||0|null|local|vector|forecasts_anomalies||0.192||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_c622570370581449|branch|93b27befbc5b9e2c|8ffd0455e647df1a|e3af31abed045e90|174394979|data/forecast_anomalies/forecast_anomaly_2020-12-16.gz.parquet|t20047.6515185342s|e128cc0c021123b9|41344002|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_c66947172d67849e|branch|281054f7ee3db3f7|8ffd0455e647df1a|e3af31abed045e90|1007926580|data/forecast_anomalies/forecast_anomaly_2022-09-07.gz.parquet|t20047.6591162245s|9ea0f1b7a8a39e50|41267613|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_c7dd1fe94090f3af|branch|0b471341f083f01a|8ffd0455e647df1a|e3af31abed045e90|-1153766758|data/forecast_anomalies/forecast_anomaly_2024-06-03.gz.parquet|t20047.6666041739s|a48105ead0e2c857|41386732|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_c81b883cc71cce0f|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-409439947||t20050.7618324728s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_c83ef772500ac1c1|branch|c178f42d5aa9dfca|8ffd0455e647df1a|e3af31abed045e90|2050092413|data/forecast_anomalies/forecast_anomaly_2021-08-06.gz.parquet|t20047.654959478s|1d104f6b08db9c70|41285460|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_c8617e9342e20de9|branch|262c9344faa3e96d|8ffd0455e647df1a|e3af31abed045e90|-1688607942|data/forecast_anomalies/forecast_anomaly_2019-01-11.gz.parquet|t20047.6420903961s|f088999a05681f74|41332153|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_c8b3a71269165b0c|branch|2c93b04e74b50dbd|8ffd0455e647df1a|e3af31abed045e90|1404638179|data/forecast_anomalies/forecast_anomaly_2021-10-05.gz.parquet|t20047.6556031658s|f87476fda0affa20|41361980|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_c8b4884014398b20|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1344860393||t20049.2771273755s||0|null|local|vector|forecasts_anomalies||0.217||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_c94092adda778eab|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1739457850||t20049.2772846499s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_c9516f64d3defa27|branch|f50d50d2b8b029e1|8ffd0455e647df1a|e3af31abed045e90|-1177512636|data/forecast_anomalies/forecast_anomaly_2014-11-15.gz.parquet|t20047.3746336129s|1f123ae5b07ffcdc|41373662|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_c9d73bf78a91f33e|branch|98c845320dc3129f|8ffd0455e647df1a|e3af31abed045e90|1605842068|data/forecast_anomalies/forecast_anomaly_2019-07-19.gz.parquet|t20047.6442855423s|380e2067407bef15|41298553|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_c9fa23ebee7b9f7b|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|393384229||t20050.761871414s||0|null|local|vector|forecasts_anomalies||0.231||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_ca83acf708bcfe34|branch|02fc3f429d0aaa19|8ffd0455e647df1a|e3af31abed045e90|571079039|data/forecast_anomalies/forecast_anomaly_2022-06-17.gz.parquet|t20047.6580515124s|191d2e1e1a000a71|41282516|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_cb6a1b7cc51be7df|branch|f735188fd32176f6|8ffd0455e647df1a|e3af31abed045e90|533653422|data/forecast_anomalies/forecast_anomaly_2022-03-08.gz.parquet|t20047.6573431453s|464e661b77a25d8a|41350803|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_cb83c56f66d36cb7|branch|99df9cdbe1f88898|8ffd0455e647df1a|e3af31abed045e90|1290356861|data/forecast_anomalies/forecast_anomaly_2023-12-06.gz.parquet|t20047.6645106483s|4ead02378f935155|41389045|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_cb8afb52225dbf2f|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-940857296||t20049.2774023857s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_cc60e57847a07967|branch|006499f30c7c4503|8ffd0455e647df1a|e3af31abed045e90|1122151837|data/forecast_anomalies/forecast_anomaly_2024-10-07.gz.parquet|t20047.6679512889s|10054c5f3ef1a1ef|41459014|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_cc67600a1cbc5a9b|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-144740961||t20049.2773931353s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_cc73eea2b2a43f28|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1629629292||t20050.7616029314s||0|null|local|vector|forecasts_anomalies||0.313||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_cc74f54f5fc5c335|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1997600864||t20050.7617064993s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_ccc5af5fea8f5eca|branch|a562291217d68850|8ffd0455e647df1a|e3af31abed045e90|632094746|data/forecast_anomalies/forecast_anomaly_2017-12-20.gz.parquet|t20047.6374829325s|aaf0ef10ccc4580f|41330573|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_cce8d9105b214f36|branch|628dc48a901515eb|8ffd0455e647df1a|e3af31abed045e90|-412257904|data/forecast_anomalies/forecast_anomaly_2024-03-08.gz.parquet|t20047.6658103459s|522e0f8d0f7002ff|41337545|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_cd06dd74105988e8|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1717902766||t20049.2772263887s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_ce2e55bcf2920657|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1942959982||t20049.2775583452s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_cece6079105f599d|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-362937039||t20050.7619430629s||0|null|local|vector|forecasts_anomalies||0.229||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_cf1eaf0bd724623b|branch|8433fb19d1694e55|8ffd0455e647df1a|e3af31abed045e90|932946444|data/forecast_anomalies/forecast_anomaly_2019-03-15.gz.parquet|t20047.6428429233s|d35136cf0dd6f980|41318093|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_cf60c996a44ae15e|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-541998058||t20049.2773552281s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_cfa46357c5422e85|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-779206481||t20050.7615637825s||0|null|local|vector|forecasts_anomalies||0.237||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_cfa95e9198546970|branch|06ae1942d1695b3b|8ffd0455e647df1a|e3af31abed045e90|-1264441042|data/forecast_anomalies/forecast_anomaly_2019-08-23.gz.parquet|t20047.6447113995s|a1e34c79f729002a|41300990|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_d0390b12ffa5829b|branch|f725280d987df58f|8ffd0455e647df1a|e3af31abed045e90|-1691356186|data/forecast_anomalies/forecast_anomaly_2023-06-29.gz.parquet|t20047.6627404215s|57b73b9bab3e0925|41382251|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_d142aabb95c9ad93|branch|dc2447f4cfbb9f79|8ffd0455e647df1a|e3af31abed045e90|-107941760|data/forecast_anomalies/forecast_anomaly_2022-01-19.gz.parquet|t20047.6565965927s|d878bcf28bb24ea7|41300965|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_d1dcc04de8e19fcb|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1948105261||t20050.7616309746s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_d2343708b4801d42|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|85729250||t20050.7619847456s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_d331e2b6793d7155|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|929242628||t20049.2770660814s||0|null|local|vector|forecasts_anomalies||0.206||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_d3fbf1a69b6b26be|branch|1120e7462fb063dd|8ffd0455e647df1a|e3af31abed045e90|-632225608|data/forecast_anomalies/forecast_anomaly_2022-10-30.gz.parquet|t20047.6595490617s|78300259ced471b6|41380155|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_d47281ea8904481e|branch|36dc662f94783ea7|8ffd0455e647df1a|e3af31abed045e90|1689545400|data/forecast_anomalies/forecast_anomaly_2022-08-04.gz.parquet|t20047.6587553094s|561edd64db5b33a1|41249041|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_d4967cc55f0e94cf|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-746278426||t20050.7617769808s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_d4b03f2167d116cf|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1401889139||t20050.7617252622s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_d4f9a1cbe274cac9|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|873725093||t20049.2769948651s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_d533e65a430d190e|branch|a8bb86af3f9a8b4b|8ffd0455e647df1a|e3af31abed045e90|-1241459950|data/forecast_anomalies/forecast_anomaly_2020-07-30.gz.parquet|t20047.6492919283s|ee50c517ae316e6d|41346364|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_d6fa9ba18df4c1d7|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|2106580754||t20049.2770045074s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_d6fe282effbfe1f8|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1326080357||t20050.7618662258s||0|null|local|vector|forecasts_anomalies||0.274||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_d727bb243bfd9ea4|branch|4912a267d3427271|8ffd0455e647df1a|e3af31abed045e90|1475180731|data/forecast_anomalies/forecast_anomaly_2018-01-12.gz.parquet|t20047.6378760072s|668bc2c8caaa4c25|41318726|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_d7761fa68eb52f2e|branch|840231440f93db0d|8ffd0455e647df1a|e3af31abed045e90|963188174|data/forecast_anomalies/forecast_anomaly_2016-11-01.gz.parquet|t20047.6320209107s|9e6bd60552dc264d|41305708|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_d7ac9cee9d34ddfb|branch|c86b8fde6451a09d|8ffd0455e647df1a|e3af31abed045e90|-882505642|data/forecast_anomalies/forecast_anomaly_2019-09-19.gz.parquet|t20047.6453690985s|0db8e6232de3512a|41279770|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_d8e3ec83c4661fb8|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1238736592||t20049.2770422119s||0|null|local|vector|forecasts_anomalies||0.215||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_d9bd259e77fde9b7|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-115924689||t20049.2772028383s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_daa1680142861f17|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|2062040288||t20049.2775062164s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_daf107a6ef5c2e1a|branch|36be71b40c0d5ee7|8ffd0455e647df1a|e3af31abed045e90|1729804231|data/forecast_anomalies/forecast_anomaly_2017-10-18.gz.parquet|t20047.6362958293s|f4a2fc6d0b8c54bd|41328916|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_dafeca41b7224b6a|branch|b5e4980242e4ebcf|8ffd0455e647df1a|e3af31abed045e90|-1633211840|data/forecast_anomalies/forecast_anomaly_2015-04-14.gz.parquet|t20047.376503203s|d0c49f9b0e81f3d0|41327338|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_db9278e77e069871|branch|4444dbcb1b07ecc6|8ffd0455e647df1a|e3af31abed045e90|529853397|data/forecast_anomalies/forecast_anomaly_2021-04-01.gz.parquet|t20047.6530201662s|39af88dc1db67a04|41358167|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_dbaca4e11eb6f8c9|branch|a61c3ddaacdf842c|8ffd0455e647df1a|e3af31abed045e90|-1293975377|data/forecast_anomalies/forecast_anomaly_2014-05-23.gz.parquet|t20047.3727112346s|90c458446ea7b7c3|41402294|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_dbbf532b78f9ec5a|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|428817998||t20049.2770897066s||0|null|local|vector|forecasts_anomalies||0.189||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_dc3e4570d57266e9|branch|65aabb7a57ebbad4|8ffd0455e647df1a|e3af31abed045e90|1520915303|data/forecast_anomalies/forecast_anomaly_2018-09-16.gz.parquet|t20047.6405881201s|a673729490700068|41304958|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_dcee3b09142f0c1b|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|870986057||t20049.27704682s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_de30fd2af545f3a6|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1383149604||t20050.7618421478s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_de5abb6115e28248|branch|9c801ab05861da3c|8ffd0455e647df1a|e3af31abed045e90|-1283143672|data/forecast_anomalies/forecast_anomaly_2021-04-26.gz.parquet|t20047.6532390279s|2111c7226f822277|41397939|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_de72968a6ebde4db|branch|03d759c7a7e9421f|8ffd0455e647df1a|e3af31abed045e90|-659236243|data/forecast_anomalies/forecast_anomaly_2019-04-16.gz.parquet|t20047.6432854015s|3a9c2f793e707848|41337807|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_df7e969f3a854f98|branch|9f22d15b16c879ea|8ffd0455e647df1a|e3af31abed045e90|1799815697|data/forecast_anomalies/forecast_anomaly_2020-09-18.gz.parquet|t20047.6501369217s|933119ed8195aa1a|41362516|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_df7fe8b742d400da|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1418553319||t20049.2770137212s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_directory|stem|3b4562a08dc8ceff|3a659ad3d390f436|b4f5e9cdfa77e842|-470912529||t20047.862769339s|271db55f47f9100d|99|qs|local|vector|||0||
+forecasts_anomalies_e00833e61acd61f5|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-11205662||t20049.2774734446s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_e01ef5c3700b8ef1|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-651413354||t20050.7617490147s||0|null|local|vector|forecasts_anomalies||0.188||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_e19a33e7c565d36f|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-2110195941||t20050.7619987809s||0|null|local|vector|forecasts_anomalies||0.203||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_e3161d7cf75cb7bf|branch|cce8a2395851dee5|8ffd0455e647df1a|e3af31abed045e90|-1480205375|data/forecast_anomalies/forecast_anomaly_2018-11-23.gz.parquet|t20047.6412901961s|f1da0655c8d9309c|41389423|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_e3323324679a82ae|branch|3fd09eb0c2a3a8a1|8ffd0455e647df1a|e3af31abed045e90|-2084719425|data/forecast_anomalies/forecast_anomaly_2016-09-22.gz.parquet|t20047.63141815s|a88c4aa235a97fe8|41407983|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_e3ba407b53e6d634|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1042108404||t20050.7617582382s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_e45a9907d59db540|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-396089112||t20050.7618514365s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_e46800ff9ff97786|branch|e300a30395086ec9|8ffd0455e647df1a|e3af31abed045e90|-926792865|data/forecast_anomalies/forecast_anomaly_2017-04-18.gz.parquet|t20047.6339977632s|5b42549d57dfefc4|41402733|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_e4cff765511c5fff|branch|b9ce6b62d511e7f6|8ffd0455e647df1a|e3af31abed045e90|2011219914|data/forecast_anomalies/forecast_anomaly_2024-08-23.gz.parquet|t20047.6674519957s|d89c1fc2a9d2d92a|41457448|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_e4efa0d22235646e|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|949391272||t20050.7615731304s||0|null|local|vector|forecasts_anomalies||0.189||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_e52e780f9854e76d|branch|2459e2315090b242|8ffd0455e647df1a|e3af31abed045e90|1457095786|data/forecast_anomalies/forecast_anomaly_2023-03-30.gz.parquet|t20047.6614431026s|4fa819d23027ec79|41348581|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_e601208d17409b83|branch|6cfa44e4c7ab945d|8ffd0455e647df1a|e3af31abed045e90|-368542084|data/forecast_anomalies/forecast_anomaly_2023-11-21.gz.parquet|t20047.6641501814s|3df78352ddaca7f3|41381995|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_e66899057d899388|branch|0d28f28e42e9921f|8ffd0455e647df1a|e3af31abed045e90|-1217178471|data/forecast_anomalies/forecast_anomaly_2018-05-18.gz.parquet|t20047.6394926632s|09503d78a7223e0a|41344288|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_e6b2cd88cf9b30e1|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|764450057||t20049.277122402s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_e7383b711bb09d50|branch|e2a7fb776297cec3|8ffd0455e647df1a|e3af31abed045e90|-509567303|data/forecast_anomalies/forecast_anomaly_2019-11-19.gz.parquet|t20047.6462373642s|e00736971436a620|41382658|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_e9de8ae2fb9d4afa|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1638593950||t20050.76172069s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_e9ec48b9ee92f83c|branch|ca03a2b691496431|8ffd0455e647df1a|e3af31abed045e90|-1642962833|data/forecast_anomalies/forecast_anomaly_2023-05-24.gz.parquet|t20047.6623100509s|46e0f5b7703c21a0|41397602|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_ea5f9a5e691f39aa|branch|5f012c641b5e5f16|8ffd0455e647df1a|e3af31abed045e90|-1132413562|data/forecast_anomalies/forecast_anomaly_2021-02-21.gz.parquet|t20047.6521324338s|a045b53123c40c48|41348219|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_ea7388eddb8c48b2|branch|0bbc50e9b1fad797|8ffd0455e647df1a|e3af31abed045e90|-1230801936|data/forecast_anomalies/forecast_anomaly_2018-04-26.gz.parquet|t20047.6389996423s|bfc097d1eb5735df|41365924|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_eb3608ffb166e796|branch|0dbbf21f061b9858|8ffd0455e647df1a|e3af31abed045e90|1773617422|data/forecast_anomalies/forecast_anomaly_2022-08-02.gz.parquet|t20047.6586295343s|376d43f7054eb86d|41212820|file|local|vector|forecasts_anomalies||0.004||
+forecasts_anomalies_eb8ae245b510e128|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1322783143||t20049.277501651s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_edb4d6bfb33a0335|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1689382870||t20050.7618231695s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_ee8f690ff5659590|branch|39cc23e127ea63e1|8ffd0455e647df1a|e3af31abed045e90|1572883764|data/forecast_anomalies/forecast_anomaly_2022-04-14.gz.parquet|t20047.6576326107s|43122ca6d830abba|41330434|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_ef5a124793937f21|branch|7d4e24c5a326a1ed|8ffd0455e647df1a|e3af31abed045e90|-2138732324|data/forecast_anomalies/forecast_anomaly_2016-05-08.gz.parquet|t20047.3812005024s|cb73630a46b42932|41406487|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_ef77c1c0912e1f7a|branch|13953cec8b47bd3e|8ffd0455e647df1a|e3af31abed045e90|-220099343|data/forecast_anomalies/forecast_anomaly_2019-05-04.gz.parquet|t20047.6434269834s|a9df24a42b8af1dd|41382653|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_f0d35c6221ab7a1f|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|2067957975||t20050.7616494869s||0|null|local|vector|forecasts_anomalies||0.191||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_f0d953abe9bafd78|branch|19efef83386425e9|8ffd0455e647df1a|e3af31abed045e90|1713729620|data/forecast_anomalies/forecast_anomaly_2021-06-04.gz.parquet|t20047.6538907249s|846148d78d96fb1f|41371190|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_f0dcb8728083a38b|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-197341195||t20049.2771885749s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_f26ee46c84430db4|branch|cd4032192a0323be|8ffd0455e647df1a|e3af31abed045e90|-198645363|data/forecast_anomalies/forecast_anomaly_2022-02-01.gz.parquet|t20047.6570419113s|e833d68d0f3f6244|41352760|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_f276995a6b27270d|branch|c27cb85826609e32|8ffd0455e647df1a|e3af31abed045e90|-1461277475|data/forecast_anomalies/forecast_anomaly_2021-12-10.gz.parquet|t20047.6563682243s|ec023e329bba7370|41337814|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_f290af514083dd25|branch|8ef3ba84136e51f1|8ffd0455e647df1a|e3af31abed045e90|-751112114|data/forecast_anomalies/forecast_anomaly_2022-07-19.gz.parquet|t20047.6583108749s|519dd99343a91c58|41240640|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_f346fb955b2a9e20|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-163394620||t20050.7617113367s||0|null|local|vector|forecasts_anomalies||0.196||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_f44f0f244528eadb|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1265766996||t20050.7617952805s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_f479abb1f77b6614|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-243983137||t20049.2771982486s||0|null|local|vector|forecasts_anomalies||0.186||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_f508050dea713873|branch|15270173559e2e67|8ffd0455e647df1a|e3af31abed045e90|1643003620|data/forecast_anomalies/forecast_anomaly_2020-10-18.gz.parquet|t20047.6506008623s|456a168fa3e4e7c3|41413718|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_f518ca42458fc200|branch|5560aaa4f40ec654|8ffd0455e647df1a|e3af31abed045e90|-803379476|data/forecast_anomalies/forecast_anomaly_2022-04-16.gz.parquet|t20047.6574878739s|1fd86d50b17e1ffa|41307259|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_f52294be836e94c6|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|1532876535||t20049.2773695014s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_f5439580aae3e624|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-759006446||t20049.2770988618s||0|null|local|vector|forecasts_anomalies||0.182||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_f56550e8b8eb5b1f|branch|718c55ece3f6638d|8ffd0455e647df1a|e3af31abed045e90|-416462611|data/forecast_anomalies/forecast_anomaly_2024-04-16.gz.parquet|t20047.6660956041s|66618c8ec7b6f9f4|41341205|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_f57024a96a7f1c3c|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-897418034||t20050.761753592s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_f6c6a88d3ac21700|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-10734281||t20050.7616971683s||0|null|local|vector|forecasts_anomalies||0.187||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_f6ea4a35d971c112|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-109128105||t20050.7617303419s||0|null|local|vector|forecasts_anomalies||0.229||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_f6f1dd8e10fa9417|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-65423007||t20050.7617160206s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_f79328a31eb82fd0|branch|afebd5a41f3cb72c|8ffd0455e647df1a|e3af31abed045e90|101860892|data/forecast_anomalies/forecast_anomaly_2015-01-12.gz.parquet|t20047.375452872s|77c13b6c0f3e04ac|41235068|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_f7eef22c9fa0b5d1|branch|cc8380279d9d1296|8ffd0455e647df1a|e3af31abed045e90|1659485285|data/forecast_anomalies/forecast_anomaly_2015-04-15.gz.parquet|t20047.3767262256s|ec1df74a6023a535|41324309|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_f84654c4f40adf33|branch|e96a019a9c3f80ab|8ffd0455e647df1a|e3af31abed045e90|356398428|data/forecast_anomalies/forecast_anomaly_2021-03-27.gz.parquet|t20047.6525779511s|fde2be75f6c04f90|41359297|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_fa0b28f7cf8cb061|branch|5770862c4532ab1f|8ffd0455e647df1a|e3af31abed045e90|467921371|data/forecast_anomalies/forecast_anomaly_2021-10-06.gz.parquet|t20047.6554573135s|bf077ac77d81f320|41359545|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_fab2eb8253c7bb6e|branch|2e3f9d6390231d77|8ffd0455e647df1a|e3af31abed045e90|1322790612|data/forecast_anomalies/forecast_anomaly_2022-01-12.gz.parquet|t20047.6567489271s|3cf56a6667207141|41318725|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_fad28a26743130a9|branch|e916073032fbfd14|8ffd0455e647df1a|e3af31abed045e90|1456495969|data/forecast_anomalies/forecast_anomaly_2024-12-17.gz.parquet|t20047.6684430014s|14918be93deefaea|100061|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_faff4db82471f1df|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|-1192781569||t20049.2775784486s||0|null|local|vector|forecasts_anomalies||0.321||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_fb8c82f0de847083|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|1845604906||t20050.761767936s||0|null|local|vector|forecasts_anomalies||0.183||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_fba355fa6beffb72|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|464367539||t20049.2775486909s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_fbb68b9a0b487eda|branch|10e7e0b169c33a4f|8ffd0455e647df1a|e3af31abed045e90|-284324950|data/forecast_anomalies/forecast_anomaly_2017-02-07.gz.parquet|t20047.6334796986s|748a47c4896806f6|41373105|file|local|vector|forecasts_anomalies||0.003||
+forecasts_anomalies_fbd90379c7f500a2|branch|2a3b7f464021e179|8ffd0455e647df1a|e3af31abed045e90|2055014024|data/forecast_anomalies/forecast_anomaly_2019-08-24.gz.parquet|t20047.6449225057s|85937cd6199368c1|41311051|file|local|vector|forecasts_anomalies||0.002||
+forecasts_anomalies_fc10391f13591621|branch|error|8ffd0455e647df1a|e3ca85766d4509f4|2038531445||t20049.2772075579s||0|null|local|vector|forecasts_anomalies||0.184||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column doy doesnt exist.
+forecasts_anomalies_fcb96efd45cee56b|branch|error|8ffd0455e647df1a|7396e89b64c1aa00|-1291897830||t20050.7617396323s||0|null|local|vector|forecasts_anomalies||0.185||ℹ In index 1.Caused by error in column_select Cant select columns that dont exist. Column month doesnt exist.
+forecasts_anomalies_fe98e4811a54e0a5|branch|3adddcc98a11279a|8ffd0455e647df1a|e3af31abed045e90|1643072906|data/forecast_anomalies/forecast_anomaly_2018-10-03.gz.parquet|t20047.6411220968s|1b8be39d3c16a404|41357429|file|local|vector|forecasts_anomalies||0.003||
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+forecasts_anomalies_ff86391f764a6b02|branch|47bc960ff90a4cbb|8ffd0455e647df1a|e3af31abed045e90|-378303295|data/forecast_anomalies/forecast_anomaly_2022-11-12.gz.parquet|t20047.6597797248s|2023f9349b2a7883|41341817|file|local|vector|forecasts_anomalies||0.002||
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+weather_historical_means_AWS|stem|b09b8987c98d79b4|4c9c3c1564ff09ba|e139900d37730200|1497932096||t20050.761468614s|0f5cc5be67b9db73|64|qs|local|vector|||0.555||
+weather_historical_means_AWS_upload|stem|47667cc37bcc5050|29911a7f839673b8|d7d481581704851b|-224252342||t20049.2700147542s|e435a6b9e7e6ea9f|179|qs|local|vector|||524.028||
+weather_historical_means_directory|stem|39abf80a2113dc5f|a7e8497f8ecd7fed|b4f5e9cdfa77e842|1771912669||t20047.8634208437s|8781e7d3a4a21eb4|105|qs|local|vector|||0||
tar_get_error|function|3c106aa142d6c9a9
plot_targets|object|718ad17f619b9b2f
report_targets|object|718ad17f619b9b2f
download_modis_ndvi_delete|function|33709e5ea023c37c
create_data_directory|function|90b18168daa27c11
-download_sentinel_ndvi|function|a56efa4dcafa639f
transform_raster|function|0dc0c7d04248eec3
create_country_polygons|function|d55b8c17ed672bf5
-set_ecmwf_api_parameter|function|ee3123dfaf994abc
+set_ecmwf_api_parameter|function|7cf2e43e2e4aa743
calculate_weather_historical_means|function|ae3f281d755ccc1a
documentation_targets|object|0c4b888b73fc526f
get_sentinel_ndvi_api_parameters|function|8f738174cda16175
@@ -141,23 +2481,24 @@ aws_bucket|object|db87ce1c67408764
get_grib_metadata|function|3b1e629e6e50def5
get_remote_rasters|function|c2977b9d348c2ebe
AWS_get_folder|function|55fffed1bc2bedc5
-data_targets|object|e39302d448ab2828
-model_targets|object|51a53f769e95a912
+data_targets|object|73ede8dd38910a6b
+model_targets|object|2e25d39f7d9ec500
make_africa_outbreak_scale_map|function|a030e3c2c6822b5a
-.Random.seed|object|2aef93433d1d8e10
+.Random.seed|object|0e1bbd991bd73382
col_na|function|354cc7c01998e895
f|object|afac86fc13d4ff24
load_env|function|84cd5d62f5afa7ee
get_wahis_rvf_outbreaks_raw|function|65f46a23746e3e85
augment_data_old|function|06b3311d36ec63f5
+get_sentinel_ndvi_token|function|32daee882b8d80e8
plot_outbreak_history|function|7db76de203a74b84
-calculate_weather_anomalies|function|031d0aee356ffc04
+calculate_weather_anomalies|function|358d9e3de595a55e
submit_modis_ndvi_bundle_request|function|551657d0ffbc016f
download_modis_ndvi|function|1984481a2abc5759
get_wahis_rvf_controls_raw|function|cbfc96d406ecbac8
submit_modis_ndvi_task_request|function|25a7f129e52c207b
get_glw|function|e2b086b7b6fe8f72
-static_targets|object|ff31abdc2d81b81a
+static_targets|object|7464eec4ee6de2c1
deploy_targets|object|718ad17f619b9b2f
aws_s3_upload_single_type|function|1a54b513a98e58f9
update_env_key|function|3a01617a95158f19
@@ -174,21 +2515,20 @@ create_ndvi_date_lookup|function|711d97064d7ed0bd
get_glw_data|function|d7d08b8ceb1608e6
set_model_dates|function|7576c8b410b7d5ad
preprocess_wahis_rvf_controls|function|7abf6062954f84e6
-calculate_forecasts_anomalies|function|dd7f0ce2bf55b502
+calculate_forecasts_anomalies|function|0d7ab8b116ec8db8
preprocess_soil|function|7688e77bef098270
preprocess_nasa_weather|function|5d547c41ad4924d9
-AWS_put_files|function|e16cb1fe8d3926c3
-calculate_ndvi_anomalies|function|5228a151e9f54dec
-dynamic_targets|object|9805596353024d3b
+AWS_put_files|function|1511387f13a5426c
+calculate_ndvi_anomalies|function|d2bcb1deb82c8dbd
+dynamic_targets|object|2cd2a413e6440165
augment_data|function|9c3d1e9c896537cd
aggregate_augmented_data_by_adm|function|2315722e5d2c9d69
make_south_africa_outbreaks_timeline|function|d9a26b0369bd3c5f
-transform_sentinel_ndvi|function|efc5eb06378859b8
get_elevation_data|function|bb15959b7239e7f2
transform_nasa_weather|function|8b9806b579b46850
process_elevation|function|def403139e928bbd
get_slope_aspect|function|fbf92d48be249950
-transform_modis_ndvi|function|e441aa783b2dbeac
+transform_modis_ndvi|function|d82f25b73d8b8959
get_landcover_data|function|b9eb2daf28122f4c
get_bioclim_data|function|fdfc4dbadaf58fdf
preprocess_glw_data|function|8f29fef126869b9b
@@ -197,35 +2537,250 @@ delete_crashed_tasks|function|9a6ef925be530731
submit_modis_ndvi_task_request_continent|function|3b684dccca004f23
get_nasa_weather_coordinates|function|37d517f8f8c205a8
extract_grib_data|function|9eb6399488a626bf
+download_sentinel_ndvi|function|16a560f14900247b
get_outbreak_history_animation|function|b0d9c4448582c262
get_modis_ndvi_token|function|7f3f4a8f39aea32f
clear_ecwmf_tasks|function|39d98d3172c6f4ba
get_outbreak_history|function|0515c34f4109a803
-transform_ecmwf_forecasts|function|cb87363d0dc00e8b
-get_daily_outbreak_history|function|1f89894584987f78
-modis_ndvi_token|stem|6f22c640d6050289|c9651bea035be41f|d768f2be884267f9|-1215548249||t20047.8343924139s|d71cb223d0e1842f|169|qs|local|vector|||0.28||
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