diff --git a/R/calc_outbreak_history.R b/R/calc_outbreak_history.R deleted file mode 100644 index 7fa4024..0000000 --- a/R/calc_outbreak_history.R +++ /dev/null @@ -1,230 +0,0 @@ - -# This is going to be dynamic branching over list of dates. Then a target to convert to raster stacks, one for parquet, and one for animation -get_daily_outbreak_history <- function(dates_df, - wahis_rvf_outbreaks_preprocessed, - continent_raster_template, - continent_polygon, - country_polygons, - output_dir = "data/outbreak_history_dataset", - output_filename = "outbreak_history.parquet", - beta_dist = .01, - beta_time = 0.5, - beta_cases = 1, - within_km = 500, - max_years = 10, - recent = 1/6) { - - # Create directory if it does not yet exist - dir.create(output_dir, recursive = TRUE, showWarnings = FALSE) - - daily_outbreak_history <- map_dfr(dates_df$date, function(date) calc_outbreak_history(date = date, - wahis_rvf_outbreaks_preprocessed, - continent_raster_template, - continent_polygon, - country_polygons, - beta_dist = .01, - beta_time = 0.5, - beta_cases = 1, - within_km = 500, - max_years = 10, - recent = 1/6)) - - daily_recent_outbreak_history <- terra::rast(daily_outbreak_history$recent_outbreaks_rast) - daily_old_outbreak_history <- terra::rast(daily_outbreak_history$old_outbreaks_rast) - - recent_output_filename <- paste0(output_dir, "/", tools::file_path_sans_ext(output_filename), "_recent_", dates_df$year[1], ".", tools::file_ext(output_filename)) - old_output_filename <- paste0(output_dir, "/", tools::file_path_sans_ext(output_filename), "_old_", dates_df$year[1], ".", tools::file_ext(output_filename)) - - if(grepl("\\.parquet", output_filename)) { - # Convert to dataframe - recent <- as.data.frame(daily_recent_outbreak_history, xy = TRUE) |> as_tibble() - arrow::write_parquet(recent, recent_output_filename, compression = "gzip", compression_level = 5) - terra::writeRaster(daily_recent_outbreak_history, filename = paste0(tools::file_path_sans_ext(recent_output_filename), ".tif"), overwrite=T, gdal=c("COMPRESS=LZW")) - - old <- as.data.frame(daily_old_outbreak_history, xy = TRUE) |> as_tibble() - arrow::write_parquet(old, old_output_filename, compression = "gzip", compression_level = 5) - terra::writeRaster(daily_old_outbreak_history, filename = paste0(tools::file_path_sans_ext(old_output_filename), ".tif"), overwrite=T, gdal=c("COMPRESS=LZW")) - - } else { - terra::writeRaster(daily_recent_outbreak_history, filename = paste0(tools::file_path_sans_ext(recent_output_filename), ".tif"), overwrite=T, gdal=c("COMPRESS=LZW")) - terra::writeRaster(daily_old_outbreak_history, filename = paste0(tools::file_path_sans_ext(old_output_filename), ".tif"), overwrite=T, gdal=c("COMPRESS=LZW")) - } - - c(recent_output_filename, old_output_filename) - -} - -# test <- get_daily_outbreak_history(dates = dates, -# wahis_rvf_outbreaks_preprocessed = wahis_rvf_outbreaks_preprocessed, -# continent_raster_template = continent_raster_template, -# continent_polygon = continent_polygon, -# country_polygons = country_polygons) -# -# get_outbreak_history_animation(daily_old_outbreak_history) - -#' Calculate the proximity in recent history and space of RVF outbreaks -#' -#' Two components: Within season (defined as in the current year), -#' and in previous season -#' -#' @param date The current date -#' @param season_cutoff_date -#' @param wahis_rvf_outbreaks_preprocessed -#' @param continent_raster_template -#' @return -#' @author 'Noam Ross and Nathan Layman' -#' @export -calc_outbreak_history <- function(date, - wahis_rvf_outbreaks_preprocessed, - continent_raster_template, - continent_polygon, - country_polygons, - beta_dist = .01, - beta_time = 0.5, - beta_cases = 1, - within_km = 500, - max_years = 10, - recent = 1/6) { # two months - - message(paste("Extracting outbreak history for", as.Date(date))) - # Identify time in years since outbreak. - # Establish a weighting factor that captures how recently the outbreak occurred tapering off exponentially - # A history of outbreaks can have either a interference effect (previous exposure leads to resistance) - # or amplifying effect (previous outbreaks ignite new ones nearby) - outbreak_history <- wahis_rvf_outbreaks_preprocessed |> - mutate(end_date = pmin(date, coalesce(outbreak_end_date, outbreak_start_date), na.rm = T), - years_since = as.numeric(as.duration(date - end_date), "years"), - weight = ifelse(is.na(cases) | cases == 1, 1, log10(cases + 1))*exp(-beta_time*years_since)) |> - filter(end_date <= date & years_since < max_years & years_since > 0) - - raster_template <- terra::unwrap(continent_raster_template) - raster_template[] <- 1 - raster_template <- terra::crop(raster_template, terra::vect(continent_polygon$geometry), mask = TRUE) - names(raster_template) <- as.Date(date) - - outbreak_history <- outbreak_history |> sf::st_as_sf(coords = c("longitude", "latitude"), crs = 4326) - - old_outbreaks <- outbreak_history |> filter(years_since >= recent) - recent_outbreaks <- outbreak_history |> filter(years_since < recent) - - recent_outbreak_rast <- get_outbreak_distance_weights(recent_outbreaks, raster_template, within_km) - old_outbreaks_rast <- get_outbreak_distance_weights(old_outbreaks, raster_template, within_km) - - # Integrate space and time - # Multiply the time weight by the distance weights - tibble(date = as.Date(date), - recent_outbreaks_rast = list(recent_outbreak_rast), - old_outbreaks_rast = list(old_outbreaks_rast)) - -} - - -get_outbreak_distance_weights <- function(outbreaks, raster_template, within_km = 500, beta_dist = 0.01) { - - if(!nrow(outbreaks)) { - raster_template[!is.na(raster_template)] <- 0 - return(raster_template) - } - - # Identify unique events - outbreaks <- outbreaks |> select(cases, years_since, weight) |> distinct() - - # raster <- crop(raster_template, outbreak_circles, mask = TRUE) - # raster <- terra::mask(raster_template, outbreak_circles, updatevalue = 0) - # For each pixel in the raster, calculate the most recent outbreak within `within_km` km - xy <- s2::as_s2_lnglat(terra::crds(raster_template)) - idx <- which(!is.nan(raster_template[])) - - #Get the unique outbreaks$geometry values while maintaining the sf object characteristics - - # We don't want unique LOCATIONS. We want unique outbreaks. An outbreak at a farm 6 months ago and another at the - # same place 12 months ago should both contribute to the weight. - # # Create an index for the unique values of outbreaks$geometry and a column of that index for each outbreak - # locations <- unique(outbreaks$geometry) - # attributes(locations) <- attributes(outbreaks$geometry) # Make into geometry set - # outbreaks$idx <- match(outbreaks$geometry, locations) - - xy_o <- s2::as_s2_lnglat(outbreaks) - - # For each pixel identify the outbreaks within `within_km` km - # matches <- s2::s2_dwithin_matrix(xy, xy_o, within_km * 1000) - # 883 origins (xy_o) x 133491 cells (xy) = 117872553 distances. - # but some of those distances cross the buffer. It's every cell to every origin. - # We don't need to calculate that just within the circles around each origin - # Also this doesn't connect to log cases at all. It's just a strict spatial - # distance weight at this point. - # s2::s2_distance_matrix units are in METERS - matches_dist <- s2::s2_distance_matrix(xy, xy_o) - - # Drop all distances greater than within_km - # Not sure why we need to do this given choice of beta_dist - # Enforcing prior? - matches_dist[matches_dist > (within_km * 1000)] <- NA - - # Calculate a weighting factor based on distance. Note we haven't included log10 cases yet. - # This is negative exponential decay - points closer to the origin will be 1 and those farther - # away will be closer to zero mediated by beta_dist. - weights <- exp(-beta_dist*matches_dist/1000) - - # Incorporate time and log10(cases + 1) - weights <- sweep(weights, 2, outbreaks$weight, "*") - - # Combine contributions from all outbreaks - weights <- rowSums(weights, na.rm = T) - - raster_template[idx] <- weights - - raster_template -} - -get_outbreak_history_animation <- function(input_files, - output_dir = "outputs", - output_filename = "outbreak_history_2007.gif", - layers = NULL, - title = NULL, - ...) { - - title <- paste(title, '{current_frame}') |> stringr::str_squish() - - # Create directory if it does not yet exist - dir.create(output_dir, recursive = TRUE, showWarnings = FALSE) - - # Change resolution to make it easier to make the gif - outbreak_raster <- terra::rast(input_files) - - # if(length(layers > 1)) outbreak_raster <- terra::subset(outbreak_raster, layers) - - df <- as.data.frame(outbreak_raster, xy=TRUE) - - df_long <- df %>% - pivot_longer(-c(x, y), names_to="date", values_to="value") |> - mutate(date = as.Date(date), - display_date = format(date, "%B %Y")) - - p <- ggplot(df_long, aes(x=x, y=y, fill=value)) + - geom_raster() + - scale_fill_viridis_c(limits=c(min(df_long$value, na.rm=T), - max(df_long$value, na.rm=T)), - trans = scales::sqrt_trans()) + - labs(title = title, x = "Longitude", y = "Latitude", fill = "Weight\n") + - theme_minimal() + - theme(text=element_text(size = 14), - legend.title = element_text(vjust = 0.05)) - - # I can't get anim_save to work on my mac. Switching to ImageMagick rather than bother fixing it - # gifs save and render fine but can't be opened once saved. I tried re-installing gifski - # on brew and building the package from source and nothing worked so I gave up. - gganim <- gganimate::animate(p + gganimate::transition_manual(frames = date), - fps = 10, - end_pause = 20, - wrap = F, - renderer = gganimate::magick_renderer()) - - # animate(anim, nframes = 400,fps = 8.1, width = 550, height = 350, - # renderer = gifski_renderer("car_companies_2.gif"), end_pause = 15, start_pause = 25) - - magick::image_write(gganim, path=paste(output_dir, output_filename, sep = "/")) - - return(output_filename) - - } diff --git a/R/get_outbreak_history.R b/R/get_outbreak_history.R new file mode 100644 index 0000000..e9d1dc0 --- /dev/null +++ b/R/get_outbreak_history.R @@ -0,0 +1,260 @@ + +# This is going to be dynamic branching over list of dates. Then a target to convert to raster stacks, one for parquet, and one for animation +get_daily_outbreak_history <- function(dates_df, + wahis_outbreaks, + wahis_distance_matrix, + wahis_raster_template, + output_dir = "data/outbreak_history_dataset", + output_filename = "outbreak_history.tif", + save_parquet = T, + beta_time = 0.5, + max_years = 10, + recent = 3/12) { + + if(!grepl("(tif|tiff|nc|asc)", tools::file_ext(output_filename))) stop("output_filename extension must be .tif, .tiff, .nc, or .asc!") + + # Create directory if it does not yet exist + dir.create(output_dir, recursive = TRUE, showWarnings = FALSE) + + wahis_raster_template <- terra::unwrap(wahis_raster_template) + + daily_outbreak_history <- map_dfr(dates_df$date, ~get_outbreak_history(date = .x, + wahis_outbreaks, + wahis_distance_matrix, + wahis_raster_template, + beta_time = beta_time, + max_years = max_years, + recent = recent)) + + daily_recent_outbreak_history <- terra::rast(daily_outbreak_history$recent_outbreaks_rast) + daily_old_outbreak_history <- terra::rast(daily_outbreak_history$old_outbreaks_rast) + + recent_output_filename <- paste0(output_dir, "/", tools::file_path_sans_ext(output_filename), "_recent_", dates_df$year[1], ".", tools::file_ext(output_filename)) + recent <- as.data.frame(daily_recent_outbreak_history, xy = TRUE) |> as_tibble() + arrow::write_parquet(recent, paste0(tools::file_path_sans_ext(recent_output_filename), ".parquet"), compression = "gzip", compression_level = 5) + terra::writeRaster(daily_recent_outbreak_history, filename = recent_output_filename, overwrite=T, gdal=c("COMPRESS=LZW")) + + old_output_filename <- paste0(output_dir, "/", tools::file_path_sans_ext(output_filename), "_old_", dates_df$year[1], ".", tools::file_ext(output_filename)) + old <- as.data.frame(daily_old_outbreak_history, xy = TRUE) |> as_tibble() + arrow::write_parquet(old, paste0(tools::file_path_sans_ext(old_output_filename), ".parquet"), compression = "gzip", compression_level = 5) + terra::writeRaster(daily_old_outbreak_history, filename = old_output_filename, overwrite=T, gdal=c("COMPRESS=LZW")) + + c(recent_output_filename, old_output_filename) + +} + +#' Get the outbreak history for a given day +#' +#' @param date +#' @param wahis_outbreaks +#' @param wahis_distance_matrix +#' @param wahis_raster_template +#' @param beta_time +#' @param max_years +#' @param recent +#' +#' @return +#' @export +#' +#' @examples +get_outbreak_history <- function(date, + wahis_outbreaks, + wahis_distance_matrix, + wahis_raster_template, + beta_time = 0.5, + max_years = 10, + recent = 1/6) { + + message(paste("Extracting outbreak history for", as.Date(date))) + + outbreak_history <- wahis_outbreaks |> + arrange(outbreak_id) |> + mutate(end_date = pmin(date, end_date, na.rm = T), + years_since = as.numeric(as.duration(date - end_date), "years")) |> + filter(date > end_date, years_since < max_years & years_since >= 0) |> + mutate(time_weight = ifelse(is.na(cases), 1, log10(cases + 1))*exp(-beta_time*years_since)) + + old_outbreaks <- outbreak_history |> filter(years_since >= recent) |> + combine_weights(wahis_distance_matrix, wahis_raster_template) |> setNames(as.Date(date)) + + recent_outbreaks <- outbreak_history |> filter(years_since < recent) |> + combine_weights(wahis_distance_matrix, wahis_raster_template) |> setNames(as.Date(date)) + + tibble(date = as.Date(date), + recent_outbreaks_rast = list(recent_outbreaks), + old_outbreaks_rast = list(old_outbreaks)) +} + +#' Combining time and distance weights. +#' Optimized for speed. +#' +#' @param outbreaks +#' @param wahis_distance_matrix +#' @param wahis_raster_template +#' +#' @return +#' @export +#' +#' @examples +combine_weights <- function(outbreaks, + wahis_distance_matrix, + wahis_raster_template) { + + if(!nrow(outbreaks)) { + wahis_raster_template[!is.na(wahis_raster_template)] <- 0 + return(wahis_raster_template) + } + # Multiply time weights by distance weights + + # Super fast matrix multiplication step. This is the secret sauce. + # Performs sweep(outbreaks$time_weight, "*") and rowsums() all in once go + # and indexes the wahis_distance_matrix (which was calculated only once) + # instead of re-calculating distances every day. These changes + # sped it up from needing 7 hours to calculate the daily history for + # 2010 to doing the same thing in 4.3 minutes. + weights <- wahis_distance_matrix[,outbreaks$outbreak_id] |> + as.matrix() |> Rfast::mat.mult(as.matrix(outbreaks$time_weight)) + + idx <- which(!is.nan(wahis_raster_template[])) + wahis_raster_template[idx] <- weights + + wahis_raster_template +} + +#' Calculate a matrix of spatial distance weights between every outbreak +#' and every cell in the raster template within a given distance +#' +#' @param wahis_outbreaks +#' @param wahis_raster_template +#' @param within_km +#' @param beta_dist +#' +#' @return +#' @export +#' +#' @examples +get_outbreak_distance_matrix <- function(wahis_outbreaks, wahis_raster_template, within_km = 500, beta_dist = 0.01) { + + wahis_raster_template <- wahis_raster_template |> terra::unwrap() + + xy <- as.data.frame(wahis_raster_template, xy = TRUE) |> select(y, x) |> rename(longitude = x, latitude = y) + + # For each outbreak origin identify the distance to every other point in Africa within `within_km` km + dist_mat <- geodist::geodist(xy, wahis_outbreaks |> arrange(outbreak_id), measure = "vincenty") # Good enough for our purposes and _much_ faster than s2 + + # Drop all distances greater than within_km + # Not sure why we need to do this given choice of beta_dist + dist_mat[dist_mat > (within_km * 1000)] <- NA + + # Calculate a weighting factor based on distance. Note we haven't included log10 cases yet. + # This is negative exponential decay - points closer to the origin will be 1 and those farther + # away will be closer to zero mediated by beta_dist. + dist_mat <- exp(-beta_dist*dist_mat/1000) + + # Facilitate matrix math later + dist_mat[is.na(dist_mat)] <- 0 + + dist_mat +} + +#' Animate a stacked SpatRaster file +#' +#' @param input_files +#' @param output_dir +#' @param output_filename +#' @param layers +#' @param title +#' @param ... +#' +#' @return +#' @export +#' +#' @examples +get_outbreak_history_animation <- function(input_file, + output_dir = "outputs", + num_cores = 1, + ...) { + + output_basename = tools::file_path_sans_ext(basename(input_file)) + output_filename = paste0(output_dir, "/", output_basename, ".gif") + + # Create temporary directory if it does not yet exist + tmp_dir <- paste(output_dir, output_basename, sep = "/") + dir.create(tmp_dir, recursive = TRUE, showWarnings = FALSE) + + message(paste("Animating", output_filename)) + + # Load the raster + outbreak_raster <- terra::rast(input_file) + + df <- as.data.frame(outbreak_raster, xy=TRUE) + + lims <- c(min(select(df, c(-x, -y)), na.rm=T), + max(select(df, c(-x, -y)), na.rm=T)) + + date_indices <- which(names(df) %in% setdiff(names(df), c("x", "y"))) + coordinates <- df |> select(x,y) + + title <- stringr::str_split(tools::file_path_sans_ext(basename(input_file)), "_")[[1]] |> + head(-1) |> paste(collapse = " ") |> + stringr::str_to_title() + + png_files <- parallel::mclapply(mc.cores = num_cores, + date_indices, + function(i) plot_outbreak_history(coordinates, + weights = df[,i], + date = names(df)[i], + tmp_dir = tmp_dir, + title = paste(title, names(df)[i]), + lims = lims)) |> + unlist() |> sort() + + # Add in a delay at end before looping back to beginning. This is in frames not seconds + png_files <- c(png_files, rep(png_files |> tail(1), 50)) + + # Render the animation + gif_file <- gifski::gifski(png_files, + delay = 0.04, + gif_file = output_filename) + + # Clean up temporary files + unlink(tmp_dir, recursive = T) + + # Return the location of the rendered animation + output_filename +} + +plot_outbreak_history <- function(coordinates, + weights, + date, + tmp_dir, + title = NULL, + lims = NULL) { + + filename <- paste0(tmp_dir, "/", date, ".png") + + p <- ggplot(coordinates |> mutate(value = weights), aes(x=x, y=y, fill=value)) + + geom_raster() + + scale_fill_viridis_c(limits = lims, + trans = scales::sqrt_trans()) + + labs(title = title, x = "Longitude", y = "Latitude", fill = "Weight\n") + + theme_minimal() + + theme(text=element_text(size = 18), + legend.title = element_text(vjust = 0.05)) + + if(!is.null(filename)) { + png(filename = filename, width = 600, height = 600) + print(p) + dev.off() + return(filename) + } + + p +} + +# test <- get_daily_outbreak_history(dates = dates, +# wahis_rvf_outbreaks_preprocessed = wahis_rvf_outbreaks_preprocessed, +# continent_raster_template = continent_raster_template, +# continent_polygon = continent_polygon) +# +# get_outbreak_history_animation(daily_old_outbreak_history) \ No newline at end of file diff --git a/_targets.R b/_targets.R index 100851f..19ac3a1 100644 --- a/_targets.R +++ b/_targets.R @@ -151,29 +151,40 @@ dynamic_targets <- tar_plan( tar_group(), iteration = "group"), - # Map over year batch over day otherwise too many branches. + tar_target(wahis_outbreaks, wahis_rvf_outbreaks_preprocessed |> + mutate(end_date = coalesce(outbreak_end_date, outbreak_start_date), na.rm = T) |> + select(cases, end_date, latitude, longitude) |> + distinct() |> + arrange(end_date) |> + mutate(outbreak_id = 1:n())), + + tar_target(wahis_raster_template, terra::rast(terra::ext(continent_polygon), resolution = 0.1, vals = 1) |> + terra::crop(terra::vect(continent_polygon$geometry), mask = TRUE) |> + terra::wrap()), + + tar_target(wahis_distance_matrix, get_outbreak_distance_matrix(wahis_outbreaks, wahis_raster_template)), + + # 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, - wahis_rvf_outbreaks_preprocessed, - continent_raster_template, - continent_polygon, - country_polygons), - head(wahis_outbreak_dates, 1), + wahis_outbreaks, + wahis_distance_matrix, + wahis_raster_template, + output_dir = "data/outbreak_history_dataset", + output_filename = "outbreak_history.tif", + save_parquet = T, + beta_time = 0.5, + max_years = 10, + recent = 3/12), + map(wahis_outbreak_dates), iteration = "vector", format = "file", repository = "local"), - tar_target(wahis_outbreak_history_recent_animation, get_outbreak_history_animation(input_files = c("data/outbreak_history_dataset/outbreak_history_recent_2007.tif"), - output_dir = "outputs", - output_filename = "outbreak_history_recent_2007.gif", - title = "Recent Outbreak History", - wahis_outbreak_history)), # Just included to enforce dependency with wahis_outbreak_history + # Takes raster files and makes animations from the layers + tar_target(wahis_outbreak_history_animations, map(wahis_outbreak_history, ~get_outbreak_history_animation(input_file = .x, + output_dir = "outputs")), + pattern = map(wahis_outbreak_history)), # Just included to enforce dependency with wahis_outbreak_history - tar_target(wahis_outbreak_history_old_animation, get_outbreak_history_animation(input_files = c("data/outbreak_history_dataset/outbreak_history_old_2007.tif"), - output_dir = "outputs", - output_filename = "outbreak_history_old_2007.gif", - title = "Old Outbreak History", - wahis_outbreak_history)), # Just included to enforce dependency with wahis_outbreak_history - # SENTINEL NDVI ----------------------------------------------------------- # 2018-present # 10 day period diff --git a/_targets/meta/meta b/_targets/meta/meta index b0c579f..a899241 100644 --- a/_targets/meta/meta +++ b/_targets/meta/meta @@ -1,5 +1,5 @@ name|type|data|command|depend|seed|path|time|size|bytes|format|repository|iteration|parent|children|seconds|warnings|error -.Random.seed|object|214b22db05576363||||||||||||||| +.Random.seed|object|671ac217838e7e4b||||||||||||||| aggregate_augmented_data_by_adm|function|0ba2d0669462f71c||||||||||||||| aggregated_data_rsa|pattern|6dbb43f34bc42ac8|ea0a3280c45817ae||-1696630435||||137860|qs|aws|vector||aggregated_data_rsa_94f732f8*aggregated_data_rsa_5e501efa*aggregated_data_rsa_34327510*aggregated_data_rsa_40e9884c*aggregated_data_rsa_5ababfa3|288.617|| aggregated_data_rsa_34327510|branch|c1e4fd089c317f41|ea0a3280c45817ae|1b56fcad8b0f2922|1726064958|bucket=open-rvfcast-data*region=us-east-1*key=_targets/aggregated_data_rsa_34327510*endpoint=TlVMTA*version=|t19755.8889066061s||27572|qs|aws|vector|aggregated_data_rsa||56.413|| @@ -446,13 +446,14 @@ aws_s3_upload_single_type|function|6d277b68ccbb67a2||||||||||||||| bioclim_preprocessed|stem|1b1a48600ccae883|5f41665e5cc07c28|f18aeee5346c4b65|1289283391|data/bioclim_dataset/bioclim.parquet|t19926.8606447956s|70d824b00d5241b0|24881359|file|local|vector|||60.777|| cache_aws_branched_target|function|6e2abfa4969de1bf||||||||||||||| calc_daily_outbreak_history|function|b822309d11aabbee||||||||||||||| -calc_outbreak_history|function|7d453979a781a661||||||||||||||| +calc_outbreak_history|function|c05b557590001c12||||||||||||||| calculate_forecasts_anomalies|function|e79c27516696d72f||||||||||||||| calculate_ndvi_anomalies|function|fa9de87422ce7598||||||||||||||| calculate_ndvi_historical_means|function|62d8a66e5ef237be||||||||||||||| calculate_weather_anomalies|function|d0c9f646d334634b||||||||||||||| calculate_weather_historical_means|function|ac8b9ff61133bd68||||||||||||||| col_na|function|81bde41e453c6fa2||||||||||||||| 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0000000..2996b3f Binary files /dev/null and b/outputs/outbreak_history_recent_2023.gif differ diff --git a/outputs/outbreak_history_recent_2024.gif b/outputs/outbreak_history_recent_2024.gif new file mode 100644 index 0000000..2b0ee75 Binary files /dev/null and b/outputs/outbreak_history_recent_2024.gif differ diff --git a/packages.R b/packages.R index 575ae49..14b4903 100644 --- a/packages.R +++ b/packages.R @@ -20,5 +20,4 @@ library(arrow) library(visNetwork) library(rstac) library(rnaturalearth) -library(rnaturalearthhires) -library(containerTemplateUtils) \ No newline at end of file +library(rnaturalearthhires) \ No newline at end of file diff --git a/renv.lock b/renv.lock index 104fe10..8160465 100644 --- a/renv.lock +++ b/renv.lock @@ -128,6 +128,20 @@ ], "Hash": "ae6cbbe1492f4de79c45fce06f967ce8" }, + "RcppArmadillo": { + "Package": "RcppArmadillo", + "Version": "14.0.0-1", + "Source": "Repository", + "Repository": "RSPM", + "Requirements": [ + "R", + "Rcpp", + "methods", + "stats", + "utils" + ], + "Hash": "a711769be34214addf7805278b72d56b" + }, "RcppEigen": { "Package": "RcppEigen", "Version": "0.3.3.9.3", @@ -142,6 +156,17 @@ ], "Hash": "1e035db628cefb315c571202d70202fe" }, + "RcppGSL": { + "Package": "RcppGSL", + "Version": "0.3.13", + "Source": "Repository", + "Repository": "RSPM", + "Requirements": [ + "Rcpp", + "stats" + ], + "Hash": "e8fc7310d256a7b6c4de8e57ab76c55d" + }, "RcppParallel": { "Package": "RcppParallel", "Version": "5.1.7", @@ -152,6 +177,36 @@ ], "Hash": "a45594a00f5dbb073d5ec9f48592a08a" }, + "RcppZiggurat": { + "Package": "RcppZiggurat", + "Version": "0.1.6", + "Source": "Repository", + "Repository": "RSPM", + "Requirements": [ + "R", + "Rcpp", + "RcppGSL", + "graphics", + "parallel", + "stats", + "utils" + ], + "Hash": "75b4a36aeeed440ad03b996081190703" + }, + "Rfast": { + "Package": "Rfast", + "Version": "2.1.0", + "Source": "Repository", + "Repository": "CRAN", + "Requirements": [ + "R", + "Rcpp", + "RcppArmadillo", + "RcppParallel", + "RcppZiggurat" + ], + "Hash": "79e8394e1fa06a4ae954b70ca9b16e8f" + }, "archive": { "Package": "archive", "Version": "1.1.8", @@ -968,6 +1023,13 @@ ], "Hash": "4d43570de08ab49ba86bb2ccb6fe117d" }, + "geodist": { + "Package": "geodist", + "Version": "0.1.0", + "Source": "Repository", + "Repository": "RSPM", + "Hash": "44be46e0ab530e07869976da2e85490d" + }, "gert": { "Package": "gert", "Version": "2.0.0", @@ -1005,29 +1067,6 @@ ], "Hash": "ceb49d19444b9b3acfce8ee34e23e2f5" }, - "gganimate": { - "Package": "gganimate", - "Version": "1.0.9", - "Source": "Repository", - "Repository": "RSPM", - "Requirements": [ - "cli", - "ggplot2", - "glue", - "grDevices", - "grid", - "lifecycle", - "progress", - "rlang", - "scales", - "stringi", - "transformr", - "tweenr", - "utils", - "vctrs" - ], - "Hash": "c6e8a7ff1b78529309cb2186ec1e3d38" - }, "ggforce": { "Package": "ggforce", "Version": "0.4.1", @@ -1114,6 +1153,13 @@ ], "Hash": "03533b1c875028233598f848fda44c4c" }, + "gifski": { + "Package": "gifski", + "Version": "1.12.0-2", + "Source": "Repository", + "Repository": "RSPM", + "Hash": "94ea43ec9e47684c20810e9272605425" + }, "gitcreds": { "Package": "gitcreds", "Version": "0.1.2", @@ -1560,13 +1606,6 @@ ], "Hash": "4fbd3679ec8ee169ba28d4b1ea7d0e8f" }, - "lpSolve": { - "Package": "lpSolve", - "Version": "5.6.20", - "Source": "Repository", - "Repository": "RSPM", - "Hash": "2801c8082e89ed84cc0dbe43de850d31" - }, "lubridate": { "Package": "lubridate", "Version": "1.9.2", @@ -1580,18 +1619,6 @@ ], "Hash": "e25f18436e3efd42c7c590a1c4c15390" }, - "magick": { - "Package": "magick", - "Version": "2.8.4", - "Source": "Repository", - "Repository": "RSPM", - "Requirements": [ - "Rcpp", - "curl", - "magrittr" - ], - "Hash": "63adf42f6fa0fca09999a328e1ae8204" - }, "magrittr": { "Package": "magrittr", "Version": "2.0.3", @@ -2728,21 +2755,6 @@ ], "Hash": "5ac22900ae0f386e54f1c307eca7d843" }, - "transformr": { - "Package": "transformr", - "Version": "0.1.5", - "Source": "Repository", - "Repository": "RSPM", - "Requirements": [ - "cpp11", - "lpSolve", - "rlang", - "sf", - "tweenr", - "vctrs" - ], - "Hash": "584eda9966ed571b3adc75e338116147" - }, "triebeard": { "Package": "triebeard", "Version": "0.4.1",