145 lines
6.7 KiB
R
145 lines
6.7 KiB
R
subchunkify <- function(g, fig_height=7, fig_width=5) {
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g_deparsed <- paste0(deparse(
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function() {g}
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), collapse = '')
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sub_chunk <- paste0("
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`","``{r sub_chunk_", floor(runif(1) * 10000), ", fig.height=", fig_height, ", fig.width=", fig_width, ", echo=FALSE}",
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"\n(",
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g_deparsed
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, ")()",
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"\n`","``
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")
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cat(knitr::knit(text = knitr::knit_expand(text = sub_chunk), quiet = TRUE))
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}
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create_CI_map <- function(pivot_raster, pivot_shape, pivot_spans, show_legend = F, legend_is_portrait = F, week, age, borders = FALSE){
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map <- tm_shape(pivot_raster, unit = "m") +
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tm_raster(breaks = c(0,0.5,1,2,3,4,5,6,7,Inf), palette = "RdYlGn",legend.is.portrait = legend_is_portrait ,midpoint = NA) +
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tm_layout(main.title = paste0("\nMax CI week ", week,"\n", age, " weeks old"),
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main.title.size = 0.7, legend.show = show_legend)
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if (borders) {
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map <- map +
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tm_shape(pivot_shape) +
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tm_borders(lwd = 3) +
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tm_text("sub_field", size = 1/2) +
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tm_shape(pivot_spans) +
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tm_borders(lwd = 0.5, alpha = 0.5)
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}
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return(map)
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}
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create_CI_diff_map <- function(pivot_raster, pivot_shape, pivot_spans, show_legend = F, legend_is_portrait = F, week_1, week_2, age, borders = TRUE){
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map <- tm_shape(pivot_raster, unit = "m") +
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tm_raster(breaks = c(-3,-2,-1,0,1,2,3), palette = "RdYlGn",legend.is.portrait = legend_is_portrait, midpoint = 0, title = "CI difference") +
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tm_layout(main.title = paste0("CI change week ", week_1, " - week ", week_2, "\n", age, " weeks old"),
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main.title.size = 0.7, legend.show = show_legend)
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if (borders) {
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map <- map +
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tm_shape(pivot_shape) +
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tm_borders(lwd = 3) +
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tm_text("sub_field", size = 1/2) +
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tm_shape(pivot_spans) +
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tm_borders(lwd = 0.5, alpha = 0.5)
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}
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return(map)
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}
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ci_plot <- function(pivotName){
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# pivotName = "1.1"
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pivotShape <- AllPivots0 %>% terra::subset(field %in% pivotName) %>% st_transform(crs(CI))
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age <- harvesting_data %>% dplyr::filter(field %in% pivotName) %>% sort("year") %>% tail(., 1) %>% dplyr::select(age) %>% unique() %>% pull() %>% round()
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AllPivots2 <- AllPivots0 %>% dplyr::filter(field %in% pivotName)
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singlePivot <- CI %>% crop(., pivotShape) %>% mask(., pivotShape)
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singlePivot_m1 <- CI_m1 %>% crop(., pivotShape) %>% mask(., pivotShape)
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singlePivot_m2 <- CI_m2 %>% crop(., pivotShape) %>% mask(., pivotShape)
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# singlePivot_m3 <- CI_m3 %>% crop(., pivotShape) %>% mask(., pivotShape)
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abs_CI_last_week <- last_week_dif_raster_abs %>% crop(., pivotShape) %>% mask(., pivotShape)
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abs_CI_three_week <- three_week_dif_raster_abs %>% crop(., pivotShape) %>% mask(., pivotShape)
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planting_date <- harvesting_data %>% dplyr::filter(field %in% pivotName) %>% ungroup() %>% dplyr::select(season_start) %>% unique()
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joined_spans2 <- AllPivots0 %>% st_transform(crs(pivotShape)) %>% dplyr::filter(field %in% pivotName) #%>% unique() %>% st_crop(., pivotShape)
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CImap_m2 <- create_CI_map(singlePivot_m2, AllPivots2, joined_spans2, show_legend= T, legend_is_portrait = T, week = week_minus_2, age = age -2, borders = borders)
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CImap_m1 <- create_CI_map(singlePivot_m1, AllPivots2, joined_spans2, show_legend= F, legend_is_portrait = F, week = week_minus_1, age = age -1, borders = borders)
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CImap <- create_CI_map(singlePivot, AllPivots2, joined_spans2, show_legend= F, legend_is_portrait = F, week = week, age = age, borders = borders)
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CI_max_abs_last_week <- create_CI_diff_map(abs_CI_last_week,AllPivots2, joined_spans2, show_legend = T, legend_is_portrait = T, week_1 = week, week_2 = week_minus_1, age = age, borders = borders)
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CI_max_abs_three_week <- create_CI_diff_map(abs_CI_three_week, AllPivots2, joined_spans2, show_legend = T, legend_is_portrait = T, week_1 = week, week_2 = week_minus_3, age = age, borders = borders)
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tst <- tmap_arrange(CImap_m2, CImap_m1, CImap,CI_max_abs_last_week, CI_max_abs_three_week, nrow = 1)
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cat(paste("## Field", pivotName, "-", age, "weeks after planting/harvest", "\n"))
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# cat("\n")
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# cat('<h2> Pivot', pivotName, '- week', week, '-', age$Age, 'weeks after planting/harvest <h2>')
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# cat(paste("# Pivot",pivots$pivot[i],"\n"))
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print(tst)
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}
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cum_ci_plot <- function(pivotName){
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# pivotName = "1.1"
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data_ci <- CI_quadrant %>% filter(field == pivotName)
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if (nrow(data_ci) == 0) {
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return(cum_ci_plot2(pivotName)) # Return an empty data frame if no data is found
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}
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data_ci2 <- data_ci %>% mutate(CI_rate = cumulative_CI/DOY,
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week = week(Date))%>% group_by(field) %>%
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mutate(mean_rolling10 = rollapplyr(CI_rate , width = 10, FUN = mean, partial = TRUE))
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date_preperation_perfect_pivot <- data_ci2 %>% group_by(season) %>% summarise(min_date = min(Date),
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max_date = max(Date),
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days = max_date - min_date)
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unique_seasons <- unique(date_preperation_perfect_pivot$season)
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g <- ggplot(data= data_ci2 %>% filter(season %in% unique_seasons)) +
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facet_wrap(~season, scales = "free_x") +
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geom_line( aes(Date, mean_rolling10, col = sub_field, group = sub_field)) +
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labs(title = paste("14 day rolling MEAN CI rate - Pivot ", pivotName),
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color = "Field name")+
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scale_x_date(date_breaks = "1 month", date_labels = "%m-%Y") +
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theme_minimal() +
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theme(axis.text.x = element_text(angle = 60, hjust = 1),
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legend.justification=c(1,0), legend.position = c(1, 0),
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legend.title = element_text(size = 8),
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legend.text = element_text(size = 8)) +
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guides(color = guide_legend(nrow = 2, byrow = TRUE))
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subchunkify(g, 3.2, 10)
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}
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cum_ci_plot2 <- function(pivotName){
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end_date <- Sys.Date()
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start_date <- end_date %m-% months(11) # 11 months ago from end_date
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date_seq <- seq.Date(from = start_date, to = end_date, by = "month")
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midpoint_date <- start_date + (end_date - start_date) / 2
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g <- ggplot() +
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scale_x_date(limits = c(start_date, end_date), date_breaks = "1 month", date_labels = "%m-%Y") +
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scale_y_continuous(limits = c(0, 4)) +
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labs(title = paste("14 day rolling MEAN CI rate - Field ", pivotName),
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x = "Date", y = "CI Rate") +
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theme(axis.text.x = element_text(angle = 60, hjust = 1),
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legend.justification = c(1, 0), legend.position = c(1, 0),
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legend.title = element_text(size = 8),
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legend.text = element_text(size = 8)) +
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annotate("text", x = midpoint_date, y = 2, label = "No data available", size = 6, hjust = 0.5)
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subchunkify(g, 3.2, 10)
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} |