adjusted scripts to be more generalised
This commit is contained in:
Timon
parent
238520ff89
commit
66d6f80532
1
r_app/.gitignore
vendored
1
r_app/.gitignore
vendored
|
|
@ -16,4 +16,5 @@ renv
|
|||
.Rprofile
|
||||
# Ignore OSX files
|
||||
.DS_Store
|
||||
CI_report_dashboard_planet_files
|
||||
|
||||
|
|
|
|||
|
|
@ -11,7 +11,6 @@ library(lubridate)
|
|||
library(exactextractr)
|
||||
|
||||
library(CIprep)
|
||||
source(here("r_app", "parameters_project.R"))
|
||||
|
||||
# Vang alle command line argumenten op
|
||||
args <- commandArgs(trailingOnly = TRUE)
|
||||
|
|
@ -57,6 +56,8 @@ weekly_CI_mosaic <- here(laravel_storage_dir, "weekly_mosaic")
|
|||
daily_vrt <- here(data_dir, "vrt")
|
||||
harvest_dir <- here(data_dir, "HarvestData")
|
||||
|
||||
source(here("r_app", "parameters_project.R"))
|
||||
|
||||
dir.create(here(laravel_storage_dir))
|
||||
dir.create(here(data_dir))
|
||||
dir.create(here(extracted_CI_dir))
|
||||
|
|
@ -134,6 +135,12 @@ create_mask_and_crop <- function(file, field_boundaries) {
|
|||
|
||||
vrt_list <- list()
|
||||
|
||||
# for (file in raster_files) {
|
||||
# v_crop <- create_mask_and_crop(file, field_boundaries)
|
||||
# message(file, " processed")
|
||||
# gc()
|
||||
# }
|
||||
|
||||
for (file in filtered_files) {
|
||||
v_crop <- create_mask_and_crop(file, field_boundaries)
|
||||
emtpy_or_full <- global(v_crop, "notNA")
|
||||
|
|
@ -271,7 +278,7 @@ if (new_project_question == TRUE) {
|
|||
|
||||
pivot_stats <- extracted_values %>%
|
||||
map(readRDS) %>% list_rbind() %>%
|
||||
group_by(pivot_quadrant) %>%
|
||||
group_by(subField) %>%
|
||||
summarise(across(everything(), ~ first(na.omit(.))))
|
||||
|
||||
saveRDS(pivot_stats, here(cumulative_CI_vals_dir,"combined_CI_data.rds")) #used to save the rest of the data into one file
|
||||
|
|
@ -309,15 +316,15 @@ if (new_project_question == TRUE) {
|
|||
|
||||
# gather data into long format for easier calculation and visualisation
|
||||
pivot_stats_long <- pivot_stats2 %>%
|
||||
tidyr::gather("Date", value, -pivot_quadrant, -pivot ) %>%
|
||||
tidyr::gather("Date", value, -Field, -subField, -sub_area ) %>%
|
||||
mutate(Date = right(Date, 8),
|
||||
Date = lubridate::ymd(Date)
|
||||
) %>%
|
||||
drop_na(c("value","Date")) %>%
|
||||
mutate(value = as.numeric(value))%>%
|
||||
filter_all(all_vars(!is.infinite(.))) %>%
|
||||
rename(Field = pivot_quadrant,
|
||||
subField = Field) %>%
|
||||
# rename(Field = pivot_quadrant,
|
||||
# subField = Field) %>%
|
||||
unique()
|
||||
|
||||
|
||||
|
|
|
|||
File diff suppressed because one or more lines are too long
|
|
@ -1,27 +1,28 @@
|
|||
---
|
||||
# title: paste0("CI report week ", week, " - all pivots from ", last_tuesday, " to ", today)
|
||||
params:
|
||||
ref: word-styles-reference-var1.docx
|
||||
output_file: "CI_report.docx"
|
||||
ref: "word-styles-reference-var1.docx"
|
||||
output_file: CI_report.docx
|
||||
report_date: "2023-12-12"
|
||||
data_dir: "chemba"
|
||||
output:
|
||||
html_document:
|
||||
toc: yes
|
||||
df_print: paged
|
||||
word_document:
|
||||
reference_docx: !expr file.path("word-styles-reference-var1.docx")
|
||||
toc: true
|
||||
reference_docx: "file.path(\"word-styles-reference-var1.docx\")"
|
||||
toc: yes
|
||||
editor_options:
|
||||
chunk_output_type: console
|
||||
---
|
||||
|
||||
```{r setup, include=FALSE}
|
||||
#set de filename van de output
|
||||
knitr::opts_chunk$set(echo = TRUE)
|
||||
output_file <- params$output_file
|
||||
report_date <- params$report_date
|
||||
|
||||
|
||||
# Activeer de renv omgeving
|
||||
renv::activate()
|
||||
# knitr::opts_chunk$set(echo = TRUE)
|
||||
# output_file <- params$output_file
|
||||
# report_date <- params$report_date
|
||||
#
|
||||
#
|
||||
# # Activeer de renv omgeving
|
||||
# renv::activate()
|
||||
|
||||
# Optioneel: Herstel de omgeving als dat nodig is
|
||||
# Je kunt dit commentaar geven als je het normaal niet wilt uitvoeren
|
||||
|
|
@ -38,7 +39,7 @@ library(lubridate)
|
|||
library(exactextractr)
|
||||
library(zoo)
|
||||
library(raster)
|
||||
|
||||
library(terra)
|
||||
library(rsample)
|
||||
library(caret)
|
||||
library(randomForest)
|
||||
|
|
@ -49,15 +50,16 @@ library(CAST)
|
|||
```
|
||||
|
||||
```{r directories, message=FALSE, warning=FALSE, include=FALSE}
|
||||
laravel_storage_dir <- here("laravel_app/storage/app/",params$data_dir)
|
||||
project_dir <- "chemba"
|
||||
# laravel_storage_dir <- here("laravel_app/storage/app/",params$data_dir)
|
||||
laravel_storage_dir <- here("laravel_app/storage/app",project_dir)
|
||||
|
||||
data_dir_project <- here(laravel_storage_dir, "Data")
|
||||
# message('DATA_DIR',data_dir_project)
|
||||
extracted_CI_dir <- here(data_dir_project, "extracted_ci")
|
||||
data_dir <- here(laravel_storage_dir, "Data")
|
||||
# message('DATA_DIR',data_dir)
|
||||
extracted_CI_dir <- here(data_dir, "extracted_ci")
|
||||
daily_CI_vals_dir <- here(extracted_CI_dir, "daily_vals")
|
||||
cumulative_CI_vals_dir <- here(extracted_CI_dir, "cumulative_vals")
|
||||
harvest_dir <- here(data_dir_project, "HarvestData")
|
||||
harvest_dir <- here(data_dir, "HarvestData")
|
||||
|
||||
weekly_CI_mosaic <- here(laravel_storage_dir, "weekly_mosaic")
|
||||
|
||||
|
|
@ -69,6 +71,7 @@ source(here("r_app", "parameters_project.R"))
|
|||
```{r week, message=FALSE, warning=FALSE, include=FALSE}
|
||||
# week <- 5
|
||||
#today = "2023-12-12"
|
||||
report_date <- Sys.Date()
|
||||
today <- as.character(report_date)
|
||||
week <- week(today)
|
||||
|
||||
|
|
@ -138,11 +141,11 @@ AllPivots <- merge(AllPivots0, harvesting_data, by = c("Field", "subField")) #%>
|
|||
head(AllPivots)
|
||||
|
||||
AllPivots_merged <- AllPivots %>%
|
||||
group_by(Field) %>% summarise()
|
||||
group_by(Field) %>% summarise(sub_area = first(sub_area))
|
||||
|
||||
AllPivots_merged <- st_transform(AllPivots_merged, crs = proj4string(CI))
|
||||
|
||||
pivot_names <- unique(CI_quadrant$pivot)
|
||||
pivot_names <- unique(CI_quadrant$Field)
|
||||
|
||||
```
|
||||
|
||||
|
|
@ -228,7 +231,7 @@ create_CI_diff_map <- function(pivot_raster, pivot_shape, pivot_spans, show_lege
|
|||
}
|
||||
|
||||
ci_plot <- function(pivotName){
|
||||
# pivotName = "1.1"
|
||||
# pivotName = "AG1D06P"
|
||||
pivotShape <- AllPivots_merged %>% terra::subset(Field %in% pivotName) %>% st_transform(crs(CI))
|
||||
age <- AllPivots %>% dplyr::filter(Field %in% pivotName) %>% st_drop_geometry() %>% dplyr::select(Age) %>% unique()
|
||||
|
||||
|
|
@ -243,9 +246,9 @@ ci_plot <- function(pivotName){
|
|||
abs_CI_last_week <- last_week_dif_raster_abs %>% crop(., pivotShape) %>% mask(., pivotShape)
|
||||
abs_CI_three_week <- three_week_dif_raster_abs %>% crop(., pivotShape) %>% mask(., pivotShape)
|
||||
|
||||
planting_date <- pivots_dates %>% dplyr::filter(Field %in% pivotName) %>% ungroup() %>% dplyr::select(planting_date) %>% unique()
|
||||
planting_date <- harvesting_data %>% dplyr::filter(Field %in% pivotName) %>% ungroup() %>% dplyr::select(Season_start) %>% unique()
|
||||
|
||||
joined_spans2 <- joined_spans %>% st_transform(crs(pivotShape)) %>% dplyr::filter(Field %in% pivotName) %>% unique() %>% st_crop(., pivotShape)
|
||||
joined_spans2 <- joined_spans %>% st_transform(crs(pivotShape)) %>% dplyr::filter(Field %in% pivotName) #%>% unique() %>% st_crop(., pivotShape)
|
||||
|
||||
CImap_m2 <- create_CI_map(singlePivot_m2, AllPivots2, joined_spans2, show_legend= T, legend_is_portrait = T, week = week_minus_2, age = age -2)
|
||||
CImap_m1 <- create_CI_map(singlePivot_m1, AllPivots2, joined_spans2, show_legend= F, legend_is_portrait = F, week = week_minus_1, age = age -1)
|
||||
|
|
@ -270,7 +273,7 @@ ci_plot <- function(pivotName){
|
|||
|
||||
cum_ci_plot <- function(pivotName){
|
||||
|
||||
# pivotName = "1.17"
|
||||
# pivotName = "1.1"
|
||||
data_ci <- CI_quadrant %>% filter(Field == pivotName)
|
||||
data_ci2 <- data_ci %>% mutate(CI_rate = cumulative_CI/DOY,
|
||||
week = week(Date))%>% group_by(Field) %>%
|
||||
|
|
@ -371,10 +374,9 @@ tm_shape(CI, unit = "m")+
|
|||
|
||||
```
|
||||
|
||||
# Estate fields
|
||||
\newpage
|
||||
|
||||
```{r plots_ci_estate, echo=FALSE, fig.height=3.8, fig.width=10, message=FALSE, warning=FALSE, results='asis'}
|
||||
```{r plots_ci_estate, eval=FALSE, fig.height=3.8, fig.width=10, message=FALSE, warning=FALSE, include=FALSE, results='asis'}
|
||||
# # pivots <- AllPivots_merged %>% filter(pivot != c("1.1", "1.17"))
|
||||
pivots_estate <- AllPivots_merged %>% filter(pivot %in% c("1.1", "1.2", "1.3", "1.4", "1.6", "1.7", "1.8", "1.9", "1.10", "1.11", "1.12", "1.13", "1.14" , "1.16" , "1.17" , "1.18" , "6.1", "6.2", "DL1.1", "DL1.3")) %>% filter(pivot != "1.17")
|
||||
|
||||
|
|
@ -397,7 +399,7 @@ pivots_grouped <- AllPivots_merged %>%
|
|||
|
||||
# Iterate over each subgroup
|
||||
for (subgroup in unique(pivots_grouped$sub_area)) {
|
||||
cat("\n## Subgroup:", subgroup, "\n") # Add a title for the subgroup
|
||||
cat("\n# Subgroup: ", subgroup, "\n") # Add a title for the subgroup
|
||||
subset_data <- filter(pivots_grouped, sub_area == subgroup)
|
||||
walk(subset_data$Field, ~ {
|
||||
cat("\n") # Add an empty line for better spacing
|
||||
|
|
@ -457,15 +459,15 @@ ggplot(data= CI_all2%>% filter(season =="Data_2022"), aes(DOY, cumulative_CI, co
|
|||
```
|
||||
# Yield prediction
|
||||
The below table shows estimates of the biomass if you would harvest them now.
|
||||
```{r message=FALSE, warning=FALSE, include=FALSE}
|
||||
```{r eval=FALSE, message=FALSE, warning=FALSE, include=FALSE}
|
||||
CI_quadrant <- readRDS(here(cumulative_CI_vals_dir,"All_pivots_Cumulative_CI_quadrant_year_v2.rds")) %>%
|
||||
rename( pivot_quadrant = Field)#All_pivots_Cumulative_CI.rds
|
||||
ggplot(CI_quadrant %>% filter(pivot %in% "1.11")) +
|
||||
geom_line(aes(DOY, cumulative_CI, col = as.factor(season))) +
|
||||
facet_wrap(~pivot_quadrant)
|
||||
|
||||
pivots_dates0 <- readRDS(here(harvest_dir, "harvest_data_new")) %>% ungroup() %>% unique() %>%
|
||||
dplyr::select(pivot, pivot_quadrant, Tcha_2021, Tcha_2022 ) %>%
|
||||
pivots_dates0 <- pivots_dates0 %>% ungroup() %>% unique() %>%
|
||||
dplyr::select(Field, subField, Tcha_2021, Tcha_2022 ) %>%
|
||||
pivot_longer(cols = c("Tcha_2021", "Tcha_2022"), names_to = "Tcha_Year", values_to = "Tcha") %>%
|
||||
filter(Tcha > 50) %>%
|
||||
mutate(season = as.integer(str_extract(Tcha_Year, "\\d+")))
|
||||
|
|
@ -537,7 +539,7 @@ pred_rf_2023 <- predict(model_ffs_rf, newdata=prediction_2023) %>%
|
|||
|
||||
```
|
||||
|
||||
```{r yield_plaatjes, echo=FALSE}
|
||||
```{r yield_plaatjes, eval=FALSE, include=FALSE}
|
||||
ggplot(pred_ffs_rf, aes(y = predicted_Tcha , x = Tcha , col = pivot )) +
|
||||
geom_point() +geom_abline() +
|
||||
scale_x_continuous(limits = c(50, 160))+
|
||||
|
|
|
|||
Binary file not shown.
|
After Width: | Height: | Size: 136 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 161 KiB |
|
|
@ -6,8 +6,7 @@ if(project_dir == "chemba"){
|
|||
|
||||
|
||||
field_boundaries_sf <- st_read(here(data_dir, "pivot.geojson")) %>% dplyr::select(pivot, pivot_quadrant)%>%
|
||||
mutate(sub_area = case_when(pivot %in% c("1.1", "1.2", "1.3", "1.4", "1.6", "1.7", "1.8", "1.9", "1.10",
|
||||
"1.11", "1.12", "1.13", "1.14" , "1.16" , "1.17" , "1.18" , "6.1", "6.2", "DL1.1", "DL1.3") ~ "estate",
|
||||
mutate(sub_area = case_when(pivot %in% c("1.1", "1.2", "1.3", "1.4", "1.6", "1.7", "1.8", "1.9", "1.10", "1.11", "1.12", "1.13", "1.14" , "1.16" , "1.17" , "1.18" , "6.1", "6.2", "DL1.1", "DL1.3") ~ "estate",
|
||||
TRUE ~ "Cooperative"))
|
||||
names(field_boundaries_sf) <- c("Field", "subField", "geometry", "sub_area")
|
||||
|
||||
|
|
@ -16,7 +15,7 @@ if(project_dir == "chemba"){
|
|||
|
||||
# field_boundaries_merged <- st_read(here(data_dir, "pivot.geojson")) %>% dplyr::select(pivot, pivot_quadrant) %>% group_by(pivot) %>% summarise() %>% vect()
|
||||
|
||||
joined_spans <-st_read(here(data_dir_project, "span.geojson")) %>% st_transform(crs(field_boundaries_sf))
|
||||
joined_spans <-st_read(here(data_dir, "span.geojson")) %>% st_transform(crs(field_boundaries_sf))
|
||||
names(joined_spans) <- c("Field", "area", "radius", "spans", "span", "geometry")
|
||||
|
||||
|
||||
|
|
@ -27,14 +26,14 @@ if(project_dir == "chemba"){
|
|||
)
|
||||
|
||||
harvesting_data <- pivots_dates0 %>%
|
||||
dplyr::select(c("pivot_quadrant", "season_start_2021", "season_end_2021", "season_start_2022",
|
||||
dplyr::select(c("pivot_quadrant", "pivot", "season_start_2021", "season_end_2021", "season_start_2022",
|
||||
"season_end_2022", "season_start_2023", "season_end_2023", "season_start_2024", "season_end_2024", "Age")) %>%
|
||||
pivot_longer(cols = starts_with("season"), names_to = "Year", values_to = "value") %>%
|
||||
separate(Year, into = c("name", "Year"), sep = "(?<=season_start|season_end)\\_", remove = FALSE) %>%
|
||||
mutate(name = str_to_title(name)) %>%
|
||||
pivot_wider(names_from = name, values_from = value) %>%
|
||||
rename(subField = pivot_quadrant) %>%
|
||||
mutate(Field = substr(subField, 1, 3))
|
||||
rename(Field = pivot,
|
||||
subField = pivot_quadrant)
|
||||
|
||||
|
||||
|
||||
|
|
@ -46,11 +45,12 @@ if(project_dir == "chemba"){
|
|||
} else if (project_dir == "xinavane"){
|
||||
library(readxl)
|
||||
message("Yield data for Xinavane")
|
||||
field_boundaries_sf <- st_read(here(data_dir, "Xinavane_demo.geojson")) %>% dplyr::select(-Pivot)
|
||||
names(field_boundaries_sf) <- c("Field", "subField", "geometry")
|
||||
|
||||
field_boundaries <- st_read(here(data_dir, "Xinavane_demo.geojson")) %>% vect()
|
||||
field_boundaries_sf <- st_read(here(data_dir, "Xinavane_demo.geojson"))
|
||||
field_boundaries <- field_boundaries_sf %>% vect()
|
||||
|
||||
joined_spans <- field_boundaries
|
||||
joined_spans <- field_boundaries_sf %>% dplyr::select(Field)
|
||||
|
||||
pivots_dates0 <- read_excel(here(harvest_dir, "Yield data.xlsx"),
|
||||
skip = 3,
|
||||
|
|
@ -65,11 +65,11 @@ if(project_dir == "chemba"){
|
|||
tcha = 6,
|
||||
tchy = 7,
|
||||
Season_end = 8,
|
||||
age = 9,
|
||||
Age = 9,
|
||||
ratoon = 10
|
||||
) %>%
|
||||
mutate(Season_end = ymd(Season_end),
|
||||
Season_start = as.Date(Season_end - (duration(months = age))),
|
||||
Season_start = as.Date(Season_end - (duration(months = Age))),
|
||||
subField = Field) #don't forget to add 2022 as a year for the 'curent' season
|
||||
|
||||
pivots_dates0 <- pivots_dates0 %>%
|
||||
|
|
@ -84,7 +84,7 @@ if(project_dir == "chemba"){
|
|||
mutate(Season_start = Season_start + years(6))
|
||||
|
||||
|
||||
harvesting_data <- pivots_dates0 %>% select(c("Field","subField", "Year", "Season_start","Season_end", "Age" ))
|
||||
harvesting_data <- pivots_dates0 %>% dplyr::select(c("Field","subField", "Year", "Season_start","Season_end", "Age" , "sub_area", "tcha"))
|
||||
|
||||
|
||||
} else {
|
||||
|
|
|
|||
Loading…
Reference in a new issue