results_table_complex.qmd

---
title: "Complex tasks results (tables)"
author:
  - name: Piotr Tompalski
    email: piotr.tompalski@nrcan-rncan.gc.ca
format: html
engine: knitr
lightbox: true
date: 08/15/2024
date-modified: today
---

## Complex task 1 - detailed results 

```{r, echo=FALSE, message=F, warning=F}
library(tidyverse)
library(gt)

D <- readRDS("complex1.rds")

DD <- D %>% 
  ungroup() %>% 
  select(tool, cores, density=density_points_rnd, processing_time, task_mode) %>%
   mutate(density_labels = fct_reorder(
    paste0("Density: ", round(density), " pts/m²"), density
  )) %>% 
  select(-density) %>%
  mutate(processing_time = hms::as_hms(as_datetime(seconds_to_period(round(as.numeric(processing_time))))))


DD <- DD %>% group_by(cores, density_labels) %>%
  # filter(task=="Normalization") %>%
  arrange(density_labels, cores) %>%
  mutate(min_proc_time=min(processing_time, na.rm=T)) %>%
  mutate(delta_proc_time = processing_time - min_proc_time,
         delta_proc_time_perc = round(as.numeric(delta_proc_time) / as.numeric(min_proc_time) * 100,1)) %>%
  select(-min_proc_time) %>%
  #replace 0 with NA
  mutate(across(contains("delta"), ~if_else(.x==0, NA, .x)))


theTable <- 
  DD %>%
  ungroup() %>%
  pivot_wider(names_from = c(tool, task_mode), values_from = c(processing_time, delta_proc_time, delta_proc_time_perc)) 


theTable <- 
  theTable %>% #arrange(density, cores) %>% 
  group_by(density_labels) %>%
  relocate(density_labels)  


theTable %>% 
  gt() %>%
  
  #merge columns related to processing time
  
  cols_merge(
    columns = c(processing_time_lasR_pipe, delta_proc_time_lasR_pipe, delta_proc_time_perc_lasR_pipe),
    pattern = "{1}<br><small><<+{2}s +{3}%>></small>"
  ) %>%
  
  
  cols_merge(
    columns = c(processing_time_lidR_sequential, delta_proc_time_lidR_sequential, delta_proc_time_perc_lidR_sequential),
    pattern = "{1}<br><small><<+{2}s +{3}%>></small>"
  ) %>%
  cols_merge(
    columns = c(processing_time_lasR_sequential, delta_proc_time_lasR_sequential, delta_proc_time_perc_lasR_sequential),
    pattern = "{1}<br><small><<+{2}s +{3}%>></small>"
  ) %>%
  cols_merge(
      columns = c(processing_time_lastools_sequential, delta_proc_time_lastools_sequential, delta_proc_time_perc_lastools_sequential),
    pattern = "{1}<br><small><<+{2}s +{3}%>></small>"
  ) %>%
  
  tab_spanner(
    label = "Processing time",
    columns = c(processing_time_lasR_pipe, processing_time_lidR_sequential, processing_time_lasR_sequential, processing_time_lastools_sequential)
  ) %>%
  cols_label(
    processing_time_lasR_pipe = "lasR (pipe)",
    processing_time_lidR_sequential = "lidR",
    processing_time_lasR_sequential = "lasR",
    processing_time_lastools_sequential = "lastools"
  )%>% 
  
  cols_align(
    align = "center",
    columns = everything()
  ) %>%
  
  cols_width(
    cores ~ pct(5),
    starts_with("processing_time_") ~ pct(20),
  
  ) %>%
  
  opt_stylize(style = 1,color = "gray", add_row_striping = F)


```