PRJ3820-acc-tab-plot.Rmd

---
title: "PRJ3820-create-lit-rev-acc-smy"
output: html_document
date: "2023-09-27"
editor_options: 
  chunk_output_type: console
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```


```{r cars}

library(tidyverse)
library(readxl)
library(plotly)
library(pals)

root_dn = "C:/Users/McMillanAn/OneDrive - MWLR/Projects/PRJ3820-DOC-GNSS/"
plotdir = paste0(root_dn, "plots/")

# dpal = distinct_palette(n = 25, pal = "brewerPlus", add = "lightgrey")

c25 <- c(
  "dodgerblue2", "#E31A1C", # red
  "green4",
  "#6A3D9A", # purple
  "#FF7F00", # orange
  "black", "gold1",
  "skyblue2", "#FB9A99", # lt pink
  "palegreen2",
  "#CAB2D6", # lt purple
  "#FDBF6F", # lt orange
  "maroon", "orchid1", "deeppink1", "blue1", 
  "darkturquoise", "green1", "yellow4", "yellow3",
  "darkorange4", "brown"
)



c25_nm = alphabet()
c25_nm = polychrome()
# c25_nm = glasbey()
# c25_nm = kelly()
c25 = unname(c25_nm)


```

## read the excel file



```{r pressure, echo=FALSE}


dn = "C:/Users/McMillanAn/OneDrive - MWLR/Projects/PRJ3820-DOC-GNSS/Analysis/"
fn = "GNSS-Lit-Review.xlsx"
ffn = paste0(dn,fn)



AccTab_Data = readxl::read_excel(ffn, sheet = "Accuracy Table", "B1:U70")

# 
# Ref_color_key = readxl::read_excel(ffn, sheet = "Ref-color-key", "C2:G21")
# 
# AccTab_Data = AccTab_Data %>% 
#   left_join(Ref_color_key, by = 'Ref')

AccTab_Data_ffn = paste0(dn, "AccTab_Data.RDS" )
saveRDS(AccTab_Data, AccTab_Data_ffn)

```


read the binary version of the Accuracy Table data

```{r}

dn = "C:/Users/McMillanAn/OneDrive - MWLR/Projects/PRJ3820-DOC-GNSS/Analysis/"
AccTab_Data_ffn = paste0(dn, "AccTab_Data.RDS" )

AccTab_Data = readRDS(AccTab_Data_ffn)




AccTab_Data_mdf = AccTab_Data %>% 
  arrange(acc_avg) %>% 
  mutate(idx = 1:nrow(.)) %>% 
  select(idx, acc_avg, Ref,occ_tm = `Occupation time`, rec = `Receiver Make/Model`, col =  colhex, coldesc, edgecol) %>% 
  filter(!is.na(Ref))
  


```




# ~~~~~~~~~~~~~~~~ #
# Figure 1001 (FIG 5) - GNSS positioning accuracy plot
# ~~~~~~~~~~~~~~~~ #

```{r}

fignum = 1001
figdesc = "GNSS positioning accuracy plot"
figfmt = "png"
fig_ffn = paste0(plotdir, fignum,"-", figdesc, ".", figfmt)




# AccTab_Data_mdf$Ref = factor(AccTab_Data_mdf$Ref, levels = unique(AccTab_Data_mdf$Ref))
# AccTab_Data_mdf$Ref = factor(AccTab_Data_mdf$Ref, levels = unique(AccTab_Data_mdf$Ref))



saveRDS(Ref_color_key, paste0(datadir, 'RefColPal.RDS'))
Ref_color_key = readRDS(paste0(datadir, 'RefColPal.RDS'))




COLORS = Ref_color_key$colhex
COLORS_DESC = Ref_color_key$coldesc
EDGECOLORS = Ref_color_key$edgecol

levels(AccTab_Data_mdf$Ref)

COL_REF_TBL = data.frame(Ref = levels(AccTab_Data_mdf$Ref), COLORS = COLORS, COLORS_DESC = COLORS_DESC)

Refs_Unique = unique(AccTab_Data_mdf$Ref)

# AccTab_Data_mdf$Ref
# COLORS[9] = "#FFFFFF"
shapelist = c(rep(1:6,11),1:3)

g = ggplot(AccTab_Data_mdf) + geom_point(aes(acc_avg, idx, color = Ref,  size = occ_tm),  alpha=1) + scale_x_reverse()
g = g + labs(x = "horizontal accuracy (m)", y = "", size = "Occupation time [min]", color = "Reference")


# g = g + scale_color_manual(values = EDGECOLORS)  + scale_fill_manual(values = COLORS)

FULL_REF_COL_TBL = data.frame(Refs = as.character(Refs_Unique), Cols = COLORS) %>% as_tibble %>% dplyr::arrange(Refs)



# g = g + scale_fill_manual(values = COLORS, labels = Refs_Unique)  #+ scale_fill_manual(values = COLORS)
g = g + scale_color_manual(values = COLORS, labels = Refs_Unique)


g = g + lims(x = c(20, 0), y = c(0,60))
g = g + theme_minimal()
g = g + guides(color = guide_legend(override.aes = list(size=5), reverse=T))
# g = g + guides(color = 'none')
g = g + theme(axis.text.y = element_blank())

g


ggsave(filename = fig_ffn, plot = g, width = 16, height = 18, units = "cm", bg = "white")

# ggplotly(g)

```





# ~~~~~~~~~~~~~~~~ #
# Figure 1002 (FIG 6)- GNSS positioning accuracy plot
# ~~~~~~~~~~~~~~~~ #

```{r}

fignum = 1002
figdesc = "GNSS positioning accuracy plot - zoomin"
figfmt = "png"
fig_ffn = paste0(plotdir, fignum,"-", figdesc, ".", figfmt)


AccTab_Data_mdf2 = AccTab_Data_mdf %>% filter(acc_avg<20.0 & !is.na(occ_tm))

Remaining_Refs = unique(AccTab_Data_mdf2$Ref)

COL_REF_TBL_filt = COL_REF_TBL %>% filter(Ref %in% Remaining_Refs)

COLORS_filt = COL_REF_TBL_filt$COLORS

g = ggplot(AccTab_Data_mdf2, aes(acc_avg, idx, color = Ref, size = occ_tm)) + 
  geom_point(alpha=1) 
g

g = g + scale_x_reverse()

g = g + labs(x = "Horizontal accuracy (m)", y = "", size = "Occupation time (min)", color = "Receiver Type")
g = g + lims(x = c(2.0, 0), y = c(0,30))
g = g + geom_vline(aes(xintercept=1), linetype = "dashed")

# g = g + scale_fill_manual(values = COLORS, labels = Refs_Unique)  #+ scale_fill_manual(values = COLORS)
g = g + scale_color_manual(values = COLORS, labels = Refs_Unique)


g = g + theme_minimal()
g = g + guides(color = guide_legend(override.aes = list(size=5), reverse=T))
# g = g + guides(color = 'none')
g = g + theme(axis.text.y = element_blank(), legend.position = "right")
g


ggsave(filename = fig_ffn, plot = g, width = 16, height = 16, units = "cm", bg = "white")


```



# ~~~~~~~~~~~~~~~~ #
# Figure 1003 - GNSS positioning accuracy plot
# ~~~~~~~~~~~~~~~~ #

```{r}

fignum = 1003
figdesc = "GNSS positioning accuracy plot by ref - zoomin"
figfmt = "png"
fig_ffn = paste0(plotdir, fignum,"-", figdesc, ".", figfmt)


AccTab_Data_mdf2 = AccTab_Data_mdf %>% filter(acc_avg<2.0 & !is.na(occ_tm))


g = ggplot(AccTab_Data_mdf2, aes(acc_avg, idx, color = Ref, size = occ_tm)) + 
  geom_point(alpha=0.5) 
g

g = g + scale_x_reverse()

g = g + labs(x = "accuracy (RMSE)", y = "", size = "Occupation time (min)", color = "Reference")
g = g + lims(x = c(2.0, 0), y = c(0,30))
g = g + geom_vline(aes(xintercept=1), linetype = "dashed")
g = g + theme_minimal()
g = g + theme(axis.text.y = element_blank(), legend.position = "right")
g


ggsave(filename = fig_ffn, plot = g, width = 16, height = 16, units = "cm", bg = "white")

ggplotly(g)

```