## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(warning = FALSE,
message = FALSE,
fig.pos = "!H",
echo = TRUE,
eval = TRUE) # this vignette by default does not evaluate the code snippets
## -----------------------------------------------------------------------------
pkgs = c('IceSat2R', 'sf', 'mapview', 'data.table', 'stargazer', 'glue', 'utils',
'reshape2', 'plotly', 'magrittr', 'geodist', 'CopernicusDEM', 'terra')
load_pkgs = lapply(pkgs, require, character.only = TRUE) # load required R packages
sf::sf_use_s2(use_s2 = FALSE) # disable 's2' in this vignette
mapview::mapviewOptions(leafletHeight = '600px',
leafletWidth = '700px') # applies to all leaflet maps
## ----echo = F-----------------------------------------------------------------
#.........................................................................................
# For reproducibility purposes save only the 'date' and 'RGT' matches of winter and summer
#.........................................................................................
# data.table::fwrite(x = rgts_ws, file = system.file('data_files', 'vignette_data', 'winter_summer_inters.csv', package = "IceSat2R"), row.names = F)
## ----echo = FALSE-------------------------------------------------------------
subs_join_s = readRDS(file = system.file('data_files', 'vignette_data', 'Greenland_grid_cells.RDS', package = "IceSat2R"))
## -----------------------------------------------------------------------------
mapview::mapview(subs_join_s, legend = F)
## -----------------------------------------------------------------------------
join_geoms = 1:5
subs_join_reduced = subs_join_s[join_geoms]
mapview::mapview(subs_join_reduced, legend = F)
## ----echo = F, results = 'asis'-----------------------------------------------
pth_subs_RGTs = system.file('data_files', 'vignette_data', 'Greenland_RGTs_grid_cells.csv', package = "IceSat2R")
dtbl_RGTs = data.table::fread(pth_subs_RGTs, header = T, stringsAsFactors = F)
dtbl_RGTs = dtbl_RGTs[order(dtbl_RGTs$RGT, decreasing = F), ]
stargazer::stargazer(dtbl_RGTs,
summary = FALSE,
rownames = FALSE,
header = FALSE,
float = FALSE,
table.placement = 'h',
title = 'Greenland Grid Cells')
# #.................................................................
# # I came to these RGT's after processing the next for-loop for
# # - all 9 Greenland geoms
# # - all RGT's (of the 'rgts_ws' variable)
# #.................................................................
#
# require(magrittr)
# logs_out_dtbl = data.table::rbindlist(logs_out) # the output of the 'logs_out' list is required!
# logs_out_dtbl$index = names(dat_out_w) # the output of the 'dat_out_w' list is required!
# logs_out_dtbl = logs_out_dtbl[order(logs_out_dtbl$N_rows_winter, decreasing = T), ]
# logs_out_dtbl_subs = subset(logs_out_dtbl, N_rows_winter > 0 & N_rows_summer > 0)
# vec_grid = as.vector(unlist(lapply(strsplit(logs_out_dtbl_subs$index, '_'), function(x) x[3])))
# logs_out_dtbl_subs$greenland_cell = vec_grid
# spl_rgt = split(logs_out_dtbl_subs, by = 'greenland_cell')
# spl_subs = spl_rgt[as.character(1:5)] %>%
# lapply(function(x) x[1:4, ]) %>%
# data.table::rbindlist()
## ----echo = FALSE-------------------------------------------------------------
pth_logs = system.file('data_files', 'vignette_data', 'LOGs.csv', package = "IceSat2R")
logs_out_dtbl = data.table::fread(file = pth_logs, stringsAsFactors = F, header = T)
## ----results = 'asis'---------------------------------------------------------
logs_out_dtbl = logs_out_dtbl[order(logs_out_dtbl$N_rows_winter, decreasing = T), ]
stargazer::stargazer(logs_out_dtbl,
summary = FALSE,
rownames = FALSE,
header = FALSE,
float = FALSE,
table.placement = 'h',
title = 'LOGs')
## ----echo = FALSE-------------------------------------------------------------
ws_vis = readRDS(file = system.file('data_files', 'vignette_data', 'plotly_beams.RDS', package = "IceSat2R"))
## -----------------------------------------------------------------------------
ws_vis_mlt = reshape2::melt(ws_vis, id.vars = c('segment_id_winter', 'beam_winter'))
ws_vis_mlt = data.table::data.table(ws_vis_mlt, stringsAsFactors = F)
ws_vis_mlt_spl = split(ws_vis_mlt, by = 'beam_winter')
# BEAMS = names(ws_vis_mlt_spl) # plot all beams
## -----------------------------------------------------------------------------
#...................................
# function to plot each subplot beam
#...................................
plotly_beams = function(spl_data,
beam,
left_width,
left_height,
right_width,
right_height) {
subs_iter = spl_data[[beam]]
cat(glue::glue("Plot for Beam '{beam}' will be created ..."), '\n')
#......................
# plot for all segments
#......................
fig_lns = plot_ly(data = subs_iter,
x = ~segment_id_winter,
y = ~value,
color = ~variable,
colors = c("blue", "red"),
line = list(width = 2),
text =~glue::glue("land-ice-height: {value} Segment-id: {segment_id_winter}"),
hoverinfo = "text",
width = left_width,
height = left_height) %>%
plotly::layout(xaxis = list(gridcolor = "grey", showgrid = T),
yaxis = list(gridcolor = "grey", showgrid = T)) %>%
plotly::add_lines()
#..............................
# plot for a subset of segments
#..............................
segm_ids = 588326:588908 # this subset of segments show a big difference betw. summer and winter
plt_title = glue::glue("Beam: '{beam}' ( Segments: from {min(segm_ids)} to {max(segm_ids)} )")
subs_iter_segm = subset(subs_iter, segment_id_winter %in% segm_ids)
fig_spl = plot_ly(data = subs_iter_segm,
x = ~segment_id_winter,
y = ~value,
color = ~variable,
colors = c("blue", "red"),
line = list(width = 2),
text =~glue::glue("land-ice-height: {value} Segment-id: {segment_id_winter}"),
hoverinfo = "text",
width = right_width,
height = right_height) %>%
plotly::layout(xaxis = list(gridcolor = "grey", showgrid = T),
yaxis = list(gridcolor = "grey", showgrid = T)) %>%
plotly::add_lines(showlegend = FALSE)
both_plt = plotly::subplot(list(fig_lns, fig_spl), nrows=1, margin = 0.03, widths = c(0.7, 0.3)) %>%
plotly::layout(title = plt_title)
# plotly::export(p = both_plt, file = glue::glue('{beam}.png'))
return(both_plt)
}
## -----------------------------------------------------------------------------
plt_gt1l = plotly_beams(spl_data = ws_vis_mlt_spl,
beam = "gt1l",
left_width = 1800,
left_height = 800,
right_width = 900,
right_height = 400)
plt_gt1l
## -----------------------------------------------------------------------------
plt_gt1r = plotly_beams(spl_data = ws_vis_mlt_spl,
beam = "gt1r",
left_width = 1800,
left_height = 800,
right_width = 900,
right_height = 400)
plt_gt1r
## ----echo = F-----------------------------------------------------------------
# #......................................................
# # save all images for all beams in a separate directory
# #......................................................
#
# nams_ws = names(dat_out_w)
# save_summary = save_dat = list()
#
# for (nam_iter in nams_ws) {
#
# cat("-----------------\n")
# cat(nam_iter, '\n')
# cat("-----------------\n")
#
# w_subs = dat_out_w[[nam_iter]]
# s_subs = dat_out_s[[nam_iter]]
#
# cols_keep = c('date', 'segment_id', 'longitude', 'latitude', 'h_li', 'beam')
#
# w_subs_hq = subset(w_subs, atl06_quality_summary == 0)
# w_subs_hq = w_subs_hq[, ..cols_keep]
# colnames(w_subs_hq) = glue::glue("{cols_keep}_winter")
#
# s_subs_hq = subset(s_subs, atl06_quality_summary == 0)
# s_subs_hq = s_subs_hq[, ..cols_keep]
# colnames(s_subs_hq) = glue::glue("{cols_keep}_summer")
#
# sw_hq_merg = merge(x = w_subs_hq,
# y = s_subs_hq,
# by.x = c('segment_id_winter', 'beam_winter'),
# by.y = c('segment_id_summer', 'beam_summer'))
#
# if (nrow(sw_hq_merg) > 0) {
# sw_hq_merg$dif_height = sw_hq_merg$h_li_winter - sw_hq_merg$h_li_summer
#
# save_dat[[nam_iter]] = sw_hq_merg
# save_summary[[nam_iter]] = data.table::setDT(list(name_iter = nam_iter,
# min = min(sw_hq_merg$dif_height),
# mean = mean(sw_hq_merg$dif_height),
# median = median(sw_hq_merg$dif_height),
# max = max(sw_hq_merg$dif_height),
# N_rows = nrow(sw_hq_merg)))
# #.......................................
# # save the plots for visual verification
# #.......................................
#
# cols_viz = c('segment_id_winter', 'beam_winter', 'h_li_winter', 'h_li_summer')
# ws_vis = sw_hq_merg[, ..cols_viz]
#
# ws_vis_mlt = reshape2::melt(ws_vis, id.vars = c('segment_id_winter', 'beam_winter'))
# ws_vis_mlt = data.table::data.table(ws_vis_mlt, stringsAsFactors = F)
# ws_vis_mlt_spl = split(ws_vis_mlt, by = 'beam_winter')
#
# dir_save = file.path('all_beams_all_RGTs', nam_iter) # !! create the 'all_beams_all_RGTs' directory first
# if (!dir.exists(dir_save)) dir.create(dir_save)
#
# BEAMS = names(ws_vis_mlt_spl) # plot all beams
#
# for (beam in BEAMS) {
#
# subs_iter = ws_vis_mlt_spl[[beam]]
#
# cat(glue::glue("Plot for Beam '{beam}' will be saved ..."), '\n')
#
# #......................
# # plot for all segments
# #......................
#
# fig_lines = plotly::plot_ly(data = subs_iter,
# x = ~segment_id_winter,
# y = ~value,
# color = ~variable,
# colors = c("blue", "red"),
# line = list(width = 2),
# text = ~glue::glue("land-ice-height: {value} Segment-id: {segment_id_winter}"),
# hoverinfo = "text",
# width = 1800,
# height = 1000) %>%
#
# plotly::layout(xaxis = list(gridcolor = "grey", showgrid = T),
# yaxis = list(gridcolor = "grey", showgrid = T)) %>%
#
# plotly::add_lines()
#
# plotly::export(p = fig_lines, file = file.path(dir_save, glue::glue('{beam}.png')))
# }
# }
# else {
# message(glue::glue("Empty data table after merging for idx and RGT: '{nam_iter}'"))
# }
# }
#
# save_summary = data.table::rbindlist(save_summary)
# save_summary = save_summary[order(save_summary$max, decreasing = T), ]
# save_summary
## ----echo = FALSE-------------------------------------------------------------
# merg_cells_viz = readRDS(file = system.file('data_files', 'vignette_data', '3d_plot.RDS', package = "IceSat2R"))