Fixing minor issues in the workflow

.gitignore

@@ -15,3 +15,7 @@ R/.Rhistory
 # Ignore helper and scout folders
 helper/
 scout/
+
+# temp cache
+__pycache__/
+diagnostics/

R/EIA comparison.R

@@ -47,3 +47,6 @@ eia_comp<-eia_ratios_sector %>%  filter(year<2024) %>%
   facet_wrap(~sector,nrow=2,labeller = labeller(sector=s_label))+
   ggtitle("Ratio of max monthly electricity consumption in the winter max to max monthly electricity consumption in the summer",subtitle = "EIA 861 2001-2023 (boxplot) vs. BSS 2024 baseline (red dot)")
 save_plot(paste0(graph_dir,"/",filename_prefix,"/eia_seasonal_ratio_comp.jpg"),eia_comp,base_height = 6,base_width = 12,bg="white")
+
+# restore previous working directory, otherwise will mess up python script calls
+setwd("../")

R/annual_graphs.R

@@ -19,7 +19,7 @@ scenarios <- c("brk", "fossil", "accel", "aeo", "ref", "state",
 scenario_for_baseline <- "aeo"
 
 # I/O locations (unchanged names)
-input_dir   <- "../scout_tsv"   # where TSVs live
+input_dir   <- "../scout/scout_tsv"   # where TSVs live
 filename_prefix <- ""
 graph_dir   <- "graphs/annual_results"        # where graphs are written
 
@@ -300,3 +300,6 @@ wide_all <- .make_factor(wide, setall_codes)
 .make_split_plots_for(wide_S1, "_S1", mm_long, states, to, sec, eu, colors)
 .make_split_plots_for(wide_S2, "_S2", mm_long, states, to, sec, eu, colors)
 .make_split_plots_for(wide_all, "", mm_long, states, to, sec, eu, colors)
+
+# restore previous working directory, otherwise will mess up python script calls
+setwd("../")

R/calibration.R

@@ -1,5 +1,6 @@
-
-setwd("R")
+if (basename(getwd()) != "R") {
+    setwd("R")
+}
 #install the packages if they're not already installed
 packages <- c("tidyverse", "scales", "cowplot", "maps", "mapdata", "colorspace")
 install.packages(setdiff(packages, rownames(installed.packages())))
@@ -22,14 +23,17 @@ eia_gross<-read_csv("../map_meas/eia_gross_consumption_by_state_sector_year_mont
 state_monthly<-read_csv("../diagnostics/state_monthly_for_cal.csv")
 
 # if you have TMY
-state_monthly_tmy<-read_csv("../diagnostics/state_monthly_for_cal_tmy.csv") %>%
-  mutate(type="state_monthly_tmy_kwh") %>% rename("kwh"="state_monthly_tmy_kwh")
+if (file.exists("../diagnostics/state_monthly_for_cal_tmy.csv")) {
+  state_monthly_tmy<-read_csv("../diagnostics/state_monthly_for_cal_tmy.csv") %>%
+    mutate(type="state_monthly_tmy_kwh") %>% rename("kwh"="state_monthly_tmy_kwh")
+}
 
 type_label<-c(state_monthly_uncal_kwh="BSS uncalibrated",state_monthly_cal_kwh="BSS calibrated",state_monthly_tmy_kwh="BSS uncalibrated, TMY weather")
 s_label<-c(com="Commercial",res="Residential",all="Buildings")
 
 # calculate monthly state-level calibration ratios ------------------------
 monthly_ratios<-state_monthly %>%
+  dplyr::mutate_at(vars(month, year), as.numeric) %>%
   inner_join(eia_gross,by=c("in.state","month","sector","year")) %>%
   mutate(gross_over_bss=gross.kWh/state_monthly_uncal_kwh,
          net_over_bss=sales.kWh/state_monthly_uncal_kwh) %>% 
@@ -133,3 +137,6 @@ ggplot(aes(x=x,y=y))+
 
 
 save_plot(plot_grid(quadgraph,leg,nrow = 1,rel_widths = c(4,1)),filename = "graphs/fig_max_ratios.jpg",base_height = 7,bg = "white")
+
+# restore previous base directory
+setwd("../")