R/get_cdec.R
In ryanpeek/wateRshedTools: Watershed Tools For Datetime Data
Defines functions
get_cdec
Documented in
get_cdec
#' Get CDEC Data
#'
#' This function takes a \emph{station} and \emph{sensor} along
#' with a \emph{duration} and \emph{start} and \emph{end} date.
#' It returns associated CDEC sensor data in a dataframe.
#' This function can download data for a single station or
#' a list of multiple stations at once using \strong{purrr}.
#'
#' Commonly used sensors include:
#' \itemize{
#' \item 1 stage (ft)
#' \item 20 flow (cfs)
#' \item 2 rain accum (in)
#' \item 16 precip tippingbucket (in)
#' \item 45 ppt incremental (in)
#' \item 3 snow water content (in)
#' \item 18 snow depth (in)
#' \item 6 reservoir elevation (ft)
#' \item 15 reservoir storage (ac-ft)
#' \item 76 reservoir inflow
#' \item 25 water temp
#' \item 4 air temp
#' }
#' @seealso
#' \itemize{
#' \item To see a list of Real-Time Stations: \url{http://cdec.water.ca.gov/misc/realStations.html}
#' \item To see a list of Daily Stations: \url{http://cdec.water.ca.gov/misc/dailyStations.html}
#' \item To see a list of sensors: \url{http://cdec.water.ca.gov/misc/senslist.html}
#' }
#' @param station Station is 3 letter abbreviation (see \url{https://info.water.ca.gov/staMeta.html})
#' @param sensor Sensor is number.
#' @param duration Duration is E=event, D=Daily, H=Hourly.
#' @param start A start date formatted as "YYYY-MM-DD".
#' @param end A end date formatted as "YYYY-MM-DD".
#' @return Will return a dataframe with station ID and associated sensor data.
#' @importFrom magrittr %>%
#' @importFrom janitor clean_names
#' @importFrom rlang .data
#' @examples
#' # set up the parameters to use in function:
#' library(dplyr)
#' library(purrr)
#' sens <- c(20)
#' startT <- c("2013-12-01")
#' endT <- c("2019-03-01")
#' stations <- c("CLW", "MLW", "TIS")
#' dur <- c("H") # hourly here, try this with "H" "D" or "E"
#' # combine into one argument list (note, order matches function order)
#' varList <- list(stations, sens, dur, startT, endT)
#' # now run function:
#' # now map each argument in parallel, then combine
#' cdec_hrly <- pmap(varList, get_cdec) %>% bind_rows()
#' # check records by station
#' table(cdec_hrly$station_id)
#' # check date range
#' cdec_hrly %>%
#' group_by(station_id) %>%
#' summarize(mx=max(datetime), mn=min(datetime))
#' # Format to Daily Data (requires dplyr)
#' cdec <- cdec_hrly %>%
#' mutate(date = as.Date(datetime)) %>%
#' group_by(station_id, date) %>%
#' summarize("daily_cfs" = mean(value, na.rm = TRUE)) %>%
#' filter(!is.na(daily_cfs))
#' # here we can add Water Year and plot
#' library(lubridate)
#' cdec <- cdec %>%
#' add_WYD("date") %>%
#' mutate(month = lubridate::month(date),
#' mday = lubridate::mday(date),
#' md = format(date, "%m/%d"))
#' # now make datasets for each overtopping weir
#' # Tisdale overtops at 45.45 feet:
#' tis<- cdec %>%
#' filter(station_id == "TIS") %>%
#' mutate(WY_rev = as.numeric(as.character(WY))+.3)
#' # Colusa Weir overtopping
#' col<- cdec %>%
#' filter(station_id == "CLW") %>%
#' mutate(WY_rev = as.numeric(as.character(WY))+.6)
#' # Moulton Weir overtopping
#' mol<- cdec %>%
#' filter(station_id == "MLW") %>%
#' mutate(WY_rev = as.numeric(as.character(WY))+.9)
#' # now plot!
#' library(ggplot2)
#' ggplot() +
#' geom_point(data=tis, aes(x=DOWY, y=WY_rev, shape=station_id,
#' color=station_id), size=2.5, alpha=0.9) +
#' geom_point(data=col, aes(x=DOWY, y=WY_rev, shape=station_id,
#' color=station_id), size=2, alpha=0.9) +
#' geom_point(data=mol, aes(x=DOWY, y=WY_rev,
#' shape=station_id, color=station_id), size=1, alpha=0.9) +
#' theme_bw(base_size = 10) +
#' scale_shape_manual("Station", values = c(16,17,15))+
#' labs(x= "", y= "Water Year") +
#' scale_color_viridis_d("Station", direction = -1, option = "D") +
#' scale_y_continuous(breaks= seq(2012.5, 2020.5, 1), labels=c(seq(2012, 2020, 1))) +
#' scale_x_continuous(breaks = seq(0, 365, 61),
#' labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
#' limits = c(0, 340)) +
#' theme(plot.title = element_text(hjust = 0.5),
#' legend.position = c(0.9, 0.7))
#' # single plot:
#' (tis.plot<-ggplot() +
#' geom_tile(data=tis, aes(x=DOWY, y=WY,
#' fill=station_id), show.legend = FALSE) +
#' labs(x= "", y= "Water Year", title = "Tisdale Overtopping") +
#' scale_fill_viridis_d("Station", direction = -1, option = "C") +
#' scale_y_continuous(breaks= seq(2012.5, 2020.5, 1), labels=c(seq(2012, 2020, 1))) +
#' scale_x_continuous(breaks = seq(0, 365, 61),
#' labels = c("Oct", "Dec", "Feb",
#' "Apr", "Jun", "Aug"),
#' limits = c(0, 340)) +
#' theme(plot.title = element_text(hjust = 0.5)) +
#' coord_cartesian(expand = FALSE))
#' @export
get_cdec <- function(
station,
sensor,
duration,
start,
end){
# Set up the Path ---------------------------------------------------------
linkCDEC <- paste("http://cdec.water.ca.gov/dynamicapp/req/CSVDataServlet?Stations=", station,
"&SensorNums=", sensor,
"&dur_code=", duration,
"&Start=", start,
"&End=", end, sep="")
# Read in and Format ------------------------------------------------------
# implement and download data
df <- readr::read_csv(linkCDEC) %>%
janitor::clean_names() %>%
dplyr::select(-c(.data$obs_date, .data$data_flag)) %>%
dplyr::rename(datetime = .data$date_time) %>%
data.frame()
# coerce to numeric for value col, create NAs for missing values, sometimes listed as "---"
df$value <- suppressWarnings(as.numeric(df$value))
cdec<-paste0("cdec_",duration,"_",station) # make a station name
if(dim(df)[1]>0){
cat(paste0("Downloaded Station ", cdec," successfully, in current workspace!\n\n"))
return(df)
} else {
cat(paste0("No data available for Station ", cdec, " for this daterange or interval! \n\n"))
}
}
# ADD WATER YEAR TYPES ----------------------------------------------------
# wytypes <- load("data/ca_wytypes.rda")
# ## Join
# cdec <- left_join(cdec, wytypes, by="WY")
# cdec$WYtype <- factor(cdec$WYtype, levels = c("C","D","BN","AN","W"))
# cdec$station_id <- factor(cdec$station_id,levels = c("MLW", "CLW","TIS"))
# cdec$WY <- as.factor(cdec$WY)
# FILTER TO WEIRS ---------------------------------------------------------
# # Tisdale overtopping at 45.45 feet or approx:
# tis<- cdec %>%
# filter(station_id == "TIS") %>%
# mutate(WY_rev = as.numeric(as.character(WY))+.3)
#
# #Colusa Weir overtopping
# col<- cdec %>%
# filter(station_id == "CLW") %>%
# mutate(WY_rev = as.numeric(as.character(WY))+.6)
#
# #Moulton Weir overtopping
# mol<- cdec %>%
# filter(station_id == "MLW") %>%
# mutate(WY_rev = as.numeric(as.character(WY))+.9)
# SAME LINE ---------------------------------------------------------------
#
# ggplot() +
# geom_point(data=tis, aes(x=DOWY, y=WY_rev, shape=station_id,
# color=Yr_type_SAC), size=2.5, alpha=0.9) +
# geom_point(data=col, aes(x=DOWY, y=WY_rev, shape=station_id,
# color=Yr_type_SAC), size=2, alpha=0.9) +
# geom_point(data=mol, aes(x=DOWY, y=WY_rev,
# shape=station_id, color=Yr_type_SAC), size=1, alpha=0.9) +
# theme_bw(base_size = 10) +
# scale_shape_manual("Station", values = c(16,17,15))+
# labs(x= "", y= "Water Year")+
# scale_color_viridis_d("WYT", direction = -1, option = "D") +
# scale_y_continuous(breaks= seq(1998.5, 2018.5, 1), labels=c(seq(1998, 2018, 1))) +
# scale_x_continuous(breaks = seq(0, 365, 61),
# labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
# limits = c(0, 340)) +
# theme(plot.title = element_text(hjust = 0.5),
# legend.position = c(0.9, 0.7))
# #facet_grid(station_id~.)
# ggsave(filename = "figs/example_cdec_weirs_flow_same_line.png", width = 11, height = 7, units = "in", dpi = 250)
# GEOM TILE -------------------------------------------------------------
# ggplot() +
# geom_tile(data=tis, aes(x=DOWY, y=WY_rev, fill=Yr_type_SAC, color=station_id, height=0.4)) +
# geom_tile(data=col, aes(x=DOWY, y=WY_rev, color=station_id, fill=Yr_type_SAC, height=0.3)) +
# geom_tile(data=mol, aes(x=DOWY, y=WY_rev, color=station_id, fill=Yr_type_SAC, height=0.25)) +
# theme_bw(base_size = 10) +
# scale_color_manual("Station", values = c("gray70","white", "black"), guide=FALSE)+
# labs(x= "", y= "Water Year", title = "Overtopping at Tisdale, Moulton, and Colusa Weirs, 1998-2017",
# caption = "CDEC stations top to bottom for each year (smallest to largest boxes): CLW, MLW, TIS")+
# scale_fill_viridis_d("WYT", direction = -1, option = "D") +
# scale_y_continuous(breaks= seq(1998.5, 2018.5, 1), labels=c(seq(1998, 2018, 1))) +
# scale_x_continuous(breaks = seq(0, 365, 61),
# labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
# limits = c(0, 340)) +
# theme(plot.title = element_text(hjust = 0.5),
# legend.position = c(0.9, 0.7))
#
# #facet_grid(station_id~.)
# ggsave(filename = "figs/example_cdec_weirs_flow_geom_tile.png", width = 11, height = 7, units = "in", dpi = 250)
# TILE PLOTS ---------------------------------------------------------------
# (tis.plot<-ggplot() +
# geom_tile(data=tis, aes(x=DOWY, y=WY,
# fill=Yr_type_SAC), show.legend = F) +
# theme_bw(base_size = 10) +
# labs(x= "", y= "Water Year", title = "Tisdale Overtopping") +
# scale_fill_viridis_d("Water Year Type", direction = -1, option = "C") +
# scale_x_continuous(breaks = seq(0, 365, 61),
# labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
# limits = c(0, 340)) +
# theme(plot.title = element_text(hjust = 0.5)) +
# coord_cartesian(expand = F))
#coord_polar(clip = "on") # check out with coord_polar()!
# (col.plot<-ggplot()+
# geom_tile(data=col, aes(x=DOWY, y=WY,
# fill=Yr_type_SAC), show.legend = F) +
# theme_bw(base_size = 10) +
# labs(x="", y= "Water Year", title = "Colusa Weir Overtopping")+
# scale_fill_viridis_d("Water Year Type", direction = -1, option = "C") +
# scale_x_continuous(breaks = seq(0, 365, 61),
# labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
# limits = c(0, 340)) +
# theme(plot.title = element_text(hjust = 0.5)) +
# coord_cartesian(expand = F))
#
#
# (mol.plot<-ggplot()+
# geom_tile(data=mol, aes(x=DOWY, y=WY,
# fill=Yr_type_SAC), show.legend = F) +
# theme_bw(base_size = 10) +
# labs(x= "", y= "Water Year", title = "Moulton Weir Overtopping")+
# scale_fill_viridis_d("Water Year Type", direction = -1, option = "C") +
# scale_x_continuous(breaks = seq(0, 365, 61),
# labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
# limits = c(0, 340)) +
# theme(plot.title = element_text(hjust = 0.5)) +
# coord_cartesian(expand = F))
#stacked cowplot moo moo
# library(cowplot)
# plot_grid(mol.plot, col.plot, tis.plot, nrow = 3, align = "v")
#
#
# # or all together but with facets
# ggplot() + geom_tile(data=cdec, aes(x=DOWY, y=as.factor(WY),
# fill=Yr_type_SAC),
# show.legend = T) +
# theme_bw(base_size = 10) +
# labs(x= "", y= "Water Year")+
# scale_fill_viridis_d("WYT", direction = -1, option = "D") +
# scale_x_continuous(breaks = seq(0, 365, 61),
# labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
# limits = c(0, 340)) +
# theme(plot.title = element_text(hjust = 0.5),
# legend.position = c(0.9, 0.85)) +
# facet_grid(station_id~.)
#
# ggsave(filename = "figs/example_cdec_weirs_flow_faceted.png", width = 11, height = 7, units = "in", dpi = 250)
#save(cdec_hrly, file = "data/cdec_hrly_tis_clw_mlw.rda")
### POLAR
# or all together but with facets
# ggplot() + geom_tile(data=cdec, aes(x=DOWY, y=as.factor(WY),
# fill=Yr_type_SAC),
# show.legend = T) +
# theme_bw(base_size = 8) +
# labs(x= "", y= "Water Year")+
# scale_fill_viridis_d("WYT", direction = -1, option = "D") +
# scale_x_continuous(breaks = seq(0, 365, 61),
# labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
# limits = c(0, 340)) +
# facet_grid(.~station_id) +
# coord_polar()
#
# ggsave(filename = "figs/example_cdec_weirs_flow_polar.png", width = 11, height = 7, units = "in", dpi = 250)
#
ryanpeek/wateRshedTools documentation built on Jan. 6, 2023, 7:06 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions get_cdec
Documented in get_cdec
#' Get CDEC Data
#'
#' This function takes a \emph{station} and \emph{sensor} along
#' with a \emph{duration} and \emph{start} and \emph{end} date.
#' It returns associated CDEC sensor data in a dataframe.
#' This function can download data for a single station or
#' a list of multiple stations at once using \strong{purrr}.
#'
#' Commonly used sensors include:
#' \itemize{
#' \item 1 stage (ft)
#' \item 20 flow (cfs)
#' \item 2 rain accum (in)
#' \item 16 precip tippingbucket (in)
#' \item 45 ppt incremental (in)
#' \item 3 snow water content (in)
#' \item 18 snow depth (in)
#' \item 6 reservoir elevation (ft)
#' \item 15 reservoir storage (ac-ft)
#' \item 76 reservoir inflow
#' \item 25 water temp
#' \item 4 air temp
#' }
#' @seealso
#' \itemize{
#' \item To see a list of Real-Time Stations: \url{http://cdec.water.ca.gov/misc/realStations.html}
#' \item To see a list of Daily Stations: \url{http://cdec.water.ca.gov/misc/dailyStations.html}
#' \item To see a list of sensors: \url{http://cdec.water.ca.gov/misc/senslist.html}
#' }
#' @param station Station is 3 letter abbreviation (see \url{https://info.water.ca.gov/staMeta.html})
#' @param sensor Sensor is number.
#' @param duration Duration is E=event, D=Daily, H=Hourly.
#' @param start A start date formatted as "YYYY-MM-DD".
#' @param end A end date formatted as "YYYY-MM-DD".
#' @return Will return a dataframe with station ID and associated sensor data.
#' @importFrom magrittr %>%
#' @importFrom janitor clean_names
#' @importFrom rlang .data
#' @examples
#' # set up the parameters to use in function:
#' library(dplyr)
#' library(purrr)
#' sens <- c(20)
#' startT <- c("2013-12-01")
#' endT <- c("2019-03-01")
#' stations <- c("CLW", "MLW", "TIS")
#' dur <- c("H") # hourly here, try this with "H" "D" or "E"
#' # combine into one argument list (note, order matches function order)
#' varList <- list(stations, sens, dur, startT, endT)
#' # now run function:
#' # now map each argument in parallel, then combine
#' cdec_hrly <- pmap(varList, get_cdec) %>% bind_rows()
#' # check records by station
#' table(cdec_hrly$station_id)
#' # check date range
#' cdec_hrly %>%
#' group_by(station_id) %>%
#' summarize(mx=max(datetime), mn=min(datetime))
#' # Format to Daily Data (requires dplyr)
#' cdec <- cdec_hrly %>%
#' mutate(date = as.Date(datetime)) %>%
#' group_by(station_id, date) %>%
#' summarize("daily_cfs" = mean(value, na.rm = TRUE)) %>%
#' filter(!is.na(daily_cfs))
#' # here we can add Water Year and plot
#' library(lubridate)
#' cdec <- cdec %>%
#' add_WYD("date") %>%
#' mutate(month = lubridate::month(date),
#' mday = lubridate::mday(date),
#' md = format(date, "%m/%d"))
#' # now make datasets for each overtopping weir
#' # Tisdale overtops at 45.45 feet:
#' tis<- cdec %>%
#' filter(station_id == "TIS") %>%
#' mutate(WY_rev = as.numeric(as.character(WY))+.3)
#' # Colusa Weir overtopping
#' col<- cdec %>%
#' filter(station_id == "CLW") %>%
#' mutate(WY_rev = as.numeric(as.character(WY))+.6)
#' # Moulton Weir overtopping
#' mol<- cdec %>%
#' filter(station_id == "MLW") %>%
#' mutate(WY_rev = as.numeric(as.character(WY))+.9)
#' # now plot!
#' library(ggplot2)
#' ggplot() +
#' geom_point(data=tis, aes(x=DOWY, y=WY_rev, shape=station_id,
#' color=station_id), size=2.5, alpha=0.9) +
#' geom_point(data=col, aes(x=DOWY, y=WY_rev, shape=station_id,
#' color=station_id), size=2, alpha=0.9) +
#' geom_point(data=mol, aes(x=DOWY, y=WY_rev,
#' shape=station_id, color=station_id), size=1, alpha=0.9) +
#' theme_bw(base_size = 10) +
#' scale_shape_manual("Station", values = c(16,17,15))+
#' labs(x= "", y= "Water Year") +
#' scale_color_viridis_d("Station", direction = -1, option = "D") +
#' scale_y_continuous(breaks= seq(2012.5, 2020.5, 1), labels=c(seq(2012, 2020, 1))) +
#' scale_x_continuous(breaks = seq(0, 365, 61),
#' labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
#' limits = c(0, 340)) +
#' theme(plot.title = element_text(hjust = 0.5),
#' legend.position = c(0.9, 0.7))
#' # single plot:
#' (tis.plot<-ggplot() +
#' geom_tile(data=tis, aes(x=DOWY, y=WY,
#' fill=station_id), show.legend = FALSE) +
#' labs(x= "", y= "Water Year", title = "Tisdale Overtopping") +
#' scale_fill_viridis_d("Station", direction = -1, option = "C") +
#' scale_y_continuous(breaks= seq(2012.5, 2020.5, 1), labels=c(seq(2012, 2020, 1))) +
#' scale_x_continuous(breaks = seq(0, 365, 61),
#' labels = c("Oct", "Dec", "Feb",
#' "Apr", "Jun", "Aug"),
#' limits = c(0, 340)) +
#' theme(plot.title = element_text(hjust = 0.5)) +
#' coord_cartesian(expand = FALSE))
#' @export
get_cdec <- function(
station,
sensor,
duration,
start,
end){
# Set up the Path ---------------------------------------------------------
linkCDEC <- paste("http://cdec.water.ca.gov/dynamicapp/req/CSVDataServlet?Stations=", station,
"&SensorNums=", sensor,
"&dur_code=", duration,
"&Start=", start,
"&End=", end, sep="")
# Read in and Format ------------------------------------------------------
# implement and download data
df <- readr::read_csv(linkCDEC) %>%
janitor::clean_names() %>%
dplyr::select(-c(.data$obs_date, .data$data_flag)) %>%
dplyr::rename(datetime = .data$date_time) %>%
data.frame()
# coerce to numeric for value col, create NAs for missing values, sometimes listed as "---"
df$value <- suppressWarnings(as.numeric(df$value))
cdec<-paste0("cdec_",duration,"_",station) # make a station name
if(dim(df)[1]>0){
cat(paste0("Downloaded Station ", cdec," successfully, in current workspace!\n\n"))
return(df)
} else {
cat(paste0("No data available for Station ", cdec, " for this daterange or interval! \n\n"))
}
}
# ADD WATER YEAR TYPES ----------------------------------------------------
# wytypes <- load("data/ca_wytypes.rda")
# ## Join
# cdec <- left_join(cdec, wytypes, by="WY")
# cdec$WYtype <- factor(cdec$WYtype, levels = c("C","D","BN","AN","W"))
# cdec$station_id <- factor(cdec$station_id,levels = c("MLW", "CLW","TIS"))
# cdec$WY <- as.factor(cdec$WY)
# FILTER TO WEIRS ---------------------------------------------------------
# # Tisdale overtopping at 45.45 feet or approx:
# tis<- cdec %>%
# filter(station_id == "TIS") %>%
# mutate(WY_rev = as.numeric(as.character(WY))+.3)
#
# #Colusa Weir overtopping
# col<- cdec %>%
# filter(station_id == "CLW") %>%
# mutate(WY_rev = as.numeric(as.character(WY))+.6)
#
# #Moulton Weir overtopping
# mol<- cdec %>%
# filter(station_id == "MLW") %>%
# mutate(WY_rev = as.numeric(as.character(WY))+.9)
# SAME LINE ---------------------------------------------------------------
#
# ggplot() +
# geom_point(data=tis, aes(x=DOWY, y=WY_rev, shape=station_id,
# color=Yr_type_SAC), size=2.5, alpha=0.9) +
# geom_point(data=col, aes(x=DOWY, y=WY_rev, shape=station_id,
# color=Yr_type_SAC), size=2, alpha=0.9) +
# geom_point(data=mol, aes(x=DOWY, y=WY_rev,
# shape=station_id, color=Yr_type_SAC), size=1, alpha=0.9) +
# theme_bw(base_size = 10) +
# scale_shape_manual("Station", values = c(16,17,15))+
# labs(x= "", y= "Water Year")+
# scale_color_viridis_d("WYT", direction = -1, option = "D") +
# scale_y_continuous(breaks= seq(1998.5, 2018.5, 1), labels=c(seq(1998, 2018, 1))) +
# scale_x_continuous(breaks = seq(0, 365, 61),
# labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
# limits = c(0, 340)) +
# theme(plot.title = element_text(hjust = 0.5),
# legend.position = c(0.9, 0.7))
# #facet_grid(station_id~.)
# ggsave(filename = "figs/example_cdec_weirs_flow_same_line.png", width = 11, height = 7, units = "in", dpi = 250)
# GEOM TILE -------------------------------------------------------------
# ggplot() +
# geom_tile(data=tis, aes(x=DOWY, y=WY_rev, fill=Yr_type_SAC, color=station_id, height=0.4)) +
# geom_tile(data=col, aes(x=DOWY, y=WY_rev, color=station_id, fill=Yr_type_SAC, height=0.3)) +
# geom_tile(data=mol, aes(x=DOWY, y=WY_rev, color=station_id, fill=Yr_type_SAC, height=0.25)) +
# theme_bw(base_size = 10) +
# scale_color_manual("Station", values = c("gray70","white", "black"), guide=FALSE)+
# labs(x= "", y= "Water Year", title = "Overtopping at Tisdale, Moulton, and Colusa Weirs, 1998-2017",
# caption = "CDEC stations top to bottom for each year (smallest to largest boxes): CLW, MLW, TIS")+
# scale_fill_viridis_d("WYT", direction = -1, option = "D") +
# scale_y_continuous(breaks= seq(1998.5, 2018.5, 1), labels=c(seq(1998, 2018, 1))) +
# scale_x_continuous(breaks = seq(0, 365, 61),
# labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
# limits = c(0, 340)) +
# theme(plot.title = element_text(hjust = 0.5),
# legend.position = c(0.9, 0.7))
#
# #facet_grid(station_id~.)
# ggsave(filename = "figs/example_cdec_weirs_flow_geom_tile.png", width = 11, height = 7, units = "in", dpi = 250)
# TILE PLOTS ---------------------------------------------------------------
# (tis.plot<-ggplot() +
# geom_tile(data=tis, aes(x=DOWY, y=WY,
# fill=Yr_type_SAC), show.legend = F) +
# theme_bw(base_size = 10) +
# labs(x= "", y= "Water Year", title = "Tisdale Overtopping") +
# scale_fill_viridis_d("Water Year Type", direction = -1, option = "C") +
# scale_x_continuous(breaks = seq(0, 365, 61),
# labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
# limits = c(0, 340)) +
# theme(plot.title = element_text(hjust = 0.5)) +
# coord_cartesian(expand = F))
#coord_polar(clip = "on") # check out with coord_polar()!
# (col.plot<-ggplot()+
# geom_tile(data=col, aes(x=DOWY, y=WY,
# fill=Yr_type_SAC), show.legend = F) +
# theme_bw(base_size = 10) +
# labs(x="", y= "Water Year", title = "Colusa Weir Overtopping")+
# scale_fill_viridis_d("Water Year Type", direction = -1, option = "C") +
# scale_x_continuous(breaks = seq(0, 365, 61),
# labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
# limits = c(0, 340)) +
# theme(plot.title = element_text(hjust = 0.5)) +
# coord_cartesian(expand = F))
#
#
# (mol.plot<-ggplot()+
# geom_tile(data=mol, aes(x=DOWY, y=WY,
# fill=Yr_type_SAC), show.legend = F) +
# theme_bw(base_size = 10) +
# labs(x= "", y= "Water Year", title = "Moulton Weir Overtopping")+
# scale_fill_viridis_d("Water Year Type", direction = -1, option = "C") +
# scale_x_continuous(breaks = seq(0, 365, 61),
# labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
# limits = c(0, 340)) +
# theme(plot.title = element_text(hjust = 0.5)) +
# coord_cartesian(expand = F))
#stacked cowplot moo moo
# library(cowplot)
# plot_grid(mol.plot, col.plot, tis.plot, nrow = 3, align = "v")
#
#
# # or all together but with facets
# ggplot() + geom_tile(data=cdec, aes(x=DOWY, y=as.factor(WY),
# fill=Yr_type_SAC),
# show.legend = T) +
# theme_bw(base_size = 10) +
# labs(x= "", y= "Water Year")+
# scale_fill_viridis_d("WYT", direction = -1, option = "D") +
# scale_x_continuous(breaks = seq(0, 365, 61),
# labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
# limits = c(0, 340)) +
# theme(plot.title = element_text(hjust = 0.5),
# legend.position = c(0.9, 0.85)) +
# facet_grid(station_id~.)
#
# ggsave(filename = "figs/example_cdec_weirs_flow_faceted.png", width = 11, height = 7, units = "in", dpi = 250)
#save(cdec_hrly, file = "data/cdec_hrly_tis_clw_mlw.rda")
### POLAR
# or all together but with facets
# ggplot() + geom_tile(data=cdec, aes(x=DOWY, y=as.factor(WY),
# fill=Yr_type_SAC),
# show.legend = T) +
# theme_bw(base_size = 8) +
# labs(x= "", y= "Water Year")+
# scale_fill_viridis_d("WYT", direction = -1, option = "D") +
# scale_x_continuous(breaks = seq(0, 365, 61),
# labels = c("Oct", "Dec", "Feb", "Apr", "Jun", "Aug"),
# limits = c(0, 340)) +
# facet_grid(.~station_id) +
# coord_polar()
#
# ggsave(filename = "figs/example_cdec_weirs_flow_polar.png", width = 11, height = 7, units = "in", dpi = 250)
#
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.