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# Copyright 2017 Province of British Columbia
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and limitations under the License.
#' Extract monthly flows information from the HYDAT database
#'
#' Tidy data of monthly loads information from the SED_DLY_LOADS HYDAT table. `station_number` and
#' `prov_terr_state_loc` can both be supplied. If both are omitted all values from the `hy_stations` table are returned.
#' That is a large vector for `hy_sed_monthly_loads`.
#'
#' @inheritParams hy_stations
#' @param start_date Leave blank if all dates are required. Date format needs to be in YYYY-MM-DD. Date is inclusive.
#' @param end_date Leave blank if all dates are required. Date format needs to be in YYYY-MM-DD. Date is inclusive.
#'
#' @return A tibble of monthly sediment loads.
#'
#' @format A tibble with 8 variables:
#' \describe{
#' \item{STATION_NUMBER}{Unique 7 digit Water Survey of Canada station number}
#' \item{Year}{Year of record.}
#' \item{Month}{Numeric month value}
#' \item{Full_Month}{Logical value is there is full record from Month}
#' \item{No_days}{Number of days in that month}
#' \item{Sum_stat}{Summary statistic being used.}
#' \item{Value}{Value of the measurement in tonnes.}
#' \item{Date_occurred}{Observation date. Formatted as a Date class. MEAN is a annual summary
#' and therefore has an NA value for Date.}
#' }
#'
#' @examples
#' \dontrun{
#' hy_sed_monthly_loads(station_number = "01CE003")
#' }
#'
#' @family HYDAT functions
#' @source HYDAT
#' @export
hy_sed_monthly_loads <- function(station_number = NULL,
hydat_path = NULL,
prov_terr_state_loc = NULL,
start_date = NULL,
end_date = NULL) {
## Determine which dates should be queried
dates_null <- date_check(start_date, end_date)
## Read in database
hydat_con <- hy_src(hydat_path)
if (!dplyr::is.src(hydat_path)) {
on.exit(hy_src_disconnect(hydat_con), add = TRUE)
}
## Determine which stations we are querying
stns <- station_choice(hydat_con, station_number, prov_terr_state_loc)
## Creating rlang symbols
sym_YEAR <- sym("YEAR")
sym_STATION_NUMBER <- sym("STATION_NUMBER")
sym_variable <- sym("variable")
sym_temp <- sym("temp")
sym_temp2 <- sym("temp2")
## Data manipulations to make it "tidy"
sed_monthly_loads <- dplyr::tbl(hydat_con, "SED_DLY_LOADS")
sed_monthly_loads <- dplyr::filter(sed_monthly_loads, !!sym_STATION_NUMBER %in% stns)
## Do the initial subset to take advantage of dbplyr only issuing sql query when it has too
## by year
if (!dates_null[["start_is_null"]]) sed_monthly_loads <- dplyr::filter(sed_monthly_loads, !!sym_YEAR >= lubridate::year(start_date))
if (!dates_null[["end_is_null"]]) sed_monthly_loads <- dplyr::filter(sed_monthly_loads, !!sym_YEAR <= lubridate::year(end_date))
sed_monthly_loads <- dplyr::select(sed_monthly_loads, STATION_NUMBER:MAX)
sed_monthly_loads <- dplyr::collect(sed_monthly_loads)
if (is.data.frame(sed_monthly_loads) && nrow(sed_monthly_loads) == 0) {
stop("This station is not present in HYDAT")
}
## Need to rename columns for gather
colnames(sed_monthly_loads) <- c(
"STATION_NUMBER", "Year", "Month", "Full_Month", "No_days", "MEAN_Value",
"TOTAL_Value", "MIN_DAY", "MIN_Value", "MAX_DAY", "MAX_Value"
)
sed_monthly_loads <- tidyr::gather(sed_monthly_loads, !!sym_variable, !!sym_temp, -(STATION_NUMBER:No_days))
sed_monthly_loads <- tidyr::separate(sed_monthly_loads, !!sym_variable, into = c("Sum_stat", "temp2"), sep = "_")
sed_monthly_loads <- tidyr::spread(sed_monthly_loads, !!sym_temp2, !!sym_temp)
## convert into R date for date of occurence.
sed_monthly_loads <- dplyr::mutate(sed_monthly_loads, Date_occurred = paste0(Year, "-", Month, "-", DAY))
## Check if DAY is NA and if so give it an NA value so the date parse correctly.
sed_monthly_loads <- dplyr::mutate(sed_monthly_loads, Date_occurred = ifelse(is.na(DAY), NA, Date_occurred))
sed_monthly_loads <- dplyr::mutate(sed_monthly_loads, Date_occurred = lubridate::ymd(Date_occurred, quiet = TRUE))
## Then when a date column exist fine tune the subset
if (!dates_null[["start_is_null"]]) sed_monthly_loads <- dplyr::filter(sed_monthly_loads, Date_occurred >= start_date)
if (!dates_null[["end_is_null"]]) sed_monthly_loads <- dplyr::filter(sed_monthly_loads, Date_occurred <= end_date)
sed_monthly_loads <- dplyr::select(sed_monthly_loads, -DAY)
sed_monthly_loads <- dplyr::mutate(sed_monthly_loads, Full_Month = Full_Month == 1)
attr(sed_monthly_loads, "missed_stns") <- setdiff(unique(stns), unique(sed_monthly_loads$STATION_NUMBER))
as.hy(sed_monthly_loads)
}
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