Esta viñeta ejemplifica el uso del paquete para los datos generados por el software MNEMOS. Dichos registros provienen de la base de datos del SNIH, por lo que la única diferencia radica en el formato de presentación de las series.
This vignette exemplifies the use of the package for the data generated by the software MNEMOS. These records come from the SNIH database, so the only difference lies in the presentation format of the series.
El formato de salida del software MNEMOS es el de una planilla excel que en sus pestañas contiene las distintas variables que registra una estación hidro-meteorológica.
The output format of the MNEMOS software is that of an excel spreadsheet that in its sheets it contains the different variables recorded by a hydro-meteorological station.
# set path to file
path <- system.file('extdata', 'mnemos_guido.xlsx', package = 'hydrotoolbox')
# as we can have multiple sheets, we can get an idea of its content
read_mnemos(path = path, get_sheet = TRUE)
# suppose that we want to read the daily minimum temperature
tmax_guido <- read_mnemos(path = path, by = 'day',
out_name = 'tmax(ºC)', sheet = '11413-017')
plot(x = tmax_guido[ , 1], y = tmax_guido[ , 2],
col = 'dodgerblue', type = 'l',
xlab = 'date', ylab = 'Tmin(ºC)')Si bien esta función resulta de gran utilidad, a medida que la cantidad de variables a analizar crece, cargar estas tablas, ordenarlas y modificarlas, se vuelve tarea complicada. La solución que ofrece hydrotoolbox es la de trabajar con los objetos y métodos que el paquete provee. En las siguientes secciones muestro cómo usarlos.
Although this function is very useful, as the number of variables to be analyzed grows, loading these tables, ordering and modifying them becomes a complicated task. The solution that hydrotoolbox offers is to work with the objects and methods that the package provides. In the following sections I will show you how to use them.
Como menciono en los principios de diseño de este paquete
(vignette('package_overview', package = 'hydrotoolbox')),
los datos que se registran en las estaciones deben almacenarse en un
mismo objeto. Por ello primero habrá que crear dicho objeto (o estación
hidro-meteorológica) y luego usar hm_build_generic(), un
método que permite cargar automáticamente al objeto todas las variables
que la estación real registra.
As I mentioned in the design principles of this package
(vignette ('package_overview', package = 'hydrotoolbox')),
the data that is recorded in the stations must be stored in the same
object. For this reason, you must first create the object (or
hydro-meteorological station) and then use
hm_build_generic(), a method that allows you to
automatically load all variables to the object that the real world
station records.
# in this path you will find the raw example data
path <- system.file('extdata', package = 'hydrotoolbox')
list.files(path)
# we load in a single object (hydromet_station class)
# the streamflow and water height series
guido <-
hm_create() %>% # create the met-station
hm_build_generic(path = path,
file_name = 'mnemos_guido.xlsx',
slot_name = c('qd', 'evap', 'tair',
'tmax', 'tmin', 'wspd'),
by = c('day', 'day', '6 hour',
'day', 'day', '6 hour'),
out_name = list(c('qd(m3/s)', 'flag'),
c('e(mm/d)', 'flag'),
c('tdb(ºC)', 'flag'),
c('tmax(ºC)', 'flag'),
c('tmin(ºC)', 'flag'),
c('w(km/h)', 'flag')),
FUN = read_mnemos,
sheet = 1L:6L)
# we can explore the data-set inside it by using hm_show
guido %>% hm_show()Dado que la función constructora es la única que difiere de lo
desarrollado para los datos del SNIH, recomiendo (re)visitar esta viñeta
(vignette('snih_arg', package = 'hydrotoolbox'))
Since the constructor function is the only one that differs from what
was developed for SNIH data, I recommend (re)visiting this vignette
(vignette ('snih_arg', package = 'hydrotoolbox'))