Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
# Load package
library(plumbertableau)
# Set random seed
set.seed(35487)
# R chunks
knitr::read_chunk(path = "../inst/plumber/loess/plumber.R",
labels = "loess")
## ---- eval = FALSE------------------------------------------------------------
# # from CRAN
# install.packages("plumbertableau")
#
# # from GitHub
# remotes::install_github("rstudio/plumbertableau")
## ----fig.width=6.5, fig.height=4.5--------------------------------------------
x <- seq(1, 10, length.out = 100)
y <- 1/x^2 + rnorm(length(x), sd = 0.05)
fit <- loess(y ~ x, span = 0.75)
y_fit <- predict(fit, data.frame(x, y))
# Plot the data and prediction.
plot(x, y)
lines(x, y_fit)
## ----loess, eval = FALSE------------------------------------------------------
# library(plumber)
# library(plumbertableau)
#
# #* @apiTitle Loess Smoothing
# #* @apiDescription Loess smoothing for Tableau
#
# #* Fit a loess curve to the inputs and return the curve values
# #* @param alpha Degree of smoothing
# #* @tableauArg x:integer X values for fitting
# #* @tableauArg y:numeric Y values for fitting
# #* @tableauReturn numeric Fitted loess values
# #* @post /predict
# function(x, y, alpha = 0.75) {
# alpha <- as.numeric(alpha)
# l_out <- loess(y ~ x, span = alpha)
# predict(l_out, data.frame(x, y))
# }
#
# #* @plumber
# tableau_extension
## ---- eval = FALSE------------------------------------------------------------
# #* Annotate me!
# function(x, y, alpha = 0.75) {
# alpha <- as.numeric(alpha)
# l_out <- loess(y ~ x, span = alpha)
# predict(l_out, data.frame(x, y))
# }
## ---- eval=FALSE--------------------------------------------------------------
# #* @tableauArg x:integer X values for fitting
# #* @tableauArg y:numeric Y values for fitting
## ---- eval=FALSE--------------------------------------------------------------
# #* @tableauArg y:numeric? Y values for fitting
#
# **Data returned to Tableau** is described with `@tableauReturn`. The syntax is similar to `@tableauArg`, without an argument name: `#* @tableauReturn Type Description`.
#
## ---- eval=FALSE--------------------------------------------------------------
# #* @tableauReturn numeric Fitted loess values
## ---- eval=FALSE--------------------------------------------------------------
# #* @param alpha Degree of smoothing
## ---- eval = FALSE------------------------------------------------------------
# #* @plumber
# tableau_extension
## -----------------------------------------------------------------------------
mock_tableau_request(script = "/predict",
data = mtcars[,c("hp", "mpg")])
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