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pass ... from dyplot.prophet to dygraph::dygraph, addresses #1158 (#1177)

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* Pass ... from dyplot.prophet to dygraph to be able to set additional parameters

* Add documentation for ... in dyplot.prophet

Co-authored-by: Ben Letham <bletham@gmail.com>
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Adriano Fantini 2020-02-04 22:39:17 +01:00 committed by GitHub
parent 9320ed1fb5
commit 187bf06bf7
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1 changed files with 18 additions and 18 deletions
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36
R/R/plot.R
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@ -25,8 +25,8 @@ df_for_plotting <- function(m, fcst) {
#' @param x Prophet object.
#' @param fcst Data frame returned by predict(m, df).
#' @param uncertainty Optional boolean indicating if the uncertainty interval for yhat
#' should be plotted, which will only be done if x$uncertainty.samples > 0.
#' Must be present in fcst as yhat_lower and yhat_upper.
#' should be plotted, which will only be done if x$uncertainty.samples > 0.
#' Must be present in fcst as yhat_lower and yhat_upper.
#' @param plot_cap Boolean indicating if the capacity should be shown in the
#' figure, if available.
#' @param xlabel Optional label for x-axis
@ -82,7 +82,7 @@ plot.prophet <- function(x, fcst, uncertainty = TRUE, plot_cap = TRUE,
#' @param m Prophet object.
#' @param fcst Data frame returned by predict(m, df).
#' @param uncertainty Optional boolean indicating if the uncertainty interval should be
#' plotted for the trend, from fcst columns trend_lower and trend_upper.This will
#' plotted for the trend, from fcst columns trend_lower and trend_upper.This will
#' only be done if m$uncertainty.samples > 0.
#' @param plot_cap Boolean indicating if the capacity should be shown in the
#' figure, if available.
@ -124,10 +124,10 @@ prophet_plot_components <- function(
if (!(name %in% c('weekly', 'yearly')) &&
(name %in% colnames(fcst))) {
if (m$seasonalities[[name]]$period == 7) {
panels[[length(panels) + 1]] <- plot_weekly(m, uncertainty,
panels[[length(panels) + 1]] <- plot_weekly(m, uncertainty,
weekly_start, name)
} else if (m$seasonalities[[name]]$period == 365.25) {
panels[[length(panels) + 1]] <- plot_yearly(m, uncertainty,
panels[[length(panels) + 1]] <- plot_yearly(m, uncertainty,
yearly_start, name)
} else {
panels[[length(panels) + 1]] <- plot_seasonality(m, name, uncertainty)
@ -237,13 +237,13 @@ seasonality_plot_df <- function(m, ds) {
#' @param weekly_start Integer specifying the start day of the weekly
#' seasonality plot. 0 (default) starts the week on Sunday. 1 shifts by 1 day
#' to Monday, and so on.
#' @param name Name of seasonality component if previously changed
#' @param name Name of seasonality component if previously changed
#' from default 'weekly'.
#'
#' @return A ggplot2 plot.
#'
#' @keywords internal
plot_weekly <- function(m, uncertainty = TRUE, weekly_start = 0,
plot_weekly <- function(m, uncertainty = TRUE, weekly_start = 0,
name = 'weekly') {
# Compute weekly seasonality for a Sun-Sat sequence of dates.
days <- seq(set_date('2017-01-01'), by='d', length.out=7) + as.difftime(
@ -280,13 +280,13 @@ plot_weekly <- function(m, uncertainty = TRUE, weekly_start = 0,
#' @param yearly_start Integer specifying the start day of the yearly
#' seasonality plot. 0 (default) starts the year on Jan 1. 1 shifts by 1 day
#' to Jan 2, and so on.
#' @param name Name of seasonality component if previously changed
#' @param name Name of seasonality component if previously changed
#' from default 'yearly'.
#'
#' @return A ggplot2 plot.
#'
#' @keywords internal
plot_yearly <- function(m, uncertainty = TRUE, yearly_start = 0,
plot_yearly <- function(m, uncertainty = TRUE, yearly_start = 0,
name = 'yearly') {
# Compute yearly seasonality for a Jan 1 - Dec 31 sequence of dates.
days <- seq(set_date('2017-01-01'), by='d', length.out=365) + as.difftime(
@ -403,9 +403,9 @@ add_changepoints_to_plot <- function(m, threshold = 0.01, cp_color = "red",
#' @param x Prophet object.
#' @param fcst Data frame returned by predict(m, df).
#' @param uncertainty Optional boolean indicating if the uncertainty interval for yhat
#' should be plotted, which will only be done if x$uncertainty.samples > 0. Must be
#' should be plotted, which will only be done if x$uncertainty.samples > 0. Must be
#' present in fcst as yhat_lower and yhat_upper.
#' @param ... additional arguments
#' @param ... additional arguments passed to dygraph::dygraph
#' @importFrom dplyr "%>%"
#' @return A dygraph plot.
#'
@ -421,14 +421,14 @@ add_changepoints_to_plot <- function(m, threshold = 0.01, cp_color = "red",
#' }
#'
#' @export
dyplot.prophet <- function(x, fcst, uncertainty=TRUE,
...)
dyplot.prophet <- function(x, fcst, uncertainty=TRUE,
...)
{
forecast.label='Predicted'
actual.label='Actual'
# create data.frame for plotting
df <- df_for_plotting(x, fcst)
# build variables to include, or not, the uncertainty data
if(uncertainty && x$uncertainty.samples && exists("yhat_lower", where = df))
{
@ -443,13 +443,13 @@ dyplot.prophet <- function(x, fcst, uncertainty=TRUE,
dfTS <- xts::xts(df %>% dplyr::select_(.dots=colsToKeep), order.by = df$ds)
# base plot
dyBase <- dygraphs::dygraph(dfTS)
dyBase <- dygraphs::dygraph(dfTS, ...)
presAnnotation <- function(dygraph, x, text) {
dygraph %>%
dygraphs::dyAnnotation(x, text, text, attachAtBottom = TRUE)
}
dyBase <- dyBase %>%
# plot actual values
dygraphs::dySeries(
@ -458,7 +458,7 @@ dyplot.prophet <- function(x, fcst, uncertainty=TRUE,
# plot forecast and ribbon
dygraphs::dySeries(forecastCols, label=forecast.label, color='blue') %>%
# allow zooming
dygraphs::dyRangeSelector() %>%
dygraphs::dyRangeSelector() %>%
# make unzoom button
dygraphs::dyUnzoom()
if (!is.null(x$holidays)) {