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Fix merge issues

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This commit is contained in:
Ben Letham 2017-12-22 12:19:09 -08:00
parent 451c886c73
commit a19589a662
1 changed files with 7 additions and 6 deletions
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13
R/R/plot.R
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@ -1,4 +1,3 @@
#
#' Merge history and forecast for plotting.
#'
#' @param m Prophet object.
@ -97,7 +96,7 @@ prophet_plot_components <- function(
# Plot the trend
panels <- list(plot_forecast_component(fcst, 'trend', uncertainty, plot_cap))
# Plot holiday components, if present.
if (!is.null(m$holidays) & ('holidays' %in% colnames(fcst))) {
if (!is.null(m$holidays) && ('holidays' %in% colnames(fcst))) {
panels[[length(panels) + 1]] <- plot_forecast_component(
fcst, 'holidays', uncertainty, FALSE)
}
@ -127,7 +126,7 @@ prophet_plot_components <- function(
grid::grid.newpage()
grid::pushViewport(grid::viewport(layout = grid::grid.layout(length(panels),
1)))
for (i in 1:length(panels)) {
for (i in seq_along(panels)) {
print(panels[[i]], vp = grid::viewport(layout.pos.row = i,
layout.pos.col = 1))
}
@ -181,7 +180,7 @@ plot_forecast_component <- function(
#'
#' @keywords internal
seasonality_plot_df <- function(m, ds) {
df_list <- list(ds = ds, cap = 1)
df_list <- list(ds = ds, cap = 1, floor = 0)
for (name in names(m$extra_regressors)) {
df_list[[name]] <- 0
}
@ -203,7 +202,8 @@ seasonality_plot_df <- function(m, ds) {
#' @keywords internal
plot_weekly <- function(m, uncertainty = TRUE, weekly_start = 0) {
# Compute weekly seasonality for a Sun-Sat sequence of dates.
days <- seq(set_date('2017-01-01'), by='d', length.out=7) + weekly_start
days <- seq(set_date('2017-01-01'), by='d', length.out=7) + as.difftime(
weekly_start, units = "days")
df.w <- seasonality_plot_df(m, days)
seas <- predict_seasonal_components(m, df.w)
seas$dow <- factor(weekdays(df.w$ds), levels=weekdays(df.w$ds))
@ -236,7 +236,8 @@ plot_weekly <- function(m, uncertainty = TRUE, weekly_start = 0) {
#' @keywords internal
plot_yearly <- function(m, uncertainty = TRUE, yearly_start = 0) {
# Compute yearly seasonality for a Jan 1 - Dec 31 sequence of dates.
days <- seq(set_date('2017-01-01'), by='d', length.out=365) + yearly_start
days <- seq(set_date('2017-01-01'), by='d', length.out=365) + as.difftime(
yearly_start, units = "days")
df.y <- seasonality_plot_df(m, days)
seas <- predict_seasonal_components(m, df.y)
seas$ds <- df.y$ds