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