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Allow shifting the start date of the weekly seasonality plot

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Ben Letham 2017-04-13 01:51:17 -07:00
parent d937f47612
commit cacfdc635e
4 changed files with 35 additions and 10 deletions
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15
R/R/prophet.R
View file

@ -987,13 +987,16 @@ plot.prophet <- function(x, fcst, uncertainty = TRUE, plot_cap = TRUE,
#' plotted for the trend, from fcst columns trend_lower and trend_upper.
#' @param plot_cap Boolean indicating if the capacity should be shown in the
#' figure, if available.
#' @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.
#'
#' @return Invisibly return a list containing the plotted ggplot objects
#'
#' @export
#' @importFrom dplyr "%>%"
prophet_plot_components <- function(m, fcst, uncertainty = TRUE,
plot_cap = TRUE) {
plot_cap = TRUE, weekly_start = 0) {
df <- df_for_plotting(m, fcst)
# Plot the trend
panels <- list(plot_trend(df, uncertainty, plot_cap))
@ -1003,7 +1006,7 @@ prophet_plot_components <- function(m, fcst, uncertainty = TRUE,
}
# Plot weekly seasonality, if present
if ("weekly" %in% colnames(df)) {
panels[[length(panels) + 1]] <- plot_weekly(m, uncertainty)
panels[[length(panels) + 1]] <- plot_weekly(m, uncertainty, weekly_start)
}
# Plot yearly seasonality, if present
if ("yearly" %in% colnames(df)) {
@ -1083,12 +1086,16 @@ plot_holidays <- function(m, df, uncertainty = TRUE) {
#'
#' @param m Prophet model object
#' @param uncertainty Boolean to plot uncertainty intervals.
#' @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.
#'
#' @return A ggplot2 plot.
plot_weekly <- function(m, uncertainty = TRUE) {
plot_weekly <- function(m, uncertainty = TRUE, weekly_start = 0) {
# Compute weekly seasonality for a Sun-Sat sequence of dates.
df.w <- data.frame(
ds=seq.Date(zoo::as.Date('2017-01-01'), by='d', length.out=7), cap=1.)
ds=seq.Date(zoo::as.Date('2017-01-01'), by='d', length.out=7) +
weekly_start, cap=1.)
df.w <- setup_dataframe(m, df.w)$df
seas <- predict_seasonal_components(m, df.w)
seas$dow <- factor(weekdays(df.w$ds), levels=weekdays(df.w$ds))

6
R/man/plot_weekly.Rd
View file

@ -4,12 +4,16 @@
\alias{plot_weekly}
\title{Plot the weekly component of the forecast.}
\usage{
plot_weekly(m, uncertainty = TRUE)
plot_weekly(m, uncertainty = TRUE, weekly_start = 0)
}
\arguments{
\item{m}{Prophet model object}
\item{uncertainty}{Boolean to plot uncertainty intervals.}
\item{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.}
}
\value{
A ggplot2 plot.

7
R/man/prophet_plot_components.Rd
View file

@ -6,7 +6,8 @@
Prints a ggplot2 with panels for trend, weekly and yearly seasonalities if
present, and holidays if present.}
\usage{
prophet_plot_components(m, fcst, uncertainty = TRUE, plot_cap = TRUE)
prophet_plot_components(m, fcst, uncertainty = TRUE, plot_cap = TRUE,
weekly_start = 0)
}
\arguments{
\item{m}{Prophet object.}
@ -18,6 +19,10 @@ plotted for the trend, from fcst columns trend_lower and trend_upper.}
\item{plot_cap}{Boolean indicating if the capacity should be shown in the
figure, if available.}
\item{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.}
}
\value{
Invisibly return a list containing the plotted ggplot objects

17
python/fbprophet/forecaster.py
View file

@ -914,7 +914,8 @@ class Prophet(object):
fig.tight_layout()
return fig
def plot_components(self, fcst, uncertainty=True, plot_cap=True):
def plot_components(self, fcst, uncertainty=True, plot_cap=True,
weekly_start=0):
"""Plot the Prophet forecast components.
Will plot whichever are available of: trend, holidays, weekly
@ -926,6 +927,9 @@ class Prophet(object):
uncertainty: Optional boolean to plot uncertainty intervals.
plot_cap: Optional boolean indicating if the capacity should be shown
in the figure, if available.
weekly_start: Optional int 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.
Returns
-------
@ -951,7 +955,8 @@ class Prophet(object):
artists += self.plot_holidays(fcst, ax=ax,
uncertainty=uncertainty)
elif plot == 'weekly':
artists += self.plot_weekly(ax=ax, uncertainty=uncertainty)
artists += self.plot_weekly(ax=ax, uncertainty=uncertainty,
weekly_start=weekly_start)
elif plot == 'yearly':
artists += self.plot_yearly(ax=ax, uncertainty=uncertainty)
@ -1027,7 +1032,7 @@ class Prophet(object):
ax.set_ylabel('holidays')
return artists
def plot_weekly(self, ax=None, uncertainty=True):
def plot_weekly(self, ax=None, uncertainty=True, weekly_start=0):
"""Plot the weekly component of the forecast.
Parameters
@ -1035,6 +1040,9 @@ class Prophet(object):
ax: Optional matplotlib Axes to plot on. One will be created if this
is not provided.
uncertainty: Optional boolean to plot uncertainty intervals.
weekly_start: Optional int 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.
Returns
-------
@ -1045,7 +1053,8 @@ class Prophet(object):
fig = plt.figure(facecolor='w', figsize=(10, 6))
ax = fig.add_subplot(111)
# Compute weekly seasonality for a Sun-Sat sequence of dates.
days = pd.date_range(start='2017-01-01', periods=7)
days = (pd.date_range(start='2017-01-01', periods=7) +
pd.Timedelta(days=weekly_start))
df_w = pd.DataFrame({'ds': days, 'cap': 1.})
df_w = self.setup_dataframe(df_w)
seas = self.predict_seasonal_components(df_w)