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Allow not showing capacity on plots

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Ben Letham 2017-04-10 22:48:43 -07:00
parent 208399678c
commit 8155143af0
5 changed files with 64 additions and 34 deletions
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29
R/R/prophet.R
View file

@ -900,6 +900,8 @@ df_for_plotting <- function(m, fcst) {
#' @param fcst Data frame returned by predict(m, df).
#' @param uncertainty Boolean indicating if the uncertainty interval for yhat
#' should be plotted. 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
#' @param ylabel Optional label for y-axis
#' @param ... additional arguments
@ -917,12 +919,12 @@ df_for_plotting <- function(m, fcst) {
#' }
#'
#' @export
plot.prophet <- function(x, fcst, uncertainty = TRUE, xlabel = 'ds',
ylabel = 'y', ...) {
plot.prophet <- function(x, fcst, uncertainty = TRUE, plot_cap = TRUE,
xlabel = 'ds', ylabel = 'y', ...) {
df <- df_for_plotting(x, fcst)
gg <- ggplot2::ggplot(df, ggplot2::aes(x = ds, y = y)) +
ggplot2::labs(x = xlabel, y = ylabel)
if (exists('cap', where = df)) {
if (exists('cap', where = df) && plot_cap) {
gg <- gg + ggplot2::geom_line(
ggplot2::aes(y = cap), linetype = 'dashed', na.rm = TRUE)
}
@ -949,15 +951,18 @@ plot.prophet <- function(x, fcst, uncertainty = TRUE, xlabel = 'ds',
#' @param fcst Data frame returned by predict(m, df).
#' @param uncertainty Boolean indicating if the uncertainty interval should be
#' 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.
#'
#' @return Invisibly return a list containing the plotted ggplot objects
#'
#' @export
#' @importFrom dplyr "%>%"
prophet_plot_components <- function(m, fcst, uncertainty = TRUE) {
prophet_plot_components <- function(m, fcst, uncertainty = TRUE,
plot_cap = TRUE) {
df <- df_for_plotting(m, fcst)
# Plot the trend
panels <- list(plot_trend(df, uncertainty))
panels <- list(plot_trend(df, uncertainty, plot_cap))
# Plot holiday components, if present.
if (!is.null(m$holidays)) {
panels[[length(panels) + 1]] <- plot_holidays(m, df, uncertainty)
@ -985,13 +990,15 @@ prophet_plot_components <- function(m, fcst, uncertainty = TRUE) {
#'
#' @param df Forecast dataframe for plotting.
#' @param uncertainty Boolean to plot uncertainty intervals.
#' @param plot_cap Boolean indicating if the capacity should be shown in the
#' figure, if available.
#'
#' @return A ggplot2 plot.
plot_trend <- function(df, uncertainty = TRUE) {
plot_trend <- function(df, uncertainty = TRUE, plot_cap = TRUE) {
df.t <- df[!is.na(df$trend),]
gg.trend <- ggplot2::ggplot(df.t, ggplot2::aes(x = ds, y = trend)) +
ggplot2::geom_line(color = "#0072B2", na.rm = TRUE)
if (exists('cap', where = df.t)) {
if (exists('cap', where = df.t) && plot_cap) {
gg.trend <- gg.trend + ggplot2::geom_line(ggplot2::aes(y = cap),
linetype = 'dashed',
na.rm = TRUE)
@ -1046,8 +1053,8 @@ plot_holidays <- function(m, df, uncertainty = TRUE) {
#' @return A ggplot2 plot.
plot_weekly <- function(m, uncertainty = TRUE) {
# 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))
df.w <- data.frame(
ds=seq.Date(zoo::as.Date('2017-01-01'), by='d', length.out=7), 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))
@ -1075,8 +1082,8 @@ plot_weekly <- function(m, uncertainty = TRUE) {
#' @return A ggplot2 plot.
plot_yearly <- function(m, uncertainty = TRUE) {
# Compute yearly seasonality for a Jan 1 - Dec 31 sequence of dates.
df.y <- data.frame(ds=seq.Date(zoo::as.Date('2017-01-01'), by='d',
length.out=365))
df.y <- data.frame(
ds=seq.Date(zoo::as.Date('2017-01-01'), by='d', length.out=365), cap=1.)
df.y <- setup_dataframe(m, df.y)$df
seas <- predict_seasonal_components(m, df.y)
seas$ds <- df.y$ds

7
R/man/plot.prophet.Rd
View file

@ -4,8 +4,8 @@
\alias{plot.prophet}
\title{Plot the prophet forecast.}
\usage{
\method{plot}{prophet}(x, fcst, uncertainty = TRUE, xlabel = "ds",
ylabel = "y", ...)
\method{plot}{prophet}(x, fcst, uncertainty = TRUE, plot_cap = TRUE,
xlabel = "ds", ylabel = "y", ...)
}
\arguments{
\item{x}{Prophet object.}
@ -15,6 +15,9 @@
\item{uncertainty}{Boolean indicating if the uncertainty interval for yhat
should be plotted. Must be present in fcst as yhat_lower and yhat_upper.}
\item{plot_cap}{Boolean indicating if the capacity should be shown in the
figure, if available.}
\item{xlabel}{Optional label for x-axis}
\item{ylabel}{Optional label for y-axis}

5
R/man/plot_trend.Rd
View file

@ -4,12 +4,15 @@
\alias{plot_trend}
\title{Plot the prophet trend.}
\usage{
plot_trend(df, uncertainty = TRUE)
plot_trend(df, uncertainty = TRUE, plot_cap = TRUE)
}
\arguments{
\item{df}{Forecast dataframe for plotting.}
\item{uncertainty}{Boolean to plot uncertainty intervals.}
\item{plot_cap}{Boolean indicating if the capacity should be shown in the
figure, if available.}
}
\value{
A ggplot2 plot.

5
R/man/prophet_plot_components.Rd
View file

@ -6,7 +6,7 @@
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)
prophet_plot_components(m, fcst, uncertainty = TRUE, plot_cap = TRUE)
}
\arguments{
\item{m}{Prophet object.}
@ -15,6 +15,9 @@ prophet_plot_components(m, fcst, uncertainty = TRUE)
\item{uncertainty}{Boolean indicating if the uncertainty interval should be
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.}
}
\value{
Invisibly return a list containing the plotted ggplot objects

52
python/fbprophet/forecaster.py
View file

@ -857,13 +857,16 @@ class Prophet(object):
return pd.DataFrame({'ds': dates})
def plot(self, fcst, uncertainty=True, xlabel='ds', ylabel='y'):
def plot(self, fcst, uncertainty=True, plot_cap=True, xlabel='ds',
ylabel='y'):
"""Plot the Prophet forecast.
Parameters
----------
fcst: pd.DataFrame output of self.predict.
uncertainty: Optional boolean to plot uncertainty intervals.
plot_cap: Optional boolean indicating if the capacity should be shown
in the figure, if available.
xlabel: Optional label name on X-axis
ylabel: Optional label name on Y-axis
@ -875,7 +878,7 @@ class Prophet(object):
ax = fig.add_subplot(111)
ax.plot(self.history['ds'].values, self.history['y'], 'k.')
ax.plot(fcst['ds'].values, fcst['yhat'], ls='-', c='#0072B2')
if 'cap' in fcst:
if 'cap' in fcst and plot_cap:
ax.plot(fcst['ds'].values, fcst['cap'], ls='--', c='k')
if uncertainty:
ax.fill_between(fcst['ds'].values, fcst['yhat_lower'],
@ -887,7 +890,7 @@ class Prophet(object):
fig.tight_layout()
return fig
def plot_components(self, fcst, uncertainty=True):
def plot_components(self, fcst, uncertainty=True, plot_cap=True):
"""Plot the Prophet forecast components.
Will plot whichever are available of: trend, holidays, weekly
@ -897,31 +900,41 @@ class Prophet(object):
----------
fcst: pd.DataFrame output of self.predict.
uncertainty: Optional boolean to plot uncertainty intervals.
plot_cap: Optional boolean indicating if the capacity should be shown
in the figure, if available.
Returns
-------
a matplotlib figure.
"""
# Identify components to be plotted
components = [('plot_trend', True),
('plot_holidays', self.holidays is not None),
('plot_weekly', 'weekly' in fcst),
('plot_yearly', 'yearly' in fcst)]
components = [(plot, cond) for plot, cond in components if cond]
components = [('trend', True),
('holidays', self.holidays is not None),
('weekly', 'weekly' in fcst),
('yearly', 'yearly' in fcst)]
components = [plot for plot, cond in components if cond]
npanel = len(components)
fig, axes = plt.subplots(npanel, 1, facecolor='w',
figsize=(9, 3 * npanel))
artists = []
for ax, plot in zip(axes,
[getattr(self, plot) for plot, _ in components]):
artists += plot(fcst, ax=ax, uncertainty=uncertainty)
for ax, plot in zip(axes, components):
if plot == 'trend':
artists += self.plot_trend(
fcst, ax=ax, uncertainty=uncertainty, plot_cap=plot_cap)
elif plot == 'holidays':
artists += self.plot_holidays(fcst, ax=ax,
uncertainty=uncertainty)
elif plot == 'weekly':
artists += self.plot_weekly(ax=ax, uncertainty=uncertainty)
elif plot == 'yearly':
artists += self.plot_yearly(ax=ax, uncertainty=uncertainty)
fig.tight_layout()
return artists
def plot_trend(self, fcst, ax=None, uncertainty=True):
def plot_trend(self, fcst, ax=None, uncertainty=True, plot_cap=True):
"""Plot the trend component of the forecast.
Parameters
@ -929,6 +942,8 @@ class Prophet(object):
fcst: pd.DataFrame output of self.predict.
ax: Optional matplotlib Axes to plot on.
uncertainty: Optional boolean to plot uncertainty intervals.
plot_cap: Optional boolean indicating if the capacity should be shown
in the figure, if available.
Returns
-------
@ -941,7 +956,7 @@ class Prophet(object):
ax = fig.add_subplot(111)
artists += ax.plot(fcst['ds'].values, fcst['trend'], ls='-',
c='#0072B2')
if 'cap' in fcst:
if 'cap' in fcst and plot_cap:
artists += ax.plot(fcst['ds'].values, fcst['cap'], ls='--', c='k')
if uncertainty:
artists += [ax.fill_between(
@ -988,12 +1003,11 @@ class Prophet(object):
ax.set_ylabel('holidays')
return artists
def plot_weekly(self, fcst, ax=None, uncertainty=True):
def plot_weekly(self, ax=None, uncertainty=True):
"""Plot the weekly component of the forecast.
Parameters
----------
fcst: pd.DataFrame output of self.predict.
ax: Optional matplotlib Axes to plot on. One will be created if this
is not provided.
uncertainty: Optional boolean to plot uncertainty intervals.
@ -1008,7 +1022,7 @@ class Prophet(object):
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)
df_w = pd.DataFrame({'ds': days})
df_w = pd.DataFrame({'ds': days, 'cap': 1.})
df_w = self.setup_dataframe(df_w)
seas = self.predict_seasonal_components(df_w)
days = days.weekday_name
@ -1025,12 +1039,11 @@ class Prophet(object):
ax.set_ylabel('weekly')
return artists
def plot_yearly(self, fcst, ax=None, uncertainty=True):
def plot_yearly(self, ax=None, uncertainty=True):
"""Plot the yearly component of the forecast.
Parameters
----------
fcst: pd.DataFrame output of self.predict.
ax: Optional matplotlib Axes to plot on. One will be created if
this is not provided.
uncertainty: Optional boolean to plot uncertainty intervals.
@ -1044,7 +1057,8 @@ class Prophet(object):
fig = plt.figure(facecolor='w', figsize=(10, 6))
ax = fig.add_subplot(111)
# Compute yearly seasonality for a Jan 1 - Dec 31 sequence of dates.
df_y = pd.DataFrame({'ds': pd.date_range(start='2017-01-01', periods=365)})
df_y = pd.DataFrame(
{'ds': pd.date_range(start='2017-01-01', periods=365), 'cap': 1.})
df_y = self.setup_dataframe(df_y)
seas = self.predict_seasonal_components(df_y)
artists += ax.plot(df_y['ds'], seas['yearly'], ls='-',