mirror of
https://github.com/saymrwulf/prophet.git
synced 2026-07-30 20:18:11 +00:00
Figsize argument (#706)
* Add 'figsize' argument to all plotting methods * Add docstrings for 'figsize' arguments
This commit is contained in:
Florian Schäfer
Ben Letham
parent
95fa4460a9
commit
55ca33891e
1 changed files with 26 additions and 16 deletions
|
|
@ -31,6 +31,7 @@ except ImportError:
|
|||
|
||||
def plot(
|
||||
m, fcst, ax=None, uncertainty=True, plot_cap=True, xlabel='ds', ylabel='y',
|
||||
figsize=(10, 6)
|
||||
):
|
||||
"""Plot the Prophet forecast.
|
||||
|
||||
|
|
@ -44,13 +45,14 @@ def plot(
|
|||
in the figure, if available.
|
||||
xlabel: Optional label name on X-axis
|
||||
ylabel: Optional label name on Y-axis
|
||||
figsize: Optional tuple width, height in inches.
|
||||
|
||||
Returns
|
||||
-------
|
||||
A matplotlib figure.
|
||||
"""
|
||||
if ax is None:
|
||||
fig = plt.figure(facecolor='w', figsize=(10, 6))
|
||||
fig = plt.figure(facecolor='w', figsize)
|
||||
ax = fig.add_subplot(111)
|
||||
else:
|
||||
fig = ax.get_figure()
|
||||
|
|
@ -73,6 +75,7 @@ def plot(
|
|||
|
||||
def plot_components(
|
||||
m, fcst, uncertainty=True, plot_cap=True, weekly_start=0, yearly_start=0,
|
||||
figsize=None
|
||||
):
|
||||
"""Plot the Prophet forecast components.
|
||||
|
||||
|
|
@ -93,6 +96,7 @@ def plot_components(
|
|||
yearly_start: Optional int 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.
|
||||
figsize: Optional tuple width, height in inches.
|
||||
|
||||
Returns
|
||||
-------
|
||||
|
|
@ -112,8 +116,8 @@ def plot_components(
|
|||
components.append('extra_regressors_{}'.format(mode))
|
||||
npanel = len(components)
|
||||
|
||||
fig, axes = plt.subplots(npanel, 1, facecolor='w',
|
||||
figsize=(9, 3 * npanel))
|
||||
figsize = figsize if figsize else (9, 3 * npanel)
|
||||
fig, axes = plt.subplots(npanel, 1, facecolor='w', figsize=figsize)
|
||||
|
||||
if npanel == 1:
|
||||
axes = [axes]
|
||||
|
|
@ -158,7 +162,7 @@ def plot_components(
|
|||
|
||||
|
||||
def plot_forecast_component(
|
||||
m, fcst, name, ax=None, uncertainty=True, plot_cap=False,
|
||||
m, fcst, name, ax=None, uncertainty=True, plot_cap=False, figsize=(10, 6)
|
||||
):
|
||||
"""Plot a particular component of the forecast.
|
||||
|
||||
|
|
@ -171,6 +175,7 @@ def plot_forecast_component(
|
|||
uncertainty: Optional boolean to plot uncertainty intervals.
|
||||
plot_cap: Optional boolean indicating if the capacity should be shown
|
||||
in the figure, if available.
|
||||
figsize: Optional tuple width, height in inches.
|
||||
|
||||
Returns
|
||||
-------
|
||||
|
|
@ -178,7 +183,7 @@ def plot_forecast_component(
|
|||
"""
|
||||
artists = []
|
||||
if not ax:
|
||||
fig = plt.figure(facecolor='w', figsize=(10, 6))
|
||||
fig = plt.figure(facecolor='w', figsize=figsize)
|
||||
ax = fig.add_subplot(111)
|
||||
fcst_t = fcst['ds'].dt.to_pydatetime()
|
||||
artists += ax.plot(fcst_t, fcst[name], ls='-', c='#0072B2')
|
||||
|
|
@ -218,7 +223,7 @@ def seasonality_plot_df(m, ds):
|
|||
return df
|
||||
|
||||
|
||||
def plot_weekly(m, ax=None, uncertainty=True, weekly_start=0):
|
||||
def plot_weekly(m, ax=None, uncertainty=True, weekly_start=0, figsize=(10, 6)):
|
||||
"""Plot the weekly component of the forecast.
|
||||
|
||||
Parameters
|
||||
|
|
@ -230,6 +235,7 @@ def plot_weekly(m, ax=None, uncertainty=True, weekly_start=0):
|
|||
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.
|
||||
figsize: Optional tuple width, height in inches.
|
||||
|
||||
Returns
|
||||
-------
|
||||
|
|
@ -237,7 +243,7 @@ def plot_weekly(m, ax=None, uncertainty=True, weekly_start=0):
|
|||
"""
|
||||
artists = []
|
||||
if not ax:
|
||||
fig = plt.figure(facecolor='w', figsize=(10, 6))
|
||||
fig = plt.figure(facecolor='w', figsize=figsize)
|
||||
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) +
|
||||
|
|
@ -261,7 +267,7 @@ def plot_weekly(m, ax=None, uncertainty=True, weekly_start=0):
|
|||
return artists
|
||||
|
||||
|
||||
def plot_yearly(m, ax=None, uncertainty=True, yearly_start=0):
|
||||
def plot_yearly(m, ax=None, uncertainty=True, yearly_start=0, figsize=(10, 6)):
|
||||
"""Plot the yearly component of the forecast.
|
||||
|
||||
Parameters
|
||||
|
|
@ -273,6 +279,7 @@ def plot_yearly(m, ax=None, uncertainty=True, yearly_start=0):
|
|||
yearly_start: Optional int 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.
|
||||
figsize: Optional tuple width, height in inches.
|
||||
|
||||
Returns
|
||||
-------
|
||||
|
|
@ -280,7 +287,7 @@ def plot_yearly(m, ax=None, uncertainty=True, yearly_start=0):
|
|||
"""
|
||||
artists = []
|
||||
if not ax:
|
||||
fig = plt.figure(facecolor='w', figsize=(10, 6))
|
||||
fig = plt.figure(facecolor='w', figsize=figsize)
|
||||
ax = fig.add_subplot(111)
|
||||
# Compute yearly seasonality for a Jan 1 - Dec 31 sequence of dates.
|
||||
days = (pd.date_range(start='2017-01-01', periods=365) +
|
||||
|
|
@ -305,7 +312,7 @@ def plot_yearly(m, ax=None, uncertainty=True, yearly_start=0):
|
|||
return artists
|
||||
|
||||
|
||||
def plot_seasonality(m, name, ax=None, uncertainty=True):
|
||||
def plot_seasonality(m, name, ax=None, uncertainty=True, figsize=(10, 6)):
|
||||
"""Plot a custom seasonal component.
|
||||
|
||||
Parameters
|
||||
|
|
@ -315,6 +322,7 @@ def plot_seasonality(m, name, ax=None, uncertainty=True):
|
|||
ax: Optional matplotlib Axes to plot on. One will be created if
|
||||
this is not provided.
|
||||
uncertainty: Optional boolean to plot uncertainty intervals.
|
||||
figsize: Optional tuple width, height in inches.
|
||||
|
||||
Returns
|
||||
-------
|
||||
|
|
@ -322,7 +330,7 @@ def plot_seasonality(m, name, ax=None, uncertainty=True):
|
|||
"""
|
||||
artists = []
|
||||
if not ax:
|
||||
fig = plt.figure(facecolor='w', figsize=(10, 6))
|
||||
fig = plt.figure(facecolor='w', figsize=figsize)
|
||||
ax = fig.add_subplot(111)
|
||||
# Compute seasonality from Jan 1 through a single period.
|
||||
start = pd.to_datetime('2017-01-01 0000')
|
||||
|
|
@ -368,11 +376,11 @@ def add_changepoints_to_plot(
|
|||
ax, m, fcst, threshold=0.01, cp_color='r', cp_linestyle='--', trend=True,
|
||||
):
|
||||
"""Add markers for significant changepoints to prophet forecast plot.
|
||||
|
||||
|
||||
Example:
|
||||
fig = m.plot(forecast)
|
||||
add_changepoints_to_plot(fig.gca(), m, forecast)
|
||||
|
||||
|
||||
Parameters
|
||||
----------
|
||||
ax: axis on which to overlay changepoint markers.
|
||||
|
|
@ -382,7 +390,7 @@ def add_changepoints_to_plot(
|
|||
cp_color: Color of changepoint markers.
|
||||
cp_linestyle: Linestyle for changepoint markers.
|
||||
trend: If True, will also overlay the trend.
|
||||
|
||||
|
||||
Returns
|
||||
-------
|
||||
a list of matplotlib artists
|
||||
|
|
@ -398,7 +406,9 @@ def add_changepoints_to_plot(
|
|||
return artists
|
||||
|
||||
|
||||
def plot_cross_validation_metric(df_cv, metric, rolling_window=0.1, ax=None):
|
||||
def plot_cross_validation_metric(
|
||||
df_cv, metric, rolling_window=0.1, ax=None, figsize=(10, 6)
|
||||
):
|
||||
"""Plot a performance metric vs. forecast horizon from cross validation.
|
||||
|
||||
Cross validation produces a collection of out-of-sample model predictions
|
||||
|
|
@ -431,7 +441,7 @@ def plot_cross_validation_metric(df_cv, metric, rolling_window=0.1, ax=None):
|
|||
a matplotlib figure.
|
||||
"""
|
||||
if ax is None:
|
||||
fig = plt.figure(facecolor='w', figsize=(10, 6))
|
||||
fig = plt.figure(facecolor='w', figsize=figsize)
|
||||
ax = fig.add_subplot(111)
|
||||
else:
|
||||
fig = ax.get_figure()
|
||||
|
|
|
|||
Loading…
Reference in a new issue