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@@ -2,7 +2,7 @@
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# All rights reserved.
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#
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# This source code is licensed under the BSD-style license found in the
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-# LICENSE file in the root directory of this source tree. An additional grant
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+# LICENSE file in the root directory of this source tree. An additional grant
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# of patent rights can be found in the PATENTS file in the same directory.
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from __future__ import absolute_import
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@@ -36,6 +36,7 @@ except ImportError:
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class Prophet(object):
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# Plotting default color for R/Python consistency
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forecast_color = '#0072B2'
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+
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def __init__(
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self,
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growth='linear',
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@@ -180,7 +181,6 @@ class Prophet(object):
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else:
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self.changepoints_t = np.array([0]) # dummy changepoint
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-
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def get_changepoint_matrix(self):
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A = np.zeros((self.history.shape[0], len(self.changepoints_t)))
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for i, t_i in enumerate(self.changepoints_t):
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@@ -261,7 +261,6 @@ class Prophet(object):
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# This relies pretty importantly on pandas keeping the columns in order.
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return pd.DataFrame(expanded_holidays)
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-
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def make_all_seasonality_features(self, df):
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seasonal_features = [
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# Add a column of zeros in case no seasonality is used.
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@@ -626,7 +625,8 @@ class Prophet(object):
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ax.plot(fcst['ds'].values, fcst['cap'], ls='--', c='k')
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if uncertainty:
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ax.fill_between(fcst['ds'].values, fcst['yhat_lower'],
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- fcst['yhat_upper'], color=self.forecast_color, alpha=0.2)
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+ fcst['yhat_upper'], color=self.forecast_color,
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+ alpha=0.2)
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ax.grid(True, which='major', c='gray', ls='-', lw=1, alpha=0.2)
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ax.set_xlabel(xlabel)
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ax.set_ylabel(ylabel)
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@@ -655,21 +655,24 @@ class Prophet(object):
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('plot_yearly', 'yearly' in fcst)]
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components = [(plot, cond) for plot, cond in components if cond]
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npanel = len(components)
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-
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- fig, axes = plt.subplots(npanel, 1, facecolor='w', figsize=(9, 3 * npanel))
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+
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+ fig, axes = plt.subplots(npanel, 1, facecolor='w',
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+ figsize=(9, 3 * npanel))
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artists = []
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- for ax, plot in zip(axes, [getattr(self, plot) for plot, _ in components]):
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+ for ax, plot in zip(axes,
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+ [getattr(self, plot) for plot, _ in components]):
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artists += plot(fcst, ax=ax, uncertainty=uncertainty)
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-
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+
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fig.tight_layout()
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return artists
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-
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+
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def plot_trend(self, fcst, ax=None, uncertainty=True, **plotargs):
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artists = []
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if not ax:
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ax = fig.add_subplot(111)
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- artists += ax.plot(fcst['ds'].values, fcst['trend'], ls='-', c=self.forecast_color)
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+ artists += ax.plot(fcst['ds'].values, fcst['trend'], ls='-',
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+ c=self.forecast_color)
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if 'cap' in fcst:
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artists += ax.plot(fcst['ds'].values, fcst['cap'], ls='--', c='k')
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if uncertainty:
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@@ -682,7 +685,6 @@ class Prophet(object):
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ax.set_ylabel('trend')
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return artists
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-
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def plot_holidays(self, fcst, ax=None, uncertainty=True):
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artists = []
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if not ax:
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@@ -694,10 +696,12 @@ class Prophet(object):
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# NOTE the above CI calculation is incorrect if holidays overlap
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# in time. Since it is just for the visualization we will not
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# worry about it now.
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- artists += ax.plot(fcst['ds'].values, y_holiday, ls='-', c=self.forecast_color)
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+ artists += ax.plot(fcst['ds'].values, y_holiday, ls='-',
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+ c=self.forecast_color)
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if uncertainty:
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- artists += [ax.fill_between(fcst['ds'].values, y_holiday_l, y_holiday_u,
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- color=self.forecast_color, alpha=0.2)]
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+ artists += [ax.fill_between(fcst['ds'].values,
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+ y_holiday_l, y_holiday_u,
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+ color=self.forecast_color, alpha=0.2)]
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ax.grid(True, which='major', c='gray', ls='-', lw=1, alpha=0.2)
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ax.xaxis.set_major_locator(MaxNLocator(nbins=7))
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ax.set_xlabel('ds')
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@@ -715,10 +719,12 @@ class Prophet(object):
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y_weekly = [df_s.loc[d]['weekly'] for d in days]
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y_weekly_l = [df_s.loc[d]['weekly_lower'] for d in days]
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y_weekly_u = [df_s.loc[d]['weekly_upper'] for d in days]
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- artists += ax.plot(range(len(days)), y_weekly, ls='-', c=self.forecast_color)
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+ artists += ax.plot(range(len(days)), y_weekly, ls='-',
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+ c=self.forecast_color)
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if uncertainty:
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- artists += [ax.fill_between(range(len(days)), y_weekly_l, y_weekly_u,
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- color=self.forecast_color, alpha=0.2)]
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+ artists += [ax.fill_between(range(len(days)),
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+ y_weekly_l, y_weekly_u,
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+ color=self.forecast_color, alpha=0.2)]
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ax.grid(True, which='major', c='gray', ls='-', lw=1, alpha=0.2)
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ax.set_xticks(range(len(days)))
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ax.set_xticklabels(days)
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@@ -734,7 +740,7 @@ class Prophet(object):
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df_s['doy'] = df_s['ds'].map(lambda x: x.strftime('2000-%m-%d'))
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df_s = df_s.groupby('doy').first().sort_index()
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artists += ax.plot(pd.to_datetime(df_s.index), df_s['yearly'], ls='-',
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- c=self.forecast_color)
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+ c=self.forecast_color)
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if uncertainty:
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artists += [ax.fill_between(
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pd.to_datetime(df_s.index), df_s['yearly_lower'],
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@@ -748,5 +754,4 @@ class Prophet(object):
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return artists
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-
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# fb-block 9
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Isaac Laughlin