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Allow _ in holiday name, fix #50

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This commit is contained in:
Ben Letham 2017-03-02 16:36:00 +02:00
parent 5cec062fce
commit 4b7a418121
2 changed files with 21 additions and 11 deletions
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10
R/R/prophet.R
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@ -134,8 +134,8 @@ validate_inputs <- function(m) {
stop('Holidays dataframe must have ds field.')
}
for (h in unique(m$holidays$holiday)) {
if (grepl("_", h)) {
stop('Holiday name cannot contain "_"')
if (grepl("_delim_", h)) {
stop('Holiday name cannot contain "_delim_"')
}
if (h %in% c('zeros', 'yearly', 'weekly', 'yhat', 'seasonal', 'trend')) {
stop(paste0('Holiday name "', h, '" reserved.'))
@ -306,7 +306,7 @@ fourier_series <- function(dates, period, series.order) {
#'
make_seasonality_features <- function(dates, period, series.order, prefix) {
features <- fourier_series(dates, period, series.order)
colnames(features) <- paste(prefix, 1:ncol(features), sep = '_')
colnames(features) <- paste(prefix, 1:ncol(features), sep = '_delim_')
return(data.frame(features))
}
@ -332,7 +332,7 @@ make_holiday_features <- function(m, dates) {
offsets <- c(0)
}
names <- paste(
.$holiday, '_', ifelse(offsets < 0, '-', '+'), abs(offsets), sep = '')
.$holiday, '_delim_', ifelse(offsets < 0, '-', '+'), abs(offsets), sep = '')
dplyr::data_frame(ds = .$ds + offsets, holiday = names)
}) %>%
dplyr::mutate(x = scale.ratio) %>%
@ -650,7 +650,7 @@ predict_seasonal_components <- function(m, df) {
# Broken down into components
components <- dplyr::data_frame(component = colnames(seasonal.features)) %>%
dplyr::mutate(col = 1:n()) %>%
tidyr::separate(component, c('component', 'part'), sep = "_",
tidyr::separate(component, c('component', 'part'), sep = "_delim_",
extra = "merge", fill = "right") %>%
dplyr::filter(component != 'zeros')

22
python/fbprophet/forecaster.py
View file

@ -49,9 +49,6 @@ class Prophet(object):
interval_width=0.80,
uncertainty_samples=1000,
):
if growth not in ('linear', 'logistic'):
raise ValueError("growth setting must be 'linear' or 'logistic'")
self.growth = growth
self.changepoints = pd.to_datetime(changepoints)
@ -90,6 +87,19 @@ class Prophet(object):
self.stan_fit = None
self.params = {}
self.history = None
self.validate_inputs()
def validate_inputs(self):
if self.growth not in ('linear', 'logistic'):
raise ValueError(
"Parameter 'growth' should be 'linear' or 'logistic'.")
if self.holidays is not None:
for h in self.holidays['holiday'].unique():
if '_delim_' in h:
raise ValueError('Holiday name cannot contain "_delim_"')
if h in ['zeros', 'yearly', 'weekly', 'yhat', 'seasonal',
'trend']:
raise ValueError('Holiday name {} reserved.'.format(h))
@classmethod
def get_linear_model(cls):
@ -215,7 +225,7 @@ class Prophet(object):
def make_seasonality_features(cls, dates, period, series_order, prefix):
features = cls.fourier_series(dates, period, series_order)
columns = [
'{}_{}'.format(prefix, i + 1)
'{}_delim_{}'.format(prefix, i + 1)
for i in range(features.shape[1])
]
return pd.DataFrame(features, columns=columns)
@ -245,7 +255,7 @@ class Prophet(object):
except KeyError:
loc = None
key = '{}_{}{}'.format(
key = '{}_delim_{}{}'.format(
row.holiday,
'+' if offset >= 0 else '-',
abs(offset)
@ -469,7 +479,7 @@ class Prophet(object):
components = pd.DataFrame({
'col': np.arange(seasonal_features.shape[1]),
'component': [x.split('_')[0] for x in seasonal_features.columns],
'component': [x.split('_delim_')[0] for x in seasonal_features.columns],
})
# Remove the placeholder
components = components[components['component'] != 'zeros']