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Fix type casting for extra regressors, and a shape issue

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This commit is contained in:
Ben Letham 2018-12-03 15:22:19 -08:00
parent 91917df8f0
commit 13d96cff8f
2 changed files with 17 additions and 22 deletions
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8
R/R/prophet.R
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@ -357,6 +357,10 @@ setup_dataframe <- function(m, df, initialize_scales = FALSE) {
if (!(name %in% colnames(df))) {
stop('Regressor "', name, '" missing from dataframe')
}
df[[name]] <- as.numeric(df[[name]])
if (anyNA(df[[name]])) {
stop('Found NaN in column ', name)
}
}
df <- df %>%
@ -386,12 +390,8 @@ setup_dataframe <- function(m, df, initialize_scales = FALSE) {
}
for (name in names(m$extra_regressors)) {
df[[name]] <- as.numeric(df[[name]])
props <- m$extra_regressors[[name]]
df[[name]] <- (df[[name]] - props$mu) / props$std
if (anyNA(df[[name]])) {
stop('Found NaN in column ', name)
}
}
return(list("m" = m, "df" = df))
}

31
python/fbprophet/forecaster.py
View file

@ -15,6 +15,7 @@ from datetime import timedelta
import logging
import numpy as np
import pandas as pd
import pystan # noqa F401
from fbprophet.diagnostics import prophet_copy
@ -33,11 +34,6 @@ from fbprophet.plot import (
logging.basicConfig()
logger = logging.getLogger(__name__)
try:
import pystan # noqa F401
except ImportError:
logger.exception('You cannot run fbprophet without pystan installed')
class Prophet(object):
"""Prophet forecaster.
@ -160,13 +156,13 @@ class Prophet(object):
raise ValueError("Parameter 'changepoint_range' must be in [0, 1]")
if self.holidays is not None:
if not (
isinstance(holidays, pd.DataFrame)
and 'ds' in holidays # noqa W503
and 'holiday' in holidays # noqa W503
isinstance(self.holidays, pd.DataFrame)
and 'ds' in self.holidays # noqa W503
and 'holiday' in self.holidays # noqa W503
):
raise ValueError("holidays must be a DataFrame with 'ds' and "
"'holiday' columns.")
holidays['ds'] = pd.to_datetime(holidays['ds'])
self.holidays['ds'] = pd.to_datetime(self.holidays['ds'])
has_lower = 'lower_window' in self.holidays
has_upper = 'upper_window' in self.holidays
if has_lower + has_upper == 1:
@ -253,6 +249,9 @@ class Prophet(object):
if name not in df:
raise ValueError(
'Regressor "{}" missing from dataframe'.format(name))
df[name] = pd.to_numeric(df[name])
if df[name].isnull().any():
raise ValueError('Found NaN in column ' + name)
df = df.sort_values('ds')
df.reset_index(inplace=True, drop=True)
@ -277,10 +276,7 @@ class Prophet(object):
df['y_scaled'] = (df['y'] - df['floor']) / self.y_scale
for name, props in self.extra_regressors.items():
df[name] = pd.to_numeric(df[name])
df[name] = ((df[name] - props['mu']) / props['std'])
if df[name].isnull().any():
raise ValueError('Found NaN in column ' + name)
return df
def initialize_scales(self, initialize_scales, df):
@ -1092,6 +1088,9 @@ class Prophet(object):
)
for par in stan_fit.model_pars:
self.params[par] = stan_fit[par]
# Shape vector parameters
if par in ['delta', 'beta'] and len(self.params[par].shape) < 2:
self.params[par] = self.params[par].reshape((-1, 1))
else:
try:
params = model.optimizing(
@ -1102,12 +1101,8 @@ class Prophet(object):
dat, init=stan_init, iter=1e4, algorithm='Newton',
**kwargs
)
self.params = params
# Reshape all parameters to matrix shape
for p, v in self.params.items():
if len(v.shape) == 1:
self.params[p] = v.reshape((-1, 1))
for par in params:
self.params[par] = params[par].reshape((1, -1))
# If no changepoints were requested, replace delta with 0s
if len(self.changepoints) == 0: