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我正在尝试在 Python 中使用 htsprophet 包。我正在使用下面的示例代码。此示例来自https://github.com/CollinRooney12/htsprophet/blob/master/htsprophet/runHTS.py。我得到的问题是 ValueError "holidays must be a DataFrame with 'ds' and 'holiday' column。我想知道是否有解决方法，因为我显然有一个数据框假期，其中包含 ds 和假期两列。我相信错误来自预测器文件中 fbprophet 的依赖包之一。我想知道是否有任何我需要添加的东西，或者是否有人添加了一些东西来解决这个问题。

import pandas as pd
from htsprophet.hts import hts, orderHier, makeWeekly
from htsprophet.htsPlot import plotNode, plotChild, plotNodeComponents
import numpy as np

#%% Random data (Change this to whatever data you want)
date = pd.date_range("2015-04-02", "2017-07-17")
date = np.repeat(date, 10)
medium = ["Air", "Land", "Sea"]
businessMarket = ["Birmingham","Auburn","Evanston"]
platform = ["Stone Tablet","Car Phone"]
mediumDat = np.random.choice(medium, len(date))
busDat = np.random.choice(businessMarket, len(date))
platDat = np.random.choice(platform, len(date))
sessions = np.random.randint(1000,10000,size=(len(date),1))
data = pd.DataFrame(date, columns = ["day"])
data["medium"] = mediumDat
data["platform"] = platDat
data["businessMarket"] = busDat
data["sessions"] = sessions

#%% Run HTS
##
# Make the daily data weekly (optional)
##
data1 = makeWeekly(data)
##
# Put the data in the format to run HTS, and get the nodes input (a list of list that describes the hierarchical structure)
##
data2, nodes = orderHier(data, 1, 2, 3)
##
# load in prophet inputs (Running HTS runs prophet, so all inputs should be gathered beforehand)
# Made up holiday data
##
holidates = pd.date_range("12/25/2013","12/31/2017", freq = 'A')
holidays = pd.DataFrame(["Christmas"]*5, columns = ["holiday"])
holidays["ds"] = holidates
holidays["lower_window"] = [-4]*5
holidays["upper_window"] = [0]*5
##
# Run hts with the CVselect function (this decides which hierarchical aggregation method to use based on minimum mean Mean Absolute Scaled Error)
# h (which is 12 here) - how many steps ahead you would like to forecast.  If youre using daily data you don't have to specify freq.
#
# NOTE: CVselect takes a while, so if you want results in minutes instead of half-hours pick a different method
##
myDict = hts(data2, 52, nodes, holidays = holidays, method = "FP", transform = "BoxCox")
##
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问题出在带有“fitForecast.py”文件的 htsProphet 包中。fbProphet 对象的实例化仅依赖于位置参数，但是添加到 fbProphet 类中的新参数。这意味着参数不再对应。

您可以通过破解 fbProphet 模块并将位置参数更改为关键字参数来解决此问题，只需修复“73-74”行就足以让它运行：

Prophet(growth=growth, changepoints=changepoints1, n_changepoints=n_changepoints1, yearly_seasonality=yearly_seasonality, weekly_seasonality=weekly_seasonality, holidays=holidays, seasonality_prior_scale=seasonality_prior_scale, \
                            holidays_prior_scale=holidays_prior_scale, changepoint_prior_scale=changepoint_prior_scale, mcmc_samples=mcmc_samples, interval_width=interval_width, uncertainty_samples=uncertainty_samples)

我会为此向创建者提交一个错误。

于 2018-07-18T11:11:45.977 回答