這讓我發瘋了，我已經搜索了幾個小時，但在這方面遇到了麻煩。
通常我會在 SQL 中做這樣的事情，但它是 python 模型的一部分，我很難理解變數賦值是如何作業的。
我有一本字典（使用 Facebook Prophet 的 GitHub 中的語法）：
param_grid = {
'changepoint_prior_scale': [.01, 0.05],
'changepoint_range': [0.8, 0.9],
'monthly_fourier': [5, 10],
'monthly_prior_scale': [.01, 0.05],
'daily_fourier': [5, 10],
'daily_prior_scale': [.01, 0.05],
'weekly_fourier': [5, 10],
'weekly_prior_scale': [.01, 0.05],
'yearly_fourier': [5],
'yearly_prior_scale': [.01, 0.05]
}
然后我創建所有引數排列的字典：
# Generate all combinations of parameters
all_params = [dict(zip(param_grid.keys(), v)) for v in itertools.product(*param_grid.values())]
mape = [] # Store the RMSEs for each params here for later
看起來像這樣（供參考）：
print(all_params)
[{'changepoint_prior_scale': 0.01, 'changepoint_range': 0.8, 'monthly_fourier': 5,
'monthly_prior_scale': 0.01, 'daily_fourier': 5, 'daily_prior_scale': 0.01, 'weekly_fourier': 5,
'weekly_prior_scale': 0.01, 'yearly_fourier': 5, 'yearly_prior_scale': 0.01},
{'changepoint_prior_scale': 0.01, 'changepoint_range': 0.8, 'monthly_fourier': 5,
'monthly_prior_scale': 0.01, 'daily_fourier': 5, 'daily_prior_scale': 0.01, 'weekly_fourier': 5,
'weekly_prior_scale': 0.01, 'yearly_fourier': 5, 'yearly_prior_scale': 0.05}....... etc.,]
然后，我想要做的是將每個值傳遞給它對應的模型組件：
for params in all_params:
m = Prophet(
changepoint_prior_scale = all_params['changepoint_prior_scale'],
changepoint_range = all_params['changepoint_range'],
seasonality_mode = 'multiplicative',
growth = 'logistic',
holidays=Holidays,
).add_seasonality(
name='monthly',
period=30.5,
fourier_order = all_params['monthly_fourier'],
prior_scale = all_params['monthly_prior_scale']
).add_seasonality(
name='daily',
period=1,
fourier_order = all_params['daily_fourier'],
prior_scale = all_params['daily_prior_scale']
etc.,
我知道語法一定很奇怪，但我不知道如何將字典的值分配給模型變數。
例如，我希望第一個模型回圈運行這個：
for params in all_params:
m = Prophet(
changepoint_prior_scale = 0.01,
changepoint_range = 0.8,
seasonality_mode = 'multiplicative',
growth = 'logistic',
holidays=Holidays,
).add_seasonality(
name='monthly',
period=30.5,
fourier_order = 5,
prior_scale = .01
).add_seasonality(
name='daily',
period=1,
fourier_order = 5,
prior_scale = .01
etc.,
我確定這是 python 101，希望有人能幫助我指出正確的方向。
uj5u.com熱心網友回復：
你快了！看這里
for params in all_params:
m = Prophet(
changepoint_prior_scale = all_params['changepoint_prior_scale'],
changepoint_range = all_params['changepoint_range'],
seasonality_mode = 'multiplicative',...
請注意，您已制作params但仍在all_params用于訪問！像這樣改變它：
for params in all_params:
m = Prophet(
changepoint_prior_scale = params['changepoint_prior_scale'],
changepoint_range = params['changepoint_range'],
seasonality_mode = 'multiplicative',...
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標籤：Python 字典 for循环 变量 facebook-prophet