| リビジョン | c62d3ddc87005d128bf2a21002fa74d9f1c2e2c8 (tree) |
|---|---|
| 日時 | 2022-11-24 04:08:53 |
| 作者 | Lorenzo Isella <lorenzo.isella@gmai...> |
| コミッター | Lorenzo Isella |
A parallelized and faster version of the code.
R-codes/arima_simple1_parallel.R (diff)| @@ -9,7 +9,6 @@ | ||
| 9 | 9 | library(timetk) # for `tk_ts` |
| 10 | 10 | library(tictoc) |
| 11 | 11 | library(openxlsx) |
| 12 | -## library(workflowsets) | |
| 13 | 12 | library(furrr) |
| 14 | 13 | |
| 15 | 14 | tidymodels_prefer() |
| @@ -58,7 +57,9 @@ | ||
| 58 | 57 | |
| 59 | 58 | |
| 60 | 59 | |
| 60 | +tic() | |
| 61 | 61 | |
| 62 | +set.seed(1234) | |
| 62 | 63 | |
| 63 | 64 | |
| 64 | 65 | plan(multisession, workers = 4) |
| @@ -82,69 +83,46 @@ | ||
| 82 | 83 | pull(geo) |> |
| 83 | 84 | su() |
| 84 | 85 | |
| 85 | -ms_list <- c("DE", "AT", "FI") | |
| 86 | - | |
| 86 | +## ms_list <- c("DE", "AT", "FI") | |
| 87 | 87 | |
| 88 | -tic() | |
| 89 | - | |
| 90 | -out.total <- c() | |
| 88 | +ms_data <- future_map(ms_list, extract_ms_data ) | |
| 91 | 89 | |
| 92 | 90 | |
| 93 | -set.seed(1234) | |
| 94 | - | |
| 95 | - | |
| 96 | - | |
| 97 | - | |
| 98 | -ms_data <- map(ms_list, extract_ms_data ) | |
| 99 | - | |
| 100 | - | |
| 101 | -splits_parallel <- map( ms_data, | |
| 91 | +splits_parallel <- future_map( ms_data, | |
| 102 | 92 | function(x) time_series_split(x, assess = "3 months", cumulative = TRUE) |
| 103 | 93 | ) |
| 104 | 94 | |
| 105 | 95 | |
| 106 | 96 | |
| 107 | 97 | |
| 108 | -model_fit_arima_parallel <- map(splits_parallel, function(x) arima_parallel(x)) | |
| 98 | +model_fit_arima_parallel <- future_map(splits_parallel, function(x) arima_parallel(x)) | |
| 109 | 99 | |
| 110 | 100 | |
| 111 | -model_table_parallel <-map(model_fit_arima_parallel, modeltime_table) | |
| 101 | +model_table_parallel <-future_map(model_fit_arima_parallel, modeltime_table) | |
| 112 | 102 | |
| 113 | -## calibration_table_parallel <- map2( model_table, | |
| 114 | - | |
| 115 | -## modeltime_calibrate(testing(splits))) | |
| 116 | 103 | |
| 117 | -testing_splits <- map(splits_parallel,testing ) | |
| 104 | +testing_splits <- future_map(splits_parallel,testing ) | |
| 118 | 105 | |
| 119 | -calibration_table_parallel <- map2( model_table_parallel, | |
| 106 | +calibration_table_parallel <- future_map2( model_table_parallel, | |
| 120 | 107 | testing_splits, modeltime_calibrate |
| 121 | 108 | ) |
| 122 | 109 | |
| 123 | -refit_parallel <-map2( calibration_table_parallel, ms_data, | |
| 110 | +refit_parallel <-future_map2( calibration_table_parallel, ms_data, | |
| 124 | 111 | modeltime_refit |
| 125 | 112 | ) |
| 126 | 113 | |
| 127 | 114 | |
| 128 | -new_forecast_parallel <- map2(refit_parallel, ms_data, | |
| 115 | +new_forecast_parallel <- future_map2(refit_parallel, ms_data, | |
| 129 | 116 | function(x,y) modeltime_forecast(x,h = "3 months", actual_data = y) |
| 130 | 117 | ) |
| 131 | 118 | |
| 132 | 119 | |
| 133 | 120 | |
| 134 | -out.total <- map2_df(new_forecast_parallel, ms_list, extract_results) | |
| 135 | - | |
| 121 | +out.total <- future_map2_dfr(new_forecast_parallel, ms_list, extract_results) | |
| 136 | 122 | |
| 137 | 123 | |
| 138 | 124 | |
| 139 | -## out.total <- out.forecast_parallel |> | |
| 140 | -## filter(.key=="prediction") |> | |
| 141 | -## select(.index, .value) |> | |
| 142 | -## mutate(geo=sel_ms) | |
| 143 | - | |
| 144 | - | |
| 145 | - | |
| 146 | - | |
| 147 | - if (choose_log==1){ | |
| 125 | +if (choose_log==1){ | |
| 148 | 126 | |
| 149 | 127 | out.total <- out.total |> |
| 150 | 128 | mutate(.value=exp(.value)) |
| @@ -160,14 +138,8 @@ | ||
| 160 | 138 | |
| 161 | 139 | save_excel(out.total, fn) |
| 162 | 140 | |
| 141 | +toc() | |
| 142 | + | |
| 163 | 143 | ###################################################################### |
| 164 | 144 | |
| 165 | - | |
| 166 | - | |
| 167 | - | |
| 168 | - | |
| 169 | - | |
| 170 | - | |
| 171 | - | |
| 172 | - | |
| 173 | 145 | print("So far so good") |
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