Series-based config class
cesnet_tszoo.configs.series_based_config.SeriesBasedConfig
Bases: SeriesBasedHandler
, DatasetConfig
This class is used for configuring the SeriesBasedCesnetDataset
.
Used to configure the following:
- Train, validation, test, all sets (time period, sizes, features)
- Handling missing values (default values,
fillers
) - Handling anomalies (
anomaly handlers
) - Data transformation using
transformers
- Dataloader options (train/val/test/all/init workers, batch size, train loading order)
- Plotting
Important Notes:
- Custom fillers must inherit from the
fillers
base class. - Custom anomaly handlers must inherit from the
anomaly handlers
base class. - Selected anomaly handler is only used for train set.
- It is recommended to use the
transformers
base class, though this is not mandatory as long as it meets the required methods.- If a transformer is already initialized and
partial_fit_initialized_transformers
isFalse
, the transformer does not requirepartial_fit
. - Otherwise, the transformer must support
partial_fit
. - Transformers must implement
transform
method. - Both
partial_fit
andtransform
methods must accept an input of typenp.ndarray
with shape(times, features)
.
- If a transformer is already initialized and
train_ts
,val_ts
, andtest_ts
must not contain any overlapping time series IDs.
For available configuration options, refer to here.
Attributes:
Name | Type | Description |
---|---|---|
used_train_workers |
Tracks the number of train workers in use. Helps determine if the train dataloader should be recreated based on worker changes. |
|
used_val_workers |
Tracks the number of validation workers in use. Helps determine if the validation dataloader should be recreated based on worker changes. |
|
used_test_workers |
Tracks the number of test workers in use. Helps determine if the test dataloader should be recreated based on worker changes. |
|
used_all_workers |
Tracks the total number of all workers in use. Helps determine if the all dataloader should be recreated based on worker changes. |
|
uses_all_ts |
Whether all time series set should be used. |
|
import_identifier |
Tracks the name of the config upon import. None if not imported. |
|
logger |
Logger for displaying information. |
The following attributes are initialized when set_dataset_config_and_initialize
is called:
Attributes:
Name | Type | Description |
---|---|---|
all_ts |
If no specific sets (train/val/test) are provided, all time series IDs are used. When any set is defined, only the time series IDs in defined sets are used. |
|
train_ts_row_ranges |
Initialized when |
|
val_ts_row_ranges |
Initialized when |
|
test_ts_row_ranges |
Initialized when |
|
all_ts_row_ranges |
Initialized when |
|
display_time_period |
Used to display the configured value of |
|
aggregation |
The aggregation period used for the data. |
|
source_type |
The source type of the data. |
|
database_name |
Specifies which database this config applies to. |
|
transform_with_display |
Used to display the configured type of |
|
fill_missing_with_display |
Used to display the configured type of |
|
handle_anomalies_with_display |
Used to display the configured type of |
|
features_to_take_without_ids |
Features to be returned, excluding time or time series IDs. |
|
indices_of_features_to_take_no_ids |
Indices of non-ID features in |
|
is_transformer_custom |
Flag indicating whether the transformer is custom. |
|
is_filler_custom |
Flag indicating whether the filler is custom. |
|
is_anomaly_handler_custom |
Flag indicating whether the anomaly handler is custom. |
|
ts_id_name |
Name of the time series ID, dependent on |
|
used_times |
List of all times used in the configuration. |
|
used_ts_ids |
List of all time series IDs used in the configuration. |
|
used_ts_row_ranges |
List of time series IDs with their respective time ID ranges. |
|
used_fillers |
List of all fillers used in the configuration. |
|
used_anomaly_handlers |
List of all anomaly handlers used in the configuration. |
|
used_singular_train_time_series |
Currently used singular train set time series for dataloader. |
|
used_singular_val_time_series |
Currently used singular validation set time series for dataloader. |
|
used_singular_test_time_series |
Currently used singular test set time series for dataloader. |
|
used_singular_all_time_series |
Currently used singular all set time series for dataloader. |
|
transformers |
Prepared transformers for fitting/transforming. Can be one transformer, array of transformers or |
|
are_transformers_premade |
Indicates whether the transformers are premade. |
|
train_fillers |
Fillers used in the train set. |
|
val_fillers |
Fillers used in the validation set. |
|
test_fillers |
Fillers used in the test set. |
|
all_fillers |
Fillers used for the all set. |
|
anomaly_handlers |
Prepared anomaly handlers for fitting/handling anomalies. Can be array of anomaly handlers or |
|
is_initialized |
Flag indicating if the configuration has already been initialized. If true, config initialization will be skipped. |
|
version |
Version of cesnet-tszoo this config was made in. |
|
export_update_needed |
Whether config was updated to newer version and should be exported. |
Configuration options
Attributes:
Name | Type | Description |
---|---|---|
time_period |
Defines the time period for returning data from |
|
train_ts |
Defines which time series IDs are used in the training set. Can be a list of IDs, or an integer/float to specify a random selection. An |
|
val_ts |
Defines which time series IDs are used in the validation set. Same as |
|
test_ts |
Defines which time series IDs are used in the test set. Same as |
|
features_to_take |
Defines which features are used. |
|
default_values |
Default values for missing data, applied before fillers. Can set one value for all features or specify for each feature. |
|
train_batch_size |
Batch size for the train dataloader. Affects number of returned time series in one batch. |
|
val_batch_size |
Batch size for the validation dataloader. Affects number of returned time series in one batch. |
|
test_batch_size |
Batch size for the test dataloader. Affects number of returned time series in one batch. |
|
all_batch_size |
Batch size for the all dataloader. Affects number of returned time series in one batch. |
|
fill_missing_with |
Defines how to fill missing values in the dataset. Can pass enum |
|
transform_with |
Defines the transformer used to transform the dataset. Can pass enum |
|
handle_anomalies_with |
Defines the anomaly handler for handling anomalies in the train set. Can pass enum |
|
partial_fit_initialized_transformer |
If |
|
include_time |
If |
|
include_ts_id |
If |
|
time_format |
Format for the returned time data. When using TimeFormat.DATETIME, time will be returned as separate list along rest of the values. |
|
train_workers |
Number of workers for loading training data. |
|
val_workers |
Number of workers for loading validation data. |
|
test_workers |
Number of workers for loading test data. |
|
all_workers |
Number of workers for loading all data. |
|
init_workers |
Number of workers for initial dataset processing during configuration. |
|
nan_threshold |
Maximum allowable percentage of missing data. Time series exceeding this threshold are excluded. Time series over the threshold will not be used. Used for |
|
train_dataloader_order |
Defines the order of data returned by the training dataloader. |
|
random_state |
Fixes randomness for reproducibility during configuration and dataset initialization. |
Source code in cesnet_tszoo\configs\series_based_config.py
19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 |
|
has_all
has_all() -> bool
Returns whether all set is used.
Source code in cesnet_tszoo\configs\series_based_config.py
207 208 209 |
|
has_test
has_test() -> bool
Returns whether test set is used.
Source code in cesnet_tszoo\configs\series_based_config.py
203 204 205 |
|
has_train
has_train() -> bool
Returns whether training set is used.
Source code in cesnet_tszoo\configs\series_based_config.py
195 196 197 |
|
has_val
has_val() -> bool
Returns whether validation set is used.
Source code in cesnet_tszoo\configs\series_based_config.py
199 200 201 |
|