Takes multiple inputs via nested dictionaries. The function iterates through a dictionary and runs input_data() for each item. This allows for multiple items to be added at a single time. The param dictionary will take the form: {'target_1': {param_1: value_1}, 'ta
(self, param_dictionary)
| 328 | return self |
| 329 | |
| 330 | def bulk_import_data(self, param_dictionary): |
| 331 | """Takes multiple inputs via nested dictionaries. |
| 332 | |
| 333 | The function iterates through a dictionary and runs input_data() |
| 334 | for each item. This allows for multiple items to be added at a |
| 335 | single time. The param dictionary will take the form: |
| 336 | |
| 337 | {'target_1': {param_1: value_1}, 'target_2': {param_2: value_2}} |
| 338 | |
| 339 | Parameters |
| 340 | ---------- |
| 341 | param_dictionary : dict |
| 342 | A nested dictionary of parameters. |
| 343 | |
| 344 | Returns |
| 345 | ------- |
| 346 | pyfair.model.FairModel |
| 347 | A reference to this object of type FairModel |
| 348 | |
| 349 | Examples |
| 350 | -------- |
| 351 | >>> model = pyfair.FairModel(name="Insider Threat") |
| 352 | >>> model.bulk_import_data({ |
| 353 | ... 'Loss Event Frequency': {'mean': 90, 'stdev': 100}, |
| 354 | ... 'Loss Magnitude': {'constant': 4000}, |
| 355 | ... }) |
| 356 | |
| 357 | """ |
| 358 | # Iterate through each key, value pair and run through input_data() |
| 359 | for target, parameters in param_dictionary.items(): |
| 360 | self.input_data(target, **parameters) |
| 361 | return self |
| 362 | |
| 363 | def input_raw_data(self, target, array): |
| 364 | """Supply a raw array to the model |