|
48 | 48 | }
|
49 | 49 | }
|
50 | 50 |
|
| 51 | +AERO_MODE_CTOR_SAMPLED = { |
| 52 | + "test_mode": { |
| 53 | + "mass_frac": [{"H2O": [1]}], |
| 54 | + "diam_type": "geometric", |
| 55 | + "mode_type": "sampled", |
| 56 | + "size_dist": [ |
| 57 | + {"diam": [1, 2, 3, 4]}, |
| 58 | + {"num_conc": [100, 200, 300]}, |
| 59 | + ], |
| 60 | + } |
| 61 | +} |
| 62 | + |
51 | 63 |
|
52 | 64 | class TestAeroMode:
|
53 | 65 | @staticmethod
|
@@ -289,3 +301,127 @@ def test_segfault_case(): # TODO #319
|
289 | 301 | )
|
290 | 302 | print(fishy_ctor_arg)
|
291 | 303 | ppmc.AeroMode(aero_data, fishy_ctor_arg)
|
| 304 | + |
| 305 | + @staticmethod |
| 306 | + @pytest.mark.skipif(platform.machine() == "arm64", reason="TODO #348") |
| 307 | + def test_sampled_without_size_dist(): |
| 308 | + # arrange |
| 309 | + aero_data = ppmc.AeroData(AERO_DATA_CTOR_ARG_MINIMAL) |
| 310 | + fishy_ctor_arg = copy.deepcopy(AERO_MODE_CTOR_LOG_NORMAL) |
| 311 | + fishy_ctor_arg["test_mode"]["mode_type"] = "sampled" |
| 312 | + |
| 313 | + # act |
| 314 | + with pytest.raises(Exception) as exc_info: |
| 315 | + ppmc.AeroMode(aero_data, fishy_ctor_arg) |
| 316 | + |
| 317 | + # assert |
| 318 | + assert str(exc_info.value) == "size_dist key must be set for mode_type=sampled" |
| 319 | + |
| 320 | + @staticmethod |
| 321 | + @pytest.mark.parametrize( |
| 322 | + "fishy", |
| 323 | + ( |
| 324 | + None, |
| 325 | + [], |
| 326 | + [{}, {}, {}], |
| 327 | + [{}, []], |
| 328 | + [{"diam": None}, {}], |
| 329 | + [{"num_conc": None}, {}], |
| 330 | + [{"diam": None, "": None}, {}], |
| 331 | + [{"num_conc": None, "": None}, {}], |
| 332 | + ), |
| 333 | + ) |
| 334 | + @pytest.mark.skipif(platform.machine() == "arm64", reason="TODO #348") |
| 335 | + def test_sampled_with_fishy_size_dist(fishy): |
| 336 | + # arrange |
| 337 | + aero_data = ppmc.AeroData(AERO_DATA_CTOR_ARG_MINIMAL) |
| 338 | + fishy_ctor_arg = copy.deepcopy(AERO_MODE_CTOR_LOG_NORMAL) |
| 339 | + fishy_ctor_arg["test_mode"]["mode_type"] = "sampled" |
| 340 | + fishy_ctor_arg["test_mode"]["size_dist"] = fishy |
| 341 | + |
| 342 | + # act |
| 343 | + with pytest.raises(Exception) as exc_info: |
| 344 | + ppmc.AeroMode(aero_data, fishy_ctor_arg) |
| 345 | + |
| 346 | + # assert |
| 347 | + assert ( |
| 348 | + str(exc_info.value) |
| 349 | + == "size_dist value must be an iterable of two single-element dicts" |
| 350 | + + " (first with 'diam', second with 'num_conc' as keys)" |
| 351 | + ) |
| 352 | + |
| 353 | + @staticmethod |
| 354 | + @pytest.mark.skipif(platform.machine() == "arm64", reason="TODO #348") |
| 355 | + def test_sampled_with_diam_of_different_len_than_num_conc(): |
| 356 | + # arrange |
| 357 | + aero_data = ppmc.AeroData(AERO_DATA_CTOR_ARG_MINIMAL) |
| 358 | + fishy_ctor_arg = copy.deepcopy(AERO_MODE_CTOR_LOG_NORMAL) |
| 359 | + fishy_ctor_arg["test_mode"]["mode_type"] = "sampled" |
| 360 | + fishy_ctor_arg["test_mode"]["size_dist"] = [ |
| 361 | + {"diam": [1, 2, 3]}, |
| 362 | + {"num_conc": [1, 2, 3]}, |
| 363 | + ] |
| 364 | + |
| 365 | + # act |
| 366 | + with pytest.raises(Exception) as exc_info: |
| 367 | + ppmc.AeroMode(aero_data, fishy_ctor_arg) |
| 368 | + |
| 369 | + # assert |
| 370 | + assert ( |
| 371 | + str(exc_info.value) |
| 372 | + == "size_dist['num_conc'] must have len(size_dist['diam'])-1 elements" |
| 373 | + ) |
| 374 | + |
| 375 | + @staticmethod |
| 376 | + def test_sampled(): |
| 377 | + # arrange |
| 378 | + aero_data = ppmc.AeroData(AERO_DATA_CTOR_ARG_MINIMAL) |
| 379 | + |
| 380 | + # act |
| 381 | + sut = ppmc.AeroMode(aero_data, AERO_MODE_CTOR_SAMPLED) |
| 382 | + |
| 383 | + # assert |
| 384 | + assert sut.type == "sampled" |
| 385 | + assert sut.num_conc == np.sum( |
| 386 | + AERO_MODE_CTOR_SAMPLED["test_mode"]["size_dist"][1]["num_conc"] |
| 387 | + ) |
| 388 | + assert ( |
| 389 | + sut.sample_num_conc |
| 390 | + == AERO_MODE_CTOR_SAMPLED["test_mode"]["size_dist"][1]["num_conc"] |
| 391 | + ) |
| 392 | + assert ( |
| 393 | + np.array(sut.sample_radius) * 2 |
| 394 | + == AERO_MODE_CTOR_SAMPLED["test_mode"]["size_dist"][0]["diam"] |
| 395 | + ).all() |
| 396 | + |
| 397 | + @staticmethod |
| 398 | + def test_set_sample(): |
| 399 | + # arrange |
| 400 | + aero_data = ppmc.AeroData(AERO_DATA_CTOR_ARG_MINIMAL) |
| 401 | + |
| 402 | + diams = [1, 2, 3, 4] |
| 403 | + num_concs = [100, 200, 300] |
| 404 | + sut = ppmc.AeroMode( |
| 405 | + aero_data, |
| 406 | + { |
| 407 | + "test_mode": { |
| 408 | + "mass_frac": [{"H2O": [1]}], |
| 409 | + "diam_type": "geometric", |
| 410 | + "mode_type": "sampled", |
| 411 | + "size_dist": [ |
| 412 | + {"diam": diams}, |
| 413 | + {"num_conc": num_concs}, |
| 414 | + ], |
| 415 | + } |
| 416 | + }, |
| 417 | + ) |
| 418 | + num_conc_orig = sut.num_conc |
| 419 | + # act |
| 420 | + diams = [0.5 * x for x in diams] |
| 421 | + num_concs = [2 * x for x in num_concs] |
| 422 | + sut.set_sample(diams, num_concs) |
| 423 | + # assert |
| 424 | + assert sut.num_conc == np.sum(num_concs) |
| 425 | + assert sut.sample_num_conc == num_concs |
| 426 | + assert (np.array(sut.sample_radius) * 2 == diams).all() |
| 427 | + assert sut.num_conc == num_conc_orig * 2 |
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