How to use assertAlmostEqual method in autotest
Best Python code snippet using autotest_python
test_Cluster.py
Source:test_Cluster.py 
...26 from Bio.Cluster import mean, median27 elif TestCluster.module == 'Pycluster':28 from Pycluster import mean, median29 data = numpy.array([34.3, 3, 2])30 self.assertAlmostEqual(mean(data), 13.1, places=3)31 self.assertAlmostEqual(median(data), 3.0, places=3)32 data = [5, 10, 15, 20]33 self.assertAlmostEqual(mean(data), 12.5, places=3)34 self.assertAlmostEqual(median(data), 12.5, places=3)35 data = [1, 2, 3, 5, 7, 11, 13, 17]36 self.assertAlmostEqual(mean(data), 7.375, places=3)37 self.assertAlmostEqual(median(data), 6.0, places=3)38 data = [100, 19, 3, 1.5, 1.4, 1, 1, 1]39 self.assertAlmostEqual(mean(data), 15.988, places=3)40 self.assertAlmostEqual(median(data), 1.45, places=3)41 def test_matrix_parse(self):42 if TestCluster.module == 'Bio.Cluster':43 from Bio.Cluster import treecluster44 elif TestCluster.module == 'Pycluster':45 from Pycluster import treecluster46 # Normal matrix, no errors47 data1 = numpy.array([[1.1, 1.2],48 [1.4, 1.3],49 [1.1, 1.5],50 [2.0, 1.5],51 [1.7, 1.9],52 [1.7, 1.9],53 [5.7, 5.9],54 [5.7, 5.9],55 [3.1, 3.3],56 [5.4, 5.3],57 [5.1, 5.5],58 [5.0, 5.5],59 [5.1, 5.2]])60 # Another normal matrix, no errors; written as a list61 data2 = [[1.1, 2.2, 3.3, 4.4, 5.5],62 [3.1, 3.2, 1.3, 2.4, 1.5],63 [4.1, 2.2, 0.3, 5.4, 0.5],64 [12.1, 2.0, 0.0, 5.0, 0.0]]65 # Ragged matrix66 data3 = [[91.1, 92.2, 93.3, 94.4, 95.5],67 [93.1, 93.2, 91.3, 92.4],68 [94.1, 92.2, 90.3],69 [12.1, 92.0, 90.0, 95.0, 90.0]]70 # Matrix with bad cells71 data4 = [[7.1, 7.2, 7.3, 7.4, 7.5],72 [7.1, 7.2, 7.3, 7.4, 'snoopy'],73 [7.1, 7.2, 7.3, None, None]]74 # Matrix with a bad row75 data5 = [[23.1, 23.2, 23.3, 23.4, 23.5],76 None,77 [23.1, 23.0, 23.0, 23.0, 23.0]]78 # Various references that don't point to matrices at all79 data6 = "snoopy"80 data7 = {'a': [[2.3, 1.2], [3.3, 5.6]]}81 data8 = []82 data9 = [None]83 try:84 treecluster(data1)85 except Exception: # TODO - Which exceptions?86 self.fail("treecluster failed to accept matrix data1")87 try:88 treecluster(data2)89 except Exception: # TODO - Which exceptions?90 self.fail("treecluster failed to accept matrix data2")91 self.assertRaises(TypeError, lambda: treecluster(data3))92 self.assertRaises(TypeError, lambda: treecluster(data4))93 self.assertRaises(TypeError, lambda: treecluster(data5))94 self.assertRaises(TypeError, lambda: treecluster(data6))95 self.assertRaises(TypeError, lambda: treecluster(data7))96 self.assertRaises(TypeError, lambda: treecluster(data8))97 self.assertRaises(TypeError, lambda: treecluster(data9))98 def test_kcluster(self):99 if TestCluster.module == 'Bio.Cluster':100 from Bio.Cluster import kcluster101 elif TestCluster.module == 'Pycluster':102 from Pycluster import kcluster103 nclusters = 3104 # First data set105 weight = numpy.array([1, 1, 1, 1, 1])106 data = numpy.array([[1.1, 2.2, 3.3, 4.4, 5.5],107 [3.1, 3.2, 1.3, 2.4, 1.5],108 [4.1, 2.2, 0.3, 5.4, 0.5],109 [12.1, 2.0, 0.0, 5.0, 0.0]])110 mask = numpy.array([[1, 1, 1, 1, 1],111 [1, 1, 1, 1, 1],112 [1, 1, 1, 1, 1],113 [1, 1, 1, 1, 1]], int)114 # TODO - Use a context manager here once we drop Python 2.6115 # Method should be one letter:116 self.assertRaises(ValueError, kcluster, data,117 **{"nclusters": nclusters, "mask": mask,118 "weight": weight, "transpose": 0, "npass": 100,119 "method": "any", "dist": "e"})120 # Distance should be one letter:121 self.assertRaises(ValueError, kcluster, data,122 **{"nclusters": nclusters, "mask": mask,123 "weight": weight, "transpose": 0, "npass": 100,124 "method": "a", "dist": "euclidean"})125 clusterid, error, nfound = kcluster(data, nclusters=nclusters,126 mask=mask, weight=weight,127 transpose=0, npass=100,128 method='a', dist='e')129 self.assertEqual(len(clusterid), len(data))130 correct = [0, 1, 1, 2]131 mapping = [clusterid[correct.index(i)] for i in range(nclusters)]132 for i in range(len(clusterid)):133 self.assertEqual(clusterid[i], mapping[correct[i]])134 # Second data set135 weight = numpy.array([1, 1])136 data = numpy.array([[1.1, 1.2],137 [1.4, 1.3],138 [1.1, 1.5],139 [2.0, 1.5],140 [1.7, 1.9],141 [1.7, 1.9],142 [5.7, 5.9],143 [5.7, 5.9],144 [3.1, 3.3],145 [5.4, 5.3],146 [5.1, 5.5],147 [5.0, 5.5],148 [5.1, 5.2]])149 mask = numpy.array([[1, 1],150 [1, 1],151 [1, 1],152 [1, 1],153 [1, 1],154 [1, 1],155 [1, 1],156 [1, 1],157 [1, 1],158 [1, 1],159 [1, 1],160 [1, 1],161 [1, 1]], int)162 # TODO - Use a context manager here once we drop Python 2.6163 # Method should be one letter:164 self.assertRaises(ValueError, kcluster, data,165 **{"nclusters": 3, "mask": mask,166 "weight": weight, "transpose": 0, "npass": 100,167 "method": "any", "dist": "e"})168 # Distance should be one letter:169 self.assertRaises(ValueError, kcluster, data,170 **{"nclusters": 3, "mask": mask,171 "weight": weight, "transpose": 0, "npass": 100,172 "method": "a", "dist": "euclidean"})173 clusterid, error, nfound = kcluster(data, nclusters=3, mask=mask,174 weight=weight, transpose=0,175 npass=100, method='a', dist='e')176 self.assertEqual(len(clusterid), len(data))177 correct = [0, 0, 0, 0, 0, 0, 1, 1, 2, 1, 1, 1, 1]178 mapping = [clusterid[correct.index(i)] for i in range(nclusters)]179 for i in range(len(clusterid)):180 self.assertEqual(clusterid[i], mapping[correct[i]])181 def test_clusterdistance(self):182 if TestCluster.module == 'Bio.Cluster':183 from Bio.Cluster import clusterdistance184 elif TestCluster.module == 'Pycluster':185 from Pycluster import clusterdistance186 # First data set187 weight = numpy.array([1, 1, 1, 1, 1])188 data = numpy.array([[1.1, 2.2, 3.3, 4.4, 5.5],189 [3.1, 3.2, 1.3, 2.4, 1.5],190 [4.1, 2.2, 0.3, 5.4, 0.5],191 [12.1, 2.0, 0.0, 5.0, 0.0]])192 mask = numpy.array([[1, 1, 1, 1, 1],193 [1, 1, 1, 1, 1],194 [1, 1, 1, 1, 1],195 [1, 1, 1, 1, 1]], int)196 # Cluster assignments197 c1 = [0]198 c2 = [1, 2]199 c3 = [3]200 # TODO - Use a context manager here once we drop Python 2.6201 # Method should be one letter:202 self.assertRaises(ValueError, clusterdistance, data,203 **{"mask": mask, "weight": weight,204 "index1": c1, "index2": c2, "transpose": 0,205 "method": "any", "dist": "e"})206 # Distance should be one letter:207 self.assertRaises(ValueError, clusterdistance, data,208 **{"mask": mask, "weight": weight,209 "index1": c1, "index2": c2, "transpose": 0,210 "method": "a", "dist": "euclidean"})211 distance = clusterdistance(data, mask=mask, weight=weight,212 index1=c1, index2=c2, dist='e',213 method='a', transpose=0)214 self.assertAlmostEqual(distance, 6.650, places=3)215 distance = clusterdistance(data, mask=mask, weight=weight,216 index1=c1, index2=c3, dist='e',217 method='a', transpose=0)218 self.assertAlmostEqual(distance, 32.508, places=3)219 distance = clusterdistance(data, mask=mask, weight=weight,220 index1=c2, index2=c3, dist='e',221 method='a', transpose=0)222 self.assertAlmostEqual(distance, 15.118, places=3)223 # Second data set224 weight = numpy.array([1, 1])225 data = numpy.array([[1.1, 1.2],226 [1.4, 1.3],227 [1.1, 1.5],228 [2.0, 1.5],229 [1.7, 1.9],230 [1.7, 1.9],231 [5.7, 5.9],232 [5.7, 5.9],233 [3.1, 3.3],234 [5.4, 5.3],235 [5.1, 5.5],236 [5.0, 5.5],237 [5.1, 5.2]])238 mask = numpy.array([[1, 1],239 [1, 1],240 [1, 1],241 [1, 1],242 [1, 1],243 [1, 1],244 [1, 1],245 [1, 1],246 [1, 1],247 [1, 1],248 [1, 1],249 [1, 1],250 [1, 1]], int)251 # Cluster assignments252 c1 = [0, 1, 2, 3]253 c2 = [4, 5, 6, 7]254 c3 = [8]255 # TODO - Use a context manager here once we drop Python 2.6256 # Method should be one letter:257 self.assertRaises(ValueError, clusterdistance, data,258 **{"mask": mask, "weight": weight,259 "index1": c1, "index2": c2,260 "method": "any", "dist": "e",261 "transpose": 0})262 # Distance should be one letter:263 self.assertRaises(ValueError, clusterdistance, data,264 **{"mask": mask, "weight": weight,265 "index1": c1, "index2": c2,266 "method": "a", "dist": "euclidena",267 "transpose": 0})268 distance = clusterdistance(data, mask=mask, weight=weight,269 index1=c1, index2=c2, dist='e',270 method='a', transpose=0)271 self.assertAlmostEqual(distance, 5.833, places=3)272 distance = clusterdistance(data, mask=mask, weight=weight,273 index1=c1, index2=c3, dist='e',274 method='a', transpose=0)275 self.assertAlmostEqual(distance, 3.298, places=3)276 distance = clusterdistance(data, mask=mask, weight=weight,277 index1=c2, index2=c3, dist='e',278 method='a', transpose=0)279 self.assertAlmostEqual(distance, 0.360, places=3)280 def test_treecluster(self):281 if TestCluster.module == 'Bio.Cluster':282 from Bio.Cluster import treecluster283 elif TestCluster.module == 'Pycluster':284 from Pycluster import treecluster285 # First data set286 weight1 = [1, 1, 1, 1, 1]287 data1 = numpy.array([[1.1, 2.2, 3.3, 4.4, 5.5],288 [3.1, 3.2, 1.3, 2.4, 1.5],289 [4.1, 2.2, 0.3, 5.4, 0.5],290 [12.1, 2.0, 0.0, 5.0, 0.0]])291 mask1 = numpy.array([[1, 1, 1, 1, 1],292 [1, 1, 1, 1, 1],293 [1, 1, 1, 1, 1],294 [1, 1, 1, 1, 1]], int)295 # TODO - Use a context manager here once we drop Python 2.6296 # Method should be one letter:297 self.assertRaises(ValueError, treecluster,298 **{"data": data1, "mask": mask1, "weight": weight1,299 "transpose": 0, "method": "any", "dist": "e"})300 # Distance should be one letter:301 self.assertRaises(ValueError, treecluster,302 **{"data": data1, "mask": mask1, "weight": weight1,303 "transpose": 0, "method": "any", "dist": "euclidean"})304 # test first data set305 # Pairwise average-linkage clustering"306 tree = treecluster(data=data1, mask=mask1, weight=weight1,307 transpose=0, method='a', dist='e')308 self.assertEqual(len(tree), len(data1) - 1)309 self.assertEqual(tree[0].left, 2)310 self.assertEqual(tree[0].right, 1)311 self.assertAlmostEqual(tree[0].distance, 2.600, places=3)312 self.assertEqual(tree[1].left, -1)313 self.assertEqual(tree[1].right, 0)314 self.assertAlmostEqual(tree[1].distance, 7.300, places=3)315 self.assertEqual(tree[2].left, 3)316 self.assertEqual(tree[2].right, -2)317 self.assertAlmostEqual(tree[2].distance, 21.348, places=3)318 # Pairwise single-linkage clustering319 tree = treecluster(data=data1, mask=mask1, weight=weight1,320 transpose=0, method='s', dist='e')321 self.assertEqual(len(tree), len(data1) - 1)322 self.assertEqual(tree[0].left, 1)323 self.assertEqual(tree[0].right, 2)324 self.assertAlmostEqual(tree[0].distance, 2.600, places=3)325 self.assertEqual(tree[1].left, 0)326 self.assertEqual(tree[1].right, -1)327 self.assertAlmostEqual(tree[1].distance, 5.800, places=3)328 self.assertEqual(tree[2].left, -2)329 self.assertEqual(tree[2].right, 3)330 self.assertAlmostEqual(tree[2].distance, 12.908, places=3)331 # Pairwise centroid-linkage clustering332 tree = treecluster(data=data1, mask=mask1, weight=weight1,333 transpose=0, method='c', dist='e')334 self.assertEqual(len(tree), len(data1) - 1)335 self.assertEqual(tree[0].left, 1)336 self.assertEqual(tree[0].right, 2)337 self.assertAlmostEqual(tree[0].distance, 2.600, places=3)338 self.assertEqual(tree[1].left, 0)339 self.assertEqual(tree[1].right, -1)340 self.assertAlmostEqual(tree[1].distance, 6.650, places=3)341 self.assertEqual(tree[2].left, -2)342 self.assertEqual(tree[2].right, 3)343 self.assertAlmostEqual(tree[2].distance, 19.437, places=3)344 # Pairwise maximum-linkage clustering345 tree = treecluster(data=data1, mask=mask1, weight=weight1,346 transpose=0, method='m', dist='e')347 self.assertEqual(len(tree), len(data1) - 1)348 self.assertEqual(tree[0].left, 2)349 self.assertEqual(tree[0].right, 1)350 self.assertAlmostEqual(tree[0].distance, 2.600, places=3)351 self.assertEqual(tree[1].left, -1)352 self.assertEqual(tree[1].right, 0)353 self.assertAlmostEqual(tree[1].distance, 8.800, places=3)354 self.assertEqual(tree[2].left, 3)355 self.assertEqual(tree[2].right, -2)356 self.assertAlmostEqual(tree[2].distance, 32.508, places=3)357 # Second data set358 weight2 = [1, 1]359 data2 = numpy.array([[0.8223, 0.9295],360 [1.4365, 1.3223],361 [1.1623, 1.5364],362 [2.1826, 1.1934],363 [1.7763, 1.9352],364 [1.7215, 1.9912],365 [2.1812, 5.9935],366 [5.3290, 5.9452],367 [3.1491, 3.3454],368 [5.1923, 5.3156],369 [4.7735, 5.4012],370 [5.1297, 5.5645],371 [5.3934, 5.1823]])372 mask2 = numpy.array([[1, 1],373 [1, 1],374 [1, 1],375 [1, 1],376 [1, 1],377 [1, 1],378 [1, 1],379 [1, 1],380 [1, 1],381 [1, 1],382 [1, 1],383 [1, 1],384 [1, 1]], int)385 # Test second data set386 # Pairwise average-linkage clustering387 tree = treecluster(data=data2, mask=mask2, weight=weight2,388 transpose=0, method='a', dist='e')389 self.assertEqual(len(tree), len(data2) - 1)390 self.assertEqual(tree[0].left, 5)391 self.assertEqual(tree[0].right, 4)392 self.assertAlmostEqual(tree[0].distance, 0.003, places=3)393 self.assertEqual(tree[1].left, 9)394 self.assertEqual(tree[1].right, 12)395 self.assertAlmostEqual(tree[1].distance, 0.029, places=3)396 self.assertEqual(tree[2].left, 2)397 self.assertEqual(tree[2].right, 1)398 self.assertAlmostEqual(tree[2].distance, 0.061, places=3)399 self.assertEqual(tree[3].left, 11)400 self.assertEqual(tree[3].right, -2)401 self.assertAlmostEqual(tree[3].distance, 0.070, places=3)402 self.assertEqual(tree[4].left, -4)403 self.assertEqual(tree[4].right, 10)404 self.assertAlmostEqual(tree[4].distance, 0.128, places=3)405 self.assertEqual(tree[5].left, 7)406 self.assertEqual(tree[5].right, -5)407 self.assertAlmostEqual(tree[5].distance, 0.224, places=3)408 self.assertEqual(tree[6].left, -3)409 self.assertEqual(tree[6].right, 0)410 self.assertAlmostEqual(tree[6].distance, 0.254, places=3)411 self.assertEqual(tree[7].left, -1)412 self.assertEqual(tree[7].right, 3)413 self.assertAlmostEqual(tree[7].distance, 0.391, places=3)414 self.assertEqual(tree[8].left, -8)415 self.assertEqual(tree[8].right, -7)416 self.assertAlmostEqual(tree[8].distance, 0.532, places=3)417 self.assertEqual(tree[9].left, 8)418 self.assertEqual(tree[9].right, -9)419 self.assertAlmostEqual(tree[9].distance, 3.234, places=3)420 self.assertEqual(tree[10].left, -6)421 self.assertEqual(tree[10].right, 6)422 self.assertAlmostEqual(tree[10].distance, 4.636, places=3)423 self.assertEqual(tree[11].left, -11)424 self.assertEqual(tree[11].right, -10)425 self.assertAlmostEqual(tree[11].distance, 12.741, places=3)426 # Pairwise single-linkage clustering427 tree = treecluster(data=data2, mask=mask2, weight=weight2,428 transpose=0, method='s', dist='e')429 self.assertEqual(len(tree), len(data2) - 1)430 self.assertEqual(tree[0].left, 4)431 self.assertEqual(tree[0].right, 5)432 self.assertAlmostEqual(tree[0].distance, 0.003, places=3)433 self.assertEqual(tree[1].left, 9)434 self.assertEqual(tree[1].right, 12)435 self.assertAlmostEqual(tree[1].distance, 0.029, places=3)436 self.assertEqual(tree[2].left, 11)437 self.assertEqual(tree[2].right, -2)438 self.assertAlmostEqual(tree[2].distance, 0.033, places=3)439 self.assertEqual(tree[3].left, 1)440 self.assertEqual(tree[3].right, 2)441 self.assertAlmostEqual(tree[3].distance, 0.061, places=3)442 self.assertEqual(tree[4].left, 10)443 self.assertEqual(tree[4].right, -3)444 self.assertAlmostEqual(tree[4].distance, 0.077, places=3)445 self.assertEqual(tree[5].left, 7)446 self.assertEqual(tree[5].right, -5)447 self.assertAlmostEqual(tree[5].distance, 0.092, places=3)448 self.assertEqual(tree[6].left, 0)449 self.assertEqual(tree[6].right, -4)450 self.assertAlmostEqual(tree[6].distance, 0.242, places=3)451 self.assertEqual(tree[7].left, -7)452 self.assertEqual(tree[7].right, -1)453 self.assertAlmostEqual(tree[7].distance, 0.246, places=3)454 self.assertEqual(tree[8].left, 3)455 self.assertEqual(tree[8].right, -8)456 self.assertAlmostEqual(tree[8].distance, 0.287, places=3)457 self.assertEqual(tree[9].left, -9)458 self.assertEqual(tree[9].right, 8)459 self.assertAlmostEqual(tree[9].distance, 1.936, places=3)460 self.assertEqual(tree[10].left, -10)461 self.assertEqual(tree[10].right, -6)462 self.assertAlmostEqual(tree[10].distance, 3.432, places=3)463 self.assertEqual(tree[11].left, 6)464 self.assertEqual(tree[11].right, -11)465 self.assertAlmostEqual(tree[11].distance, 3.535, places=3)466 # Pairwise centroid-linkage clustering467 tree = treecluster(data=data2, mask=mask2, weight=weight2,468 transpose=0, method='c', dist='e')469 self.assertEqual(len(tree), len(data2) - 1)470 self.assertEqual(tree[0].left, 4)471 self.assertEqual(tree[0].right, 5)472 self.assertAlmostEqual(tree[0].distance, 0.003, places=3)473 self.assertEqual(tree[1].left, 12)474 self.assertEqual(tree[1].right, 9)475 self.assertAlmostEqual(tree[1].distance, 0.029, places=3)476 self.assertEqual(tree[2].left, 1)477 self.assertEqual(tree[2].right, 2)478 self.assertAlmostEqual(tree[2].distance, 0.061, places=3)479 self.assertEqual(tree[3].left, -2)480 self.assertEqual(tree[3].right, 11)481 self.assertAlmostEqual(tree[3].distance, 0.063, places=3)482 self.assertEqual(tree[4].left, 10)483 self.assertEqual(tree[4].right, -4)484 self.assertAlmostEqual(tree[4].distance, 0.109, places=3)485 self.assertEqual(tree[5].left, -5)486 self.assertEqual(tree[5].right, 7)487 self.assertAlmostEqual(tree[5].distance, 0.189, places=3)488 self.assertEqual(tree[6].left, 0)489 self.assertEqual(tree[6].right, -3)490 self.assertAlmostEqual(tree[6].distance, 0.239, places=3)491 self.assertEqual(tree[7].left, 3)492 self.assertEqual(tree[7].right, -1)493 self.assertAlmostEqual(tree[7].distance, 0.390, places=3)494 self.assertEqual(tree[8].left, -7)495 self.assertEqual(tree[8].right, -8)496 self.assertAlmostEqual(tree[8].distance, 0.382, places=3)497 self.assertEqual(tree[9].left, -9)498 self.assertEqual(tree[9].right, 8)499 self.assertAlmostEqual(tree[9].distance, 3.063, places=3)500 self.assertEqual(tree[10].left, 6)501 self.assertEqual(tree[10].right, -6)502 self.assertAlmostEqual(tree[10].distance, 4.578, places=3)503 self.assertEqual(tree[11].left, -10)504 self.assertEqual(tree[11].right, -11)505 self.assertAlmostEqual(tree[11].distance, 11.536, places=3)506 # Pairwise maximum-linkage clustering507 tree = treecluster(data=data2, mask=mask2, weight=weight2,508 transpose=0, method='m', dist='e')509 self.assertEqual(len(tree), len(data2) - 1)510 self.assertEqual(tree[0].left, 5)511 self.assertEqual(tree[0].right, 4)512 self.assertAlmostEqual(tree[0].distance, 0.003, places=3)513 self.assertEqual(tree[1].left, 9)514 self.assertEqual(tree[1].right, 12)515 self.assertAlmostEqual(tree[1].distance, 0.029, places=3)516 self.assertEqual(tree[2].left, 2)517 self.assertEqual(tree[2].right, 1)518 self.assertAlmostEqual(tree[2].distance, 0.061, places=3)519 self.assertEqual(tree[3].left, 11)520 self.assertEqual(tree[3].right, 10)521 self.assertAlmostEqual(tree[3].distance, 0.077, places=3)522 self.assertEqual(tree[4].left, -2)523 self.assertEqual(tree[4].right, -4)524 self.assertAlmostEqual(tree[4].distance, 0.216, places=3)525 self.assertEqual(tree[5].left, -3)526 self.assertEqual(tree[5].right, 0)527 self.assertAlmostEqual(tree[5].distance, 0.266, places=3)528 self.assertEqual(tree[6].left, -5)529 self.assertEqual(tree[6].right, 7)530 self.assertAlmostEqual(tree[6].distance, 0.302, places=3)531 self.assertEqual(tree[7].left, -1)532 self.assertEqual(tree[7].right, 3)533 self.assertAlmostEqual(tree[7].distance, 0.425, places=3)534 self.assertEqual(tree[8].left, -8)535 self.assertEqual(tree[8].right, -6)536 self.assertAlmostEqual(tree[8].distance, 0.968, places=3)537 self.assertEqual(tree[9].left, 8)538 self.assertEqual(tree[9].right, 6)539 self.assertAlmostEqual(tree[9].distance, 3.975, places=3)540 self.assertEqual(tree[10].left, -10)541 self.assertEqual(tree[10].right, -7)542 self.assertAlmostEqual(tree[10].distance, 5.755, places=3)543 self.assertEqual(tree[11].left, -11)544 self.assertEqual(tree[11].right, -9)545 self.assertAlmostEqual(tree[11].distance, 22.734, places=3)546 def test_somcluster(self):547 if TestCluster.module == 'Bio.Cluster':548 from Bio.Cluster import somcluster549 elif TestCluster.module == 'Pycluster':550 from Pycluster import somcluster551 # First data set552 weight = [1, 1, 1, 1, 1]553 data = numpy.array([[1.1, 2.2, 3.3, 4.4, 5.5],554 [3.1, 3.2, 1.3, 2.4, 1.5],555 [4.1, 2.2, 0.3, 5.4, 0.5],556 [12.1, 2.0, 0.0, 5.0, 0.0]])557 mask = numpy.array([[1, 1, 1, 1, 1],558 [1, 1, 1, 1, 1],559 [1, 1, 1, 1, 1],560 [1, 1, 1, 1, 1]], int)561 # TODO - Use a context manager here once we drop Python 2.6562 # Distance should be one letter:563 self.assertRaises(ValueError, somcluster,564 **{"data": data, "mask": mask, "weight": weight,565 "transpose": 0, "nxgrid": 10, "nygrid": 10,566 "inittau": 0.02, "niter": 100, "dist": "euclidean"})567 clusterid, celldata = somcluster(data=data, mask=mask, weight=weight,568 transpose=0, nxgrid=10, nygrid=10,569 inittau=0.02, niter=100, dist='e')570 self.assertEqual(len(clusterid), len(data))571 self.assertEqual(len(clusterid[0]), 2)572 # Second data set573 weight = [1, 1]574 data = numpy.array([[1.1, 1.2],575 [1.4, 1.3],576 [1.1, 1.5],577 [2.0, 1.5],578 [1.7, 1.9],579 [1.7, 1.9],580 [5.7, 5.9],581 [5.7, 5.9],582 [3.1, 3.3],583 [5.4, 5.3],584 [5.1, 5.5],585 [5.0, 5.5],586 [5.1, 5.2]])587 mask = numpy.array([[1, 1],588 [1, 1],589 [1, 1],590 [1, 1],591 [1, 1],592 [1, 1],593 [1, 1],594 [1, 1],595 [1, 1],596 [1, 1],597 [1, 1],598 [1, 1],599 [1, 1]], int)600 clusterid, celldata = somcluster(data=data, mask=mask, weight=weight,601 transpose=0, nxgrid=10, nygrid=10,602 inittau=0.02, niter=100, dist='e')603 self.assertEqual(len(clusterid), len(data))604 self.assertEqual(len(clusterid[0]), 2)605 def test_distancematrix_kmedoids(self):606 if TestCluster.module == 'Bio.Cluster':607 from Bio.Cluster import distancematrix, kmedoids608 elif TestCluster.module == 'Pycluster':609 from Pycluster import distancematrix, kmedoids610 data = numpy.array([[2.2, 3.3, 4.4],611 [2.1, 1.4, 5.6],612 [7.8, 9.0, 1.2],613 [4.5, 2.3, 1.5],614 [4.2, 2.4, 1.9],615 [3.6, 3.1, 9.3],616 [2.3, 1.2, 3.9],617 [4.2, 9.6, 9.3],618 [1.7, 8.9, 1.1]])619 mask = numpy.array([[1, 1, 1],620 [1, 1, 1],621 [0, 1, 1],622 [1, 1, 1],623 [1, 1, 1],624 [0, 1, 0],625 [1, 1, 1],626 [1, 0, 1],627 [1, 1, 1]], int)628 weight = numpy.array([2.0, 1.0, 0.5])629 matrix = distancematrix(data, mask=mask, weight=weight)630 self.assertAlmostEqual(matrix[1][0], 1.243, places=3)631 self.assertAlmostEqual(matrix[2][0], 25.073, places=3)632 self.assertAlmostEqual(matrix[2][1], 44.960, places=3)633 self.assertAlmostEqual(matrix[3][0], 4.510, places=3)634 self.assertAlmostEqual(matrix[3][1], 5.924, places=3)635 self.assertAlmostEqual(matrix[3][2], 29.957, places=3)636 self.assertAlmostEqual(matrix[4][0], 3.410, places=3)637 self.assertAlmostEqual(matrix[4][1], 4.761, places=3)638 self.assertAlmostEqual(matrix[4][2], 29.203, places=3)639 self.assertAlmostEqual(matrix[4][3], 0.077, places=3)640 self.assertAlmostEqual(matrix[5][0], 0.040, places=3)641 self.assertAlmostEqual(matrix[5][1], 2.890, places=3)642 self.assertAlmostEqual(matrix[5][2], 34.810, places=3)643 self.assertAlmostEqual(matrix[5][3], 0.640, places=3)644 self.assertAlmostEqual(matrix[5][4], 0.490, places=3)645 self.assertAlmostEqual(matrix[6][0], 1.301, places=3)646 self.assertAlmostEqual(matrix[6][1], 0.447, places=3)647 self.assertAlmostEqual(matrix[6][2], 42.990, places=3)648 self.assertAlmostEqual(matrix[6][3], 3.934, places=3)649 self.assertAlmostEqual(matrix[6][4], 3.046, places=3)650 self.assertAlmostEqual(matrix[6][5], 3.610, places=3)651 self.assertAlmostEqual(matrix[7][0], 8.002, places=3)652 self.assertAlmostEqual(matrix[7][1], 6.266, places=3)653 self.assertAlmostEqual(matrix[7][2], 65.610, places=3)654 self.assertAlmostEqual(matrix[7][3], 12.240, places=3)655 self.assertAlmostEqual(matrix[7][4], 10.952, places=3)656 self.assertAlmostEqual(matrix[7][5], 0.000, places=3)657 self.assertAlmostEqual(matrix[7][6], 8.720, places=3)658 self.assertAlmostEqual(matrix[8][0], 10.659, places=3)659 self.assertAlmostEqual(matrix[8][1], 19.056, places=3)660 self.assertAlmostEqual(matrix[8][2], 0.010, places=3)661 self.assertAlmostEqual(matrix[8][3], 16.949, places=3)662 self.assertAlmostEqual(matrix[8][4], 15.734, places=3)663 self.assertAlmostEqual(matrix[8][5], 33.640, places=3)664 self.assertAlmostEqual(matrix[8][6], 18.266, places=3)665 self.assertAlmostEqual(matrix[8][7], 18.448, places=3)666 clusterid, error, nfound = kmedoids(matrix, npass=1000)667 self.assertEqual(clusterid[0], 5)668 self.assertEqual(clusterid[1], 5)669 self.assertEqual(clusterid[2], 2)670 self.assertEqual(clusterid[3], 5)671 self.assertEqual(clusterid[4], 5)672 self.assertEqual(clusterid[5], 5)673 self.assertEqual(clusterid[6], 5)674 self.assertEqual(clusterid[7], 5)675 self.assertEqual(clusterid[8], 2)676 self.assertAlmostEqual(error, 7.680, places=3)677 def test_pca(self):678 if TestCluster.module == 'Bio.Cluster':679 from Bio.Cluster import pca680 elif TestCluster.module == 'Pycluster':681 from Pycluster import pca682 data = numpy.array([[3.1, 1.2],683 [1.4, 1.3],684 [1.1, 1.5],685 [2.0, 1.5],686 [1.7, 1.9],687 [1.7, 1.9],688 [5.7, 5.9],689 [5.7, 5.9],690 [3.1, 3.3],691 [5.4, 5.3],692 [5.1, 5.5],693 [5.0, 5.5],694 [5.1, 5.2],695 ])696 mean, coordinates, pc, eigenvalues = pca(data)697 self.assertAlmostEqual(mean[0], 3.5461538461538464)698 self.assertAlmostEqual(mean[1], 3.5307692307692311)699 self.assertAlmostEqual(coordinates[0, 0], 2.0323189722653883)700 self.assertAlmostEqual(coordinates[0, 1], 1.2252420399694917)701 self.assertAlmostEqual(coordinates[1, 0], 3.0936985166252251)702 self.assertAlmostEqual(coordinates[1, 1], -0.10647619705157851)703 self.assertAlmostEqual(coordinates[2, 0], 3.1453186907749426)704 self.assertAlmostEqual(coordinates[2, 1], -0.46331699855941139)705 self.assertAlmostEqual(coordinates[3, 0], 2.5440202962223761)706 self.assertAlmostEqual(coordinates[3, 1], 0.20633980959571077)707 self.assertAlmostEqual(coordinates[4, 0], 2.4468278463376221)708 self.assertAlmostEqual(coordinates[4, 1], -0.28412285736824866)709 self.assertAlmostEqual(coordinates[5, 0], 2.4468278463376221)710 self.assertAlmostEqual(coordinates[5, 1], -0.28412285736824866)711 self.assertAlmostEqual(coordinates[6, 0], -3.2018619434743254)712 self.assertAlmostEqual(coordinates[6, 1], 0.019692314198662915)713 self.assertAlmostEqual(coordinates[7, 0], -3.2018619434743254)714 self.assertAlmostEqual(coordinates[7, 1], 0.019692314198662915)715 self.assertAlmostEqual(coordinates[8, 0], 0.46978641990344067)716 self.assertAlmostEqual(coordinates[8, 1], -0.17778754731982949)717 self.assertAlmostEqual(coordinates[9, 0], -2.5549912731867215)718 self.assertAlmostEqual(coordinates[9, 1], 0.19733897451533403)719 self.assertAlmostEqual(coordinates[10, 0], -2.5033710990370044)720 self.assertAlmostEqual(coordinates[10, 1], -0.15950182699250004)721 self.assertAlmostEqual(coordinates[11, 0], -2.4365601663089413)722 self.assertAlmostEqual(coordinates[11, 1], -0.23390813900973562)723 self.assertAlmostEqual(coordinates[12, 0], -2.2801521629852974)724 self.assertAlmostEqual(coordinates[12, 1], 0.0409309711916888)725 self.assertAlmostEqual(pc[0, 0], -0.66810932728062988)726 self.assertAlmostEqual(pc[0, 1], -0.74406312017235743)727 self.assertAlmostEqual(pc[1, 0], 0.74406312017235743)728 self.assertAlmostEqual(pc[1, 1], -0.66810932728062988)729 self.assertAlmostEqual(eigenvalues[0], 9.3110471246032844)730 self.assertAlmostEqual(eigenvalues[1], 1.4437456297481428)731 data = numpy.array([[2.3, 4.5, 1.2, 6.7, 5.3, 7.1],732 [1.3, 6.5, 2.2, 5.7, 6.2, 9.1],733 [3.2, 7.2, 3.2, 7.4, 7.3, 8.9],734 [4.2, 5.2, 9.2, 4.4, 6.3, 7.2]])735 mean, coordinates, pc, eigenvalues = pca(data)736 self.assertAlmostEqual(mean[0], 2.7500)737 self.assertAlmostEqual(mean[1], 5.8500)738 self.assertAlmostEqual(mean[2], 3.9500)739 self.assertAlmostEqual(mean[3], 6.0500)740 self.assertAlmostEqual(mean[4], 6.2750)741 self.assertAlmostEqual(mean[5], 8.0750)742 self.assertAlmostEqual(coordinates[0, 0], 2.6460846688406905)743 self.assertAlmostEqual(coordinates[0, 1], -2.1421701432732418)744 self.assertAlmostEqual(coordinates[0, 2], -0.56620932754145858)745 self.assertAlmostEqual(coordinates[0, 3], 0.0)746 self.assertAlmostEqual(coordinates[1, 0], 2.0644120899917544)747 self.assertAlmostEqual(coordinates[1, 1], 0.55542108669180323)748 self.assertAlmostEqual(coordinates[1, 2], 1.4818772348457117)749 self.assertAlmostEqual(coordinates[1, 3], 0.0)750 self.assertAlmostEqual(coordinates[2, 0], 1.0686641862092987)751 self.assertAlmostEqual(coordinates[2, 1], 1.9994412069101073)752 self.assertAlmostEqual(coordinates[2, 2], -1.000720598980291)753 self.assertAlmostEqual(coordinates[2, 3], 0.0)754 self.assertAlmostEqual(coordinates[3, 0], -5.77916094504174)755 self.assertAlmostEqual(coordinates[3, 1], -0.41269215032867046)756 self.assertAlmostEqual(coordinates[3, 2], 0.085052691676038017)757 self.assertAlmostEqual(coordinates[3, 3], 0.0)758 self.assertAlmostEqual(pc[0, 0], -0.26379660005997291)759 self.assertAlmostEqual(pc[0, 1], 0.064814972617134495)760 self.assertAlmostEqual(pc[0, 2], -0.91763310094893846)761 self.assertAlmostEqual(pc[0, 3], 0.26145408875373249)762 self.assertAlmostEqual(pc[1, 0], 0.05073770520434398)763 self.assertAlmostEqual(pc[1, 1], 0.68616983388698793)764 self.assertAlmostEqual(pc[1, 2], 0.13819106187213354)765 self.assertAlmostEqual(pc[1, 3], 0.19782544121828985)766 self.assertAlmostEqual(pc[2, 0], -0.63000893660095947)767 self.assertAlmostEqual(pc[2, 1], 0.091155993862151397)768 self.assertAlmostEqual(pc[2, 2], 0.045630391256086845)769 self.assertAlmostEqual(pc[2, 3], -0.67456694780914772)770 # As the last eigenvalue is zero, the corresponding eigenvector is771 # strongly affected by roundoff error, and is not being tested here.772 # For PCA, this doesn't matter since all data have a zero coefficient773 # along this eigenvector.774 self.assertAlmostEqual(eigenvalues[0], 6.7678878332578778)775 self.assertAlmostEqual(eigenvalues[1], 3.0108911400291856)776 self.assertAlmostEqual(eigenvalues[2], 1.8775592718563467)777 self.assertAlmostEqual(eigenvalues[3], 0.0)778if __name__ == "__main__":779 TestCluster.module = 'Bio.Cluster'780 runner = unittest.TextTestRunner(verbosity=2)...
test_complex.py
Source:test_complex.py
...8)9from random import random10# These tests ensure that complex math does the right thing11class ComplexTest(unittest.TestCase):12 def assertAlmostEqual(self, a, b):13 if isinstance(a, complex):14 if isinstance(b, complex):15 unittest.TestCase.assertAlmostEqual(self, a.real, b.real)16 unittest.TestCase.assertAlmostEqual(self, a.imag, b.imag)17 else:18 unittest.TestCase.assertAlmostEqual(self, a.real, b)19 unittest.TestCase.assertAlmostEqual(self, a.imag, 0.)20 else:21 if isinstance(b, complex):22 unittest.TestCase.assertAlmostEqual(self, a, b.real)23 unittest.TestCase.assertAlmostEqual(self, 0., b.imag)24 else:25 unittest.TestCase.assertAlmostEqual(self, a, b)26 def assertCloseAbs(self, x, y, eps=1e-9):27 """Return true iff floats x and y "are close\""""28 # put the one with larger magnitude second29 if abs(x) > abs(y):30 x, y = y, x31 if y == 0:32 return abs(x) < eps33 if x == 0:34 return abs(y) < eps35 # check that relative difference < eps36 self.assert_(abs((x-y)/y) < eps)37 def assertClose(self, x, y, eps=1e-9):38 """Return true iff complexes x and y "are close\""""39 self.assertCloseAbs(x.real, y.real, eps)40 self.assertCloseAbs(x.imag, y.imag, eps)41 def assertIs(self, a, b):42 self.assert_(a is b)43 def check_div(self, x, y):44 """Compute complex z=x*y, and check that z/x==y and z/y==x."""45 z = x * y46 if x != 0:47 q = z / x48 self.assertClose(q, y)49 q = z.__div__(x)50 self.assertClose(q, y)51 q = z.__truediv__(x)52 self.assertClose(q, y)53 if y != 0:54 q = z / y55 self.assertClose(q, x)56 q = z.__div__(y)57 self.assertClose(q, x)58 q = z.__truediv__(y)59 self.assertClose(q, x)60 def test_div(self):61 simple_real = [float(i) for i in xrange(-5, 6)]62 simple_complex = [complex(x, y) for x in simple_real for y in simple_real]63 for x in simple_complex:64 for y in simple_complex:65 self.check_div(x, y)66 # A naive complex division algorithm (such as in 2.0) is very prone to67 # nonsense errors for these (overflows and underflows).68 self.check_div(complex(1e200, 1e200), 1+0j)69 self.check_div(complex(1e-200, 1e-200), 1+0j)70 # Just for fun.71 for i in xrange(100):72 self.check_div(complex(random(), random()),73 complex(random(), random()))74 self.assertRaises(ZeroDivisionError, complex.__div__, 1+1j, 0+0j)75 # FIXME: The following currently crashes on Alpha76 # self.assertRaises(OverflowError, pow, 1e200+1j, 1e200+1j)77 def test_truediv(self):78 self.assertAlmostEqual(complex.__truediv__(2+0j, 1+1j), 1-1j)79 self.assertRaises(ZeroDivisionError, complex.__truediv__, 1+1j, 0+0j)80 def test_floordiv(self):81 self.assertAlmostEqual(complex.__floordiv__(3+0j, 1.5+0j), 2)82 self.assertRaises(ZeroDivisionError, complex.__floordiv__, 3+0j, 0+0j)83 def test_coerce(self):84 self.assertRaises(OverflowError, complex.__coerce__, 1+1j, 1L<<10000)85 def test_richcompare(self):86 self.assertRaises(OverflowError, complex.__eq__, 1+1j, 1L<<10000)87 self.assertEqual(complex.__lt__(1+1j, None), NotImplemented)88 self.assertIs(complex.__eq__(1+1j, 1+1j), True)89 self.assertIs(complex.__eq__(1+1j, 2+2j), False)90 self.assertIs(complex.__ne__(1+1j, 1+1j), False)91 self.assertIs(complex.__ne__(1+1j, 2+2j), True)92 self.assertRaises(TypeError, complex.__lt__, 1+1j, 2+2j)93 self.assertRaises(TypeError, complex.__le__, 1+1j, 2+2j)94 self.assertRaises(TypeError, complex.__gt__, 1+1j, 2+2j)95 self.assertRaises(TypeError, complex.__ge__, 1+1j, 2+2j)96 def test_mod(self):97 self.assertRaises(ZeroDivisionError, (1+1j).__mod__, 0+0j)98 a = 3.33+4.43j99 try:100 a % 0101 except ZeroDivisionError:102 pass103 else:104 self.fail("modulo parama can't be 0")105 def test_divmod(self):106 self.assertRaises(ZeroDivisionError, divmod, 1+1j, 0+0j)107 def test_pow(self):108 self.assertAlmostEqual(pow(1+1j, 0+0j), 1.0)109 self.assertAlmostEqual(pow(0+0j, 2+0j), 0.0)110 self.assertRaises(ZeroDivisionError, pow, 0+0j, 1j)111 self.assertAlmostEqual(pow(1j, -1), 1/1j)112 self.assertAlmostEqual(pow(1j, 200), 1)113 self.assertRaises(ValueError, pow, 1+1j, 1+1j, 1+1j)114 a = 3.33+4.43j115 self.assertEqual(a ** 0j, 1)116 self.assertEqual(a ** 0.+0.j, 1)117 self.assertEqual(3j ** 0j, 1)118 self.assertEqual(3j ** 0, 1)119 try:120 0j ** a121 except ZeroDivisionError:122 pass123 else:124 self.fail("should fail 0.0 to negative or complex power")125 try:126 0j ** (3-2j)127 except ZeroDivisionError:128 pass129 else:130 self.fail("should fail 0.0 to negative or complex power")131 # The following is used to exercise certain code paths132 self.assertEqual(a ** 105, a ** 105)133 self.assertEqual(a ** -105, a ** -105)134 self.assertEqual(a ** -30, a ** -30)135 self.assertEqual(0.0j ** 0, 1)136 b = 5.1+2.3j137 self.assertRaises(ValueError, pow, a, b, 0)138 def test_boolcontext(self):139 for i in xrange(100):140 self.assert_(complex(random() + 1e-6, random() + 1e-6))141 self.assert_(not complex(0.0, 0.0))142 def test_conjugate(self):143 self.assertClose(complex(5.3, 9.8).conjugate(), 5.3-9.8j)144 def test_constructor(self):145 class OS:146 def __init__(self, value): self.value = value147 def __complex__(self): return self.value148 class NS(object):149 def __init__(self, value): self.value = value150 def __complex__(self): return self.value151 self.assertEqual(complex(OS(1+10j)), 1+10j)152 self.assertEqual(complex(NS(1+10j)), 1+10j)153 self.assertRaises(TypeError, complex, OS(None))154 self.assertRaises(TypeError, complex, NS(None))155 self.assertAlmostEqual(complex("1+10j"), 1+10j)156 self.assertAlmostEqual(complex(10), 10+0j)157 self.assertAlmostEqual(complex(10.0), 10+0j)158 self.assertAlmostEqual(complex(10L), 10+0j)159 self.assertAlmostEqual(complex(10+0j), 10+0j)160 self.assertAlmostEqual(complex(1,10), 1+10j)161 self.assertAlmostEqual(complex(1,10L), 1+10j)162 self.assertAlmostEqual(complex(1,10.0), 1+10j)163 self.assertAlmostEqual(complex(1L,10), 1+10j)164 self.assertAlmostEqual(complex(1L,10L), 1+10j)165 self.assertAlmostEqual(complex(1L,10.0), 1+10j)166 self.assertAlmostEqual(complex(1.0,10), 1+10j)167 self.assertAlmostEqual(complex(1.0,10L), 1+10j)168 self.assertAlmostEqual(complex(1.0,10.0), 1+10j)169 self.assertAlmostEqual(complex(3.14+0j), 3.14+0j)170 self.assertAlmostEqual(complex(3.14), 3.14+0j)171 self.assertAlmostEqual(complex(314), 314.0+0j)172 self.assertAlmostEqual(complex(314L), 314.0+0j)173 self.assertAlmostEqual(complex(3.14+0j, 0j), 3.14+0j)174 self.assertAlmostEqual(complex(3.14, 0.0), 3.14+0j)175 self.assertAlmostEqual(complex(314, 0), 314.0+0j)176 self.assertAlmostEqual(complex(314L, 0L), 314.0+0j)177 self.assertAlmostEqual(complex(0j, 3.14j), -3.14+0j)178 self.assertAlmostEqual(complex(0.0, 3.14j), -3.14+0j)179 self.assertAlmostEqual(complex(0j, 3.14), 3.14j)180 self.assertAlmostEqual(complex(0.0, 3.14), 3.14j)181 self.assertAlmostEqual(complex("1"), 1+0j)182 self.assertAlmostEqual(complex("1j"), 1j)183 self.assertAlmostEqual(complex(), 0)184 self.assertAlmostEqual(complex("-1"), -1)185 self.assertAlmostEqual(complex("+1"), +1)186 class complex2(complex): pass187 self.assertAlmostEqual(complex(complex2(1+1j)), 1+1j)188 self.assertAlmostEqual(complex(real=17, imag=23), 17+23j)189 self.assertAlmostEqual(complex(real=17+23j), 17+23j)190 self.assertAlmostEqual(complex(real=17+23j, imag=23), 17+46j)191 self.assertAlmostEqual(complex(real=1+2j, imag=3+4j), -3+5j)192 c = 3.14 + 1j193 self.assert_(complex(c) is c)194 del c195 self.assertRaises(TypeError, complex, "1", "1")196 self.assertRaises(TypeError, complex, 1, "1")197 self.assertEqual(complex(" 3.14+J "), 3.14+1j)198 if test_support.have_unicode:199 self.assertEqual(complex(unicode(" 3.14+J ")), 3.14+1j)200 # SF bug 543840: complex(string) accepts strings with \0201 # Fixed in 2.3.202 self.assertRaises(ValueError, complex, '1+1j\0j')203 self.assertRaises(TypeError, int, 5+3j)204 self.assertRaises(TypeError, long, 5+3j)205 self.assertRaises(TypeError, float, 5+3j)206 self.assertRaises(ValueError, complex, "")207 self.assertRaises(TypeError, complex, None)208 self.assertRaises(ValueError, complex, "\0")209 self.assertRaises(TypeError, complex, "1", "2")210 self.assertRaises(TypeError, complex, "1", 42)211 self.assertRaises(TypeError, complex, 1, "2")212 self.assertRaises(ValueError, complex, "1+")213 self.assertRaises(ValueError, complex, "1+1j+1j")214 self.assertRaises(ValueError, complex, "--")215 if test_support.have_unicode:216 self.assertRaises(ValueError, complex, unicode("1"*500))217 self.assertRaises(ValueError, complex, unicode("x"))218 class EvilExc(Exception):219 pass220 class evilcomplex:221 def __complex__(self):222 raise EvilExc223 self.assertRaises(EvilExc, complex, evilcomplex())224 class float2:225 def __init__(self, value):226 self.value = value227 def __float__(self):228 return self.value229 self.assertAlmostEqual(complex(float2(42.)), 42)230 self.assertAlmostEqual(complex(real=float2(17.), imag=float2(23.)), 17+23j)231 self.assertRaises(TypeError, complex, float2(None))232 class complex0(complex):233 """Test usage of __complex__() when inheriting from 'complex'"""234 def __complex__(self):235 return 42j236 class complex1(complex):237 """Test usage of __complex__() with a __new__() method"""238 def __new__(self, value=0j):239 return complex.__new__(self, 2*value)240 def __complex__(self):241 return self242 class complex2(complex):243 """Make sure that __complex__() calls fail if anything other than a244 complex is returned"""245 def __complex__(self):246 return None247 self.assertAlmostEqual(complex(complex0(1j)), 42j)248 self.assertAlmostEqual(complex(complex1(1j)), 2j)249 self.assertRaises(TypeError, complex, complex2(1j))250 def test_hash(self):251 for x in xrange(-30, 30):252 self.assertEqual(hash(x), hash(complex(x, 0)))253 x /= 3.0 # now check against floating point254 self.assertEqual(hash(x), hash(complex(x, 0.)))255 def test_abs(self):256 nums = [complex(x/3., y/7.) for x in xrange(-9,9) for y in xrange(-9,9)]257 for num in nums:258 self.assertAlmostEqual((num.real**2 + num.imag**2) ** 0.5, abs(num))259 def test_repr(self):260 self.assertEqual(repr(1+6j), '(1+6j)')261 self.assertEqual(repr(1-6j), '(1-6j)')262 self.assertNotEqual(repr(-(1+0j)), '(-1+-0j)')263 def test_neg(self):264 self.assertEqual(-(1+6j), -1-6j)265 def test_file(self):266 a = 3.33+4.43j267 b = 5.1+2.3j268 fo = None269 try:270 fo = open(test_support.TESTFN, "wb")271 print >>fo, a, b272 fo.close()...
adsorbate_thermo_test.py
Source:adsorbate_thermo_test.py
...21 """22 Check values of Q_trans, S_trans, Cp_trans, dH_trans23 """24 Q_trans, S_trans, Cp_trans, dH_trans = self.adsorbate_thermo.get_translation_thermo()25 self.assertAlmostEqual(Q_trans[0], 121.638576209145)26 self.assertAlmostEqual(Q_trans[45], 301.9035599354932)27 self.assertAlmostEqual(Q_trans[-2], 811.8757895562588)28 self.assertAlmostEqual(S_trans[0], 56.54717436538365)29 self.assertAlmostEqual(S_trans[45], 64.10547399343213)30 self.assertAlmostEqual(S_trans[-2], 72.33048004244537)31 self.assertAlmostEqual(Cp_trans[0], 8.314472)32 self.assertAlmostEqual(Cp_trans[45], 8.314472)33 self.assertAlmostEqual(Cp_trans[-2], 8.314472)34 self.assertAlmostEqual(dH_trans[0], 2478.9598268)35 self.assertAlmostEqual(dH_trans[45], 6152.70928)36 self.assertAlmostEqual(dH_trans[-2], 16545.79928)37 def test_get_vibration_thermo(self):38 """39 Check values of Q_vib, S_vib, dH_vib, Cv_vib40 """41 Q_vib, S_vib, dH_vib, Cv_vib = self.adsorbate_thermo.get_vibrational_thermo()42 self.assertAlmostEqual(Q_vib[0], 11.034963254025913)43 self.assertAlmostEqual(Q_vib[45], 130.32233489549847)44 self.assertAlmostEqual(Q_vib[-2], 6018.728683338621)45 self.assertAlmostEqual(S_vib[0], 38.07225504419116)46 self.assertAlmostEqual(S_vib[45], 67.49815326008806)47 self.assertAlmostEqual(S_vib[-2], 110.22104390942083)48 self.assertAlmostEqual(dH_vib[0], 5399.089968555581)49 self.assertAlmostEqual(dH_vib[45], 19984.872272678833)50 self.assertAlmostEqual(dH_vib[-2], 75347.8861223393)51 self.assertAlmostEqual(Cv_vib[0], 28.074698286767678)52 self.assertAlmostEqual(Cv_vib[45], 36.77745028228141)53 self.assertAlmostEqual(Cv_vib[-2], 49.93125232130692)54 def test_get_thermo(self):55 """56 Check the NASA polynomials57 """58 nasa = self.adsorbate_thermo.get_thermo()59 a_low = [1253.2, 18.899, -0.0390199, 3.98049e-05, -1.52948e-08, -24879.5, 20.1649]60 a_high = [4092.47, 1.56959, 0.000643606, -5.4255e-07, 9.64746e-11, -397031, -12477.9]61 np.testing.assert_array_almost_equal(nasa.polynomials[0].coeffs, a_low, 1)62 np.testing.assert_array_almost_equal(nasa.polynomials[1].coeffs, a_high, 1)63if __name__ == '__main__':...
varasto_test.py
Source:varasto_test.py
...7 self.ylijaama = Varasto(10, 30)8 9 def test_konstruktori_luo_tyhjan_varaston(self):10 # https://docs.python.org/3/library/unittest.html#unittest.TestCase.assertAlmostEqual11 self.assertAlmostEqual(self.varasto.saldo, 0)12 def test_uudella_varastolla_oikea_tilavuus(self):13 self.assertAlmostEqual(self.varasto.tilavuus, 10)14 def test_lisays_lisaa_saldoa(self):15 self.varasto.lisaa_varastoon(8)16 self.assertAlmostEqual(self.varasto.saldo, 8)17 18 def test_lisayksessa_vain_positiviisia_arvoja(self):19 self.varasto.lisaa_varastoon(-10)20 self.assertAlmostEqual(self.varasto.saldo, 0)21 22 def test_lisayksessa_ei_ylijaama(self):23 self.varasto.lisaa_varastoon(500)24 self.assertAlmostEqual(self.varasto.saldo, 10)25 def test_lisays_lisaa_pienentaa_vapaata_tilaa(self):26 self.varasto.lisaa_varastoon(8)27 # vapaata tilaa pitäisi vielä olla tilavuus-lisättävä määrä eli 228 self.assertAlmostEqual(self.varasto.paljonko_mahtuu(), 2)29 def test_ottaminen_palauttaa_oikean_maaran(self):30 self.varasto.lisaa_varastoon(8)31 saatu_maara = self.varasto.ota_varastosta(2)32 self.assertAlmostEqual(saatu_maara, 2)33 def test_ottaminen_lisaa_tilaa(self):34 self.varasto.lisaa_varastoon(8)35 self.varasto.ota_varastosta(2)36 # varastossa pitäisi olla tilaa 10 - 8 + 2 eli 437 self.assertAlmostEqual(self.varasto.paljonko_mahtuu(), 4)38 39 def test_ottaminen_vain_positiivisilla_arvoilla(self):40 self.varasto.lisaa_varastoon(5)41 saatu_maara = self.varasto.ota_varastosta(-5)42 self.assertAlmostEqual(saatu_maara, 0)43 44 def test_varaston_tyhjentaminen_palauttaa_oikean_maaran_saldon(self):45 self.varasto.lisaa_varastoon(8)46 saatu_maara = self.varasto.ota_varastosta(10)47 self.assertAlmostEqual(saatu_maara, 8)48 self.assertAlmostEqual(self.varasto.saldo, 0)49 50 def test_konstruktori_hyvaksyy_vain_positiivisen_tilavuuden(self):51 self.assertAlmostEqual(self.neg_arvot.tilavuus, 0)52 53 def test_konstruktori_hyvaksyy_vain_positiivisen_alku_saldon(self):54 self.assertAlmostEqual(self.neg_arvot.saldo, 0)55 56 def test_konstruktori_laskee_ylijaamatilanteen_oikein(self):57 self.assertAlmostEqual(self.ylijaama.saldo, 10)58 def test_tulostus_oikein(self):...
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