def test_check_architecture2(arq="iris.arff"): pipe = Workflow( File(arq), Partition(), Map(PCA(), SVMC(), Metric(enhance=False)), Summ(field="Y", function="mean", enhance=False), Report("mean ... S: $S", enhance=False), ) # tenho file na frente train_ = pipe.enhancer.transform(sd.NoData) test_ = pipe.model(sd.NoData).transform(sd.NoData) test_ = pipe.model(sd.NoData).transform((sd.NoData, sd.NoData)) train_, test_ = pipe.dual_transform(sd.NoData, sd.NoData) train_, test_ = pipe.dual_transform(sd.NoData, (sd.NoData, sd.NoData))
def test_cache(arq="iris.arff"): pipe = Workflow(Cache(File(arq), storage_alias="default_sqlite"), Report("{history}")) train, test = pipe.dual_transform() print("Train..............\n", train.history ^ "name") print("Test..........\n", test.history ^ "name")
def test_with_summ_reduce(arq="iris.arff"): pipe = Workflow( File(arq), Partition(), Map(PCA(), SVMC(), Metric()), Map(Report("<---------------------- etapa")), Summ(), Reduce(), Report("mean ... S: $S"), ) train, test = pipe.dual_transform() print("Train..............\n", train.history ^ "longname") print("Test..........\n", test.history ^ "longname")
def test_partition(arq="iris.arff"): pipe = Workflow( File(arq), Partition(), Map(PCA(), SVMC(), Metric(enhance=False)), Summ(function="mean", enhance=False), Reduce(), Report("mean ... S: $S", enhance=False), Report("$X"), Report("$y"), ) train, test = pipe.dual_transform() print("Train..............\n", train) print("Test..........\n", test)
def test_check_architecture(arq="iris.arff"): pipe = Workflow( File(arq), Partition(partitions=2), Map(PCA(), SVMC(), Metric(enhance=False)), Summ(field="Y", function="mean", enhance=False), ) # tenho file na frente train_01 = pipe.enhancer.transform(sd.NoData) test_01 = pipe.model(sd.NoData).transform(sd.NoData) train_02, test_02 = pipe.dual_transform(sd.NoData, sd.NoData) # Collection uuid depends on data, which depends on consumption. for t, *_ in train_01, train_02, test_01, test_02: # print(111111111, t.y) pass assert train_01.uuid == train_02.uuid assert test_01.uuid == test_02.uuid
def test_pca(arq="iris.arff"): cs = File(arq).cs pipe = Workflow(File(arq), Split(), PCA(), SVMC(), Metric()) train, test = pipe.dual_transform() print("Train..............\n", train.history ^ "name") print("Test..........\n", test.history ^ "name")
def test_metric(arq="iris.arff"): pipe = Workflow(File(arq), Split(), SVMC(), Metric(enhance=False)) train, test = pipe.dual_transform() print("Train..............\n", train) print("Test..........\n", test)
def test_split(arq="iris.arff"): pipe = Workflow(File(arq), Split(), SVMC()) train, test = pipe.dual_transform() print("Train..............\n", str(train)) print("Test..........\n", str(test))
def test_svmc(arq="iris.arff"): cs = File(arq).cs pipe = Workflow(File(arq), SVMC()) train, test = pipe.dual_transform() print("Train..............\n", train) print("Test..........\n", test)