From ebfe00e12ef797328626d7d4e5bdd8bf12442c27 Mon Sep 17 00:00:00 2001 From: bbauvin <baptiste.bauvin@centrale-marseille.fr> Date: Tue, 27 Sep 2016 17:38:06 -0400 Subject: [PATCH] debugging --- Code/MonoMutliViewClassifiers/ExecClassif.py | 1 - Code/MonoMutliViewClassifiers/MonoviewClassifiers/SCM.py | 5 +++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/Code/MonoMutliViewClassifiers/ExecClassif.py b/Code/MonoMutliViewClassifiers/ExecClassif.py index db1b0432..5815e873 100644 --- a/Code/MonoMutliViewClassifiers/ExecClassif.py +++ b/Code/MonoMutliViewClassifiers/ExecClassif.py @@ -358,7 +358,6 @@ else: classifiersNames = [[result[1][0] for result in resultsMonoview if result[0]==viewIndex] for viewIndex in viewsIndices] classifiersConfigs = [[result[1][1] for result in resultsMonoview if result[0]==viewIndex] for viewIndex in viewsIndices] monoviewTime = time.time()-dataBaseTime-start -print benchmark if True: if benchmark["Multiview"]: try: diff --git a/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SCM.py b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SCM.py index 449e4f51..9a89cf31 100644 --- a/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SCM.py +++ b/Code/MonoMutliViewClassifiers/MonoviewClassifiers/SCM.py @@ -32,11 +32,12 @@ def fit(DATASET, CLASS_LABELS, NB_CORES=1,**kwargs): attributeClassification = kwargs["attributeClassification"] binaryAttributes = kwargs["binaryAttributes"] except: - attributeClassification, binaryAttributes, dsetFile = transformData(DATASET) + attributeClassification, binaryAttributes, dsetFile, name = transformData(DATASET) classifier = pyscm.scm.SetCoveringMachine(p=p, max_attributes=max_attrtibutes, model_type=model_type, verbose=False) classifier.fit(binaryAttributes, CLASS_LABELS, X=None, attribute_classifications=attributeClassification, iteration_callback=None) try: dsetFile.close() + os.remove(name) except: pass return classifier @@ -133,7 +134,7 @@ def transformData(dataArray): dsetFile = h5py.File(name, "r") packedDataset = dsetFile.get("temp_scm") attributeClassification = BaptisteRuleClassifications(packedDataset, nbExamples) - return attributeClassification, binaryAttributes, dsetFile + return attributeClassification, binaryAttributes, dsetFile, name def isBinary(dataset): -- GitLab