diff --git a/Code/MonoMultiViewClassifiers/ExecClassif.py b/Code/MonoMultiViewClassifiers/ExecClassif.py
index 4283c7003a1ddb65da641bf5bcecd2b6524de22c..df869b6806a0403f36de7d3379a62c8ce7c9a57e 100644
--- a/Code/MonoMultiViewClassifiers/ExecClassif.py
+++ b/Code/MonoMultiViewClassifiers/ExecClassif.py
@@ -845,7 +845,7 @@ def execOneBenchmark(coreIndex=-1, LABELS_DICTIONARY=None, directory=None, class
except OSError as exc:
if exc.errno != errno.EEXIST:
raise
- trainIndices, testIndices = classificationIndices
+ trainIndices = classificationIndices[0]
trainLabels = labels[trainIndices]
np.savetxt(directory + "train_labels.csv", trainLabels, delimiter=",")
resultsMonoview = []
@@ -883,7 +883,7 @@ def execOneBenchmark_multicore(nbCores=-1, LABELS_DICTIONARY=None, directory=Non
except OSError as exc:
if exc.errno != errno.EEXIST:
raise
- trainIndices, testIndices = classificationIndices
+ trainIndices = classificationIndices[0]
trainLabels = labels[trainIndices]
np.savetxt(directory + "train_labels.csv", trainLabels, delimiter=",")
np.savetxt(directory + "train_indices.csv", classificationIndices[0], delimiter=",")
@@ -929,7 +929,7 @@ def execOneBenchmarkMonoCore(DATASET=None, LABELS_DICTIONARY=None, directory=Non
except OSError as exc:
if exc.errno != errno.EEXIST:
raise
- trainIndices, testIndices = classificationIndices
+ trainIndices = classificationIndices[0]
trainLabels = labels[trainIndices]
np.savetxt(directory + "train_labels.csv", trainLabels, delimiter=",")
resultsMonoview = []
@@ -1023,7 +1023,7 @@ def execClassif(arguments):
classificationIndices = execution.genSplits(DATASET.get("Labels").value, args.CL_split, statsIterRandomStates)
- multiclassLabels, labelsCombinations, oldIndicesMulticlass = Multiclass.genMulticlassLabels(DATASET.get("Labels").value, multiclassMethod, classificationIndices)
+ multiclassLabels, labelsCombinations, indicesMulticlass = Multiclass.genMulticlassLabels(DATASET.get("Labels").value, multiclassMethod, classificationIndices)
kFolds = execution.genKFolds(statsIter, args.CL_nbFolds, statsIterRandomStates)
@@ -1060,7 +1060,7 @@ def execClassif(arguments):
initKWARGS)
directories = execution.genDirecortiesNames(directory, statsIter)
benchmarkArgumentDictionaries = execution.genArgumentDictionaries(LABELS_DICTIONARY, directories, multiclassLabels,
- labelsCombinations, oldIndicesMulticlass,
+ labelsCombinations, indicesMulticlass,
hyperParamSearch, args, kFolds,
statsIterRandomStates, metrics,
argumentDictionaries, benchmark, nbViews, views)
diff --git a/Code/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py b/Code/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py
index fa0a4eba0a6cfd0055d45a3ab35bc121cccfe00e..0926a3e313e36131f81eef1023964d257d56e715 100644
--- a/Code/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py
+++ b/Code/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py
@@ -49,12 +49,13 @@ def initConstants(args, X, classificationIndices, labelsNames, name, directory):
def initTrainTest(X, Y, classificationIndices):
- trainIndices, testIndices = classificationIndices
+ trainIndices, testIndices, testIndicesMulticlass = classificationIndices
X_train = extractSubset(X, trainIndices)
X_test = extractSubset(X, testIndices)
+ X_test_multiclass = extractSubset(X, testIndicesMulticlass)
y_train = Y[trainIndices]
y_test = Y[testIndices]
- return X_train, y_train, X_test, y_test
+ return X_train, y_train, X_test, y_test, X_test_multiclass
def getKWARGS(classifierModule, hyperParamSearch, nIter, CL_type, X_train, y_train, randomState,
@@ -127,7 +128,7 @@ def ExecMonoview(directory, X, Y, name, labelsNames, classificationIndices, KFol
+ str(nbCores) + ", algorithm : " + CL_type)
logging.debug("Start:\t Determine Train/Test split")
- X_train, y_train, X_test, y_test = initTrainTest(X, Y, classificationIndices)
+ X_train, y_train, X_test, y_test, X_test_multiclass = initTrainTest(X, Y, classificationIndices)
logging.debug("Info:\t Shape X_train:" + str(X_train.shape) + ", Length of y_train:" + str(len(y_train)))
logging.debug("Info:\t Shape X_test:" + str(X_test.shape) + ", Length of y_test:" + str(len(y_test)))
logging.debug("Done:\t Determine Train/Test split")
@@ -145,13 +146,14 @@ def ExecMonoview(directory, X, Y, name, labelsNames, classificationIndices, KFol
logging.debug("Done:\t Training")
logging.debug("Start:\t Predicting")
+ y_train_pred = cl_res.predict(X_train)
+ y_test_pred = cl_res.predict(X_test)
full_labels_pred = np.zeros(Y.shape, dtype=int)-100
- y_train_pred = cl_res.predict(X[classificationIndices[0]])
- y_test_pred = cl_res.predict(X[classificationIndices[1]])
for trainIndex, index in enumerate(classificationIndices[0]):
full_labels_pred[index] = y_train_pred[trainIndex]
for testIndex, index in enumerate(classificationIndices[1]):
full_labels_pred[index] = y_test_pred[testIndex]
+ y_test_multiclass_pred = cl_res.predict(X_test_multiclass)
logging.debug("Done:\t Predicting")
@@ -174,7 +176,7 @@ def ExecMonoview(directory, X, Y, name, labelsNames, classificationIndices, KFol
logging.info("Done:\t Saving Results")
viewIndex = args["viewIndex"]
- return viewIndex, [CL_type, cl_desc + [feat], metricsScores, full_labels_pred, clKWARGS]
+ return viewIndex, [CL_type, cl_desc + [feat], metricsScores, full_labels_pred, clKWARGS, y_test_multiclass_pred]
if __name__ == '__main__':
diff --git a/Code/MonoMultiViewClassifiers/Multiview/ExecMultiview.py b/Code/MonoMultiViewClassifiers/Multiview/ExecMultiview.py
index d8fbd7a0e4fab0fa56b75ddddc48afb63a8da776..388ebc70ef9768251c047ed4250bfd5eb3e2c0de 100644
--- a/Code/MonoMultiViewClassifiers/Multiview/ExecMultiview.py
+++ b/Code/MonoMultiViewClassifiers/Multiview/ExecMultiview.py
@@ -95,7 +95,7 @@ def ExecMultiview(directory, DATASET, name, classificationIndices, KFolds, nbCor
logging.info("Info:\t Extraction duration "+str(extractionTime)+"s")
logging.debug("Start:\t Getting train/test split")
- learningIndices, validationIndices = classificationIndices
+ learningIndices, validationIndices, testIndicesMulticlass = classificationIndices
logging.debug("Done:\t Getting train/test split")
logging.debug("Start:\t Getting classifiers modules")
@@ -129,6 +129,7 @@ def ExecMultiview(directory, DATASET, name, classificationIndices, KFolds, nbCor
fullLabels[index] = trainLabels[trainIndex]
for testIndex, index in enumerate(validationIndices):
fullLabels[index] = testLabels[testIndex]
+ testLabelsMulticlass = classifier.predict_hdf5(DATASET, usedIndices=testIndicesMulticlass, viewsIndices=viewsIndices)
logging.info("Done:\t Pertidcting")
classificationTime = time.time() - t_start
@@ -157,4 +158,4 @@ def ExecMultiview(directory, DATASET, name, classificationIndices, KFolds, nbCor
learningRate, name, imagesAnalysis)
logging.debug("Start:\t Saving preds")
- return CL_type, classificationKWARGS, metricsScores, fullLabels
+ return CL_type, classificationKWARGS, metricsScores, fullLabels, testLabelsMulticlass
diff --git a/Code/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/analyzeResults.py b/Code/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/analyzeResults.py
index 80dafb3e9bc860d26fb7d107983106b5d8ef1b2c..abc5ecb46ccbc647eca2cffa4b70443eb0e0a8f8 100644
--- a/Code/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/analyzeResults.py
+++ b/Code/MonoMultiViewClassifiers/MultiviewClassifiers/Fusion/analyzeResults.py
@@ -66,7 +66,7 @@ def execute(classifier, trainLabels,
monoviewClassifiersConfigs = classificationKWARGS["classifiersConfigs"]
fusionMethodConfig = classificationKWARGS["fusionMethodConfig"]
- learningIndices, validationIndices = classificationIndices
+ learningIndices, validationIndices, testIndicesMulticlass = classificationIndices
metricModule = getattr(Metrics, metrics[0][0])
if metrics[0][1] is not None:
metricKWARGS = dict((index, metricConfig) for index, metricConfig in enumerate(metrics[0][1]))
diff --git a/Code/MonoMultiViewClassifiers/MultiviewClassifiers/Mumbo/analyzeResults.py b/Code/MonoMultiViewClassifiers/MultiviewClassifiers/Mumbo/analyzeResults.py
index 269c5b1261536144341fc82cb77d65c758c5d1b2..85ac7a12e101480cd2f18c7fc950e25dd30c1d34 100644
--- a/Code/MonoMultiViewClassifiers/MultiviewClassifiers/Mumbo/analyzeResults.py
+++ b/Code/MonoMultiViewClassifiers/MultiviewClassifiers/Mumbo/analyzeResults.py
@@ -116,7 +116,7 @@ def getAlgoConfig(classifier, classificationKWARGS, nbCores, viewNames, hyperPar
def getReport(classifier, CLASS_LABELS, classificationIndices, DATASET, trainLabels,
testLabels, viewIndices, metric):
- learningIndices, validationIndices = classificationIndices
+ learningIndices, validationIndices, multiviewTestIndices = classificationIndices
nbView = len(viewIndices)
NB_CLASS = DATASET.get("Metadata").attrs["nbClass"]
metricModule = getattr(Metrics, metric[0])
@@ -224,7 +224,7 @@ def execute(classifier, trainLabels,
databaseName, KFolds,
hyperParamSearch, nIter, metrics,
viewsIndices, randomState, labels):
- learningIndices, validationIndices = classificationIndices
+ learningIndices, validationIndices, testIndicesMulticlass = classificationIndices
if classifier.classifiersConfigs is None:
metricsScores = getMetricsScores(metrics, trainLabels, testLabels,
validationIndices, learningIndices, labels)
diff --git a/Code/MonoMultiViewClassifiers/utils/Multiclass.py b/Code/MonoMultiViewClassifiers/utils/Multiclass.py
index c10eb2707a0d8e7d15934d616c4d4818e3a7db39..9bbd793f3409f6e62d8a8173c81d5eed12b1c3ed 100644
--- a/Code/MonoMultiViewClassifiers/utils/Multiclass.py
+++ b/Code/MonoMultiViewClassifiers/utils/Multiclass.py
@@ -21,7 +21,8 @@ def genMulticlassLabels(labels, multiclassMethod, classificationIndices):
for iterIndices in classificationIndices]
testIndices = [np.array([oldIndex for oldIndex in oldIndices if oldIndex in iterindices[1]])
for iterindices in classificationIndices]
- indicesMulticlass.append([trainIndices, testIndices])
+ testIndicesMulticlass = [np.array(iterindices[1]) for iterindices in classificationIndices]
+ indicesMulticlass.append([trainIndices, testIndices, testIndicesMulticlass])
newLabels = np.zeros(len(labels), dtype=int)-100
for labelIndex, label in enumerate(labels):
if label == combination[0]:
diff --git a/Code/MonoMultiViewClassifiers/utils/execution.py b/Code/MonoMultiViewClassifiers/utils/execution.py
index fd28b0c3b6865194ed969869a9fb16efcd362a25..e7f55fced030dfeca8d2f898f82ebc4c2078f03c 100644
--- a/Code/MonoMultiViewClassifiers/utils/execution.py
+++ b/Code/MonoMultiViewClassifiers/utils/execution.py
@@ -296,7 +296,7 @@ def genDirecortiesNames(directory, statsIter):
return directories
-def genArgumentDictionaries(labelsDictionary, directories, multiclassLabels, labelsCombinations, oldIndicesMulticlass, hyperParamSearch, args,
+def genArgumentDictionaries(labelsDictionary, directories, multiclassLabels, labelsCombinations, indicesMulticlass, hyperParamSearch, args,
kFolds, statsIterRandomStates, metrics, argumentDictionaries, benchmark, nbViews, views):
benchmarkArgumentDictionaries = []
for combinationIndex, labelsCombination in enumerate(labelsCombinations):
@@ -307,7 +307,9 @@ def genArgumentDictionaries(labelsDictionary, directories, multiclassLabels, lab
labelsDictionary[labelsCombination[0]]+
"vs"+
labelsDictionary[labelsCombination[1]]+"/",
- "classificationIndices": oldIndicesMulticlass[combinationIndex][iterIndex],
+ "classificationIndices": [indicesMulticlass[combinationIndex][0][iterIndex],
+ indicesMulticlass[combinationIndex][1][iterIndex],
+ indicesMulticlass[combinationIndex][2][iterIndex]],
"args": args,
"labels": multiclassLabels[combinationIndex],
"kFolds": kFolds[iterIndex],