From 19c50e142d0ba24c7352623f5d3aefe26fcf6f96 Mon Sep 17 00:00:00 2001
From: bbauvin <baptiste.bauvin@centrale-marseille.fr>
Date: Thu, 9 Nov 2017 11:54:12 -0500
Subject: [PATCH] Added multiclass test indices
---
.../Monoview/ExecClassifMonoView.py | 6 ++++--
Code/MonoMultiViewClassifiers/Multiview/ExecMultiview.py | 9 ++++-----
Code/MonoMultiViewClassifiers/utils/Multiclass.py | 1 +
Code/Tests/Test_MonoView/test_ExecClassifMonoView.py | 6 +++---
4 files changed, 12 insertions(+), 10 deletions(-)
diff --git a/Code/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py b/Code/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py
index 0926a3e3..376cb113 100644
--- a/Code/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py
+++ b/Code/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py
@@ -153,8 +153,10 @@ def ExecMonoview(directory, X, Y, name, labelsNames, classificationIndices, KFol
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)
-
+ if X_test_multiclass:
+ y_test_multiclass_pred = cl_res.predict(X_test_multiclass)
+ else:
+ y_test_multiclass_pred = []
logging.debug("Done:\t Predicting")
t_end = time.time() - t_start
diff --git a/Code/MonoMultiViewClassifiers/Multiview/ExecMultiview.py b/Code/MonoMultiViewClassifiers/Multiview/ExecMultiview.py
index 388ebc70..018b38fa 100644
--- a/Code/MonoMultiViewClassifiers/Multiview/ExecMultiview.py
+++ b/Code/MonoMultiViewClassifiers/Multiview/ExecMultiview.py
@@ -129,7 +129,10 @@ 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)
+ if testIndicesMulticlass:
+ testLabelsMulticlass = classifier.predict_hdf5(DATASET, usedIndices=testIndicesMulticlass, viewsIndices=viewsIndices)
+ else:
+ testLabelsMulticlass = []
logging.info("Done:\t Pertidcting")
classificationTime = time.time() - t_start
@@ -140,10 +143,6 @@ def ExecMultiview(directory, DATASET, name, classificationIndices, KFolds, nbCor
logging.info("Start:\t Result Analysis for " + CL_type)
times = (extractionTime, classificationTime)
- if set(labels[learningIndices])!=set([0,1]) or (set(trainLabels)!=set([0,1]) and set(trainLabels)!=set([0]) and set(trainLabels)!=set([1])):
- print(set(labels[learningIndices]))
- print(set(trainLabels))
- import pdb;pdb.set_trace()
stringAnalysis, imagesAnalysis, metricsScores = analysisModule.execute(classifier, trainLabels,
testLabels, DATASET,
classificationKWARGS, classificationIndices,
diff --git a/Code/MonoMultiViewClassifiers/utils/Multiclass.py b/Code/MonoMultiViewClassifiers/utils/Multiclass.py
index 9bbd793f..76a7a6bc 100644
--- a/Code/MonoMultiViewClassifiers/utils/Multiclass.py
+++ b/Code/MonoMultiViewClassifiers/utils/Multiclass.py
@@ -6,6 +6,7 @@ def genMulticlassLabels(labels, multiclassMethod, classificationIndices):
if multiclassMethod == "oneVersusOne":
nbLabels = len(set(list(labels)))
if nbLabels == 2:
+ classificationIndices = [[trainIndices, testIndices, []] for trainIndices, testIndices in classificationIndices]
return [labels], [(0,1)], [classificationIndices]
else:
combinations = itertools.combinations(np.arange(nbLabels), 2)
diff --git a/Code/Tests/Test_MonoView/test_ExecClassifMonoView.py b/Code/Tests/Test_MonoView/test_ExecClassifMonoView.py
index e0335980..e9879ed7 100644
--- a/Code/Tests/Test_MonoView/test_ExecClassifMonoView.py
+++ b/Code/Tests/Test_MonoView/test_ExecClassifMonoView.py
@@ -18,7 +18,7 @@ class Test_initConstants(unittest.TestCase):
cls.X = cls.datasetFile.create_dataset("View0", data=cls.X_value)
cls.X.attrs["name"] = "test_dataset"
cls.X.attrs["sparse"] = False
- cls.classificationIndices = [np.array([0,2,4,6,8]),np.array([1,3,5,7,9])]
+ cls.classificationIndices = [np.array([0,2,4,6,8]), np.array([1,3,5,7,9]), np.array([1,3,5,7,9])]
cls.labelsNames = ["test_true", "test_false"]
cls.name = "test"
cls.directory = "Code/Tests/temp_tests/test_dir/"
@@ -61,10 +61,10 @@ class Test_initTrainTest(unittest.TestCase):
cls.random_state = np.random.RandomState(42)
cls.X = cls.random_state.randint(0,500,(10,5))
cls.Y = cls.random_state.randint(0,2,10)
- cls.classificationIndices = [np.array([0,2,4,6,8]),np.array([1,3,5,7,9])]
+ cls.classificationIndices = [np.array([0,2,4,6,8]),np.array([1,3,5,7,9]), np.array([1,3,5,7,9])]
def test_simple(cls):
- X_train, y_train, X_test, y_test = ExecClassifMonoView.initTrainTest(cls.X, cls.Y, cls.classificationIndices)
+ X_train, y_train, X_test, y_test, X_test_multiclass = ExecClassifMonoView.initTrainTest(cls.X, cls.Y, cls.classificationIndices)
np.testing.assert_array_equal(X_train, np.array([np.array([102,435,348,270,106]),
np.array([466,214,330,458,87]),
np.array([149,308,257,343,491]),
--
GitLab