diff --git a/multiview_platform/execute.py b/multiview_platform/execute.py
index a142cb88fa45fb4f904bb71a97295b50f02195a5..39ca74f1c40b776e34354f56deeb4359b9837f16 100644
--- a/multiview_platform/execute.py
+++ b/multiview_platform/execute.py
@@ -1,6 +1,5 @@
"""This is the execution module, used to execute the code"""
-
def exec():
import multiview_platform.versions as versions
versions.test_versions()
diff --git a/multiview_platform/mono_multi_view_classifiers/exec_classif.py b/multiview_platform/mono_multi_view_classifiers/exec_classif.py
index 93c6f75964a477927c51adb142251d107d476e53..6bf02eb49a9d33196092600dea846cb1fffe8894 100644
--- a/multiview_platform/mono_multi_view_classifiers/exec_classif.py
+++ b/multiview_platform/mono_multi_view_classifiers/exec_classif.py
@@ -458,7 +458,7 @@ def exec_one_benchmark(core_index=-1, labels_dictionary=None, directory=None,
classification_indices, k_folds,
core_index, args["Base"]["type"], args["Base"]["pathf"], random_state,
labels,
- hyperParamSearch=hyper_param_search,
+ hyper_param_search=hyper_param_search,
metrics=metrics,
nIter=args["Classification"]["hps_iter"], **argument)
for argument in argument_dictionaries["Monoview"]]
diff --git a/multiview_platform/mono_multi_view_classifiers/monoview/exec_classif_mono_view.py b/multiview_platform/mono_multi_view_classifiers/monoview/exec_classif_mono_view.py
index 5c807f3ac3523e21b9b17ec7c91b5112385fa564..c61d5d12c2602d46917cf864756921b52a914ec7 100644
--- a/multiview_platform/mono_multi_view_classifiers/monoview/exec_classif_mono_view.py
+++ b/multiview_platform/mono_multi_view_classifiers/monoview/exec_classif_mono_view.py
@@ -30,22 +30,22 @@ __status__ = "Prototype" # Production, Development, Prototype
def exec_monoview_multicore(directory, name, labelsNames, classificationIndices,
KFolds, datasetFileIndex, databaseType,
path, randomState, labels,
- hyperParamSearch="randomizedSearch",
+ hyper_param_search="randomized_search",
metrics=[["accuracy_score", None]], nIter=30,
**args):
DATASET = h5py.File(path + name + str(datasetFileIndex) + ".hdf5", "r")
neededViewIndex = args["viewIndex"]
X = DATASET.get("View" + str(neededViewIndex))
Y = labels
- return ExecMonoview(directory, X, Y, name, labelsNames,
+ return exec_monoview(directory, X, Y, name, labelsNames,
classificationIndices, KFolds, 1, databaseType, path,
- randomState, hyperParamSearch=hyperParamSearch,
+ randomState, hyper_param_search=hyper_param_search,
metrics=metrics, nIter=nIter, **args)
def exec_monoview(directory, X, Y, name, labelsNames, classificationIndices,
KFolds, nbCores, databaseType, path,
- randomState, hyperParamSearch="randomizedSearch",
+ randomState, hyper_param_search="randomized_search",
metrics=[["accuracy_score", None]], nIter=30, **args):
logging.debug("Start:\t Loading data")
kwargs, \
@@ -67,7 +67,7 @@ def exec_monoview(directory, X, Y, name, labelsNames, classificationIndices,
+ str(nbCores) + ", algorithm : " + CL_type)
logging.debug("Start:\t Determine Train/Test split")
- X_train, y_train, X_test, y_test, X_test_multiclass = initTrainTest(X, Y,
+ X_train, y_train, X_test, y_test, X_test_multiclass = init_train_test(X, Y,
classificationIndices)
logging.debug("Info:\t Shape X_train:" + str(
@@ -79,7 +79,7 @@ def exec_monoview(directory, X, Y, name, labelsNames, classificationIndices,
logging.debug("Start:\t Generate classifier args")
classifierModule = getattr(monoview_classifiers, CL_type)
classifier_class_name = classifierModule.classifier_class_name
- clKWARGS, testFoldsPreds = getHPs(classifierModule, hyperParamSearch,
+ clKWARGS, testFoldsPreds = getHPs(classifierModule, hyper_parameter_search,
nIter, CL_type, classifier_class_name,
X_train, y_train,
randomState, outputFileName,
@@ -114,7 +114,7 @@ def exec_monoview(directory, X, Y, name, labelsNames, classificationIndices,
stringAnalysis, \
imagesAnalysis, \
metricsScores = execute(name, classificationIndices, KFolds, nbCores,
- hyperParamSearch, metrics, nIter, feat, CL_type,
+ hyper_parameter_search, metrics, nIter, feat, CL_type,
clKWARGS, labelsNames, X.shape,
y_train, y_train_pred, y_test, y_test_pred, t_end,
randomState, classifier, outputFileName)
diff --git a/multiview_platform/mono_multi_view_classifiers/multiview/additions/diversity_utils.py b/multiview_platform/mono_multi_view_classifiers/multiview/additions/diversity_utils.py
index 977730184b0f502af77fe4d0025e37d869eddccd..9cf1ba574b9acfe3e0374a67313704f9bf1fe3e5 100644
--- a/multiview_platform/mono_multi_view_classifiers/multiview/additions/diversity_utils.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview/additions/diversity_utils.py
@@ -4,7 +4,7 @@ import os
import numpy as np
-from ...utils.multiclass import isBiclass, genMulticlassMonoviewDecision
+from ...utils.multiclass import is_biclass, gen_multiclass_monoview_decision
def getClassifiersDecisions(allClassifersNames, viewsIndices, resultsMonoview):
diff --git a/multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py b/multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py
index 696c97e5cafd44e82d78bebbd9dd71d21d3405d8..fdbf358cf8ce67aa8fe7b9377c0bee89c3aaa43b 100644
--- a/multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py
+++ b/multiview_platform/mono_multi_view_classifiers/multiview/exec_multiview.py
@@ -80,21 +80,21 @@ def saveResults(classifier, LABELS_DICTIONARY, stringAnalysis, views, classifier
def exec_multiview_multicore(directory, coreIndex, name, learningRate, nbFolds,
databaseType, path, LABELS_DICTIONARY,
randomState, labels,
- hyperParamSearch=False, nbCores=1, metrics=None,
+ hyper_param_search=False, nbCores=1, metrics=None,
nIter=30, **arguments):
"""Used to load an HDF5 dataset for each parallel job and execute multiview classification"""
DATASET = h5py.File(path + name + str(coreIndex) + ".hdf5", "r")
- return ExecMultiview(directory, DATASET, name, learningRate, nbFolds, 1,
+ return exec_multiview(directory, DATASET, name, learningRate, nbFolds, 1,
databaseType, path, LABELS_DICTIONARY,
randomState, labels,
- hyperParamSearch=hyperParamSearch, metrics=metrics,
+ hyper_param_search=hyper_param_search, metrics=metrics,
nIter=nIter, **arguments)
def exec_multiview(directory, DATASET, name, classificationIndices, KFolds,
- nbCores, databaseType, path,
- LABELS_DICTIONARY, randomState, labels,
- hyperParamSearch=False, metrics=None, nIter=30, **kwargs):
+ nbCores, databaseType, path,
+ LABELS_DICTIONARY, randomState, labels,
+ hyper_param_search=False, metrics=None, nIter=30, **kwargs):
"""Used to execute multiview classification and result analysis"""
logging.debug("Start:\t Initialize constants")
CL_type, \
@@ -122,20 +122,20 @@ def exec_multiview(directory, DATASET, name, classificationIndices, KFolds,
logging.debug("Done:\t Getting classifiers modules")
logging.debug("Start:\t Optimizing hyperparameters")
- if hyperParamSearch != "None":
+ if hyper_param_search != "None":
classifier_config = hyper_parameter_search.searchBestSettings(DATASET, labels,
- classifier_module,
- classifier_name,
- metrics[0],
- learningIndices,
- KFolds,
- randomState,
- directory,
- nb_cores=nbCores,
- viewsIndices=viewsIndices,
- searchingTool=hyperParamSearch,
- n_iter=nIter,
- classifier_config=classifier_config)
+ classifier_module,
+ classifier_name,
+ metrics[0],
+ learningIndices,
+ KFolds,
+ randomState,
+ directory,
+ nb_cores=nbCores,
+ viewsIndices=viewsIndices,
+ searchingTool=hyper_param_search,
+ n_iter=nIter,
+ classifier_config=classifier_config)
classifier = getattr(classifier_module, classifier_name)(randomState,
**classifier_config)
@@ -177,7 +177,7 @@ def exec_multiview(directory, DATASET, name, classificationIndices, KFolds,
classifier_config, classificationIndices,
LABELS_DICTIONARY, views, nbCores, times,
name, KFolds,
- hyperParamSearch, nIter, metrics,
+ hyper_param_search, nIter, metrics,
viewsIndices, randomState, labels, classifier_module)
logging.info("Done:\t Result Analysis for " + CL_type)
@@ -283,7 +283,7 @@ if __name__ == "__main__":
if args.log:
logging.getLogger().addHandler(logging.StreamHandler())
- res = ExecMultiview(directory, DATASET, name, classificationIndices, KFolds,
+ res = exec_multiview(directory, DATASET, name, classificationIndices, KFolds,
nbCores, databaseType, path,
LABELS_DICTIONARY, randomState, labels,
hyperParamSearch=hyperParamSearch, metrics=metrics,
diff --git a/multiview_platform/mono_multi_view_classifiers/utils/execution.py b/multiview_platform/mono_multi_view_classifiers/utils/execution.py
index e5bfe258bccf5dc9dfd36c6c7ce43c6590ca0418..65cfae5df01a3b73045243d38e6f6533150fe871 100644
--- a/multiview_platform/mono_multi_view_classifiers/utils/execution.py
+++ b/multiview_platform/mono_multi_view_classifiers/utils/execution.py
@@ -108,10 +108,10 @@ def get_database_function(name, type_var):
getDatabase : function
The function that will be used to extract the database
"""
- if name not in ["Fake", "Plausible"]:
- get_database = getattr(DB, "getClassicDB" + type_var[1:])
+ if name not in ["fake", "plausible"]:
+ get_database = getattr(DB, "get_classic_db_" + type_var[1:])
else:
- get_database = getattr(DB, "get" + name + "DB" + type_var[1:])
+ get_database = getattr(DB, "get_" + name + "_db_" + type_var[1:])
return get_database
diff --git a/multiview_platform/mono_multi_view_classifiers/utils/get_multiview_db.py b/multiview_platform/mono_multi_view_classifiers/utils/get_multiview_db.py
index 0d86492787e2e290fc5d351ec446ada1c49c1049..e83eff45eb9a41b258fb71fec8a813c914155860 100644
--- a/multiview_platform/mono_multi_view_classifiers/utils/get_multiview_db.py
+++ b/multiview_platform/mono_multi_view_classifiers/utils/get_multiview_db.py
@@ -90,7 +90,7 @@ def makeMeNoisy(viewData, randomState, percentage=5):
return noisyViewData
-def getPlausibleDBhdf5(features, pathF, name, NB_CLASS=3, LABELS_NAME="",
+def get_plausible_db_hdf5(features, pathF, name, NB_CLASS=3, LABELS_NAME="",
randomState=None, full=True, add_noise=False,
noise_std=0.15, nbView=3,
nbClass=2, datasetLength=100, randomStateInt=42, nbFeatures = 10):
@@ -380,7 +380,7 @@ def copyhdf5_dataset(source_data_file, destination_data_file, source_dataset_nam
new_d_set.attrs[key] = value
-def get_classicDBhdf5(views, path_f, name_DB, nb_class, asked_labels_names,
+def get_classic_db_hdf5(views, path_f, name_DB, nb_class, asked_labels_names,
random_state, full=False, add_noise=False, noise_std=0.15,):
"""Used to load a hdf5 database"""
if full:
@@ -467,7 +467,7 @@ def add_gaussian_noise(dataset_file, random_state, path_f, dataset_name,
return noisy_dataset, dataset_name + "_noised"
-def getClassicDBcsv(views, pathF, nameDB, NB_CLASS, askedLabelsNames,
+def get_classic_db_csv(views, pathF, nameDB, NB_CLASS, askedLabelsNames,
randomState, full=False, add_noise=False, noise_std=0.15,
delimiter=","):
# TODO : Update this one
@@ -497,7 +497,7 @@ def getClassicDBcsv(views, pathF, nameDB, NB_CLASS, askedLabelsNames,
metaDataGrp.attrs["nbClass"] = len(labelsNames)
metaDataGrp.attrs["datasetLength"] = len(labels)
datasetFile.close()
- datasetFile, labelsDictionary, dataset_name = getClassicDBhdf5(views, pathF, nameDB,
+ datasetFile, labelsDictionary, dataset_name = get_classic_db_hdf5(views, pathF, nameDB,
NB_CLASS, askedLabelsNames,
randomState, full)
diff --git a/multiview_platform/tests/test_ExecClassif.py b/multiview_platform/tests/test_ExecClassif.py
index 07ba4ecc0dce6ad16f6924625072b273bc5dd53c..ea295dbf36a30be1358582a5ff15d4a1f12a94df 100644
--- a/multiview_platform/tests/test_ExecClassif.py
+++ b/multiview_platform/tests/test_ExecClassif.py
@@ -20,7 +20,7 @@ class Test_initKWARGS(unittest.TestCase):
def test_initKWARGSFunc_no_monoview(self):
benchmark = {"monoview": {}, "multiview": {}}
- args = exec_classif.initKWARGSFunc({}, benchmark)
+ args = exec_classif.init_kwargs_func({}, benchmark)
self.assertEqual(args, {"monoview": {}, "multiview": {}})
@@ -205,15 +205,15 @@ class Test_init_argument_dictionaries(unittest.TestCase):
self.assertEqual(arguments["multiview"][0], expected_output[0])
-def fakeBenchmarkExec(coreIndex=-1, a=7, args=1):
- return [coreIndex, a]
+def fakeBenchmarkExec(core_index=-1, a=7, args=1):
+ return [core_index, a]
-def fakeBenchmarkExec_mutlicore(nbCores=-1, a=6, args=1):
- return [nbCores, a]
+def fakeBenchmarkExec_mutlicore(nb_cores=-1, a=6, args=1):
+ return [nb_cores, a]
-def fakeBenchmarkExec_monocore(DATASET=1, a=4, args=1):
+def fakeBenchmarkExec_monocore(dataset_var=1, a=4, args=1):
return [a]
@@ -247,10 +247,10 @@ class Test_execBenchmark(unittest.TestCase):
res = exec_classif.exec_benchmark(1, 2, 3, cls.argumentDictionaries,
[[[1, 2], [3, 4, 5]]], 5, 6, 7, 8, 9,
10, cls.Dataset,
- execOneBenchmark=fakeBenchmarkExec,
- execOneBenchmark_multicore=fakeBenchmarkExec_mutlicore,
- execOneBenchmarkMonoCore=fakeBenchmarkExec_monocore,
- getResults=fakegetResults,
+ exec_one_benchmark=fakeBenchmarkExec,
+ exec_one_benchmark_multicore=fakeBenchmarkExec_mutlicore,
+ exec_one_benchmark_mono_core=fakeBenchmarkExec_monocore,
+ get_results=fakegetResults,
delete=fakeDelete)
cls.assertEqual(res, 3)
@@ -260,10 +260,10 @@ class Test_execBenchmark(unittest.TestCase):
res = exec_classif.exec_benchmark(2, 1, 2, cls.argumentDictionaries,
[[[1, 2], [3, 4, 5]]], 5, 6, 7, 8, 9,
10, cls.Dataset,
- execOneBenchmark=fakeBenchmarkExec,
- execOneBenchmark_multicore=fakeBenchmarkExec_mutlicore,
- execOneBenchmarkMonoCore=fakeBenchmarkExec_monocore,
- getResults=fakegetResults,
+ exec_one_benchmark=fakeBenchmarkExec,
+ exec_one_benchmark_multicore=fakeBenchmarkExec_mutlicore,
+ exec_one_benchmark_mono_core=fakeBenchmarkExec_monocore,
+ get_results=fakegetResults,
delete=fakeDelete)
cls.assertEqual(res, 3)
@@ -275,10 +275,10 @@ class Test_execBenchmark(unittest.TestCase):
res = exec_classif.exec_benchmark(2, 2, 2, cls.argumentDictionaries,
[[[1, 2], [3, 4, 5]]], 5, 6, 7, 8, 9,
10, cls.Dataset,
- execOneBenchmark=fakeBenchmarkExec,
- execOneBenchmark_multicore=fakeBenchmarkExec_mutlicore,
- execOneBenchmarkMonoCore=fakeBenchmarkExec_monocore,
- getResults=fakegetResults,
+ exec_one_benchmark=fakeBenchmarkExec,
+ exec_one_benchmark_multicore=fakeBenchmarkExec_mutlicore,
+ exec_one_benchmark_mono_core=fakeBenchmarkExec_monocore,
+ get_results=fakegetResults,
delete=fakeDelete)
cls.assertEqual(res, 3)
@@ -286,10 +286,10 @@ class Test_execBenchmark(unittest.TestCase):
res = exec_classif.exec_benchmark(2, 1, 1, cls.argumentDictionaries,
[[[1, 2], [3, 4, 5]]], 5, 6, 7, 8, 9,
10, cls.Dataset,
- execOneBenchmark=fakeBenchmarkExec,
- execOneBenchmark_multicore=fakeBenchmarkExec_mutlicore,
- execOneBenchmarkMonoCore=fakeBenchmarkExec_monocore,
- getResults=fakegetResults,
+ exec_one_benchmark=fakeBenchmarkExec,
+ exec_one_benchmark_multicore=fakeBenchmarkExec_mutlicore,
+ exec_one_benchmark_mono_core=fakeBenchmarkExec_monocore,
+ get_results=fakegetResults,
delete=fakeDelete)
cls.assertEqual(res, 3)
@@ -304,13 +304,13 @@ class Test_execBenchmark(unittest.TestCase):
def fakeExecMono(directory, name, labelsNames, classificationIndices, kFolds,
coreIndex, type, pathF, randomState, labels,
- hyperParamSearch="try", metrics="try", nIter=1, **arguments):
+ hyper_param_search="try", metrics="try", nIter=1, **arguments):
return ["Mono", arguments]
def fakeExecMulti(directory, coreIndex, name, classificationIndices, kFolds,
type, pathF, LABELS_DICTIONARY,
- randomState, labels, hyperParamSearch="", metrics=None,
+ randomState, labels, hyper_param_search="", metrics=None,
nIter=1, **arguments):
return ["Multi", arguments]
@@ -344,20 +344,20 @@ class Test_execOneBenchmark(unittest.TestCase):
"Classification": {"hps_iter": 1}}
def test_simple(cls):
- flag, results = exec_classif.execOneBenchmark(coreIndex=10,
- LABELS_DICTIONARY={
+ flag, results = exec_classif.exec_one_benchmark(core_index=10,
+ labels_dictionary={
0: "a",
1: "b"},
directory="multiview_platform/tests/tmp_tests/",
- classificationIndices=(
+ classification_indices=(
[1, 2, 3, 4],
[0, 5, 6, 7, 8]),
args=cls.args,
- kFolds=FakeKfold(),
- randomState="try",
- hyperParamSearch="try",
+ k_folds=FakeKfold(),
+ random_state="try",
+ hyper_param_search="try",
metrics="try",
- argumentDictionaries={
+ argument_dictionaries={
"Monoview": [
{
"try": 0},
@@ -369,16 +369,16 @@ class Test_execOneBenchmark(unittest.TestCase):
"try4": 10}]},
benchmark="try",
views="try",
- viewsIndices="try",
+ views_indices="try",
flag=None,
labels=np.array(
[0, 1, 2, 1,
2, 2, 2, 12,
1, 2, 1, 1,
2, 1, 21]),
- ExecMonoview_multicore=fakeExecMono,
+ exec_monoview_multicore=fakeExecMono,
exec_multiview_multicore=fakeExecMulti,
- initMultiviewArguments=fakeInitMulti)
+ init_multiview_arguments=fakeInitMulti)
cls.assertEqual(flag, None)
cls.assertEqual(results ,
@@ -411,17 +411,17 @@ class Test_execOneBenchmark_multicore(unittest.TestCase):
"Classification": {"hps_iter": 1}}
def test_simple(cls):
- flag, results = exec_classif.execOneBenchmark_multicore(
- nbCores=2,
- LABELS_DICTIONARY={0: "a", 1: "b"},
+ flag, results = exec_classif.exec_one_benchmark_multicore(
+ nb_cores=2,
+ labels_dictionary={0: "a", 1: "b"},
directory="multiview_platform/tests/tmp_tests/",
- classificationIndices=([1, 2, 3, 4], [0, 10, 20, 30, 40]),
+ classification_indices=([1, 2, 3, 4], [0, 10, 20, 30, 40]),
args=cls.args,
- kFolds=FakeKfold(),
- randomState="try",
- hyperParamSearch="try",
+ k_folds=FakeKfold(),
+ random_state="try",
+ hyper_param_search="try",
metrics="try",
- argumentDictionaries={
+ argument_dictionaries={
"monoview": [
{
"try": 0},
@@ -436,9 +436,9 @@ class Test_execOneBenchmark_multicore(unittest.TestCase):
viewsIndices="try",
flag=None,
labels=np.array([0, 1, 2, 3, 4, 2, 2, 12, 1, 2, 1, 1, 2, 1, 21]),
- ExecMonoview_multicore=fakeExecMono,
+ exec_monoview_multicore=fakeExecMono,
exec_multiview_multicore=fakeExecMulti,
- initMultiviewArguments=fakeInitMulti)
+ init_multiview_arguments=fakeInitMulti)
cls.assertEqual(flag, None)
cls.assertEqual(results ,
diff --git a/multiview_platform/tests/test_mono_view/test_ExecClassifMonoView.py b/multiview_platform/tests/test_mono_view/test_ExecClassifMonoView.py
index c5e70b74c7aadddf7b7d93bef5030e2911d1f647..43dcefa76126d59820490abff5a642a48a6eb63a 100644
--- a/multiview_platform/tests/test_mono_view/test_ExecClassifMonoView.py
+++ b/multiview_platform/tests/test_mono_view/test_ExecClassifMonoView.py
@@ -77,7 +77,7 @@ class Test_initTrainTest(unittest.TestCase):
np.array([1, 3, 5, 7, 9])]
def test_simple(cls):
- X_train, y_train, X_test, y_test, X_test_multiclass = exec_classif_mono_view.initTrainTest(
+ X_train, y_train, X_test, y_test, X_test_multiclass = exec_classif_mono_view.init_train_test(
cls.X, cls.Y, cls.classificationIndices)
np.testing.assert_array_equal(X_train, np.array(
[np.array([102, 435, 348, 270, 106]),
diff --git a/multiview_platform/tests/test_utils/test_GetMultiviewDB.py b/multiview_platform/tests/test_utils/test_GetMultiviewDB.py
index e59ce5fbc419a28643dff535be8fb6d1347a49bc..c97e04d02afcd366943b4eceeed3c6a7312077f8 100644
--- a/multiview_platform/tests/test_utils/test_GetMultiviewDB.py
+++ b/multiview_platform/tests/test_utils/test_GetMultiviewDB.py
@@ -22,7 +22,7 @@ class Test_copyhdf5Dataset(unittest.TestCase):
cls.dataset.attrs["test_arg"] = "Am I copied"
def test_simple_copy(cls):
- get_multiview_db.copyhdf5Dataset(cls.dataset_file, cls.dataset_file,
+ get_multiview_db.copyhdf5_dataset(cls.dataset_file, cls.dataset_file,
"test", "test_copy_1", np.arange(10))
np.testing.assert_array_equal(cls.dataset_file.get("test").value,
cls.dataset_file.get("test_copy_1").value)
@@ -31,7 +31,7 @@ class Test_copyhdf5Dataset(unittest.TestCase):
def test_copy_only_some_indices(cls):
usedIndices = cls.random_state.choice(10, 6, replace=False)
- get_multiview_db.copyhdf5Dataset(cls.dataset_file, cls.dataset_file,
+ get_multiview_db.copyhdf5_dataset(cls.dataset_file, cls.dataset_file,
"test", "test_copy", usedIndices)
np.testing.assert_array_equal(
cls.dataset_file.get("test").value[usedIndices, :],
@@ -68,7 +68,7 @@ class Test_filterViews(unittest.TestCase):
cls.temp_dataset_file = h5py.File(
"multiview_platform/tests/temp_tests/test_copy_temp.hdf5", "w")
cls.dataset_file.copy("Metadata", cls.temp_dataset_file)
- get_multiview_db.filterViews(cls.dataset_file, cls.temp_dataset_file,
+ get_multiview_db.filter_views(cls.dataset_file, cls.temp_dataset_file,
cls.views, np.arange(10))
cls.assertEqual(cls.dataset_file.get("View1").attrs["name"],
cls.temp_dataset_file.get("View0").attrs["name"])
@@ -82,7 +82,7 @@ class Test_filterViews(unittest.TestCase):
"multiview_platform/tests/temp_tests/test_copy_temp.hdf5", "w")
cls.dataset_file.copy("Metadata", cls.temp_dataset_file)
usedIndices = cls.random_state.choice(10, 6, replace=False)
- get_multiview_db.filterViews(cls.dataset_file, cls.temp_dataset_file,
+ get_multiview_db.filter_views(cls.dataset_file, cls.temp_dataset_file,
cls.views, usedIndices)
np.testing.assert_array_equal(
cls.dataset_file.get("View1").value[usedIndices, :],
@@ -112,7 +112,7 @@ class Test_filterLabels(unittest.TestCase):
def test_simple(cls):
newLabels, \
newLabelsNames, \
- usedIndices = get_multiview_db.filterLabels(cls.labelsSet,
+ usedIndices = get_multiview_db.filter_labels(cls.labelsSet,
cls.askedLabelsNamesSet,
cls.fullLabels,
cls.availableLabelsNames,
@@ -127,7 +127,7 @@ class Test_filterLabels(unittest.TestCase):
cls.availableLabelsNames = ["test_label_0", "test_label_1"]
newLabels, \
newLabelsNames, \
- usedIndices = get_multiview_db.filterLabels(cls.labelsSet,
+ usedIndices = get_multiview_db.filter_labels(cls.labelsSet,
cls.askedLabelsNamesSet,
cls.fullLabels,
cls.availableLabelsNames,
@@ -141,7 +141,7 @@ class Test_filterLabels(unittest.TestCase):
"test_label_2", "test_label_3",
"chicken_is_heaven"}
with cls.assertRaises(get_multiview_db.DatasetError) as catcher:
- get_multiview_db.filterLabels(cls.labelsSet,
+ get_multiview_db.filter_labels(cls.labelsSet,
cls.askedLabelsNamesSet,
cls.fullLabels,
cls.availableLabelsNames,
@@ -155,7 +155,7 @@ class Test_filterLabels(unittest.TestCase):
"test_label_3"]
newLabels, \
newLabelsNames, \
- usedIndices = get_multiview_db.filterLabels(cls.labelsSet,
+ usedIndices = get_multiview_db.filter_labels(cls.labelsSet,
cls.askedLabelsNamesSet,
cls.fullLabels,
cls.availableLabelsNames,
@@ -179,7 +179,7 @@ class Test_selectAskedLabels(unittest.TestCase):
def test_simple(cls):
newLabels, \
newLabelsNames, \
- usedIndices = get_multiview_db.selectAskedLabels(cls.askedLabelsNamesSet,
+ usedIndices = get_multiview_db.select_asked_labels(cls.askedLabelsNamesSet,
cls.availableLabelsNames,
cls.askedLabelsNames,
cls.fullLabels)
@@ -194,7 +194,7 @@ class Test_selectAskedLabels(unittest.TestCase):
"test_label_3"]
newLabels, \
newLabelsNames, \
- usedIndices = get_multiview_db.selectAskedLabels(cls.askedLabelsNamesSet,
+ usedIndices = get_multiview_db.select_asked_labels(cls.askedLabelsNamesSet,
cls.availableLabelsNames,
cls.askedLabelsNames,
cls.fullLabels)
@@ -206,7 +206,7 @@ class Test_selectAskedLabels(unittest.TestCase):
cls.askedLabelsNamesSet = {"test_label_1", "test_label_3",
"chicken_is_heaven"}
with cls.assertRaises(get_multiview_db.DatasetError) as catcher:
- get_multiview_db.selectAskedLabels(cls.askedLabelsNamesSet,
+ get_multiview_db.select_asked_labels(cls.askedLabelsNamesSet,
cls.availableLabelsNames,
cls.askedLabelsNames,
cls.fullLabels)
@@ -224,7 +224,7 @@ class Test_getAllLabels(unittest.TestCase):
"test_label_2", "test_label_3"]
def test_simple(cls):
- newLabels, newLabelsNames, usedIndices = get_multiview_db.getAllLabels(
+ newLabels, newLabelsNames, usedIndices = get_multiview_db.get_all_labels(
cls.fullLabels, cls.availableLabelsNames)
cls.assertEqual(cls.availableLabelsNames, newLabelsNames)
np.testing.assert_array_equal(usedIndices, np.arange(10))
@@ -241,7 +241,7 @@ class Test_fillLabelNames(unittest.TestCase):
cls.availableLabelsNames = ["test_label_" + str(_) for _ in range(40)]
def test_simple(cls):
- askedLabelsNames, askedLabelsNamesSet = get_multiview_db.fillLabelNames(
+ askedLabelsNames, askedLabelsNamesSet = get_multiview_db.fill_label_names(
cls.NB_CLASS,
cls.askedLabelsNames,
cls.randomState,
@@ -251,7 +251,7 @@ class Test_fillLabelNames(unittest.TestCase):
def test_missing_labels_names(cls):
cls.NB_CLASS = 39
- askedLabelsNames, askedLabelsNamesSet = get_multiview_db.fillLabelNames(
+ askedLabelsNames, askedLabelsNamesSet = get_multiview_db.fill_label_names(
cls.NB_CLASS,
cls.askedLabelsNames,
cls.randomState,
@@ -279,7 +279,7 @@ class Test_fillLabelNames(unittest.TestCase):
cls.NB_CLASS = 2
cls.askedLabelsNames = ["test_label_1", "test_label_3", "test_label_4",
"test_label_6"]
- askedLabelsNames, askedLabelsNamesSet = get_multiview_db.fillLabelNames(
+ askedLabelsNames, askedLabelsNamesSet = get_multiview_db.fill_label_names(
cls.NB_CLASS,
cls.askedLabelsNames,
cls.randomState,
@@ -298,14 +298,14 @@ class Test_allAskedLabelsAreAvailable(unittest.TestCase):
def test_asked_available_labels(cls):
cls.assertTrue(
- get_multiview_db.allAskedLabelsAreAvailable(cls.askedLabelsNamesSet,
+ get_multiview_db.all_asked_labels_are_available(cls.askedLabelsNamesSet,
cls.availableLabelsNames))
def test_asked_unavailable_label(cls):
cls.askedLabelsNamesSet = {"test_label_1", "test_label_3",
"chicken_is_heaven"}
cls.assertFalse(
- get_multiview_db.allAskedLabelsAreAvailable(cls.askedLabelsNamesSet,
+ get_multiview_db.all_asked_labels_are_available(cls.askedLabelsNamesSet,
cls.availableLabelsNames))
@@ -316,18 +316,18 @@ class Test_getClasses(unittest.TestCase):
cls.random_state = np.random.RandomState(42)
def test_multiclass(cls):
- labelsSet = get_multiview_db.getClasses(
+ labelsSet = get_multiview_db.get_classes(
cls.random_state.randint(0, 5, 30))
cls.assertEqual(labelsSet, {0, 1, 2, 3, 4})
def test_biclass(cls):
- labelsSet = get_multiview_db.getClasses(
+ labelsSet = get_multiview_db.get_classes(
cls.random_state.randint(0, 2, 30))
cls.assertEqual(labelsSet, {0, 1})
def test_one_class(cls):
with cls.assertRaises(get_multiview_db.DatasetError) as catcher:
- get_multiview_db.getClasses(np.zeros(30, dtype=int))
+ get_multiview_db.get_classes(np.zeros(30, dtype=int))
exception = catcher.exception
# cls.assertTrue("Dataset must have at least two different labels" in exception)
@@ -363,7 +363,7 @@ class Test_getClassicDBhdf5(unittest.TestCase):
cls.dataset.attrs["name"] = "test_view_" + str(i)
def test_simple(cls):
- dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBhdf5(
+ dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_hdf5(
cls.views, cls.pathF, cls.nameDB,
cls.NB_CLASS, cls.askedLabelsNames,
cls.random_state)
@@ -381,7 +381,7 @@ class Test_getClassicDBhdf5(unittest.TestCase):
askedLabelsNames = ["test_label_0", "test_label_1", "test_label_2",
"test_label_3"]
NB_CLASS = 4
- dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBhdf5(
+ dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_hdf5(
cls.views, cls.pathF, cls.nameDB,
NB_CLASS, askedLabelsNames,
cls.random_state)
@@ -398,7 +398,7 @@ class Test_getClassicDBhdf5(unittest.TestCase):
def test_all_views_asked(cls):
views = ["test_view_0", "test_view_1", "test_view_2", "test_view_3"]
- dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBhdf5(views,
+ dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_hdf5(views,
cls.pathF,
cls.nameDB,
cls.NB_CLASS,
@@ -423,7 +423,7 @@ class Test_getClassicDBhdf5(unittest.TestCase):
"test_label_3"]
NB_CLASS = 4
views = ["test_view_0", "test_view_1", "test_view_2", "test_view_3"]
- dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBhdf5(views,
+ dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_hdf5(views,
cls.pathF,
cls.nameDB,
NB_CLASS,
@@ -481,7 +481,7 @@ class Test_getClassicDBcsv(unittest.TestCase):
cls.datas.append(data)
def test_simple(cls):
- dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBcsv(
+ dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_csv(
cls.views, cls.pathF, cls.nameDB,
cls.NB_CLASS, cls.askedLabelsNames,
cls.random_state, delimiter=",")
@@ -497,7 +497,7 @@ class Test_getClassicDBcsv(unittest.TestCase):
def test_all_views_asked(cls):
views = ["test_view_0", "test_view_1", "test_view_2", "test_view_3"]
- dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBcsv(views,
+ dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_csv(views,
cls.pathF,
cls.nameDB,
cls.NB_CLASS,
@@ -522,7 +522,7 @@ class Test_getClassicDBcsv(unittest.TestCase):
askedLabelsNames = ["test_label_0", "test_label_1", "test_label_2",
"test_label_3"]
NB_CLASS = 4
- dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBcsv(
+ dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_csv(
cls.views, cls.pathF, cls.nameDB,
NB_CLASS, askedLabelsNames,
cls.random_state, delimiter=",")
@@ -541,7 +541,7 @@ class Test_getClassicDBcsv(unittest.TestCase):
"test_label_3"]
NB_CLASS = 4
views = ["test_view_0", "test_view_1", "test_view_2", "test_view_3"]
- dataset_file, labels_dictionary, dataset_name = get_multiview_db.getClassicDBcsv(views,
+ dataset_file, labels_dictionary, dataset_name = get_multiview_db.get_classic_db_csv(views,
cls.pathF,
cls.nameDB,
NB_CLASS,
diff --git a/multiview_platform/tests/test_utils/test_execution.py b/multiview_platform/tests/test_utils/test_execution.py
index 003b928bccd7816d0b84d86249fece750c4c2abe..b974324d3d0a0027762c7ca6e7ab0fbb0042eca3 100644
--- a/multiview_platform/tests/test_utils/test_execution.py
+++ b/multiview_platform/tests/test_utils/test_execution.py
@@ -3,6 +3,8 @@ import unittest
import numpy as np
+from ..utils import rm_tmp
+
from ...mono_multi_view_classifiers.utils import execution
@@ -12,7 +14,7 @@ class Test_parseTheArgs(unittest.TestCase):
self.args = []
def test_empty_args(self):
- args = execution.parseTheArgs([])
+ args = execution.parse_the_args([])
# print args
@@ -25,14 +27,14 @@ class Test_initStatsIterRandomStates(unittest.TestCase):
def test_one_statiter(cls):
cls.state = cls.randomState.get_state()[1]
- statsIterRandomStates = execution.initStatsIterRandomStates(
+ statsIterRandomStates = execution.init_stats_iter_random_states(
cls.statsIter, cls.randomState)
np.testing.assert_array_equal(statsIterRandomStates[0].get_state()[1],
cls.state)
def test_multiple_iter(cls):
cls.statsIter = 3
- statsIterRandomStates = execution.initStatsIterRandomStates(
+ statsIterRandomStates = execution.init_stats_iter_random_states(
cls.statsIter, cls.randomState)
cls.assertAlmostEqual(len(statsIterRandomStates), 3)
cls.assertNotEqual(statsIterRandomStates[0].randint(5000),
@@ -51,50 +53,51 @@ class Test_getDatabaseFunction(unittest.TestCase):
cls.type = ".csv"
def test_simple(cls):
- getDB = execution.getDatabaseFunction(cls.name, cls.type)
+ getDB = execution.get_database_function(cls.name, cls.type)
from ...mono_multi_view_classifiers.utils.get_multiview_db import \
- getClassicDBcsv
- cls.assertEqual(getDB, getClassicDBcsv)
+ get_classic_db_csv
+ cls.assertEqual(getDB, get_classic_db_csv)
def test_hdf5(cls):
cls.type = ".hdf5"
- getDB = execution.getDatabaseFunction(cls.name, cls.type)
+ getDB = execution.get_database_function(cls.name, cls.type)
from ...mono_multi_view_classifiers.utils.get_multiview_db import \
- getClassicDBhdf5
- cls.assertEqual(getDB, getClassicDBhdf5)
+ get_classic_db_hdf5
+ cls.assertEqual(getDB, get_classic_db_hdf5)
def test_plausible_hdf5(cls):
- cls.name = "Plausible"
+ cls.name = "plausible"
cls.type = ".hdf5"
- getDB = execution.getDatabaseFunction(cls.name, cls.type)
+ getDB = execution.get_database_function(cls.name, cls.type)
from ...mono_multi_view_classifiers.utils.get_multiview_db import \
- getPlausibleDBhdf5
- cls.assertEqual(getDB, getPlausibleDBhdf5)
+ get_plausible_db_hdf5
+ cls.assertEqual(getDB, get_plausible_db_hdf5)
class Test_initRandomState(unittest.TestCase):
def setUp(self):
- os.mkdir("multiview_platform/tests/temp_tests/")
+ rm_tmp()
+ os.mkdir("multiview_platform/tests/tmp_tests/")
def tearDown(self):
- os.rmdir("multiview_platform/tests/temp_tests/")
+ os.rmdir("multiview_platform/tests/tmp_tests/")
def test_random_state_42(self):
randomState_42 = np.random.RandomState(42)
- randomState = execution.initRandomState("42",
- "multiview_platform/tests/temp_tests/")
- os.remove("multiview_platform/tests/temp_tests/randomState.pickle")
+ randomState = execution.init_random_state("42",
+ "multiview_platform/tests/tmp_tests/")
+ os.remove("multiview_platform/tests/tmp_tests/randomState.pickle")
np.testing.assert_array_equal(randomState.beta(1, 100, 100),
randomState_42.beta(1, 100, 100))
def test_random_state_pickle(self):
- randomState_to_pickle = execution.initRandomState(None,
- "multiview_platform/tests/temp_tests/")
- pickled_randomState = execution.initRandomState(
- "multiview_platform/tests/temp_tests/randomState.pickle",
- "multiview_platform/tests/temp_tests/")
- os.remove("multiview_platform/tests/temp_tests/randomState.pickle")
+ randomState_to_pickle = execution.init_random_state(None,
+ "multiview_platform/tests/tmp_tests/")
+ pickled_randomState = execution.init_random_state(
+ "multiview_platform/tests/tmp_tests/randomState.pickle",
+ "multiview_platform/tests/tmp_tests/")
+ os.remove("multiview_platform/tests/tmp_tests/randomState.pickle")
np.testing.assert_array_equal(randomState_to_pickle.beta(1, 100, 100),
pickled_randomState.beta(1, 100, 100))
@@ -144,7 +147,7 @@ class Test_genSplits(unittest.TestCase):
self.splitRatio = 0.2
def test_simple(self):
- splits = execution.genSplits(self.labels, self.splitRatio,
+ splits = execution.gen_splits(self.labels, self.splitRatio,
self.statsIterRandomStates)
self.assertEqual(len(splits), 3)
self.assertEqual(len(splits[1]), 2)
@@ -159,7 +162,7 @@ class Test_genSplits(unittest.TestCase):
self.assertGreater(len(np.where(self.labels[splits[1][1]] == 2)[0]), 0)
def test_genSplits_no_iter(self):
- splits = execution.genSplits(self.labels, self.splitRatio,
+ splits = execution.gen_splits(self.labels, self.splitRatio,
self.statsIterRandomStates)
self.assertEqual(len(splits), 3)
self.assertEqual(len(splits[0]), 2)
@@ -194,7 +197,7 @@ class Test_genDirecortiesNames(unittest.TestCase):
cls.stats_iter = 5
def test_simple_ovo(cls):
- directories = execution.genDirecortiesNames(cls.directory,
+ directories = execution.gen_direcorties_names(cls.directory,
cls.stats_iter)
cls.assertEqual(len(directories), 5)
cls.assertEqual(directories[0], "../chicken_is_heaven/iter_1/")
@@ -202,7 +205,7 @@ class Test_genDirecortiesNames(unittest.TestCase):
def test_ovo_no_iter(cls):
cls.stats_iter = 1
- directories = execution.genDirecortiesNames(cls.directory,
+ directories = execution.gen_direcorties_names(cls.directory,
cls.stats_iter)
cls.assertEqual(len(directories), 1)
cls.assertEqual(directories[0], "../chicken_is_heaven/")
diff --git a/multiview_platform/tests/test_utils/test_multiclass.py b/multiview_platform/tests/test_utils/test_multiclass.py
index a73e9f2b044dd8cd42c534e21d610ba384a897ec..7b00a32842e3dcbd7b8c7d99fdd1a2c8267d4126 100644
--- a/multiview_platform/tests/test_utils/test_multiclass.py
+++ b/multiview_platform/tests/test_utils/test_multiclass.py
@@ -21,7 +21,7 @@ class Test_genMulticlassLabels(unittest.TestCase):
cls.testIndices[1]]]
def test_one_versus_one(cls):
- multiclassLabels, labelsIndices, oldIndicesMulticlass = multiclass.genMulticlassLabels(
+ multiclassLabels, labelsIndices, oldIndicesMulticlass = multiclass.gen_multiclass_labels(
cls.labels, "oneVersusOne", cls.classificationIndices)
cls.assertEqual(len(multiclassLabels), 10)
cls.assertEqual(labelsIndices,