From 9fc0c0f627c6b3ab3037f65be9079d8e13f7c55a Mon Sep 17 00:00:00 2001
From: bbauvin <baptiste.bauvin@centrale-marseille.fr>
Date: Wed, 18 Oct 2017 14:06:48 -0400
Subject: [PATCH] Added the embryo of my unittests
---
Code/Exec.py | 1 +
Code/MonoMultiViewClassifiers/ExecClassif.py | 7 +-
.../Mumbo/Classifiers/DecisionTree.py | 3 +-
.../utils/execution.py | 4 +-
Code/Tests/Test_utils/__init__.py | 0
Code/Tests/Test_utils/test_execution.py | 47 +++++
Code/Tests/__init__.py | 1 +
Code/Tests/test_ExecClassif.py | 197 ++++++++++++++++++
Code/Tests/test_poulet.py | 7 -
Code/__init__.py | 3 +-
10 files changed, 254 insertions(+), 16 deletions(-)
create mode 100644 Code/Tests/Test_utils/__init__.py
create mode 100644 Code/Tests/Test_utils/test_execution.py
create mode 100644 Code/Tests/test_ExecClassif.py
delete mode 100644 Code/Tests/test_poulet.py
diff --git a/Code/Exec.py b/Code/Exec.py
index 77d1921f..ba09d230 100644
--- a/Code/Exec.py
+++ b/Code/Exec.py
@@ -1,4 +1,5 @@
import sys
+
from MonoMultiViewClassifiers import ExecClassif
ExecClassif.execClassif(sys.argv[1:])
diff --git a/Code/MonoMultiViewClassifiers/ExecClassif.py b/Code/MonoMultiViewClassifiers/ExecClassif.py
index af290957..86b6c6d6 100644
--- a/Code/MonoMultiViewClassifiers/ExecClassif.py
+++ b/Code/MonoMultiViewClassifiers/ExecClassif.py
@@ -1,4 +1,5 @@
# Import built-in modules
+# import pdb;pdb.set_trace()
import pkgutil # for TimeStamp in CSVFile
import os
import time
@@ -101,10 +102,7 @@ def initMonoviewKWARGS(args, classifiersNames):
def initKWARGSFunc(args, benchmark):
- if "Monoview" in benchmark:
- monoviewKWARGS = initMonoviewKWARGS(args, benchmark["Monoview"])
- else:
- monoviewKWARGS = {}
+ monoviewKWARGS = initMonoviewKWARGS(args, benchmark["Monoview"])
return monoviewKWARGS
@@ -274,6 +272,7 @@ def classifyOneIter(LABELS_DICTIONARY, argumentDictionaries, nbCores, directory,
# __ EXECUTION __ #
# _______________ #
def execClassif(arguments):
+ import pdb;pdb.set_trace()
testVersions()
start = time.time()
args = execution.parseTheArgs(arguments)
diff --git a/Code/MonoMultiViewClassifiers/Multiview/Mumbo/Classifiers/DecisionTree.py b/Code/MonoMultiViewClassifiers/Multiview/Mumbo/Classifiers/DecisionTree.py
index 8eecf55e..13f8ef38 100644
--- a/Code/MonoMultiViewClassifiers/Multiview/Mumbo/Classifiers/DecisionTree.py
+++ b/Code/MonoMultiViewClassifiers/Multiview/Mumbo/Classifiers/DecisionTree.py
@@ -138,8 +138,7 @@ def getConfig(classifierConfig):
'with criterion ' + criterion + ', ' + \
' sub-sampled at ' + str(subSampling) + ' '
except KeyError:
- print classifierConfig
-
+ return "Go back, you're drunk"
def findClosest(scores, base=0.5):
diff --git a/Code/MonoMultiViewClassifiers/utils/execution.py b/Code/MonoMultiViewClassifiers/utils/execution.py
index ed9459ea..f7b457ba 100644
--- a/Code/MonoMultiViewClassifiers/utils/execution.py
+++ b/Code/MonoMultiViewClassifiers/utils/execution.py
@@ -7,8 +7,8 @@ import errno
import logging
import sklearn
-def parseTheArgs(arguments):
+def parseTheArgs(arguments):
parser = argparse.ArgumentParser(
description='This file is used to benchmark the scores fo multiple classification algorithm on multiview data.',
@@ -198,7 +198,7 @@ def initRandomState(randomStateArg, directory):
return randomState
def initLogFile(args):
- resultDirectory = "../../Results/" + args.name + "/started_" + time.strftime("%Y_%m_%d-%H_%M") + "/"
+ resultDirectory = "../Results/" + args.name + "/started_" + time.strftime("%Y_%m_%d-%H_%M") + "/"
logFileName = time.strftime("%Y%m%d-%H%M%S") + "-" + ''.join(args.CL_type) + "-" + "_".join(
args.views) + "-" + args.name + "-LOG"
if not os.path.exists(os.path.dirname(resultDirectory + logFileName)):
diff --git a/Code/Tests/Test_utils/__init__.py b/Code/Tests/Test_utils/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/Code/Tests/Test_utils/test_execution.py b/Code/Tests/Test_utils/test_execution.py
new file mode 100644
index 00000000..d88d9e32
--- /dev/null
+++ b/Code/Tests/Test_utils/test_execution.py
@@ -0,0 +1,47 @@
+import unittest
+import argparse
+import os
+import h5py
+import numpy as np
+
+from MonoMultiViewClassifiers.utils import execution
+
+
+class Test_parseTheArgs(unittest.TestCase):
+
+ def setUp(self):
+ self.args = []
+
+ def test_empty_args(self):
+ args = execution.parseTheArgs([])
+ # print args
+
+
+class Test_initRandomState(unittest.TestCase):
+
+ def test_random_state_42(self):
+ randomState_42 = np.random.RandomState(42)
+ randomState = execution.initRandomState("42", "Tests/temp_tests/")
+ os.remove("Tests/temp_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, "Tests/temp_tests/")
+ pickled_randomState = execution.initRandomState("Tests/temp_tests/randomState.pickle",
+ "Tests/temp_tests/")
+ os.remove("Tests/temp_tests/randomState.pickle")
+ np.testing.assert_array_equal(randomState_to_pickle.beta(1,100,100),
+ pickled_randomState.beta(1,100,100))
+
+
+class Test_initLogFile(unittest.TestCase):
+
+ def test_initLogFile(self):
+ pass
+
+
+class Test_genSplits(unittest.TestCase):
+
+ def test_genSplits_no_iter(self):
+ pass
\ No newline at end of file
diff --git a/Code/Tests/__init__.py b/Code/Tests/__init__.py
index e69de29b..324d3b04 100644
--- a/Code/Tests/__init__.py
+++ b/Code/Tests/__init__.py
@@ -0,0 +1 @@
+from . import test_ExecClassif
\ No newline at end of file
diff --git a/Code/Tests/test_ExecClassif.py b/Code/Tests/test_ExecClassif.py
new file mode 100644
index 00000000..9ec5b9ce
--- /dev/null
+++ b/Code/Tests/test_ExecClassif.py
@@ -0,0 +1,197 @@
+import unittest
+import argparse
+
+from MonoMultiViewClassifiers import ExecClassif
+
+
+class Test_initBenchmark(unittest.TestCase):
+
+ def test_benchmark_wanted(self):
+ benchmark_output = ExecClassif.initBenchmark(self.args)
+ self.assertEqual(1,1)
+
+ def test_initKWARGSFunc_no_monoview(self):
+ benchmark = {"Monoview":{}, "Multiview":{}}
+ args = ExecClassif.initKWARGSFunc({}, benchmark)
+ self.assertEqual(args, {})
+
+ def test_initMonoviewArguments_no_monoview(self):
+ benchmark = {"Monoview":{}, "Multiview":{}}
+ arguments = ExecClassif.initMonoviewArguments(benchmark, {}, [], [], None, 0, {})
+ self.assertEqual(arguments, {})
+
+ def test_initMonoviewArguments_empty(self):
+ benchmark = {"Monoview":{}, "Multiview":{}}
+ arguments = ExecClassif.initMonoviewArguments(benchmark, {}, [], [], None, 0, {})
+
+ def setUp(self):
+ parser = argparse.ArgumentParser(
+ description='This file is used to benchmark the scores fo multiple classification algorithm on multiview data.',
+ formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+
+ groupStandard = parser.add_argument_group('Standard arguments')
+ groupStandard.add_argument('-log', action='store_true', help='Use option to activate Logging to Console')
+ groupStandard.add_argument('--name', metavar='STRING', action='store', help='Name of Database (default: %(default)s)',
+ default='Plausible')
+ groupStandard.add_argument('--type', metavar='STRING', action='store',
+ help='Type of database : .hdf5 or .csv (default: %(default)s)',
+ default='.hdf5')
+ groupStandard.add_argument('--views', metavar='STRING', action='store', nargs="+",
+ help='Name of the views selected for learning (default: %(default)s)',
+ default=[''])
+ groupStandard.add_argument('--pathF', metavar='STRING', action='store', help='Path to the views (default: %(default)s)',
+ default='/home/bbauvin/Documents/Data/Data_multi_omics/')
+ groupStandard.add_argument('--nice', metavar='INT', action='store', type=int,
+ help='Niceness for the process', default=0)
+ groupStandard.add_argument('--randomState', metavar='STRING', action='store',
+ help="The random state seed to use or a file where we can find it's get_state", default=None)
+
+ groupClass = parser.add_argument_group('Classification arguments')
+ groupClass.add_argument('--CL_split', metavar='FLOAT', action='store',
+ help='Determine the split between learning and validation sets', type=float,
+ default=0.2)
+ groupClass.add_argument('--CL_nbFolds', metavar='INT', action='store', help='Number of folds in cross validation',
+ type=int, default=2)
+ groupClass.add_argument('--CL_nb_class', metavar='INT', action='store', help='Number of classes, -1 for all', type=int,
+ default=2)
+ groupClass.add_argument('--CL_classes', metavar='STRING', action='store', nargs="+",
+ help='Classes used in the dataset (names of the folders) if not filled, random classes will be '
+ 'selected ex. walrus mole leopard', default=["yes", "no"])
+ groupClass.add_argument('--CL_type', metavar='STRING', action='store', nargs="+",
+ help='Determine whether to use Multiview and/or Monoview, or Benchmark',
+ default=['Benchmark'])
+ groupClass.add_argument('--CL_algos_monoview', metavar='STRING', action='store', nargs="+",
+ help='Determine which monoview classifier to use if empty, considering all',
+ default=[''])
+ groupClass.add_argument('--CL_algos_multiview', metavar='STRING', action='store', nargs="+",
+ help='Determine which multiview classifier to use if empty, considering all',
+ default=[''])
+ groupClass.add_argument('--CL_cores', metavar='INT', action='store', help='Number of cores, -1 for all', type=int,
+ default=2)
+ groupClass.add_argument('--CL_statsiter', metavar='INT', action='store',
+ help="Number of iteration for each algorithm to mean results if using multiple cores, it's highly recommended to use statsiter mod(nbCores) = 0",
+ type=int,
+ default=2)
+ groupClass.add_argument('--CL_metrics', metavar='STRING', action='store', nargs="+",
+ help='Determine which metrics to use, separate metric and configuration with ":".'
+ ' If multiple, separate with space. If no metric is specified, '
+ 'considering all with accuracy for classification '
+ , default=[''])
+ groupClass.add_argument('--CL_metric_princ', metavar='STRING', action='store',
+ help='Determine which metric to use for randomSearch and optimization', default="f1_score")
+ groupClass.add_argument('--CL_GS_iter', metavar='INT', action='store',
+ help='Determine how many Randomized grid search tests to do', type=int, default=2)
+ groupClass.add_argument('--CL_HPS_type', metavar='STRING', action='store',
+ help='Determine which hyperparamter search function use', default="randomizedSearch")
+
+ groupRF = parser.add_argument_group('Random Forest arguments')
+ groupRF.add_argument('--CL_RandomForest_trees', metavar='INT', type=int, action='store', help='Number max trees',
+ default=25)
+ groupRF.add_argument('--CL_RandomForest_max_depth', metavar='INT', type=int, action='store',
+ help='Max depth for the trees',
+ default=5)
+ groupRF.add_argument('--CL_RandomForest_criterion', metavar='STRING', action='store', help='Criterion for the trees',
+ default="entropy")
+
+ groupSVMLinear = parser.add_argument_group('Linear SVM arguments')
+ groupSVMLinear.add_argument('--CL_SVMLinear_C', metavar='INT', type=int, action='store', help='Penalty parameter used',
+ default=1)
+
+ groupSVMRBF = parser.add_argument_group('SVW-RBF arguments')
+ groupSVMRBF.add_argument('--CL_SVMRBF_C', metavar='INT', type=int, action='store', help='Penalty parameter used',
+ default=1)
+
+ groupSVMPoly = parser.add_argument_group('Poly SVM arguments')
+ groupSVMPoly.add_argument('--CL_SVMPoly_C', metavar='INT', type=int, action='store', help='Penalty parameter used',
+ default=1)
+ groupSVMPoly.add_argument('--CL_SVMPoly_deg', metavar='INT', type=int, action='store', help='Degree parameter used',
+ default=2)
+
+ groupAdaboost = parser.add_argument_group('Adaboost arguments')
+ groupAdaboost.add_argument('--CL_Adaboost_n_est', metavar='INT', type=int, action='store', help='Number of estimators',
+ default=2)
+ groupAdaboost.add_argument('--CL_Adaboost_b_est', metavar='STRING', action='store', help='Estimators',
+ default='DecisionTreeClassifier')
+
+ groupDT = parser.add_argument_group('Decision Trees arguments')
+ groupDT.add_argument('--CL_DecisionTree_depth', metavar='INT', type=int, action='store',
+ help='Determine max depth for Decision Trees', default=3)
+ groupDT.add_argument('--CL_DecisionTree_criterion', metavar='STRING', action='store',
+ help='Determine max depth for Decision Trees', default="entropy")
+ groupDT.add_argument('--CL_DecisionTree_splitter', metavar='STRING', action='store',
+ help='Determine criterion for Decision Trees', default="random")
+
+ groupSGD = parser.add_argument_group('SGD arguments')
+ groupSGD.add_argument('--CL_SGD_alpha', metavar='FLOAT', type=float, action='store',
+ help='Determine alpha for SGDClassifier', default=0.1)
+ groupSGD.add_argument('--CL_SGD_loss', metavar='STRING', action='store',
+ help='Determine loss for SGDClassifier', default='log')
+ groupSGD.add_argument('--CL_SGD_penalty', metavar='STRING', action='store',
+ help='Determine penalty for SGDClassifier', default='l2')
+
+ groupKNN = parser.add_argument_group('KNN arguments')
+ groupKNN.add_argument('--CL_KNN_neigh', metavar='INT', type=int, action='store',
+ help='Determine number of neighbors for KNN', default=1)
+ groupKNN.add_argument('--CL_KNN_weights', metavar='STRING', action='store',
+ help='Determine number of neighbors for KNN', default="distance")
+ groupKNN.add_argument('--CL_KNN_algo', metavar='STRING', action='store',
+ help='Determine number of neighbors for KNN', default="auto")
+ groupKNN.add_argument('--CL_KNN_p', metavar='INT', type=int, action='store',
+ help='Determine number of neighbors for KNN', default=1)
+
+ groupSCM = parser.add_argument_group('SCM arguments')
+ groupSCM.add_argument('--CL_SCM_max_rules', metavar='INT', type=int, action='store',
+ help='Max number of rules for SCM', default=1)
+ groupSCM.add_argument('--CL_SCM_p', metavar='FLOAT', type=float, action='store',
+ help='Max number of rules for SCM', default=1.0)
+ groupSCM.add_argument('--CL_SCM_model_type', metavar='STRING', action='store',
+ help='Max number of rules for SCM', default="conjunction")
+
+ groupMumbo = parser.add_argument_group('Mumbo arguments')
+ groupMumbo.add_argument('--MU_types', metavar='STRING', action='store', nargs="+",
+ help='Determine which monoview classifier to use with Mumbo',
+ default=[''])
+ groupMumbo.add_argument('--MU_config', metavar='STRING', action='store', nargs='+',
+ help='Configuration for the monoview classifier in Mumbo separate each classifier with sapce and each argument with:',
+ default=[''])
+ groupMumbo.add_argument('--MU_iter', metavar='INT', action='store', nargs=3,
+ help='Max number of iteration, min number of iteration, convergence threshold', type=float,
+ default=[10, 1, 0.01])
+ groupMumbo.add_argument('--MU_combination', action='store_true',
+ help='Try all the monoview classifiers combinations for each view',
+ default=False)
+
+
+ groupFusion = parser.add_argument_group('Fusion arguments')
+ groupFusion.add_argument('--FU_types', metavar='STRING', action='store', nargs="+",
+ help='Determine which type of fusion to use',
+ default=[''])
+ groupEarlyFusion = parser.add_argument_group('Early Fusion arguments')
+ groupEarlyFusion.add_argument('--FU_early_methods', metavar='STRING', action='store', nargs="+",
+ help='Determine which early fusion method of fusion to use',
+ default=[''])
+ groupEarlyFusion.add_argument('--FU_E_method_configs', metavar='STRING', action='store', nargs='+',
+ help='Configuration for the early fusion methods separate '
+ 'method by space and values by :',
+ default=[''])
+ groupEarlyFusion.add_argument('--FU_E_cl_config', metavar='STRING', action='store', nargs='+',
+ help='Configuration for the monoview classifiers used separate classifier by space '
+ 'and configs must be of form argument1_name:value,argument2_name:value',
+ default=[''])
+ groupEarlyFusion.add_argument('--FU_E_cl_names', metavar='STRING', action='store', nargs='+',
+ help='Name of the classifiers used for each early fusion method', default=[''])
+
+ groupLateFusion = parser.add_argument_group('Late Early Fusion arguments')
+ groupLateFusion.add_argument('--FU_late_methods', metavar='STRING', action='store', nargs="+",
+ help='Determine which late fusion method of fusion to use',
+ default=[''])
+ groupLateFusion.add_argument('--FU_L_method_config', metavar='STRING', action='store', nargs='+',
+ help='Configuration for the fusion method', default=[''])
+ groupLateFusion.add_argument('--FU_L_cl_config', metavar='STRING', action='store', nargs='+',
+ help='Configuration for the monoview classifiers used', default=[''])
+ groupLateFusion.add_argument('--FU_L_cl_names', metavar='STRING', action='store', nargs="+",
+ help='Names of the classifier used for late fusion', default=[''])
+ groupLateFusion.add_argument('--FU_L_select_monoview', metavar='STRING', action='store',
+ help='Determine which method to use to select the monoview classifiers',
+ default="intersect")
+ self.args = parser.parse_args([])
diff --git a/Code/Tests/test_poulet.py b/Code/Tests/test_poulet.py
deleted file mode 100644
index 31e6debf..00000000
--- a/Code/Tests/test_poulet.py
+++ /dev/null
@@ -1,7 +0,0 @@
-import unittest
-
-
-class TestFromage(unittest.TestCase):
-
- def test_fromage(self):
- self.assertEqual(1,1)
\ No newline at end of file
diff --git a/Code/__init__.py b/Code/__init__.py
index f080b245..27925d1c 100644
--- a/Code/__init__.py
+++ b/Code/__init__.py
@@ -1 +1,2 @@
-from . import MonoMultiViewClassifiers, Tests, Exec
\ No newline at end of file
+from . import MonoMultiViewClassifiers, Tests, Exec
+import pdb;pdb.set_trace()
\ No newline at end of file
--
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