This commit is contained in:
2021-10-14 13:47:35 +02:00
commit 6625a8dfaa
4026 changed files with 844291 additions and 0 deletions
@@ -0,0 +1,25 @@
PROJECT(test_evaluation)
IF(WIN32)
ADD_DEFINITIONS(-DTARGET_OS_Windows)
ENDIF(WIN32)
IF(UNIX)
ADD_DEFINITIONS(-DTARGET_OS_Linux)
ENDIF(UNIX)
ADD_DEFINITIONS(-D_CRT_SECURE_NO_DEPRECATE)
ADD_DEFINITIONS(-DTARGET_ARCHITECTURE_i386)
INCLUDE_DIRECTORIES(../src)
ADD_EXECUTABLE(${PROJECT_NAME} test_kappa.cpp)
SET_PROPERTY(TARGET ${PROJECT_NAME} PROPERTY FOLDER ${TESTS_FOLDER}) # Place project in folder unit-test (for some IDE)
#INCLUDE("FindOpenViBE")
# Unfortunately we need to install the tests as any application to find .dll/.so files
# on both Windows and Linux.
OV_INSTALL_LAUNCH_SCRIPT(SCRIPT_PREFIX "${PROJECT_NAME}" EXECUTABLE_NAME "${PROJECT_NAME}")
INSTALL(TARGETS ${PROJECT_NAME}
RUNTIME DESTINATION ${DIST_BINDIR}
LIBRARY DESTINATION ${DIST_LIBDIR}
ARCHIVE DESTINATION ${DIST_LIBDIR})
@@ -0,0 +1,48 @@
#blabla
# @FIXME there is a problem of using the global log, this will cause interference if any tests are run in parallel
IF(WIN32)
SET(EXT cmd)
SET(OS_FLAGS "--no-pause")
ELSE(WIN32)
SET(EXT sh)
SET(OS_FLAGS "")
ENDIF(WIN32)
ADD_TEST(clean_Evaluation_kappa "${CMAKE_COMMAND}" "-E" "remove" "-f" ${OV_LOGFILE})
ADD_TEST(run_Evaluation_kappa "$ENV{OV_BINARY_PATH}/openvibe-designer.${EXT}" ${OS_FLAGS} "--invisible" "--no-session-management" --define Plugin_Classification_RandomizeKFoldTestData true "--play-fast" Test-kappa.xml)
#ADD_TEST(compare_Evaluation_kappa "$ENV{OV_BINARY_PATH}/test_evaluation.${EXT}" "${OS_FLAGS}" "${OV_LOGFILE}")
# It would be better to clean last, but we can't do this as it will delete the
# output we wish to include, and we can't prevent clean from running if a prev. test fails
# We need the clean to be sure that the comparator stage is not getting data from a previous run.
SET_TESTS_PROPERTIES(run_Evaluation_kappa PROPERTIES DEPENDS clean_Evaluation_kappa)
SET_TESTS_PROPERTIES(run_Evaluation_kappa PROPERTIES ATTACHED_FILES_ON_FAIL ${OV_LOGFILE})
#SET_TESTS_PROPERTIES(compare_Evaluation_kappa PROPERTIES DEPENDS run_Evaluation_kappa)
#SET_TESTS_PROPERTIES(compare_Evaluation_kappa PROPERTIES ATTACHED_FILES_ON_FAIL ${OV_LOGFILE})
ADD_TEST(run_Evaluation_statistic_generator "$ENV{OV_BINARY_PATH}/openvibe-designer.${EXT}" ${OS_FLAGS} "--invisible" "--no-session-management" --define Plugin_Classification_RandomizeKFoldTestData true "--play-fast" Test-StatisticGenerator.xml)
ADD_TEST(compare_Evaluation_statistic_generator "git" "diff" "--no-index" "--ignore-space-change" "stat.xml" "data/Statistic_comparison.xml")
ADD_TEST(clean_Evaluation_statistic_generator "${CMAKE_COMMAND}" "-E" "remove" "-f" stat.xml)
SET_TESTS_PROPERTIES(compare_Evaluation_statistic_generator PROPERTIES DEPENDS run_Evaluation_statistic_generator)
SET_TESTS_PROPERTIES(compare_Evaluation_statistic_generator PROPERTIES ATTACHED_FILES_ON_FAIL ${OV_LOGFILE})
### Do not enable the commented out sikuli tests unless you
### or your lab commits to keep them passing in the long term.
#FIND_PROGRAM(SIKULI NAMES sikuli-ide)
#IF(SIKULI)
# IF(UNIX)
# ADD_TEST(sikuli_clean_Evaluation_ROC "${CMAKE_COMMAND}" "-E" "remove" "-f" ${OV_LOGFILE} screenshot.png)
# ADD_TEST(sikuli_run_Evaluation_ROC "${SIKULI}" -t testROCCurve.UNIX.sikuli)
#
# SET_TESTS_PROPERTIES(sikuli_run_Evaluation_ROC PROPERTIES DEPENDS sikuli_clean_Evaluation_ROC)
# SET_TESTS_PROPERTIES(sikuli_run_Evaluation_ROC PROPERTIES ATTACHED_FILES_ON_FAIL ${OV_LOGFILE})
# SET_TESTS_PROPERTIES(sikuli_run_Evaluation_ROC PROPERTIES ATTACHED_FILES_ON_FAIL ${CTEST_SOURCE_DIRECTORY}/plugins/processing/evaluation/test/screenshot.png)
# ENDIF(UNIX)
#ENDIF(SIKULI)
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<Target>
<BoxIdentifier>(0x0000555d, 0x00004472)</BoxIdentifier>
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<Link>
<Identifier>(0x00004a37, 0x00005687)</Identifier>
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<Entry>
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Time:1x1,End Time,Noise 1:,Event Id,Event Date,Event Duration
0.2705078125,0.3398437500,0.0,33026,0.2705078125,0.0
0.3398437500,0.5419921875,0.0,33024,0.3398437500,0.0
0.5419921875,0.6796875000,0.0,33026,0.5419921875,0.0
0.6796875000,0.7099609375,0.0,33024,0.6796875000,0.0
0.7099609375,0.8125000000,0.0,33025,0.7099609375,0.0
0.8125000000,1.0195312500,0.0,33026,0.8125000000,0.0
1.0195312500,1.0839843750,0.0,33024,1.0195312500,0.0
1.0839843750,1.3544921875,0.0,33026,1.0839843750,0.0
1.3544921875,1.3593750000,0.0,33026,1.3544921875,0.0
1.3593750000,1.4199218750,0.0,33024,1.3593750000,0.0
1.4199218750,1.6259765625,0.0,33025,1.4199218750,0.0
1.6259765625,1.6992187500,0.0,33026,1.6259765625,0.0
1.6992187500,1.8964843750,0.0,33024,1.6992187500,0.0
1.8964843750,2.0390625000,0.0,33026,1.8964843750,0.0
2.0390625000,2.1298828125,0.0,33024,2.0390625000,0.0
2.1298828125,2.1679687500,0.0,33025,2.1298828125,0.0
2.1679687500,2.3798828125,0.0,33026,2.1679687500,0.0
2.3798828125,2.4384765625,0.0,33024,2.3798828125,0.0
2.4384765625,2.7099609375,0.0,33026,2.4384765625,0.0
2.7099609375,2.7197265625,0.0,33026,2.7099609375,0.0
2.7197265625,2.8398437500,0.0,33024,2.7197265625,0.0
2.8398437500,2.9804687500,0.0,33025,2.8398437500,0.0
2.9804687500,3.0595703125,0.0,33026,2.9804687500,0.0
3.0595703125,3.2519531250,0.0,33024,3.0595703125,0.0
3.2519531250,3.3994140625,0.0,33026,3.2519531250,0.0
3.3994140625,3.5224609375,0.0,33024,3.3994140625,0.0
3.5224609375,3.5498046875,0.0,33026,3.5224609375,0.0
3.5498046875,3.7392578125,0.0,33025,3.5498046875,0.0
3.7392578125,3.7939453125,0.0,33024,3.7392578125,0.0
3.7939453125,4.0644531250,0.0,33026,3.7939453125,0.0
4.0644531250,4.0791015625,0.0,33026,4.0644531250,0.0
4.0791015625,4.2597656250,0.0,33024,4.0791015625,0.0
4.2597656250,4.3359375000,0.0,33025,4.2597656250,0.0
4.3359375000,4.4199218750,0.0,33026,4.3359375000,0.0
4.4199218750,4.6064453125,0.0,33024,4.4199218750,0.0
4.6064453125,4.7597656250,0.0,33026,4.6064453125,0.0
4.7597656250,4.8779296875,0.0,33024,4.7597656250,0.0
4.8779296875,4.9697265625,0.0,33026,4.8779296875,0.0
4.9697265625,5.0996093750,0.0,33025,4.9697265625,0.0
5.0996093750,5.1484375000,0.0,33024,5.0996093750,0.0
5.1484375000,5.4199218750,0.0,33026,5.1484375000,0.0
5.4199218750,5.4394531250,0.0,33026,5.4199218750,0.0
5.4394531250,5.6796875000,0.0,33024,5.4394531250,0.0
5.6796875000,5.6904296875,0.0,33025,5.6796875000,0.0
5.6904296875,5.7792968750,0.0,33026,5.6904296875,0.0
5.7792968750,5.9619140625,0.0,33024,5.7792968750,0.0
5.9619140625,6.1191406250,0.0,33026,5.9619140625,0.0
6.1191406250,6.2324218750,0.0,33024,6.1191406250,0.0
6.2324218750,6.3896484375,0.0,33026,6.2324218750,0.0
6.3896484375,6.4599609375,0.0,33025,6.3896484375,0.0
6.4599609375,6.5039062500,0.0,33024,6.4599609375,0.0
6.5039062500,6.7744140625,0.0,33026,6.5039062500,0.0
6.7744140625,6.7998046875,0.0,33026,6.7744140625,0.0
6.7998046875,7.0458984375,0.0,33024,6.7998046875,0.0
7.0458984375,7.0996093750,0.0,33026,7.0458984375,0.0
7.0996093750,7.1396484375,0.0,33025,7.0996093750,0.0
7.1396484375,7.3164062500,0.0,33024,7.1396484375,0.0
7.3164062500,7.4794921875,0.0,33026,7.3164062500,0.0
7.4794921875,7.5878906250,0.0,33024,7.4794921875,0.0
7.5878906250,7.8095703125,0.0,33026,7.5878906250,0.0
7.8095703125,7.8193359375,0.0,33025,7.8095703125,0.0
7.8193359375,7.8583984375,0.0,33024,7.8193359375,0.0
7.8583984375,8.1298828125,0.0,33026,7.8583984375,0.0
8.1298828125,8.1591796875,0.0,33026,8.1298828125,0.0
8.1591796875,8.4003906250,0.0,33024,8.1591796875,0.0
8.4003906250,8.4990234375,0.0,33026,8.4003906250,0.0
8.4990234375,8.5195312500,0.0,33024,8.4990234375,0.0
8.5195312500,8.6718750000,0.0,33025,8.5195312500,0.0
8.6718750000,8.8398437500,0.0,33026,8.6718750000,0.0
8.8398437500,8.9423828125,0.0,33024,8.8398437500,0.0
8.9423828125,9.1796875000,0.0,33026,8.9423828125,0.0
9.1796875000,9.2138671875,0.0,33024,9.1796875000,0.0
9.2138671875,9.2294921875,0.0,33026,9.2138671875,0.0
9.2294921875,9.4843750000,0.0,33025,9.2294921875,0.0
9.4843750000,9.5195312500,0.0,33026,9.4843750000,0.0
9.5195312500,9.7558593750,0.0,33024,9.5195312500,0.0
9.7558593750,9.8593750000,0.0,33026,9.7558593750,0.0
9.8593750000,9.9394531250,0.0,33024,9.8593750000,0.0
9.9394531250,10.026367188,0.0,33025,9.9394531250,0.0
10.026367188,10.106445313,0.0,33026,10.026367188,0.0
1 Time:1x1 End Time Noise 1: Event Id Event Date Event Duration
2 0.2705078125 0.3398437500 0.0 33026 0.2705078125 0.0
3 0.3398437500 0.5419921875 0.0 33024 0.3398437500 0.0
4 0.5419921875 0.6796875000 0.0 33026 0.5419921875 0.0
5 0.6796875000 0.7099609375 0.0 33024 0.6796875000 0.0
6 0.7099609375 0.8125000000 0.0 33025 0.7099609375 0.0
7 0.8125000000 1.0195312500 0.0 33026 0.8125000000 0.0
8 1.0195312500 1.0839843750 0.0 33024 1.0195312500 0.0
9 1.0839843750 1.3544921875 0.0 33026 1.0839843750 0.0
10 1.3544921875 1.3593750000 0.0 33026 1.3544921875 0.0
11 1.3593750000 1.4199218750 0.0 33024 1.3593750000 0.0
12 1.4199218750 1.6259765625 0.0 33025 1.4199218750 0.0
13 1.6259765625 1.6992187500 0.0 33026 1.6259765625 0.0
14 1.6992187500 1.8964843750 0.0 33024 1.6992187500 0.0
15 1.8964843750 2.0390625000 0.0 33026 1.8964843750 0.0
16 2.0390625000 2.1298828125 0.0 33024 2.0390625000 0.0
17 2.1298828125 2.1679687500 0.0 33025 2.1298828125 0.0
18 2.1679687500 2.3798828125 0.0 33026 2.1679687500 0.0
19 2.3798828125 2.4384765625 0.0 33024 2.3798828125 0.0
20 2.4384765625 2.7099609375 0.0 33026 2.4384765625 0.0
21 2.7099609375 2.7197265625 0.0 33026 2.7099609375 0.0
22 2.7197265625 2.8398437500 0.0 33024 2.7197265625 0.0
23 2.8398437500 2.9804687500 0.0 33025 2.8398437500 0.0
24 2.9804687500 3.0595703125 0.0 33026 2.9804687500 0.0
25 3.0595703125 3.2519531250 0.0 33024 3.0595703125 0.0
26 3.2519531250 3.3994140625 0.0 33026 3.2519531250 0.0
27 3.3994140625 3.5224609375 0.0 33024 3.3994140625 0.0
28 3.5224609375 3.5498046875 0.0 33026 3.5224609375 0.0
29 3.5498046875 3.7392578125 0.0 33025 3.5498046875 0.0
30 3.7392578125 3.7939453125 0.0 33024 3.7392578125 0.0
31 3.7939453125 4.0644531250 0.0 33026 3.7939453125 0.0
32 4.0644531250 4.0791015625 0.0 33026 4.0644531250 0.0
33 4.0791015625 4.2597656250 0.0 33024 4.0791015625 0.0
34 4.2597656250 4.3359375000 0.0 33025 4.2597656250 0.0
35 4.3359375000 4.4199218750 0.0 33026 4.3359375000 0.0
36 4.4199218750 4.6064453125 0.0 33024 4.4199218750 0.0
37 4.6064453125 4.7597656250 0.0 33026 4.6064453125 0.0
38 4.7597656250 4.8779296875 0.0 33024 4.7597656250 0.0
39 4.8779296875 4.9697265625 0.0 33026 4.8779296875 0.0
40 4.9697265625 5.0996093750 0.0 33025 4.9697265625 0.0
41 5.0996093750 5.1484375000 0.0 33024 5.0996093750 0.0
42 5.1484375000 5.4199218750 0.0 33026 5.1484375000 0.0
43 5.4199218750 5.4394531250 0.0 33026 5.4199218750 0.0
44 5.4394531250 5.6796875000 0.0 33024 5.4394531250 0.0
45 5.6796875000 5.6904296875 0.0 33025 5.6796875000 0.0
46 5.6904296875 5.7792968750 0.0 33026 5.6904296875 0.0
47 5.7792968750 5.9619140625 0.0 33024 5.7792968750 0.0
48 5.9619140625 6.1191406250 0.0 33026 5.9619140625 0.0
49 6.1191406250 6.2324218750 0.0 33024 6.1191406250 0.0
50 6.2324218750 6.3896484375 0.0 33026 6.2324218750 0.0
51 6.3896484375 6.4599609375 0.0 33025 6.3896484375 0.0
52 6.4599609375 6.5039062500 0.0 33024 6.4599609375 0.0
53 6.5039062500 6.7744140625 0.0 33026 6.5039062500 0.0
54 6.7744140625 6.7998046875 0.0 33026 6.7744140625 0.0
55 6.7998046875 7.0458984375 0.0 33024 6.7998046875 0.0
56 7.0458984375 7.0996093750 0.0 33026 7.0458984375 0.0
57 7.0996093750 7.1396484375 0.0 33025 7.0996093750 0.0
58 7.1396484375 7.3164062500 0.0 33024 7.1396484375 0.0
59 7.3164062500 7.4794921875 0.0 33026 7.3164062500 0.0
60 7.4794921875 7.5878906250 0.0 33024 7.4794921875 0.0
61 7.5878906250 7.8095703125 0.0 33026 7.5878906250 0.0
62 7.8095703125 7.8193359375 0.0 33025 7.8095703125 0.0
63 7.8193359375 7.8583984375 0.0 33024 7.8193359375 0.0
64 7.8583984375 8.1298828125 0.0 33026 7.8583984375 0.0
65 8.1298828125 8.1591796875 0.0 33026 8.1298828125 0.0
66 8.1591796875 8.4003906250 0.0 33024 8.1591796875 0.0
67 8.4003906250 8.4990234375 0.0 33026 8.4003906250 0.0
68 8.4990234375 8.5195312500 0.0 33024 8.4990234375 0.0
69 8.5195312500 8.6718750000 0.0 33025 8.5195312500 0.0
70 8.6718750000 8.8398437500 0.0 33026 8.6718750000 0.0
71 8.8398437500 8.9423828125 0.0 33024 8.8398437500 0.0
72 8.9423828125 9.1796875000 0.0 33026 8.9423828125 0.0
73 9.1796875000 9.2138671875 0.0 33024 9.1796875000 0.0
74 9.2138671875 9.2294921875 0.0 33026 9.2138671875 0.0
75 9.2294921875 9.4843750000 0.0 33025 9.2294921875 0.0
76 9.4843750000 9.5195312500 0.0 33026 9.4843750000 0.0
77 9.5195312500 9.7558593750 0.0 33024 9.5195312500 0.0
78 9.7558593750 9.8593750000 0.0 33026 9.7558593750 0.0
79 9.8593750000 9.9394531250 0.0 33024 9.8593750000 0.0
80 9.9394531250 10.026367188 0.0 33025 9.9394531250 0.0
81 10.026367188 10.106445313 0.0 33026 10.026367188 0.0
@@ -0,0 +1,81 @@
Time:1x1,End Time,Noise 1:,Event Id,Event Date,Event Duration
0.2715078125,0.3408437500,0.0,33026,0.2715078125,0.0
0.3408437500,0.5429921875,0.0,33025,0.3408437500,0.0
0.5429921875,0.6806875000,0.0,33026,0.5429921875,0.0
0.6806875000,0.7109609375,0.0,33025,0.6806875000,0.0
0.7109609375,0.8135000000,0.0,33025,0.7109609375,0.0
0.8135000000,1.0295312500,0.0,33026,0.8135000000,0.0
1.0295312500,1.0939843750,0.0,33024,1.0295312500,0.0
1.0939843750,1.3569921875,0.0,33026,1.0939843750,0.0
1.3569921875,1.3693750000,0.0,33026,1.3569921875,0.0
1.3693750000,1.4299218750,0.0,33026,1.3693750000,0.0
1.4299218750,1.6359765625,0.0,33025,1.4299218750,0.0
1.6359765625,1.7092187500,0.0,33026,1.6359765625,0.0
1.7092187500,1.9064843750,0.0,33024,1.7092187500,0.0
1.9064843750,2.0490625000,0.0,33026,1.9064843750,0.0
2.0490625000,2.1398828125,0.0,33024,2.0490625000,0.0
2.1398828125,2.1779687500,0.0,33024,2.1398828125,0.0
2.1779687500,2.3898828125,0.0,33026,2.1779687500,0.0
2.3898828125,2.4484765625,0.0,33024,2.3898828125,0.0
2.4484765625,2.7159609375,0.0,33026,2.4484765625,0.0
2.7159609375,2.7297265625,0.0,33026,2.7159609375,0.0
2.7297265625,2.8498437500,0.0,33024,2.7297265625,0.0
2.8498437500,2.9904687500,0.0,33026,2.8498437500,0.0
2.9904687500,3.0695703125,0.0,33026,2.9904687500,0.0
3.0695703125,3.2619531250,0.0,33024,3.0695703125,0.0
3.2619531250,3.4094140625,0.0,33024,3.2619531250,0.0
3.4094140625,3.5324609375,0.0,33024,3.4094140625,0.0
3.5324609375,3.5598046875,0.0,33024,3.5324609375,0.0
3.5598046875,3.7492578125,0.0,33025,3.5598046875,0.0
3.7492578125,3.8039453125,0.0,33024,3.7492578125,0.0
3.8039453125,4.0744531250,0.0,33025,3.8039453125,0.0
4.0744531250,4.0891015625,0.0,33026,4.0744531250,0.0
4.0891015625,4.2697656250,0.0,33024,4.0891015625,0.0
4.2697656250,4.3459375000,0.0,33025,4.2697656250,0.0
4.3459375000,4.4299218750,0.0,33026,4.3459375000,0.0
4.4299218750,4.6164453125,0.0,33024,4.4299218750,0.0
4.6164453125,4.7697656250,0.0,33026,4.6164453125,0.0
4.7697656250,4.8879296875,0.0,33024,4.7697656250,0.0
4.8879296875,4.9797265625,0.0,33026,4.8879296875,0.0
4.9797265625,5.1096093750,0.0,33025,4.9797265625,0.0
5.1096093750,5.1584375000,0.0,33024,5.1096093750,0.0
5.1584375000,5.4299218750,0.0,33026,5.1584375000,0.0
5.4299218750,5.4494531250,0.0,33026,5.4299218750,0.0
5.4494531250,5.6896875000,0.0,33024,5.4494531250,0.0
5.6896875000,5.7004296875,0.0,33025,5.6896875000,0.0
5.7004296875,5.7892968750,0.0,33026,5.7004296875,0.0
5.7892968750,5.9719140625,0.0,33024,5.7892968750,0.0
5.9719140625,6.1291406250,0.0,33026,5.9719140625,0.0
6.1291406250,6.2424218750,0.0,33024,6.1291406250,0.0
6.2424218750,6.3996484375,0.0,33026,6.2424218750,0.0
6.3996484375,6.4699609375,0.0,33025,6.3996484375,0.0
6.4699609375,6.5139062500,0.0,33024,6.4699609375,0.0
6.5139062500,6.7844140625,0.0,33026,6.5139062500,0.0
6.7844140625,6.8098046875,0.0,33026,6.7844140625,0.0
6.8098046875,7.0558984375,0.0,33024,6.8098046875,0.0
7.0558984375,7.1096093750,0.0,33026,7.0558984375,0.0
7.1096093750,7.1496484375,0.0,33025,7.1096093750,0.0
7.1496484375,7.3264062500,0.0,33024,7.1496484375,0.0
7.3264062500,7.4894921875,0.0,33026,7.3264062500,0.0
7.4894921875,7.5978906250,0.0,33024,7.4894921875,0.0
7.5978906250,7.8155703125,0.0,33026,7.5978906250,0.0
7.8155703125,7.8293359375,0.0,33025,7.8155703125,0.0
7.8293359375,7.8683984375,0.0,33024,7.8293359375,0.0
7.8683984375,8.1398828125,0.0,33026,7.8683984375,0.0
8.1398828125,8.1691796875,0.0,33026,8.1398828125,0.0
8.1691796875,8.4103906250,0.0,33024,8.1691796875,0.0
8.4103906250,8.5090234375,0.0,33026,8.4103906250,0.0
8.5090234375,8.5295312500,0.0,33024,8.5090234375,0.0
8.5295312500,8.6818750000,0.0,33025,8.5295312500,0.0
8.6818750000,8.8498437500,0.0,33026,8.6818750000,0.0
8.8498437500,8.9523828125,0.0,33024,8.8498437500,0.0
8.9523828125,9.1896875000,0.0,33026,8.9523828125,0.0
9.1896875000,9.2238671875,0.0,33024,9.1896875000,0.0
9.2238671875,9.2394921875,0.0,33026,9.2238671875,0.0
9.2394921875,9.4943750000,0.0,33025,9.2394921875,0.0
9.4943750000,9.5295312500,0.0,33026,9.4943750000,0.0
9.5295312500,9.7658593750,0.0,33024,9.5295312500,0.0
9.7658593750,9.8693750000,0.0,33026,9.7658593750,0.0
9.8693750000,9.9494531250,0.0,33024,9.8693750000,0.0
9.9494531250,10.126367188,0.0,33025,9.9494531250,0.0
10.126367188,10.206445313,0.0,33026,100126367188,0.0
1 Time:1x1 End Time Noise 1: Event Id Event Date Event Duration
2 0.2715078125 0.3408437500 0.0 33026 0.2715078125 0.0
3 0.3408437500 0.5429921875 0.0 33025 0.3408437500 0.0
4 0.5429921875 0.6806875000 0.0 33026 0.5429921875 0.0
5 0.6806875000 0.7109609375 0.0 33025 0.6806875000 0.0
6 0.7109609375 0.8135000000 0.0 33025 0.7109609375 0.0
7 0.8135000000 1.0295312500 0.0 33026 0.8135000000 0.0
8 1.0295312500 1.0939843750 0.0 33024 1.0295312500 0.0
9 1.0939843750 1.3569921875 0.0 33026 1.0939843750 0.0
10 1.3569921875 1.3693750000 0.0 33026 1.3569921875 0.0
11 1.3693750000 1.4299218750 0.0 33026 1.3693750000 0.0
12 1.4299218750 1.6359765625 0.0 33025 1.4299218750 0.0
13 1.6359765625 1.7092187500 0.0 33026 1.6359765625 0.0
14 1.7092187500 1.9064843750 0.0 33024 1.7092187500 0.0
15 1.9064843750 2.0490625000 0.0 33026 1.9064843750 0.0
16 2.0490625000 2.1398828125 0.0 33024 2.0490625000 0.0
17 2.1398828125 2.1779687500 0.0 33024 2.1398828125 0.0
18 2.1779687500 2.3898828125 0.0 33026 2.1779687500 0.0
19 2.3898828125 2.4484765625 0.0 33024 2.3898828125 0.0
20 2.4484765625 2.7159609375 0.0 33026 2.4484765625 0.0
21 2.7159609375 2.7297265625 0.0 33026 2.7159609375 0.0
22 2.7297265625 2.8498437500 0.0 33024 2.7297265625 0.0
23 2.8498437500 2.9904687500 0.0 33026 2.8498437500 0.0
24 2.9904687500 3.0695703125 0.0 33026 2.9904687500 0.0
25 3.0695703125 3.2619531250 0.0 33024 3.0695703125 0.0
26 3.2619531250 3.4094140625 0.0 33024 3.2619531250 0.0
27 3.4094140625 3.5324609375 0.0 33024 3.4094140625 0.0
28 3.5324609375 3.5598046875 0.0 33024 3.5324609375 0.0
29 3.5598046875 3.7492578125 0.0 33025 3.5598046875 0.0
30 3.7492578125 3.8039453125 0.0 33024 3.7492578125 0.0
31 3.8039453125 4.0744531250 0.0 33025 3.8039453125 0.0
32 4.0744531250 4.0891015625 0.0 33026 4.0744531250 0.0
33 4.0891015625 4.2697656250 0.0 33024 4.0891015625 0.0
34 4.2697656250 4.3459375000 0.0 33025 4.2697656250 0.0
35 4.3459375000 4.4299218750 0.0 33026 4.3459375000 0.0
36 4.4299218750 4.6164453125 0.0 33024 4.4299218750 0.0
37 4.6164453125 4.7697656250 0.0 33026 4.6164453125 0.0
38 4.7697656250 4.8879296875 0.0 33024 4.7697656250 0.0
39 4.8879296875 4.9797265625 0.0 33026 4.8879296875 0.0
40 4.9797265625 5.1096093750 0.0 33025 4.9797265625 0.0
41 5.1096093750 5.1584375000 0.0 33024 5.1096093750 0.0
42 5.1584375000 5.4299218750 0.0 33026 5.1584375000 0.0
43 5.4299218750 5.4494531250 0.0 33026 5.4299218750 0.0
44 5.4494531250 5.6896875000 0.0 33024 5.4494531250 0.0
45 5.6896875000 5.7004296875 0.0 33025 5.6896875000 0.0
46 5.7004296875 5.7892968750 0.0 33026 5.7004296875 0.0
47 5.7892968750 5.9719140625 0.0 33024 5.7892968750 0.0
48 5.9719140625 6.1291406250 0.0 33026 5.9719140625 0.0
49 6.1291406250 6.2424218750 0.0 33024 6.1291406250 0.0
50 6.2424218750 6.3996484375 0.0 33026 6.2424218750 0.0
51 6.3996484375 6.4699609375 0.0 33025 6.3996484375 0.0
52 6.4699609375 6.5139062500 0.0 33024 6.4699609375 0.0
53 6.5139062500 6.7844140625 0.0 33026 6.5139062500 0.0
54 6.7844140625 6.8098046875 0.0 33026 6.7844140625 0.0
55 6.8098046875 7.0558984375 0.0 33024 6.8098046875 0.0
56 7.0558984375 7.1096093750 0.0 33026 7.0558984375 0.0
57 7.1096093750 7.1496484375 0.0 33025 7.1096093750 0.0
58 7.1496484375 7.3264062500 0.0 33024 7.1496484375 0.0
59 7.3264062500 7.4894921875 0.0 33026 7.3264062500 0.0
60 7.4894921875 7.5978906250 0.0 33024 7.4894921875 0.0
61 7.5978906250 7.8155703125 0.0 33026 7.5978906250 0.0
62 7.8155703125 7.8293359375 0.0 33025 7.8155703125 0.0
63 7.8293359375 7.8683984375 0.0 33024 7.8293359375 0.0
64 7.8683984375 8.1398828125 0.0 33026 7.8683984375 0.0
65 8.1398828125 8.1691796875 0.0 33026 8.1398828125 0.0
66 8.1691796875 8.4103906250 0.0 33024 8.1691796875 0.0
67 8.4103906250 8.5090234375 0.0 33026 8.4103906250 0.0
68 8.5090234375 8.5295312500 0.0 33024 8.5090234375 0.0
69 8.5295312500 8.6818750000 0.0 33025 8.5295312500 0.0
70 8.6818750000 8.8498437500 0.0 33026 8.6818750000 0.0
71 8.8498437500 8.9523828125 0.0 33024 8.8498437500 0.0
72 8.9523828125 9.1896875000 0.0 33026 8.9523828125 0.0
73 9.1896875000 9.2238671875 0.0 33024 9.1896875000 0.0
74 9.2238671875 9.2394921875 0.0 33026 9.2238671875 0.0
75 9.2394921875 9.4943750000 0.0 33025 9.2394921875 0.0
76 9.4943750000 9.5295312500 0.0 33026 9.4943750000 0.0
77 9.5295312500 9.7658593750 0.0 33024 9.5295312500 0.0
78 9.7658593750 9.8693750000 0.0 33026 9.7658593750 0.0
79 9.8693750000 9.9494531250 0.0 33024 9.8693750000 0.0
80 9.9494531250 10.126367188 0.0 33025 9.9494531250 0.0
81 10.126367188 10.206445313 0.0 33026 100126367188 0.0
@@ -0,0 +1,35 @@
<Statistic>
<Stimulations-list>
<Stimulation>
<Identifier>(0x00000000, 0x00008100)</Identifier>
<Label>OVTK_StimulationId_Label_00</Label>
<Count>500</Count>
</Stimulation>
</Stimulations-list>
<Channel-list>
<Channel>
<Name>sinusOsc 1</Name>
<Maximum>2.9959498935</Maximum>
<Minimum>-2.9958162250</Minimum>
<Mean>0.0037440891</Mean>
</Channel>
<Channel>
<Name>sinusOsc 2</Name>
<Maximum>2.9955453841</Maximum>
<Minimum>-2.9959417073</Minimum>
<Mean>0.0021516936</Mean>
</Channel>
<Channel>
<Name>sinusOsc 3</Name>
<Maximum>2.9959425273</Maximum>
<Minimum>-2.9959158246</Minimum>
<Mean>0.0004745227</Mean>
</Channel>
<Channel>
<Name>sinusOsc 4</Name>
<Maximum>2.9959140852</Maximum>
<Minimum>-2.9959417073</Minimum>
<Mean>0.0012721927</Mean>
</Channel>
</Channel-list>
</Statistic>
@@ -0,0 +1,16 @@
<OpenViBE-Classifier-Box XMLVersion="3">
<Strategy-Identifier class-id="(0xffffffff, 0xffffffff)">Native</Strategy-Identifier>
<Algorithm-Identifier class-id="(0x2ba17a3c, 0x1bd46d84)">Linear Discrimimant Analysis (LDA)</Algorithm-Identifier>
<Stimulations>
<Class-Stimulation class-id="1">OVTK_GDF_Left</Class-Stimulation>
<Class-Stimulation class-id="2">OVTK_GDF_Right</Class-Stimulation>
</Stimulations>
<OpenViBE-Classifier>
<LDA>
<Classes>1 2</Classes>
<Weights> -1.390939e+01 -3.837006e+01 -3.951661e+00 1.267055e+02 8.129262e+00 1.130540e+02</Weights>
<Bias-distance>1.04657</Bias-distance>
<Coefficient-probability>1.15779</Coefficient-probability>
</LDA>
</OpenViBE-Classifier>
</OpenViBE-Classifier-Box>
@@ -0,0 +1,50 @@
g_offset = nil
g_duration = nil
-- this function is called when the box is initialized
function initialize(box)
dofile(box:get_config("${Path_Data}") .. "/plugins/stimulation/lua-stimulator-stim-codes.lua")
g_offset = box:get_setting(2)
g_duration = box:get_setting(3)
end
-- this function is called when the box is uninitialized
function uninitialize(box)
end
function wait_until(box, time)
while box:get_current_time() < time do
box:sleep()
end
end
function wait_for(box, duration)
wait_until(box, box:get_current_time() + duration)
end
function process(box)
-- loops on every received stimulation for a given input
while box:keep_processing() do
for stimulation = 1, box:get_stimulation_count(1) do
-- gets the received stimulation
identifier, date, duration = box:get_stimulation(1, 1)
-- discards it
box:remove_stimulation(1, 1)
-- delay the OVTK_GDF_Left and Right
if identifier == OVTK_GDF_Left or identifier == OVTK_GDF_Right then
box:send_stimulation(1, OVTK_GDF_Correct, date+g_offset, 0)
box:send_stimulation(1, OVTK_GDF_Incorrect, date+g_offset+g_duration, 0)
end
end
box:sleep()
end
end
@@ -0,0 +1,29 @@
def setUp(self):
import os
import shutil
ov_binany_path=os.environ['OV_BINARY_PATH']
self.terminal = App.open("xterm -e " + ov_binany_path +"/openvibe-designer.sh --no-session-management --play-fast Test_ROCCurve.xml")
while not self.terminal.window():
wait(1)
#def takepicture:
#dir = os.path.dirname(getBundlePath()) # the folder, where your script is stored
#img = capture(SCREEN) # snapshots the screen
#shutil.move(img, os.path.join(dir, "shot.png"))
def testROCCurve(self):
import os
import shutil
try:
wait("ROCCurveResult.png",60)
assert(exists("ROCCurveResult.png"))
except (FindFailed, AssertionError):
print "Unable to find the required png"
dir = os.path.dirname(getBundlePath()) # the folder, where your script is stored
img = capture(SCREEN) # snapshots the screen
shutil.move(img, os.path.join(dir, "screenshot.png"))
raise
def tearDown(self):
self.terminal.close()
@@ -0,0 +1,46 @@
#include <fstream>
#include <sstream>
#include <string>
#include <iostream>
int main(int argc, char** argv)
{
if (argc != 2)
{
std::cout << "Usage: test_evaluation <filename>\n";
return 3;
}
std::ifstream file(argv[1], std::ios::in);
if (file.good() && !file.bad() && file.is_open()) // ...
{
std::string line;
while (getline(file, line))
{
if (line.find("Final value of Kappa") != std::string::npos)
{
std::cout << "Found kappa line " << line << std::endl;
const size_t pos = line.rfind(' ');
const std::string cutline = line.substr(pos);
std::stringstream kappa(cutline);
double coefficient;
kappa >> coefficient;
if (coefficient != 0.840677)
{
std::cout << "Wrong Kappa coefficient. Found " << coefficient << " instead of 0.840677" << std::endl;
return 1;
}
std::cout << "Test ok" << std::endl;
return 0;
}
}
}
std::cout << "Error: Problem opening [" << argv[1] << "]\n";
return 2;
}