From 971c6cb7a5f938498fd4ba8d62481b7ce054059d Mon Sep 17 00:00:00 2001 From: spo Date: Thu, 3 Dec 2015 13:26:40 +0300 Subject: [PATCH] Fix suite_FEATURE_BOOLEAN & suite_FEATURE_CONSTRUCTION --- .../tst_boolean_001/test.py | 46 +++++++++---------- .../tst_boolean_001/verificationPoints/CUT | 8 ++-- .../tst_boolean_002/test.py | 46 +++++++++---------- .../tst_boolean_003/test.py | 44 +++++++++--------- .../verificationPoints/INIT | 13 ++++-- 5 files changed, 79 insertions(+), 78 deletions(-) diff --git a/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_001/test.py b/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_001/test.py index 824640fd8..fc36b2af0 100644 --- a/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_001/test.py +++ b/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_001/test.py @@ -1,41 +1,41 @@ def main(): - #[project] NewGEOM - #[Scenario] Boolean_001 - #[Topic] 'Boolean cut' functionality - #[Tested functionality] - #[Summary description] - #[Expected results] - #[General comments] - + # [project] NewGEOM + # [Scenario] Boolean_001 + # [Topic] 'Boolean cut' functionality + # [Tested functionality] + # [Summary description] + # [Expected results] + # [General comments] + source(findFile("scripts", "common.py")) - - #[section] Application start - #[step] Launch SALOME + + # [section] Application start + # [step] Launch SALOME startApplication("salome_run.sh") set_defaults() - - #[step] Open 'for_extrusion_001.hdf' + + # [step] Open 'for_extrusion_001.hdf' open(DATA_PATH + "/for_boolean_001.hdf") - - #[step] Activate NewGeom + + # [step] Activate NewGeom clickButton(waitForObject(":SALOME*.NewGeom_QToolButton")) - - #[step] Activate Part_1 + + # [step] Activate Part_1 waitForObjectItem(":Object browser_XGUI_DataTree", "Part\\_1 (Not loaded)") clickItem(":Object browser_XGUI_DataTree", "Part\\_1 (Not loaded)", 48, 10, 0, Qt.LeftButton) openItemContextMenu(waitForObject(":Object browser_XGUI_DataTree"), "Part\\_1 (Not loaded)", 48, 10, 0) activateItem(waitForObjectItem(":_QMenu", "Activate")) - - #[step] Fit all + + # [step] Fit all fit_all() test.vp("INIT") - - #[step] Implement boolean cut for existing objects + + # [step] Implement boolean cut for existing objects boolean_cut((139, 138), (420, 195)) - #[check] Check that operation has been executed successfully + # [check] Check that operation has been executed successfully [vp CUT] test.vp("CUT") - + # [step] Close application without saving close_application() diff --git a/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_001/verificationPoints/CUT b/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_001/verificationPoints/CUT index 2a1ce3a28..6a82439d4 100644 --- a/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_001/verificationPoints/CUT +++ b/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_001/verificationPoints/CUT @@ -1,12 +1,10 @@ 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 - diff --git a/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_002/test.py b/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_002/test.py index 4c6d2d1b2..d0b3bb9ad 100644 --- a/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_002/test.py +++ b/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_002/test.py @@ -1,41 +1,41 @@ def main(): - #[project] NewGEOM - #[Scenario] Boolean_002 - #[Topic] 'Boolean fuse' functionality - #[Tested functionality] - #[Summary description] - #[Expected results] - #[General comments] - + # [project] NewGEOM + # [Scenario] Boolean_002 + # [Topic] 'Boolean fuse' functionality + # [Tested functionality] + # [Summary description] + # [Expected results] + # [General comments] + source(findFile("scripts", "common.py")) - - #[section] Application start - #[step] Launch SALOME + + # [section] Application start + # [step] Launch SALOME startApplication("salome_run.sh") set_defaults() - - #[step] Open 'for_extrusion_001.hdf' + + # [step] Open 'for_extrusion_001.hdf' open(DATA_PATH + "/for_boolean_001.hdf") - - #[step] Activate NewGeom + + # [step] Activate NewGeom clickButton(waitForObject(":SALOME*.NewGeom_QToolButton")) - - #[step] Activate Part_1 + + # [step] Activate Part_1 waitForObjectItem(":Object browser_XGUI_DataTree", "Part\\_1 (Not loaded)") clickItem(":Object browser_XGUI_DataTree", "Part\\_1 (Not loaded)", 48, 10, 0, Qt.LeftButton) openItemContextMenu(waitForObject(":Object browser_XGUI_DataTree"), "Part\\_1 (Not loaded)", 48, 10, 0) activateItem(waitForObjectItem(":_QMenu", "Activate")) - - #[step] Fit all + + # [step] Fit all fit_all() - test.vp("INIT") + test.vp("INIT") - #[step] Implement boolean fuse for existing objects + # [step] Implement boolean fuse for existing objects boolean_fuse((139, 138), (420, 195)) - #[check] Check that operation has been executed successfully + # [check] Check that operation has been executed successfully test.vp("FUSE") - + # [step] Close application without saving close_application() diff --git a/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_003/test.py b/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_003/test.py index 46b4e5562..3e107038d 100644 --- a/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_003/test.py +++ b/test.squish/suite_FEATURE_BOOLEAN/tst_boolean_003/test.py @@ -1,41 +1,41 @@ def main(): - #[project] NewGEOM - #[Scenario] Boolean_003 - #[Topic] 'Boolean common' functionality - #[Tested functionality] - #[Summary description] - #[Expected results] - #[General comments] - + # [project] NewGEOM + # [Scenario] Boolean_003 + # [Topic] 'Boolean common' functionality + # [Tested functionality] + # [Summary description] + # [Expected results] + # [General comments] + source(findFile("scripts", "common.py")) - - #[section] Application start - #[step] Launch SALOME + + # [section] Application start + # [step] Launch SALOME startApplication("salome_run.sh") set_defaults() - - #[step] Open 'for_extrusion_001.hdf' + + # [step] Open 'for_extrusion_001.hdf' open(DATA_PATH + "/for_boolean_001.hdf") - - #[step] Activate NewGeom + + # [step] Activate NewGeom clickButton(waitForObject(":SALOME*.NewGeom_QToolButton")) - - #[step] Activate Part_1 + + # [step] Activate Part_1 waitForObjectItem(":Object browser_XGUI_DataTree", "Part\\_1 (Not loaded)") clickItem(":Object browser_XGUI_DataTree", "Part\\_1 (Not loaded)", 48, 10, 0, Qt.LeftButton) openItemContextMenu(waitForObject(":Object browser_XGUI_DataTree"), "Part\\_1 (Not loaded)", 48, 10, 0) activateItem(waitForObjectItem(":_QMenu", "Activate")) - - #[step] Fit all + + # [step] Fit all fit_all() test.vp("INIT") - #[step] Implement boolean common for existing objects + # [step] Implement boolean common for existing objects boolean_common((139, 138), (420, 195)) - #[check] Check that operation has been executed successfully + # [check] Check that operation has been executed successfully test.vp("COMMON") - + # [step] Close application without saving close_application() diff --git a/test.squish/suite_FEATURE_CONSTRUCTION/tst_construction_001/verificationPoints/INIT b/test.squish/suite_FEATURE_CONSTRUCTION/tst_construction_001/verificationPoints/INIT index ab019c43b..f39b8de53 100644 --- a/test.squish/suite_FEATURE_CONSTRUCTION/tst_construction_001/verificationPoints/INIT +++ b/test.squish/suite_FEATURE_CONSTRUCTION/tst_construction_001/verificationPoints/INIT @@ -1,6 +1,9 @@ - - - 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 + + + + -- 2.39.2