Python DatasetInfo.filePath方法代码示例

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
def debug_with_new(shell):
    """
    (Function for debug and testing.)
    """
    #projFilePath = "/magnetic/synapse_debug_data/object_prediction.ilp"
    projFilePath = "/magnetic/stuart_object_predictions.ilp"

    # New project
    shell.createAndLoadNewProject(projFilePath)
    workflow = shell.projectManager.workflow

    # Add a file
    from ilastik.applets.dataSelection.opDataSelection import DatasetInfo

    rawInfo = DatasetInfo()
    #rawInfo.filePath = '/magnetic/synapse_debug_data/block256.h5/cube'
    #rawInfo.filePath = '/magnetic/synapse_small_4d.h5/volume/data'
    rawInfo.filePath = '/magnetic/validation_slices_20_40_3200_4000_1200_2000.h5/volume/data'
    opRawDataSelection = workflow.rawDataSelectionApplet.topLevelOperator
    opRawDataSelection.Dataset.resize(1)
    opRawDataSelection.Dataset[0].setValue(rawInfo)

    predictionInfo = DatasetInfo()
    #predictionInfo.filePath = '/magnetic/synapse_debug_data/block256_spots_predictions.h5/cube'
    #predictionInfo.filePath = '/magnetic/synapse_small_4d_synapse_predictions.h5/volume/data'
    predictionInfo.filePath = '/magnetic/validation_slices_20_40_3200_4000_1200_2000_pred.h5/volume/data'
    opPredDataSelection = workflow.predictionSelectionApplet.topLevelOperator
    opPredDataSelection.Dataset.resize(1)
    opPredDataSelection.Dataset[0].setValue(predictionInfo)

    # Select the feature drawer
    shell.setSelectedAppletDrawer(2)

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
    def testBasic(self):
        graph = lazyflow.graph.Graph()
        reader = OperatorWrapper( OpDataSelection, graph=graph )
        reader.ProjectFile.setValue(self.projectFile)
        reader.WorkingDirectory.setValue( os.getcwd() )
        reader.ProjectDataGroup.setValue( 'DataSelection/local_data' )
        
        # Create a list of dataset infos . . .
        datasetInfos = []
        
        # npy
        info = DatasetInfo()
        # Will be read from the filesystem since the data won't be found in the project file.
        info.location = DatasetInfo.Location.ProjectInternal
        info.filePath = self.testNpyFileName
        info.internalPath = ""
        info.invertColors = False
        info.convertToGrayscale = False
        datasetInfos.append(info)
        
        # png
        info = DatasetInfo()
        info.location = DatasetInfo.Location.FileSystem
        info.filePath = self.testPngFileName
        info.internalPath = ""
        info.invertColors = False
        info.convertToGrayscale = False
        datasetInfos.append(info)

        reader.Dataset.setValues(datasetInfos)

        # Read the test files using the data selection operator and verify the contents
        npyData = reader.Image[0][...].wait()
        pngData = reader.Image[1][...].wait()

        # Check the file name output
        print reader.ImageName[0].value
        assert reader.ImageName[0].value == self.testNpyFileName
        assert reader.ImageName[1].value == self.testPngFileName

        # Check raw images
        assert npyData.shape == (10,11,1)
        for x in range(npyData.shape[0]):
            for y in range(npyData.shape[1]):
                assert npyData[x,y,0] == x+y
        
        assert pngData.shape == (100, 200, 3)
        for x in range(pngData.shape[0]):
            for y in range(pngData.shape[1]):
                for c in range(pngData.shape[2]):
                    assert pngData[x,y,c] == (x+y) % 256

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
    def test_real_data_source(self):
        graph = lazyflow.graph.Graph()
        reader = OperatorWrapper(OpDataSelection, graph=graph,
                                 operator_kwargs={'forceAxisOrder': False})
        reader.ProjectFile.setValue(self.projectFile)
        reader.WorkingDirectory.setValue(os.getcwd())
        reader.ProjectDataGroup.setValue('DataSelection/local_data')

        info = DatasetInfo()
        # Will be read from the filesystem since the data won't be found in the project file.
        info.location = DatasetInfo.Location.ProjectInternal
        info.filePath = self.testRawDataFileName
        info.internalPath = ""
        info.invertColors = False
        info.convertToGrayscale = False
        #Use real data source
        info.realDataSource = True

        reader.Dataset.setValues([info])

        # Read the test file using the data selection operator and verify the contents
        imgData = reader.Image[0][...].wait()

        assert imgData.shape == self.imgData.shape
        numpy.testing.assert_array_equal(imgData, self.imgData)

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
    def test_fake_data_source(self):
        graph = lazyflow.graph.Graph()
        reader = OperatorWrapper(OpDataSelection, graph=graph,
                                 operator_kwargs={'forceAxisOrder': False})
        reader.ProjectFile.setValue(self.projectFile)
        reader.WorkingDirectory.setValue(os.getcwd())
        reader.ProjectDataGroup.setValue('DataSelection/local_data')

        info = DatasetInfo()
        # Will be read from the filesystem since the data won't be found in the project file.
        info.location = DatasetInfo.Location.ProjectInternal
        info.filePath = self.testRawDataFileName
        info.internalPath = ""
        info.invertColors = False
        info.convertToGrayscale = False
        # Use *fake* data source
        info.realDataSource = False
        info.axistags = vigra.defaultAxistags('tczyx')
        info.laneShape = self.imgData.shape
        info.laneDtype = self.imgData.dtype

        reader.Dataset.setValues([info])

        # Verify that now data selection operator returns fake data
        # with expected shape and type
        imgData = reader.Image[0][...].wait()

        assert imgData.shape == self.imgData.shape
        assert imgData.dtype == self.imgData.dtype
        expected_fake_data = numpy.zeros(info.laneShape, dtype=info.laneDtype)
        numpy.testing.assert_array_equal(imgData, expected_fake_data)

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
    def testBasic3DcStackFromGlobString(self):
        """Test if stacked 2d 3-channel files are loaded correctly"""
        # For some reason vigra saves 2D+c data compressed in gifs, so skip!
        self.compressedExtensions.append('.gif')
        for fileName in self.imgFileNameGlobs2Dc:
            graph = lazyflow.graph.Graph()
            reader = OperatorWrapper(OpDataSelection, graph=graph, operator_kwargs={'forceAxisOrder': False})
            reader.ProjectFile.setValue(self.projectFile)
            reader.WorkingDirectory.setValue(os.getcwd())
            reader.ProjectDataGroup.setValue('DataSelection/local_data')

            info = DatasetInfo()
            # Will be read from the filesystem since the data won't be found in the project file.
            info.location = DatasetInfo.Location.ProjectInternal
            info.filePath = fileName
            info.internalPath = ""
            info.invertColors = False
            info.convertToGrayscale = False

            reader.Dataset.setValues([info])

            # Read the test files using the data selection operator and verify the contents
            imgData3Dc = reader.Image[0][...].wait()

            # Check the file name output
            assert reader.ImageName[0].value == fileName
            # Check raw images
            assert imgData3Dc.shape == self.imgData3Dc.shape, (imgData3Dc.shape, self.imgData3Dc.shape)
            # skip this if image was saved compressed:
            if any(x in fileName.lower() for x in self.compressedExtensions):
                print("Skipping raw comparison for compressed data: {}".format(fileName))
                continue
            numpy.testing.assert_array_equal(imgData3Dc, self.imgData3Dc)

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
    def testBasic3DWrongAxes(self):
        """Test if 3D file with intentionally wrong axes is rejected """
        for fileName in self.imgFileNames3D:
            graph = lazyflow.graph.Graph()
            reader = OperatorWrapper(OpDataSelection, graph=graph, operator_kwargs={'forceAxisOrder': False})
            reader.ProjectFile.setValue(self.projectFile)
            reader.WorkingDirectory.setValue(os.getcwd())
            reader.ProjectDataGroup.setValue('DataSelection/local_data')

            info = DatasetInfo()
            # Will be read from the filesystem since the data won't be found in the project file.
            info.location = DatasetInfo.Location.ProjectInternal
            info.filePath = fileName
            info.internalPath = ""
            info.invertColors = False
            info.convertToGrayscale = False
            info.axistags = vigra.defaultAxistags('tzyc')

            try:
                reader.Dataset.setValues([info])
                assert False, "Should have thrown an exception!"
            except DatasetConstraintError:
                pass
            except:
                assert False, "Should have thrown a DatasetConstraintError!"

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
    def testBasic3D(self):
        """Test if plane 2d files are loaded correctly"""
        for fileName in self.imgFileNames3D:
            graph = lazyflow.graph.Graph()
            reader = OperatorWrapper(OpDataSelection, graph=graph, operator_kwargs={'forceAxisOrder': False})
            reader.ProjectFile.setValue(self.projectFile)
            reader.WorkingDirectory.setValue(os.getcwd())
            reader.ProjectDataGroup.setValue('DataSelection/local_data')

            info = DatasetInfo()
            # Will be read from the filesystem since the data won't be found in the project file.
            info.location = DatasetInfo.Location.ProjectInternal
            info.filePath = fileName
            info.internalPath = ""
            info.invertColors = False
            info.convertToGrayscale = False

            reader.Dataset.setValues([info])

            # Read the test files using the data selection operator and verify the contents
            imgData3D = reader.Image[0][...].wait()

            # Check the file name output
            assert reader.ImageName[0].value == fileName
            # Check raw images
            assert imgData3D.shape == self.imgData3D.shape, (imgData3D.shape, self.imgData3D.shape)
            # skip this if image was saved compressed:
            numpy.testing.assert_array_equal(imgData3D, self.imgData3D)

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
    def testWeirdAxisInfos(self):
        """
        If we add a dataset that has the channel axis in the wrong place, 
        the operator should automatically transpose it to be last.
        """
        weirdAxisFilename = os.path.join(self.workingDir, 'WeirdAxes.npy')
        expected_data = numpy.random.random( (3,100,100) )
        numpy.save(weirdAxisFilename, expected_data)

        info = DatasetInfo()
        info.filePath = weirdAxisFilename
        info.axistags = vigra.defaultAxistags('cxy')
        
        graph = Graph()
        op = OpDataSelectionGroup(graph=graph, forceAxisOrder=False)
        op.WorkingDirectory.setValue( self.workingDir )
        op.DatasetRoles.setValue( ['RoleA'] )

        op.DatasetGroup.resize( 1 )
        op.DatasetGroup[0].setValue( info )

        assert op.ImageGroup[0].ready()
        
        data_from_op = op.ImageGroup[0][:].wait()
        
        assert data_from_op.dtype == expected_data.dtype 
        assert data_from_op.shape == expected_data.shape, (data_from_op.shape, expected_data.shape)
        assert (data_from_op == expected_data).all()

        # op.Image is a synonym for op.ImageGroup[0]
        assert op.Image.ready()
        assert (op.Image[:].wait() == expected_data).all()
        
        # Ensure that files opened by the inner operators are closed before we exit.
        op.DatasetGroup.resize(0)

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
        def impl():
            projFilePath = self.PROJECT_FILE
            shell = self.shell
            
            # New project
            shell.createAndLoadNewProject(projFilePath)
            workflow = shell.projectManager.workflow

            from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
            opDataSelection = workflow.dataSelectionApplet.topLevelOperator
            for i, dataFile in enumerate(self.SAMPLE_DATA):        
                # Add a file
                info = DatasetInfo()
                info.filePath = dataFile
                opDataSelection.Dataset.resize(i+1)
                opDataSelection.Dataset[i].setValue(info)
            
            # Set some features
            opFeatures = workflow.featureSelectionApplet.topLevelOperator
            opFeatures.FeatureIds.setValue( OpPixelFeaturesPresmoothed.DefaultFeatureIds )
            opFeatures.Scales.setValue( [0.3, 0.7, 1, 1.6, 3.5, 5.0, 10.0] )
            #                    sigma:   0.3    0.7    1.0    1.6    3.5    5.0   10.0
            selections = numpy.array( [[True, False, False, False, False, False, False],
                                       [True, False, False, False, False, False, False],
                                       [True, False, False, False, False, False, False],
                                       [False, False, False, False, False, False, False],
                                       [False, False, False, False, False, False, False],
                                       [False, False, False, False, False, False, False]] )
            opFeatures.SelectionMatrix.setValue(selections)
      
            # Save and close
            shell.projectManager.saveProject()
            shell.ensureNoCurrentProject(assertClean=True)

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
 def impl():
     projFilePath = self.PROJECT_FILE
 
     shell = self.shell
     workflow = self.workflow
     
     # New project
     shell.createAndLoadNewProject(projFilePath)
 
     # Add a file
     from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
     info = DatasetInfo()
     info.filePath = self.SAMPLE_DATA
     opDataSelection = workflow.dataSelectionApplet.topLevelOperator
     opDataSelection.Dataset.resize(1)
     opDataSelection.Dataset[0].setValue(info)
     
     # Set some features
     featureGui = workflow.featureSelectionApplet.gui
     opFeatures = workflow.featureSelectionApplet.topLevelOperator
     #                    sigma:   0.3    0.7    1.0    1.6    3.5    5.0   10.0
     selections = numpy.array( [[True, False, False, False, False, False, False],
                                [True, False, False, False, False, False, False],
                                [True, False, False, False, False, False, False],
                                [False, False, False, False, False, False, False],
                                [False, False, False, False, False, False, False],
                                [False, False, False, False, False, False, False]] )
     opFeatures.SelectionMatrix.setValue(selections)
 
     # Save and close
     shell.projectManager.saveProject()
     shell.ensureNoCurrentProject(assertClean=True)

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
def debug_with_new(shell, workflow):
    """
    (Function for debug and testing.)
    """
    projFilePath = "/magnetic/test_watershed_project.ilp"

    # New project
    shell.createAndLoadNewProject(projFilePath)

    # Add a file
    from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
    info = DatasetInfo()
    #info.filePath = '/magnetic/gigacube.h5'
    #info.filePath = '/magnetic/synapse_small.npy'
    info.filePath = '/magnetic/synapse_small.npy_results.h5'
    #info.filePath = '/magnetic/singleslice.h5'
    opDataSelection = workflow.dataSelectionApplet.topLevelOperator
    opDataSelection.Dataset.resize(1)
    opDataSelection.Dataset[0].setValue(info)

    # Select the watershed drawer
    shell.setSelectedAppletDrawer(1)

    # Save the project
    shell.onSaveProjectActionTriggered()

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
    def testBasic2D(self):
        """Test if plane 2d files are loaded correctly"""
        for fileName in self.imgFileNames2D:
            graph = lazyflow.graph.Graph()
            reader = OperatorWrapper(OpDataSelection, graph=graph)
            reader.ProjectFile.setValue(self.projectFile)
            reader.WorkingDirectory.setValue(os.getcwd())
            reader.ProjectDataGroup.setValue('DataSelection/local_data')

            info = DatasetInfo()
            # Will be read from the filesystem since the data won't be found in the project file.
            info.location = DatasetInfo.Location.ProjectInternal
            info.filePath = fileName
            info.internalPath = ""
            info.invertColors = False
            info.convertToGrayscale = False

            reader.Dataset.setValues([info])

            # Read the test files using the data selection operator and verify the contents
            imgData2D = reader.Image[0][...].wait()

            # Check the file name output
            assert reader.ImageName[0].value == fileName
            # Check raw images
            assert imgData2D.shape == self.imgData2D.shape
            # skip this if image was saved compressed:
            if any(x in fileName.lower() for x in self.compressedExtensions):
                print("Skipping raw comparison for compressed data: {}".format(fileName))
                continue
            numpy.testing.assert_array_equal(imgData2D, self.imgData2D)

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
        def impl():
            projFilePath = self.PROJECT_FILE
            shell = self.shell

            # New project
            shell.createAndLoadNewProject(projFilePath, self.workflowClass())
            workflow = shell.projectManager.workflow

            from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
            opDataSelection = workflow.dataSelectionApplet.topLevelOperator
            for i, dataFile in enumerate(self.SAMPLE_DATA):
                # Add a file
                info = DatasetInfo()

                info.filePath = dataFile


                opDataSelection.DatasetGroup.resize(i+1)
                opDataSelection.DatasetGroup[i][0].setValue(info)

            # Set some features
            opFeatures = workflow.featureSelectionApplet.topLevelOperator
            #                    sigma:   0.3    0.7    1.0    1.6    3.5    5.0   10.0
            selections = numpy.array( [[True, False, False, False, False, False, False],
                                       [True, False, False, False, False, False, False],
                                       [True, False, False, False, False, False, False],
                                       [False, False, False, False, False, False, False],
                                       [False, False, False, False, False, False, False],
                                       [False, False, False, False, False, False, False]] )
            opFeatures.SelectionMatrix.setValue(selections)

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
    def testProjectLocalData(self):
        graph = lazyflow.graph.Graph()
        reader = OperatorWrapper( OpDataSelection, graph=graph )
        reader.ProjectFile.setValue(self.projectFile)
        reader.WorkingDirectory.setValue( os.getcwd() )
        reader.ProjectDataGroup.setValue( 'DataSelection/local_data' )
        
        # Create a list of dataset infos . . .
        datasetInfos = []

        # From project
        info = DatasetInfo()
        info.location = DatasetInfo.Location.ProjectInternal
        info.filePath = "This string should be ignored..."
        info._datasetId = 'dataset1' # (Cheating a bit here...)
        info.invertColors = False
        info.convertToGrayscale = False
        datasetInfos.append(info)

        reader.Dataset.setValues(datasetInfos)

        projectInternalData = reader.Image[0][...].wait()
        
        assert projectInternalData.shape == self.pngData.shape
        assert (projectInternalData == self.pngData).all()

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import filePath [as 别名]
        def impl():
            projFilePath = self.PROJECT_FILE
        
            shell = self.shell
            
            # New project
            shell.createAndLoadNewProject(projFilePath)
            workflow = shell.projectManager.workflow
        
            # Add a file
            from ilastik.applets.dataSelection.opDataSelection import DatasetInfo
            info = DatasetInfo()
            info.filePath = self.SAMPLE_DATA
            opDataSelection = workflow.dataSelectionApplet.topLevelOperator
            opDataSelection.Dataset.resize(1)
            opDataSelection.Dataset[0].setValue(info)
            
            # Set some features
            opFeatures = workflow.featureSelectionApplet.topLevelOperator
            opFeatures.FeatureIds.setValue( OpPixelFeaturesPresmoothed.DefaultFeatureIds )
            opFeatures.Scales.setValue( [0.3, 0.7, 1, 1.6, 3.5, 5.0, 10.0] )
            #                    sigma:   0.3    0.7    1.0    1.6    3.5    5.0   10.0
            selections = numpy.array( [[True, True, True, True, True, True, False],
                                       [True, True, True, True, True, True, False],
                                       [True, True, True, True, True, True, False],
                                       [True, True, True, True, True, True, False],
                                       [True, True, True, True, True, True, False],
                                       [True, True, True, True, True, True, False]] )

            opFeatures.SelectionMatrix.setValue(selections)