Module Expr Str Import alias identifier ImportFrom alias alias alias ImportFrom alias alias ImportFrom alias alias ImportFrom alias alias ImportFrom alias Import alias identifier Import alias identifier Import alias identifier ImportFrom alias alias Assign NameStore Str Assign NameStore Str Assign NameStore Str Assign NameStore Str Assign NameStore Str Assign NameStore Str Assign NameStore Str Assign NameStore Str Assign NameStore Str Assign NameStore Str Assign NameStore Str Assign NameStore Str ClassDef bases AttributeLoad NameLoad attr body Assign NameStore Str Assign NameStore Str Assign NameStore Num FunctionDef arguments args NameParam defaults body Assign AttributeStore NameLoad attr Call AttributeLoad NameLoad attr Str AttributeLoad NameLoad attr keyword Str Assign AttributeStore NameLoad attr Call AttributeLoad NameLoad attr Str Str keyword Str Assign AttributeStore NameLoad attr Call AttributeLoad NameLoad attr Str ListLoad NameLoad NameLoad keyword BinOpMod Str Call NameLoad 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NameLoad attr NameLoad body AugAssignAdd NameStore ListLoad AttributeLoad NameLoad attr orelse If CompareEq AttributeLoad NameLoad attr NameLoad body AugAssignAdd NameStore ListLoad AttributeLoad NameLoad attr AttributeLoad NameLoad attr AttributeLoad NameLoad attr orelse If CompareEq AttributeLoad NameLoad attr NameLoad body AugAssignAdd NameStore ListLoad AttributeLoad NameLoad attr If CompareEq AttributeLoad NameLoad attr NameLoad body AugAssignAdd NameStore ListLoad AttributeLoad NameLoad attr orelse AugAssignAdd NameStore ListLoad AttributeLoad NameLoad attr orelse If CompareEq AttributeLoad NameLoad attr NameLoad body AugAssignAdd NameStore ListLoad AttributeLoad NameLoad attr AttributeLoad NameLoad attr Assign AttributeStore AttributeLoad NameLoad attr attr Num orelse AugAssignAdd NameStore ListLoad AttributeLoad NameLoad attr orelse AugAssignAdd NameStore ListLoad AttributeLoad NameLoad attr Return NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr AttributeLoad AttributeLoad NameLoad attr attr keyword NameLoad Assign NameStore BinOpDiv BinOpSub Call NameLoad AttributeLoad AttributeLoad NameLoad attr attr Num Num Assign NameStore IfExp AttributeLoad NameLoad attr AttributeLoad NameLoad attr NameLoad Assign NameStore AttributeLoad NameLoad attr If CompareEq AttributeLoad NameLoad attr NameLoad body If CompareEq AttributeLoad NameLoad attr NameLoad body If BoolOpOr CompareEq AttributeLoad NameLoad attr NameLoad CompareLtE NameLoad Num body Assign NameStore Call NameLoad NameLoad NameLoad NameLoad orelse Assign NameStore BinOpSub NameLoad Call NameLoad Call NameLoad NameLoad NameLoad NameLoad keyword Num NameLoad NameLoad keyword Num If CompareIsNot NameLoad NameLoad body Assign SubscriptStore NameLoad Index UnaryOpInvert NameLoad SubscriptLoad NameLoad Index UnaryOpInvert NameLoad orelse If CompareEq AttributeLoad NameLoad attr NameLoad body If CompareEq AttributeLoad NameLoad attr NameLoad body Assign NameStore BinOpSub BinOpSub BinOpMult Num NameLoad Call NameLoad NameLoad NameLoad NameLoad Call NameLoad NameLoad NameLoad NameLoad Assign SubscriptStore NameLoad Index CompareGt NameLoad Num Num Assign SubscriptStore NameLoad Index CompareLt NameLoad Num Num orelse Assign NameStore AttributeLoad AttributeLoad NameLoad attr attr Assign NameStore Call NameLoad NameLoad NameLoad Assign NameStore Call NameLoad NameLoad keyword NameLoad keyword NameLoad Assign NameStore BinOpMult BinOpMult BinOpMult UnaryOpUSub SubscriptLoad NameLoad ExtSlice Slice Slice Index Num CompareLt SubscriptLoad NameLoad ExtSlice Slice Slice Index Num Num NameLoad NameLoad If AttributeLoad NameLoad attr body Assign SubscriptStore NameLoad Index UnaryOpInvert NameLoad SubscriptLoad NameLoad Index UnaryOpInvert NameLoad orelse If CompareEq AttributeLoad NameLoad attr NameLoad body Assign NameStore Call NameLoad Num Call NameLoad BinOpDiv AttributeLoad AttributeLoad 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AttributeLoad AttributeLoad NameLoad attr attr keyword Call AttributeLoad NameLoad attr Num Num decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam defaults body Expr Str If BoolOpAnd UnaryOpNot NameLoad CompareEq NameLoad Num body Assign NameStore BinOpAdd NameLoad ListLoad NameLoad Str Assign NameStore Num If BoolOpAnd UnaryOpNot NameLoad CompareEq NameLoad Num body Assign NameStore BinOpAdd NameLoad ListLoad Str Str Str Assign NameStore Num If BoolOpAnd UnaryOpNot NameLoad CompareEq NameLoad Num body Assign NameStore BinOpAdd NameLoad ListLoad NameLoad Assign NameStore Num If BoolOpAnd UnaryOpNot NameLoad CompareEq NameLoad Num body Assign NameStore BinOpAdd NameLoad ListLoad NameLoad Assign NameStore Num Return TupleLoad NameLoad NameLoad NameLoad decorator_list decorator_list Assign NameStore NameLoad
N/A N/A <b>Enhance Or Suppress Features</b> enhances or suppresses certain image features 
(such as speckles, ring shapes, and neurites), which can improve subsequent
identification of objects.
<hr>
This module enhances or suppresses the intensity of certain pixels relative
to the rest of the image, by applying image processing filters to the image. It
produces a grayscale image in which objects can be identified using an <b>Identify</b> module.
 N/A numpy np centrosome.cpmorphology opening closing white_tophat centrosome.filter enhance_dark_holes circular_hough centrosome.filter hessian median_filter centrosome.filter variance_transform line_integration scipy.ndimage gaussian_filter N/A cellprofiler.cpimage cpi N/A cellprofiler.cpmodule cpm N/A cellprofiler.settings cps cellprofiler.gui.help HELP_ON_MEASURING_DISTANCES PROTIP_AVOID_ICON N/A ENHANCE Enhance N/A SUPPRESS Suppress N/A E_SPECKLES Speckles N/A E_NEURITES Neurites N/A E_DARK_HOLES Dark holes N/A E_CIRCLES Circles N/A E_TEXTURE Texture N/A E_DIC DIC N/A S_FAST Fast / hexagonal N/A S_SLOW Slow / circular N/A N_GRADIENT Line structures N/A N_TUBENESS Tubeness EnhanceOrSuppressFeatures N/A N/A cpm CPModule N/A N/A module_name EnhanceOrSuppressFeatures N/A category Image Processing N/A variable_revision_number 5 create_settings N/A N/A self N/A N/A N/A N/A self image_name N/A N/A cps ImageNameSubscriber Select the input image N/A cps NONE doc 
            Select the image with features to be enhanced or suppressed. N/A N/A self filtered_image_name N/A N/A cps ImageNameProvider Name the output image FilteredBlue doc 
            Enter a name for the feature-enhanced or suppressed image. N/A N/A self method N/A N/A cps Choice Select the operation N/A ENHANCE SUPPRESS doc N/A 
            Select whether you want to enhance or suppress the features you designated.
            <ul>
            <li><i>%(ENHANCE)s:</i> Produce an image whose intensity is largely
            composed of the features of interest.</li>
            <li <i>%(SUPPRESS)s:</i> Produce an image with the features largely
            removed.</li>
            </ul> N/A globals N/A N/A self enhance_method N/A N/A cps Choice Feature type N/A E_SPECKLES E_NEURITES E_DARK_HOLES E_CIRCLES E_TEXTURE E_DIC doc N/A 
            <i>(Used only if %(ENHANCE)s is selected)</i><br>
            This module can enhance three kinds of image intensity features:
            <ul>
            <li><i>%(E_SPECKLES)s:</i> A speckle is an area of enhanced intensity
            relative to its immediate neighborhood. The module enhances
            speckles using a white tophat filter, which is the image minus the
            morphological grayscale opening of the image. The opening operation
            first suppresses the speckles by applying a grayscale erosion to reduce everything
            within a given radius to the lowest value within that radius, then uses
            a grayscale dilation to restore objects larger than the radius to an
            approximation of their former shape. The white tophat filter enhances
            speckles by subtracting the effects of opening from the original image.
            </li>
            <li><i>%(E_NEURITES)s:</i> Neurites are taken to be long, thin features
            of enhanced intensity. Choose this option to enhance the intensity
            of the neurites using the %(N_GRADIENT)s or %(N_TUBENESS)s methods
            described below.</li>
            <li><i>%(E_DARK_HOLES)s:</i> The module uses morphological reconstruction
            (the rolling-ball algorithm) to identify dark holes within brighter
            areas, or brighter ring shapes. The image is inverted so that the dark holes turn into
            bright peaks. The image is successively eroded and the eroded image
            is reconstructed at each step, resulting in an image which is
            missing the peaks. Finally, the reconstructed image is subtracted
            from the previous reconstructed image. This leaves circular bright
            spots with a radius equal to the number of iterations performed.
            </li>
            <li><i>%(E_CIRCLES)s:</i> The module calculates the circular Hough transform of
            the image at the diameter given by the feature size. The Hough transform
            will have the highest intensity at points that are centered within a ring
            of high intensity pixels where the ring diameter is the feature size. You
            may want to use the <b>EnhanceEdges</b> module to find the edges of your
            circular object and then process the output by enhancing circles. You can
            use <b>IdentifyPrimaryObjects</b> to find the circle centers and then use
            these centers as seeds in <b>IdentifySecondaryObjects</b> to find whole,
            circular objects using a watershed.</li>
            <li><i>%(E_TEXTURE)s:</i> <b>EnanceOrSuppressFeatures</b> produces an image
            whose intensity is the variance among nearby pixels. This method weights
            pixel contributions by distance using a Gaussian to calculate the weighting.
            You can use this method to separate foreground from background if the foreground
            is textured and the background is not.
            </li>
            <li><i>%(E_DIC)s:</i> This method recovers the optical density of a DIC image by
            integrating in a direction perpendicular to the shear direction of the image.
            </li>
            </ul>
            In addition, this module enables you to suppress certain features (such as speckles)
            by specifying the feature size. N/A globals N/A N/A self object_size N/A N/A cps Integer Feature size 10 2 doc N/A 
            <i>(Used only if circles, speckles or neurites are selected, or if suppressing features)</i><br>
            Enter the diameter of the largest speckle, the width of the circle
            or the width of the neurites to be enhanced or suppressed, which
            will be used to calculate an adequate filter size. %(HELP_ON_MEASURING_DISTANCES)s N/A globals N/A N/A self hole_size N/A N/A cps IntegerRange Range of hole sizes value N/A 1 10 minval 1 doc N/A 
            <i>(Used only if %(E_DARK_HOLES)s is selected)</i><br>
            The range of hole sizes to be enhanced. The algorithm will
            identify only holes whose diameters fall between these two
            values. N/A globals N/A N/A self smoothing N/A N/A cps Float Smoothing scale value 2.0 minval 0 doc N/A 
            <i>(Used only for the %(E_TEXTURE)s, %(E_DIC)s or %(E_NEURITES)s methods)</i><br>
            <ul>
            <li><i>%(E_TEXTURE)s</i>: This is the scale of the texture features, roughly
            in pixels. The algorithm uses the smoothing value entered as
            the sigma of the Gaussian used to weight nearby pixels by distance
            in the variance calculation.</li>
            <li><i>%(E_DIC)s:</i> Specifies the amount of smoothing of the image in the direction parallel to the
            shear axis of the image. The line integration method will leave
            streaks in the image without smoothing as it encounters noisy
            pixels during the course of the integration. The smoothing takes
            contributions from nearby pixels which decreases the noise but
            smooths the resulting image. </li>
            <li><i>%(E_DIC)s:</i> Increase the smoothing to
            eliminate streakiness and decrease the smoothing to sharpen
            the image.</li>
            <li><i>%(E_NEURITES)s:</i> The <i>%(N_TUBENESS)s</i> option uses this scale
            as the sigma of the Gaussian used to smooth the image prior to
            gradient detection.</li>
            </ul>
            <img src="memory:%(PROTIP_AVOID_ICON)s">&nbsp;
            Smoothing can be turned off by entering a value of zero, but this
            is not recommended. N/A globals N/A N/A self angle N/A N/A cps Float Shear angle value 0 doc N/A 
            <i>(Used only for the %(E_DIC)s method)</i><br>
            The shear angle is the direction of constant value for the
            shadows and highlights in a DIC image. The gradients in a DIC
            image run in the direction perpendicular to the shear angle.
            For example, if the shadows run diagonally from lower left
            to upper right and the highlights appear above the shadows,
            the shear angle is 45&deg;. If the shadows appear on top,
            the shear angle is 180&deg; + 45&deg; = 225&deg;.
             N/A globals N/A N/A self decay N/A N/A cps Float Decay value 0.95 minval 0.1 maxval 1 doc N/A <i>(Used only for the %(E_DIC)s method)</i><br>
                The decay setting applies an exponential decay during the process
                of integration by multiplying the accumulated sum by the decay
                at each step. This lets the integration recover from accumulated
                error during the course of the integration, but it also results
                in diminished intensities in the middle of large objects.
                Set the decay to a large value, on the order of 1 - 1/diameter
                of your objects if the intensities decrease toward the middle.
                Set the decay to a small value if there appears to be a bias
                in the integration direction. N/A globals N/A N/A self neurite_choice N/A N/A cps Choice Enhancement method N/A N_TUBENESS N_GRADIENT doc N/A 
            <i>(Used only for the %(E_NEURITES)s method)</i><br>
            Two methods can be used to enhance neurites:<br>
            <ul>
            <li><i>%(N_TUBENESS)s</i>: This method is an adaptation of
            the method used by the <a href="http://www.longair.net/edinburgh/imagej/tubeness/">
            ImageJ Tubeness plugin</a>. The image
            is smoothed with a Gaussian. The Hessian is then computed at every
            point to measure the intensity gradient and the eigenvalues of the
            Hessian are computed to determine the magnitude of the intensity.
            The absolute maximum of the two eigenvalues gives a measure of
            the ratio of the intensity of the gradient in the direction of
            its most rapid descent versus in the orthogonal direction. The
            output image is the absolute magnitude of the highest eigenvalue
            if that eigenvalue is negative (white neurite on dark background),
            otherwise, zero.</li>
            <li><i>%(N_GRADIENT)s</i>: The module takes the difference of the
            white and black tophat filters (a white tophat filtering is the image minus
            the morphological grayscale opening of the image; a black tophat filtering is the
            morphological grayscale closing of the image minus the image).
            The effect is to enhance lines whose width is the "feature size".</li>
            </ul> N/A globals N/A N/A self speckle_accuracy N/A N/A cps Choice Speed and accuracy choices N/A S_FAST S_SLOW doc N/A 
            <i>(Used only for the %(E_SPECKLES)s method)</i><br>
            <i>%(E_SPECKLES)s</i> can use a fast or slow algorithm to find
            speckles.
            <ul>
            <li><i>%(S_FAST)s:</i> Select this option for speckles that have a large
            radius (greater than 10 pixels) and need not be exactly circular.</li>
            <li><i>%(S_SLOW)s:</i> Use for speckles of small radius or to
            maintain backwards compatibility with previous versions of
            CellProfiler.</li>
            </ul>
             N/A globals N/A settings N/A N/A self N/A N/A N/A N/A N/A self image_name N/A self filtered_image_name N/A self method N/A self object_size N/A self enhance_method N/A self hole_size N/A self smoothing N/A self angle N/A self decay N/A self neurite_choice N/A self speckle_accuracy N/A visible_settings N/A N/A self N/A N/A N/A result N/A N/A self image_name N/A self filtered_image_name N/A self method N/A N/A N/A self method ENHANCE N/A N/A result N/A N/A self enhance_method N/A N/A N/A self object_size min_value 2 N/A N/A N/A self enhance_method E_DARK_HOLES N/A N/A result N/A N/A self hole_size N/A N/A N/A N/A self enhance_method E_TEXTURE N/A N/A result N/A N/A self smoothing N/A N/A N/A N/A self enhance_method E_DIC N/A N/A result N/A N/A self smoothing N/A self angle N/A self decay N/A N/A N/A N/A self enhance_method E_NEURITES N/A N/A result N/A N/A self neurite_choice N/A N/A N/A self neurite_choice N_GRADIENT N/A N/A result N/A N/A self object_size N/A N/A result N/A N/A self smoothing N/A N/A N/A N/A self enhance_method E_SPECKLES N/A N/A result N/A N/A self object_size N/A self speckle_accuracy N/A N/A N/A self object_size min_value 3 N/A N/A result N/A N/A self object_size N/A N/A result N/A N/A self object_size N/A result N/A run N/A N/A self workspace N/A N/A N/A image N/A N/A N/A workspace image_set get_image N/A N/A self image_name value must_be_grayscale True N/A radius N/A N/A N/A float N/A N/A self object_size value 1.0 2.0 N/A mask N/A N/A image has_mask N/A image mask None N/A pixel_data N/A image pixel_data N/A N/A N/A self method ENHANCE N/A N/A N/A N/A self enhance_method E_SPECKLES N/A N/A N/A N/A N/A self speckle_accuracy S_SLOW N/A radius 3 N/A N/A result N/A white_tophat pixel_data radius mask N/A N/A result N/A pixel_data N/A median_filter N/A median_filter pixel_data mask radius percent 0 mask radius percent 100 N/A N/A mask None N/A N/A N/A result N/A N/A mask N/A pixel_data N/A N/A mask N/A N/A N/A N/A self enhance_method E_NEURITES N/A N/A N/A N/A self neurite_choice N_GRADIENT N/A N/A result N/A N/A N/A 3 pixel_data N/A opening pixel_data radius mask N/A closing pixel_data radius mask N/A N/A result N/A N/A result 1 1 N/A N/A result N/A N/A result 0 0 N/A N/A sigma N/A N/A self smoothing value N/A smoothed N/A gaussian_filter pixel_data sigma N/A L N/A hessian smoothed return_hessian False return_eigenvectors False N/A result N/A N/A N/A N/A N/A L N/A N/A N/A N/A 0 N/A N/A L N/A N/A N/A N/A 0 0 sigma sigma N/A N/A image has_mask N/A N/A N/A result N/A N/A mask N/A pixel_data N/A N/A mask N/A N/A N/A N/A self enhance_method E_DARK_HOLES N/A N/A min_radius N/A max 1 N/A int N/A N/A N/A self hole_size min 2 N/A max_radius N/A int N/A N/A N/A N/A self hole_size max 1 2 N/A result N/A enhance_dark_holes pixel_data min_radius max_radius mask N/A N/A N/A N/A self enhance_method E_CIRCLES N/A N/A result N/A circular_hough pixel_data N/A radius 0.5 mask mask N/A N/A N/A N/A self enhance_method E_TEXTURE N/A N/A result N/A variance_transform pixel_data N/A N/A self smoothing value mask mask N/A N/A N/A N/A self enhance_method E_DIC N/A N/A result N/A line_integration pixel_data N/A N/A self angle value N/A N/A self decay value N/A N/A self smoothing value N/A N/A N/A NotImplementedError N/A Unimplemented enhance method: %s N/A N/A self enhance_method value N/A N/A N/A N/A self method SUPPRESS N/A N/A N/A image has_mask N/A N/A result N/A opening N/A image pixel_data radius N/A image mask N/A N/A result N/A opening N/A image pixel_data radius N/A N/A N/A ValueError N/A Unknown filtering method: %s N/A self method N/A result_image N/A N/A cpi Image result parent_image image N/A N/A N/A N/A workspace image_set add N/A N/A self filtered_image_name value result_image N/A N/A self show_window N/A N/A N/A N/A workspace display_data image N/A image pixel_data N/A N/A N/A workspace display_data result result N/A display N/A N/A self workspace figure N/A N/A N/A image N/A N/A workspace display_data image N/A result N/A N/A workspace display_data result N/A N/A N/A figure set_subplots N/A 2 1 N/A N/A N/A figure subplot_imshow_grayscale 0 0 image N/A Original: %s N/A N/A self image_name value N/A N/A N/A figure subplot_imshow_grayscale 1 0 result N/A Filtered: %s N/A N/A self filtered_image_name value sharexy N/A N/A figure subplot 0 0 N/A upgrade_settings N/A N/A self setting_values variable_revision_number module_name from_matlab N/A N/A N/A Adjust setting values if they came from a previous revision

        setting_values - a sequence of strings representing the settings
                         for the module as stored in the pipeline
        variable_revision_number - the variable revision number of the
                         module at the time the pipeline was saved. Use this
                         to determine how the incoming setting values map
                         to those of the current module version.
        module_name - the name of the module that did the saving. This can be
                      used to import the settings from another module if
                      that module was merged into the current module
        from_matlab - True if the settings came from a Matlab pipeline, False
                      if the settings are from a CellProfiler 2.0 pipeline.

        Overriding modules should return a tuple of setting_values,
        variable_revision_number and True if upgraded to CP 2.0, otherwise
        they should leave things as-is so that the caller can report
        an error.
         N/A N/A N/A from_matlab N/A variable_revision_number 1 N/A N/A setting_values N/A setting_values N/A E_SPECKLES 1,10 N/A variable_revision_number 2 N/A N/A N/A from_matlab N/A variable_revision_number 2 N/A N/A setting_values N/A setting_values N/A 2.0 0 .95 N/A variable_revision_number 3 N/A N/A N/A from_matlab N/A variable_revision_number 3 N/A N/A setting_values N/A setting_values N/A N_GRADIENT N/A variable_revision_number 4 N/A N/A N/A from_matlab N/A variable_revision_number 4 N/A N/A setting_values N/A setting_values N/A S_SLOW N/A variable_revision_number 5 N/A N/A setting_values variable_revision_number from_matlab N/A N/A N/A EnhanceOrSuppressSpeckles EnhanceOrSuppressFeatures