<tool id="ridge_filter_skimage" name="Apply ridge filter" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.05">
    <description>with scikit-image</description>
    <macros>
        <import>creators.xml</import>
        <import>tests.xml</import>
        <token name="@TOOL_VERSION@">0.22.0</token>
        <token name="@VERSION_SUFFIX@">1</token>
        <xml name="base_params">
            <param name="black_ridges" type="select" label="Mode of operation">
                <option value="true" selected="true">Enhance dark ridges (low image intensities)</option>
                <option value="false">Enhance bright ridges (high image intensities)</option>
            </param>
            <param name="sigma_min" type="float" value="1" min="0.1" label="Minimum sigma" help="Lower bound of the scale for multi-scale analysis."/>
            <param name="sigma_max" type="float" value="3" min="0.1" label="Maximum sigma" help="Upper bound of the scale for multi-scale analysis."/>
            <param name="num_sigma" type="integer" value="10" min="2" label="Number of sigma steps for multi-scale analysis"/>
        </xml>
        <xml name="frangi_params">
            <expand macro="base_params"/>
            <param name="alpha" type="float" min="0" value="0.5" label="Alpha"
                   help="Frangi correction constant that adjusts the filter's sensitivity to deviation from a plate-like structure."/>
            <param name="beta" type="float" min="0" value="0.5" label="Beta"
                   help="Frangi correction constant that adjusts the filter's sensitivity to deviation from a blob-like structure."/>
        </xml>
    </macros>
    <creator>
        <expand macro="creators/bmcv"/>
        <expand macro="creators/kostrykin"/>
    </creator>
    <edam_operations>
        <edam_operation>operation_3443</edam_operation>
    </edam_operations>
    <xrefs>
        <xref type="bio.tools">galaxy_image_analysis</xref>
        <xref type="bio.tools">scikit-image</xref>
        <xref type="biii">scikit-image</xref>
    </xrefs>
    <requirements>
        <requirement type="package" version="@TOOL_VERSION@">scikit-image</requirement>
        <requirement type="package" version="0.5.2">giatools</requirement>
    </requirements>
    <command detect_errors="aggressive"><![CDATA[

        python '$__tool_directory__/filter_skimage.py'

        '$input'
        '$output'
        '$params'

    ]]></command>
    <configfiles>
        <configfile name="params"><![CDATA[
            {

            #if $filter.filter_type == "frangi" or $filter.filter_type == "hessian" or $filter.filter_type == "meijering" or $filter.filter_type == "sato"
                "black_ridges": $filter.black_ridges,
                "sigma_min": $filter.sigma_min,
                "sigma_max": $filter.sigma_max,
                "num_sigma": $filter.num_sigma,
            #end if

            #if $filter.filter_type == "frangi" or $filter.filter_type == "hessian"
                "alpha": $filter.alpha,
                "beta": $filter.beta,
            #end if

            #if $filter.filter_type == "laplace"
                "ksize": $filter.ksize,
            #end if

                "dtype": "$dtype",
                "filter_type": "$filter.filter_type"

            }
        ]]></configfile>
    </configfiles>
    <inputs>
        <param name="input" type="data" format="tiff,png" label="Input image"/>
        <param name="dtype" type="select" label="Output pixel type"
               help="Data type used to store the pixel values in the output image.">
            <option value="float64" selected="True">64-bit floating point</option>
            <option value="float32">32-bit floating point</option>
            <option value="float16">16-bit floating point</option>
        </param>
        <conditional name="filter">
            <param name="filter_type" type="select" label="Filter">
                <option value="frangi" selected="True">Frangi vesselness filter</option>
                <option value="hessian">Hybrid Hessian filter</option>
                <option value="laplace">Laplace filter</option>
                <option value="meijering">Meijering neuriteness filter</option>
                <option value="sato">Sato tubeness filter</option>
            </param>
            <when value="frangi">
                <expand macro="frangi_params"/>
            </when>
            <when value="hessian">
                <expand macro="frangi_params"/>
            </when>
            <when value="laplace">
                <param name="ksize" type="integer" value="3" label="Kernel size"
                       help="Define the size of the discrete Laplacian operator such that it will have the size of a hypercube with this edge length (in pixels)."/>
            </when>
            <when value="meijering">
                <expand macro="base_params"/>
            </when>
            <when value="sato">
                <expand macro="base_params"/>
            </when>
        </conditional>
    </inputs>
    <outputs>
       <data format="tiff" name="output"/>
    </outputs>
    <tests>
        <!-- Single-image (Q), Single-frame (T), Single-slice (Z), multi-channel (C), Frangi (dark) -->
        <test>
            <param name="input" value="scikit-image/retina.png"/>
            <param name="dtype" value="float16"/>
            <conditional name="filter">
                <param name="filter_type" value="frangi"/>
                <param name="black_ridges" value="true"/>
                <param name="sigma_min" value="0.5"/>
                <param name="sigma_max" value="20"/>
                <param name="num_sigma" value="10"/>
                <param name="alpha" value="0.5"/>
                <param name="beta" value="0.5"/>
            </conditional>
            <expand macro="tests/intensity_image_diff" name="output" value="retina_frangi.tiff" ftype="tiff"/>
            <assert_stdout>
                <has_line line='Applying filter: "frangi"'/>
                <has_line line="Performing 2-D filtering"/>
            </assert_stdout>
        </test>
        <!-- Single-image (Q), Single-frame (T), Single-slice (Z), single-channel (C), Hessian (dark) -->
        <test>
            <param name="input" value="retina_0c_0z_0t_0q.tiff"/>
            <param name="dtype" value="float16"/>
            <conditional name="filter">
                <param name="filter_type" value="hessian"/>
                <param name="black_ridges" value="true"/>
                <param name="sigma_min" value="0.5"/>
                <param name="sigma_max" value="20"/>
                <param name="num_sigma" value="10"/>
                <param name="alpha" value="0.5"/>
                <param name="beta" value="0.5"/>
            </conditional>
            <expand macro="tests/intensity_image_diff" name="output" value="retina_0c_0z_0t_0q_hessian.tiff" ftype="tiff"/>
            <assert_stdout>
                <has_line line='Applying filter: "hessian"'/>
                <has_line line="Performing 2-D filtering"/>
            </assert_stdout>
        </test>
        <!-- Single-image (Q), Multi-frame (T), Single-slice (Z), single-channel (C), Meijering (dark) -->
        <test>
            <param name="input" value="retina_0c_0z_3t_0q.tiff"/>
            <param name="dtype" value="float16"/>
            <conditional name="filter">
                <param name="filter_type" value="meijering"/>
                <param name="black_ridges" value="true"/>
                <param name="sigma_min" value="0.5"/>
                <param name="sigma_max" value="20"/>
                <param name="num_sigma" value="10"/>
            </conditional>
            <expand macro="tests/intensity_image_diff" name="output" value="retina_0c_0z_3t_0q_meijering.tiff" ftype="tiff"/>
            <assert_stdout>
                <has_line line='Applying filter: "meijering"'/>
                <has_line line="Performing 2-D filtering"/>
            </assert_stdout>
        </test>
        <!-- Multi-image (Q), Single-frame (T), Single-slice (Z), single-channel (C), Sato (dark) -->
        <test>
            <param name="input" value="retina_0c_0z_0t_2q.tiff"/>
            <param name="dtype" value="float16"/>
            <conditional name="filter">
                <param name="filter_type" value="sato"/>
                <param name="black_ridges" value="true"/>
                <param name="sigma_min" value="0.5"/>
                <param name="sigma_max" value="20"/>
                <param name="num_sigma" value="10"/>
            </conditional>
            <expand macro="tests/intensity_image_diff" name="output" value="retina_0c_0z_0t_2q_sato.tiff" ftype="tiff"/>
            <assert_stdout>
                <has_line line='Applying filter: "sato"'/>
                <has_line line="Performing 2-D filtering"/>
            </assert_stdout>
        </test>
        <!-- Single-image (Q), Single-frame (T), Multi-slice (Z), single-channel (C), Laplace -->
        <test>
            <param name="input" value="retina_0c_5z_0t_0q.tiff"/>
            <param name="dtype" value="float16"/>
            <conditional name="filter">
                <param name="filter_type" value="laplace"/>
                <param name="ksize" value="5"/>
            </conditional>
            <expand macro="tests/intensity_image_diff" name="output" value="retina_0c_5z_0t_0q_laplace.tiff" ftype="tiff"/>
            <assert_stdout>
                <has_line line='Applying filter: "laplace"'/>
                <has_line line="Performing 3-D filtering"/>
            </assert_stdout>
        </test>
        <!-- Bright ridges, Single-image (Q), Single-frame (T), Multi-slice (Z), single-channel (C), Frangi (bright) -->
        <test>
            <param name="input" value="retina_inv_0c_0z_0t_0q.tiff"/>
            <param name="dtype" value="float16"/>
            <conditional name="filter">
                <param name="filter_type" value="frangi"/>
                <param name="black_ridges" value="false"/>
                <param name="sigma_min" value="0.5"/>
                <param name="sigma_max" value="20"/>
                <param name="num_sigma" value="10"/>
                <param name="alpha" value="0.5"/>
                <param name="beta" value="0.5"/>
            </conditional>
            <expand macro="tests/intensity_image_diff" name="output" value="retina_inv_0c_0z_0t_0q_frangi.tiff" ftype="tiff"/>
            <assert_stdout>
                <has_line line='Applying filter: "frangi"'/>
                <has_line line="Performing 2-D filtering"/>
            </assert_stdout>
        </test>
    </tests>
    <help>

**Applies a ridge filter to an image.**

Ridge filters can be used to detect ridge-like structures, such as neurites, tubes, vessels, wrinkles, or rivers. Different
ridge filters may be suited for detecting different structures, e.g., depending on contrast or noise level. 2-D and 3-D
images are supported. For multi-channel images, the filter is applied to all channels of the image. For time-series images,
the filter is also applied for all time steps.

Frangi vesselness filter
========================

Filter an image with the Frangi vesselness filter. This filter can be used to detect continuous ridges, e.g. vessels,
wrinkles, rivers. It can be used to calculate the fraction of the whole image containing such objects. Calculates the
eigenvalues of the Hessian to compute the similarity of an image region to vessels, according to the method described in
Frangi et al. (1998).

Hybrid Hessian filter 
=====================

Filter an image with the Hybrid Hessian filter (Schrijver 2001, Kroon 2009). This filter can be used to detect continuous
edges, e.g. vessels, wrinkles, rivers. It can be used to calculate the fraction of the whole image containing such objects.
Almost equal to Frangi filter, but uses alternative method of smoothing.

Laplace filter
==============

Find the edges of an image using the Laplace operator.

Meijering neuriteness filter
============================

Filter an image with the Meijering neuriteness filter. This filter can be used to detect continuous ridges, e.g. neurites,
wrinkles, rivers. It can be used to calculate the fraction of the whole image containing such objects. Calculates the
eigenvalues of the Hessian to compute the similarity of an image region to neurites, according to the method described in
Meijering et al. (2004).

Sato tubeness filter
====================

Filter an image with the Sato tubeness filter. This filter can be used to detect continuous ridges, e.g. tubes, wrinkles,
rivers. It can be used to calculate the fraction of the whole image containing such objects. Calculates the eigenvalues of
the Hessian to compute the similarity of an image region to tubes, according to the method described in Sato et al. (1998).

    </help>
    <citations>
       <citation type="doi">10.1007/BFb0056195</citation>
       <citation type="doi">10.1002/cyto.a.20022</citation>
       <citation type="doi">10.1016/S1361-8415(98)80009-1</citation>
    </citations>
</tool>