Mercurial > repos > bgruening > cp_measure_granularity

annotate measure_granularity.xml @ 5:ac5bea85a391 draft

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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 7d7a519c3a2cc612d38695b335d0f6c75a099de3"
author bgruening
date Fri, 26 Feb 2021 14:13:40 +0000
parents 382413f8ec1d
children 2564f461de62
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1 <tool id="cp_measure_granularity" name="MeasureGranularity" version="@CP_VERSION@+galaxy@VERSION_SUFFIX@">
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2 <description>output spectra of size measurements of the textures</description>
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4 <macros>
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5 <import>macros.xml</import>
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6 <token name="@VERSION_SUFFIX@">0</token>
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7 </macros>
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9 <expand macro="py_requirements"/>
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10 <expand macro="cmd_modules" />
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12 <configfiles>
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13 <inputs name="inputs" />
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14 <configfile name="script_file">
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15 import json
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16 import sys
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17 import os
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19 FOURSPACES=@SPACES@
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21 input_json_path = sys.argv[1]
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22 input_pipeline= sys.argv[2]
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24 params = json.load(open(input_json_path, "r"))
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26 def writemg():
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27 _str = "\nMeasureGranularity:[module_num:%d|svn_version:\\'Unknown\\'|variable_revision_number:3|show_window:False|notes:\\x5B\\'PARAMS\\x3A\\', \\'- Radius\\', \'- Range\\'\\x5D|batch_state:array(\\x5B\\x5D, dtype=uint8)|enabled:True|wants_pause:False]\n" % new_count
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29 image_count = len(params['rpt_image'])
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31 _str += FOURSPACES + "Image count:%d\n" % image_count
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33 for img in params['rpt_image']:
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34 obj_count = len(img['rpt_object'])
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36 _str += FOURSPACES + "Object count:%d\n" % obj_count
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38 _str += FOURSPACES + "Select an image to measure:%s\n" % img['image_to_measure']
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40 _str += FOURSPACES + "Subsampling factor for granularity measurements:%s\n" % img['subsampling_factor_granularity']
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42 _str += FOURSPACES + "Subsampling factor for background reduction:%.2f\n" % img['subsampling_factor_background_reduction']
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44 _str += FOURSPACES + "Radius of structuring element:%d\n" % img['radius']
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45 _str += FOURSPACES + "Range of the granular spectrum:%d\n" % img['range_granular_spectrum']
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47 for obj in img['rpt_object']:
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48 _str += FOURSPACES + "Select objects to meausre:%s\n" % obj['object_to_measure']
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50 return _str
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52 with open(input_pipeline) as fin:
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53 lines = fin.readlines()
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55 k, v = lines[4].strip().split(':')
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57 module_count = int(v)
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58 new_count = module_count + 1
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59 lines[4] = k + ":%d\n" % new_count
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60 with open("output.cppipe", "w") as f:
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61 f.writelines(lines)
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62 f.write(writemg())
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63
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64 f.close()
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65 </configfile>
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66 </configfiles>
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68 <inputs>
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69 <expand macro="input_pipeline_param" />
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70 <repeat name="rpt_image" title="new image" min="1">
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71 <param name="image_to_measure" type="text" label="Enter the name of a greyscale image to measure">
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72 <expand macro="text_validator" />
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73 </param>
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75 <param name="subsampling_factor_granularity" type="float" value="0.25" label="Subsampling factor for granularity measurements" help="A factor lower than 1 if the textures of interest are larger than a few pixels. A factor greater than 1 might increase the accuracy but also require more processing time. Images are typically of higher resolution than is required for granularity measurements, so the default value is 0.25."/>
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77 <param name="subsampling_factor_background_reduction" type="float" value="0.25" min="0.125" max="0.25" label="Subsampling factor for background reduction" help="A small factor should be used if the structures of interest are large." />
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79 <param name="radius" type="integer" value="10" label="Radius of structuring element" help="This radius should correspond to the radius of the textures of interest after subsampling." />
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81 <param name="range_granular_spectrum" type="integer" value="16" label="Range of the granular spectrum" help="You may need a trial run to see which granular spectrum range yields informative measurements. Start by using a wide spectrum and narrow it down to the informative range to save time." />
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83 <repeat name="rpt_object" title="new object">
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84 <param name="object_to_measure" type="text" label="Enter the name of the object whose granularity will be measured" help="You can select objects from prior modules that identify objects, such as IdentifyPrimaryObjects. If you only want to measure the granularity for the image overall, you can remove all objects.">
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85 <expand macro="text_validator" />
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86 </param>
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87 </repeat>
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88 </repeat>
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89 </inputs>
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90
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91 <outputs>
3
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92 <expand macro="output_pipeline_param" />
0
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93 </outputs>
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94
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95 <tests>
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96 <test>
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97 <expand macro="test_input_pipeline_param" />
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98 <repeat name="rpt_image">
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99 <param name="image_to_measure" value="DNA" />
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100 <param name="subsampling_factor_granularity" value="0.25" />
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101 <param name="subsampling_factor_background_reduction" value="0.25" />
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102 <param name="radius" value="10" />
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103 <param name="range_granular_spectrum" value="16" />
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104 </repeat>
3
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105 <expand macro="test_out_file" file="measure_granularity.cppipe" />
0
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106 </test>
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107 </tests>
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108
3
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109 <help>
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110 <![CDATA[
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111
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112 .. class:: infomark
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113
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114 **What it does**
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115
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116 Image granularity is a texture measurement that tries to fit a series of structure elements of increasing size into the texture of the image and outputs a spectrum of measures based on how well they fit. Granularity is measured as described by Ilya Ravkin (in the paper *Bit representation techniques and image processing*). The size of the starting structure element as well as the range of the spectrum is given as input.
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117
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118 @COMMON_HELP@
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119 ]]>
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120 </help>
0
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121 <expand macro="citations" />
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122 </tool>