Mercurial > repos > bgruening > cp_measure_image_intensity

comparison test-data/enhance_or_suppress_features.cppipe @ 3:2681008d726f draft

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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit c3917e27eb1c1deeb381aa0dc8161c07699562fb"
author bgruening
date Mon, 11 May 2020 07:52:05 -0400
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children 8536b1ae0254
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2:20525bc7f6f4 3:2681008d726f
1 CellProfiler Pipeline: http://www.cellprofiler.org
2 Version:3
3 DateRevision:319
4 GitHash:
5 ModuleCount:5
6 HasImagePlaneDetails:False
7
8 Images:[module_num:1|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'To begin creating your project, use the Images module to compile a list of files and/or folders that you want to analyze. You can also specify a set of rules to include only the desired files in your selected folders.\']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
9 :
10 Filter images?:Images only
11 Select the rule criteria:and (extension does isimage) (directory doesnot startwith ".")
12
13 Metadata:[module_num:2|svn_version:\'Unknown\'|variable_revision_number:4|show_window:False|notes:\x5B\'The Metadata module optionally allows you to extract information describing your images (i.e, metadata) which will be stored along with your measurements. This information can be contained in the file name and/or location, or in an external file.\']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
14 Extract metadata?:Yes
15 Metadata data type:Text
16 Metadata types:{}
17 Extraction method count:1
18 Metadata extraction method:Extract from file/folder names
19 Metadata source:File name
20 Regular expression to extract from file name:(?P<field1>.*)_(?P<field2>[a-zA-Z0-9]+)_(?P<field3>[a-zA-Z0-9]+)_(?P<field4>[a-zA-Z0-9]+)
21 Regular expression to extract from folder name:(?P<folderField1>.*)
22 Extract metadata from:All images
23 Select the filtering criteria:and (file does contain "")
24 Metadata file location:
25 Match file and image metadata:[]
26 Use case insensitive matching?:No
27
28 NamesAndTypes:[module_num:3|svn_version:\'Unknown\'|variable_revision_number:8|show_window:False|notes:\x5B\'The NamesAndTypes module allows you to assign a meaningful name to each image by which other modules will refer to it.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False]
29 Assign a name to:Images matching rules
30 Select the image type:Grayscale image
31 Name to assign these images:DNA
32 Match metadata:[]
33 Image set matching method:Order
34 Set intensity range from:Image metadata
35 Assignments count:1
36 Single images count:0
37 Maximum intensity:255.0
38 Process as 3D?:No
39 Relative pixel spacing in X:1.0
40 Relative pixel spacing in Y:1.0
41 Relative pixel spacing in Z:1.0
42 Select the rule criteria:and (file does startwith "im")
43 Name to assign these images:DNA
44 Name to assign these objects:Cell
45 Select the image type:Grayscale image
46 Set intensity range from:Image metadata
47 Select the image type:Grayscale image
48 Maximum intensity:255.0
49
50 Groups:[module_num:4|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'The Groups module optionally allows you to split your list of images into image subsets (groups) which will be processed independently of each other. Examples of groupings include screening batches, microtiter plates, time-lapse movies, etc.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False]
51 Do you want to group your images?:Yes
52 grouping metadata count:1
53 Metadata category:field1
54
55 EnhanceOrSuppressFeatures:[module_num:5|svn_version:\'Unknown\'|variable_revision_number:6|show_window:False|notes:\x5B\'Identify nucleoli\', \'PARAMS\x3A Range of hole sizes'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False]
56 Select the input image:DNA
57 Name the output image:DNAdarkholes
58 Select the operation:Enhance
59 Feature size:10
60 Feature type:Dark holes
61 Range of hole sizes:1,15
62 Smoothing scale:2.0
63 Shear angle:0.0
64 Decay:0.95
65 Enhancement method:Tubeness
66 Speed and accuracy:Fast