Mercurial > repos > bgruening > cp_measure_granularity
view test-data/tile.cppipe @ 4:a1a961c46d4b draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 35da2dcd86747c9bff138e100dbe08c6106f3780"
author | bgruening |
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date | Sat, 06 Feb 2021 10:09:33 +0000 |
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children | ac5bea85a391 |
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CellProfiler Pipeline: http://www.cellprofiler.org Version:3 DateRevision:319 GitHash: ModuleCount:5 HasImagePlaneDetails:False 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] : Filter images?:Images only Select the rule criteria:and (extension does isimage) (directory doesnot startwith ".") 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] Extract metadata?:Yes Metadata data type:Text Metadata types:{} Extraction method count:1 Metadata extraction method:Extract from file/folder names Metadata source:File name 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]+) Regular expression to extract from folder name:(?P<folderField1>.*) Extract metadata from:All images Select the filtering criteria:and (file does contain "") Metadata file location: Match file and image metadata:[] Use case insensitive matching?:No 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] Assign a name to:Images matching rules Select the image type:Grayscale image Name to assign these images:DNA Match metadata:[] Image set matching method:Order Set intensity range from:Image metadata Assignments count:1 Single images count:0 Maximum intensity:255.0 Process as 3D?:No Relative pixel spacing in X:1.0 Relative pixel spacing in Y:1.0 Relative pixel spacing in Z:1.0 Select the rule criteria:and (file does startwith "im") Name to assign these images:DNA Name to assign these objects:Cell Select the image type:Grayscale image Set intensity range from:Image metadata Select the image type:Grayscale image Maximum intensity:255.0 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] Do you want to group your images?:Yes grouping metadata count:1 Metadata category:field1 Tile:[module_num:5|svn_version:\'Unknown\'|variable_revision_number:1|show_window:True|notes:\x5B\'Tile the original color image, the outlined image and the image of tracked labels together.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select an input image:OrigColor Name the output image:AdjacentImage Tile assembly method:Within cycles Final number of rows:1 Final number of columns:12 Image corner to begin tiling:top left Direction to begin tiling:row Use meander mode?:No Automatically calculate number of rows?:No Automatically calculate number of columns?:Yes Select an additional image to tile:OutlineImage Select an additional image to tile:TrackedCells