Mercurial > repos > bgruening > cp_measure_image_intensity

annotate test-data/track_object_follow_neighbors.cppipe @ 5:8536b1ae0254 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 14:08:05 +0000
parents 5499dc6f8ac1
children
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5499dc6f8ac1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 35da2dcd86747c9bff138e100dbe08c6106f3780"
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1 CellProfiler Pipeline: http://www.cellprofiler.org
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2 Version:3
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3 DateRevision:319
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4 GitHash:
5499dc6f8ac1 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 35da2dcd86747c9bff138e100dbe08c6106f3780"
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5 ModuleCount:5
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6 HasImagePlaneDetails:False
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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.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False]
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9 :
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10 Filter images?:Images only
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11 Select the rule criteria:and (extension does isimage) (directory doesnot startwith ".")
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12
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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.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False]
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14 Extract metadata?:Yes
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15 Metadata data type:Text
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16 Metadata types:{}
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17 Extraction method count:1
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18 Metadata extraction method:Extract from file/folder names
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19 Metadata source:File name
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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]+)
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21 Regular expression to extract from folder name:(?P<folderField1>.*)
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22 Extract metadata from:All images
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23 Select the filtering criteria:and (file does contain "")
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24 Metadata file location:
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25 Match file and image metadata:[]
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26 Use case insensitive matching?:No
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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]
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29 Assign a name to:Images matching rules
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30 Select the image type:Grayscale image
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31 Name to assign these images:DNA
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32 Match metadata:[]
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33 Image set matching method:Order
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34 Set intensity range from:Image metadata
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35 Assignments count:1
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36 Single images count:0
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37 Maximum intensity:255.0
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38 Process as 3D?:No
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39 Relative pixel spacing in X:1.0
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40 Relative pixel spacing in Y:1.0
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41 Relative pixel spacing in Z:1.0
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42 Select the rule criteria:and (file does startwith "im")
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43 Name to assign these images:DNA
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44 Name to assign these objects:Cell
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45 Select the image type:Grayscale image
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46 Set intensity range from:Image metadata
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47 Select the image type:Grayscale image
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48 Maximum intensity:255.0
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49
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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]
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51 Do you want to group your images?:Yes
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52 grouping metadata count:1
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53 Metadata category:field1
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54
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55 TrackObjects:[module_num:5|svn_version:\'Unknown\'|variable_revision_number:7|show_window:True|notes:\x5B\'Track the embryos across images using the Overlap method\x3A tracked objects are identified by the amount of frame-to-frame overlap. Save an image of embryos labeled with a unique number across time.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False]
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56 Choose a tracking method:Follow Neighbors
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57 Select the objects to track:DNA
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58 Select object measurement to use for tracking:None
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59 Maximum pixel distance to consider matches:60
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60 Select display option:Color only
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61 Save color-coded image?:Yes
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62 Name the output image:OutputImage
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63 Select the movement model:Both
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64 Number of standard deviations for search radius:3.0
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65 Search radius limit, in pixel units (Min,Max):2.0,10.0
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66 Run the second phase of the LAP algorithm?:Yes
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67 Gap closing cost:40
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68 Split alternative cost:40
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69 Merge alternative cost:40
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70 Maximum gap displacement, in pixel units:5
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71 Maximum split score:50
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72 Maximum merge score:50
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73 Maximum temporal gap, in frames:5
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74 Filter objects by lifetime?:Yes
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75 Filter using a minimum lifetime?:No
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76 Minimum lifetime:1
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77 Filter using a maximum lifetime?:No
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78 Maximum lifetime:100
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79 Mitosis alternative cost:80
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80 Maximum mitosis distance, in pixel units:40
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81 Average cell diameter in pixels:36.0
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82 Use advanced configuration parameters:Yes
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83 Cost of cell to empty matching:11.0
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84 Weight of area difference in function matching cost:20.0