Mercurial > repos > bgruening > cp_gray_to_color
comparison test-data/ExampleHuman.cppipe @ 0:d37580e3f4d0 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 6d73056a625002d0275b5a9a90a9fae329ce47f1"
author | bgruening |
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date | Thu, 26 Mar 2020 17:46:36 -0400 |
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-1:000000000000 | 0:d37580e3f4d0 |
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1 CellProfiler Pipeline: http://www.cellprofiler.org | |
2 Version:3 | |
3 DateRevision:300 | |
4 GitHash: | |
5 ModuleCount:14 | |
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.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] | |
9 : | |
10 Filter images?:Images only | |
11 Select the rule criteria:and (extension does isimage) (directory doesnot containregexp "\x5B\\\\\\\\\\\\\\\\/\x5D\\\\\\\\.") | |
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.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] | |
14 Extract metadata?:No | |
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<Plate>.*)_(?P<Well>\x5BA-P\x5D\x5B0-9\x5D{2})_s(?P<Site>\x5B0-9\x5D)_w(?P<ChannelNumber>\x5B0-9\x5D) | |
21 Regular expression to extract from folder name:(?P<Date>\x5B0-9\x5D{4}_\x5B0-9\x5D{2}_\x5B0-9\x5D{2})$ | |
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:\x5B\x5D | |
26 Use case insensitive matching?:No | |
27 | |
28 NamesAndTypes:[module_num:3|svn_version:\'Unknown\'|variable_revision_number:8|show_window:False|notes:\x5B\'DNA\x3A DNA stained with DAPI\', \'PH3\x3A An antibody for phosphorylated histone H3 correlated with mitosis\', \'cellbody\x3A \'\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:\x5B\x5D | |
33 Image set matching method:Order | |
34 Set intensity range from:Image metadata | |
35 Assignments count:3 | |
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 contain "d0.tif") | |
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 Maximum intensity:255.0 | |
48 Select the rule criteria:and (file does contain "d1.tif") | |
49 Name to assign these images:PH3 | |
50 Name to assign these objects:Cell | |
51 Select the image type:Grayscale image | |
52 Set intensity range from:Image metadata | |
53 Maximum intensity:255.0 | |
54 Select the rule criteria:and (file does contain "d2.tif") | |
55 Name to assign these images:cellbody | |
56 Name to assign these objects:Cell | |
57 Select the image type:Grayscale image | |
58 Set intensity range from:Image metadata | |
59 Maximum intensity:255.0 | |
60 | |
61 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] | |
62 Do you want to group your images?:No | |
63 grouping metadata count:1 | |
64 Metadata category:None | |
65 | |
66 IdentifyPrimaryObjects:[module_num:5|svn_version:\'Unknown\'|variable_revision_number:13|show_window:True|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] | |
67 Select the input image:DNA | |
68 Name the primary objects to be identified:Nuclei | |
69 Typical diameter of objects, in pixel units (Min,Max):8,80 | |
70 Discard objects outside the diameter range?:Yes | |
71 Discard objects touching the border of the image?:Yes | |
72 Method to distinguish clumped objects:Intensity | |
73 Method to draw dividing lines between clumped objects:Intensity | |
74 Size of smoothing filter:10 | |
75 Suppress local maxima that are closer than this minimum allowed distance:7.0 | |
76 Speed up by using lower-resolution image to find local maxima?:Yes | |
77 Fill holes in identified objects?:After declumping only | |
78 Automatically calculate size of smoothing filter for declumping?:Yes | |
79 Automatically calculate minimum allowed distance between local maxima?:Yes | |
80 Handling of objects if excessive number of objects identified:Continue | |
81 Maximum number of objects:500 | |
82 Use advanced settings?:No | |
83 Threshold setting version:10 | |
84 Threshold strategy:Global | |
85 Thresholding method:Minimum cross entropy | |
86 Threshold smoothing scale:1.3488 | |
87 Threshold correction factor:1.0 | |
88 Lower and upper bounds on threshold:0.0,1.0 | |
89 Manual threshold:0.0 | |
90 Select the measurement to threshold with:None | |
91 Two-class or three-class thresholding?:Two classes | |
92 Assign pixels in the middle intensity class to the foreground or the background?:Foreground | |
93 Size of adaptive window:50 | |
94 Lower outlier fraction:0.05 | |
95 Upper outlier fraction:0.05 | |
96 Averaging method:Mean | |
97 Variance method:Standard deviation | |
98 # of deviations:2.0 | |
99 Thresholding method:Otsu | |
100 | |
101 IdentifyPrimaryObjects:[module_num:6|svn_version:\'Unknown\'|variable_revision_number:13|show_window:True|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] | |
102 Select the input image:PH3 | |
103 Name the primary objects to be identified:PH3 | |
104 Typical diameter of objects, in pixel units (Min,Max):8,80 | |
105 Discard objects outside the diameter range?:Yes | |
106 Discard objects touching the border of the image?:Yes | |
107 Method to distinguish clumped objects:Intensity | |
108 Method to draw dividing lines between clumped objects:Intensity | |
109 Size of smoothing filter:10 | |
110 Suppress local maxima that are closer than this minimum allowed distance:7.0 | |
111 Speed up by using lower-resolution image to find local maxima?:Yes | |
112 Fill holes in identified objects?:After declumping only | |
113 Automatically calculate size of smoothing filter for declumping?:Yes | |
114 Automatically calculate minimum allowed distance between local maxima?:Yes | |
115 Handling of objects if excessive number of objects identified:Continue | |
116 Maximum number of objects:500 | |
117 Use advanced settings?:No | |
118 Threshold setting version:10 | |
119 Threshold strategy:Global | |
120 Thresholding method:Minimum cross entropy | |
121 Threshold smoothing scale:1.3488 | |
122 Threshold correction factor:1.0 | |
123 Lower and upper bounds on threshold:0.0,1.0 | |
124 Manual threshold:0.0 | |
125 Select the measurement to threshold with:None | |
126 Two-class or three-class thresholding?:Two classes | |
127 Assign pixels in the middle intensity class to the foreground or the background?:Foreground | |
128 Size of adaptive window:50 | |
129 Lower outlier fraction:0.05 | |
130 Upper outlier fraction:0.05 | |
131 Averaging method:Mean | |
132 Variance method:Standard deviation | |
133 # of deviations:2.0 | |
134 Thresholding method:Otsu | |
135 | |
136 RelateObjects:[module_num:7|svn_version:\'Unknown\'|variable_revision_number:3|show_window:True|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] | |
137 Parent objects:Nuclei | |
138 Child objects:PH3 | |
139 Calculate child-parent distances?:None | |
140 Calculate per-parent means for all child measurements?:No | |
141 Calculate distances to other parents?:No | |
142 Parent name:None | |
143 | |
144 IdentifySecondaryObjects:[module_num:8|svn_version:\'Unknown\'|variable_revision_number:10|show_window:True|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] | |
145 Select the input objects:Nuclei | |
146 Name the objects to be identified:Cells | |
147 Select the method to identify the secondary objects:Propagation | |
148 Select the input image:cellbody | |
149 Number of pixels by which to expand the primary objects:10 | |
150 Regularization factor:0.05 | |
151 Discard secondary objects touching the border of the image?:No | |
152 Discard the associated primary objects?:No | |
153 Name the new primary objects:FilteredNuclei | |
154 Fill holes in identified objects?:Yes | |
155 Threshold setting version:10 | |
156 Threshold strategy:Global | |
157 Thresholding method:Otsu | |
158 Threshold smoothing scale:0.0 | |
159 Threshold correction factor:1.0 | |
160 Lower and upper bounds on threshold:0.0,1.0 | |
161 Manual threshold:0.0 | |
162 Select the measurement to threshold with:None | |
163 Two-class or three-class thresholding?:Three classes | |
164 Assign pixels in the middle intensity class to the foreground or the background?:Foreground | |
165 Size of adaptive window:50 | |
166 Lower outlier fraction:0.05 | |
167 Upper outlier fraction:0.05 | |
168 Averaging method:Mean | |
169 Variance method:Standard deviation | |
170 # of deviations:2.0 | |
171 Thresholding method:Otsu | |
172 | |
173 IdentifyTertiaryObjects:[module_num:9|svn_version:\'Unknown\'|variable_revision_number:3|show_window:True|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] | |
174 Select the larger identified objects:Cells | |
175 Select the smaller identified objects:Nuclei | |
176 Name the tertiary objects to be identified:Cytoplasm | |
177 Shrink smaller object prior to subtraction?:Yes | |
178 | |
179 MeasureObjectIntensity:[module_num:10|svn_version:\'Unknown\'|variable_revision_number:3|show_window:True|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] | |
180 Hidden:2 | |
181 Select an image to measure:DNA | |
182 Select an image to measure:PH3 | |
183 Select objects to measure:Nuclei | |
184 Select objects to measure:Cells | |
185 Select objects to measure:Cytoplasm | |
186 | |
187 MeasureObjectSizeShape:[module_num:11|svn_version:\'Unknown\'|variable_revision_number:1|show_window:True|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] | |
188 Select objects to measure:Nuclei | |
189 Select objects to measure:Cells | |
190 Select objects to measure:Cytoplasm | |
191 Calculate the Zernike features?:Yes | |
192 | |
193 OverlayOutlines:[module_num:12|svn_version:\'Unknown\'|variable_revision_number:4|show_window:True|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] | |
194 Display outlines on a blank image?:No | |
195 Select image on which to display outlines:DNA | |
196 Name the output image:OrigOverlay | |
197 Outline display mode:Color | |
198 Select method to determine brightness of outlines:Max of image | |
199 How to outline:Thick | |
200 Select outline color:#0080FF | |
201 Select objects to display:Cells | |
202 Select outline color:blue | |
203 Select objects to display:Nuclei | |
204 Select outline color:yellow | |
205 Select objects to display:PH3 | |
206 | |
207 SaveImages:[module_num:13|svn_version:\'Unknown\'|variable_revision_number:13|show_window:True|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] | |
208 Select the type of image to save:Image | |
209 Select the image to save:OrigOverlay | |
210 Select method for constructing file names:From image filename | |
211 Select image name for file prefix:DNA | |
212 Enter single file name:OrigBlue | |
213 Number of digits:4 | |
214 Append a suffix to the image file name?:Yes | |
215 Text to append to the image name:_Overlay | |
216 Saved file format:png | |
217 Output file location:Default Output Folder\x7C | |
218 Image bit depth:8-bit integer | |
219 Overwrite existing files without warning?:Yes | |
220 When to save:Every cycle | |
221 Record the file and path information to the saved image?:Yes | |
222 Create subfolders in the output folder?:No | |
223 Base image folder:Elsewhere...\x7C | |
224 | |
225 ExportToSpreadsheet:[module_num:14|svn_version:\'Unknown\'|variable_revision_number:12|show_window:True|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] | |
226 Select the column delimiter:Comma (",") | |
227 Add image metadata columns to your object data file?:No | |
228 Select the measurements to export:No | |
229 Calculate the per-image mean values for object measurements?:No | |
230 Calculate the per-image median values for object measurements?:No | |
231 Calculate the per-image standard deviation values for object measurements?:No | |
232 Output file location:Default Output Folder\x7C | |
233 Create a GenePattern GCT file?:No | |
234 Select source of sample row name:Metadata | |
235 Select the image to use as the identifier:None | |
236 Select the metadata to use as the identifier:None | |
237 Export all measurement types?:Yes | |
238 Press button to select measurements: | |
239 Representation of Nan/Inf:NaN | |
240 Add a prefix to file names?:No | |
241 Filename prefix:MyExpt_ | |
242 Overwrite existing files without warning?:Yes | |
243 Data to export:Do not use | |
244 Combine these object measurements with those of the previous object?:No | |
245 File name:DATA.csv | |
246 Use the object name for the file name?:Yes |