Mercurial > repos > bgruening > cp_common

comparison starting_modules.py @ 3:27396311a314 draft

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit c3917e27eb1c1deeb381aa0dc8161c07699562fb"
author bgruening
date Mon, 11 May 2020 07:45:07 -0400
parents
children e7273daa5ae2
comparison
equal deleted inserted replaced
2:3c3cd68d6d5a 3:27396311a314
1 import json
2 import sys
3 import os
4
5 FOURSPACES = " "
6
7 input_json_path = sys.argv[1]
8
9 params = json.load(open(input_json_path, "r"))
10
11
12 def write_images():
13 filter_images = params['images']['filter_images']
14
15 _str = "\nImages:[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]\n"
16 _str += FOURSPACES+":\n"
17 _str += FOURSPACES + "Filter images?:%s\n" % filter_images
18 _str += FOURSPACES + "Select the rule criteria:and (extension does isimage) (directory doesnot startwith \".\")\n"
19
20 return _str
21
22
23 def write_metadata():
24 metadata_extraction = params['metadata']['con_metadata_extraction']
25 extract = metadata_extraction['extract']
26
27 if 'extraction_method' in metadata_extraction:
28 method_count = len(metadata_extraction['extraction_method'])
29 else:
30 method_count = 1
31
32 _str = "\nMetadata:[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]\n"
33 _str += FOURSPACES + "Extract metadata?:%s\n" % extract
34
35 if extract == "No":
36 _str += FOURSPACES + "Metadata data type:Text\n"
37 _str += FOURSPACES + "Metadata types:{}\n"
38 _str += FOURSPACES + "Extraction method count:%d\n" % method_count
39 _str += FOURSPACES + "Metadata extraction method:Extract from file/folder names\n"
40 _str += FOURSPACES + "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)\n"
41 _str += FOURSPACES + "Regular expression to extract from folder name:(?P<Date>\x5B0-9\x5D{4}_\x5B0-9\x5D{2}_\x5B0-9\x5D{2})$\n"
42 _str += FOURSPACES + "Extract metadata from:All images\n"
43 _str += FOURSPACES + "Select the filtering criteria:and (file does contain \"\")\n"
44 _str += FOURSPACES + "Metadata file location:\n"
45 _str += FOURSPACES + "Match file and image metadata:\x5B\x5D\n"
46 _str += FOURSPACES + "Use case insensitive matching?:No\n"
47 else:
48 _str += FOURSPACES + "Metadata data type:Text\n" #default Text,not possible to select in Galaxy
49 _str += FOURSPACES + "Metadata types:{}\n"
50 _str += FOURSPACES + "Extraction method count:%d\n" % method_count
51
52 for methods in metadata_extraction["extraction_method"]:
53 _str += FOURSPACES + "Metadata extraction method:%s\n" % methods["metadata_extraction_method"]
54 _str += FOURSPACES + "Metadata source:%s\n" % methods["con_metadata_source"]["metadata_source"]
55
56 if "file_name_regex" in methods["con_metadata_source"]:
57 file_regex = methods["con_metadata_source"]["file_name_regex"]
58 folder_regex = "(?P<folderField1>.*)"
59 elif "folder_name_regex" in methods["con_metadata_source"]:
60 file_regex = "(?P<field1>.*)_(?P<field2>[a-zA-Z0-9]+)"
61 folder_regex = methods["con_metadata_source"]["folder_name_regex"]
62 else:
63 # default regex
64 file_regex = "(?P<field1>.*)_(?P<field2>[a-zA-Z0-9]+)"
65 folder_regex = "(?P<folderField1>.*)"
66
67 _str += FOURSPACES + "Regular expression to extract from file name:%s\n" % file_regex
68 _str += FOURSPACES + "Regular expression to extract from folder name:%s\n" % folder_regex
69
70 _str += FOURSPACES + "Extract metadata from:%s\n" % methods["con_metadata_extract_from"]["extract_metadata_from"]
71
72 if methods["con_metadata_extract_from"]["extract_metadata_from"] == "Images matching a rule":
73 rule_str =""
74 for r in methods["con_metadata_extract_from"]["r_match"]:
75 if r["con_match"]["rule_type"] == "extension":
76 rule_str += " (" + r["con_match"]["rule_type"] + " " + r["con_match"]["operator"] + " " + \
77 r["con_match"]["match_type"]+")"
78 else:
79 rule_str +=" (" + r["con_match"]["rule_type"] + " " + r["con_match"]["operator"] + " " +\
80 r["con_match"]["contain"] + " \"" + r["con_match"]["match_value"] +"\")"
81
82
83 _str += FOURSPACES + "Select the filtering criteria:" + methods["con_metadata_extract_from"]["match_all_any"] + rule_str +"\n"
84 else:
85 _str += FOURSPACES + "Select the filtering criteria:and (file does contain \"\")\n" #this line is required even if it's not used
86
87 _str += FOURSPACES + "Metadata file location:\n"
88 _str += FOURSPACES + "Match file and image metadata:\x5B\x5D\n"
89 _str += FOURSPACES + "Use case insensitive matching?:No\n"
90
91 return _str
92
93
94 def write_nameandtypes():
95 nameandtypes = params['nameandtypes']
96 assign_a_name = nameandtypes['con_assign_a_name_to']['assign_a_name_to']
97
98 if "con_select_image_type" in nameandtypes['con_assign_a_name_to']:
99 con_set_intensity = nameandtypes['con_assign_a_name_to']['con_select_image_type']['con_set_intensity']
100 max_intensity = con_set_intensity['maximum_intensity'] if "maximum_intensity" in con_set_intensity else 255.0
101 else:
102 max_intensity = 255.0
103
104 pixel_space = nameandtypes['pixel_space']
105
106 rule_count = len(nameandtypes['con_assign_a_name_to']['r_match_rule']) if "r_match_rule" in nameandtypes['con_assign_a_name_to'] else 1
107
108 process_3d = nameandtypes['pixel_space']['process_3d']
109 x_spacing = 1.0 if "x_spacing" not in pixel_space else pixel_space["x_spacing"]
110 y_spacing = 1.0 if "y_spacing" not in pixel_space else pixel_space["y_spacing"]
111 z_spacing = 1.0 if "z_spacing" not in pixel_space else pixel_space["z_spacing"]
112
113 _str = "\nNamesAndTypes:[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]\n"
114
115 _str += FOURSPACES + "Assign a name to:%s\n" % assign_a_name
116
117 if assign_a_name == "All images":
118 _str += FOURSPACES + "Select the image type:%s\n" % nameandtypes['con_assign_a_name_to']['con_select_image_type']['select_image_type']
119 _str += FOURSPACES + "Name to assign these images:%s\n" % nameandtypes['con_assign_a_name_to']['name_to_assign']
120 _str += FOURSPACES + "Match metadata:[]\n"
121
122 _str += FOURSPACES + "Image set matching method:Order\n"
123 _str += FOURSPACES + "Set intensity range from:%s\n" % con_set_intensity['set_intensity_range_from']
124 _str += FOURSPACES + "Assignments count:%s\n" % rule_count
125 _str += FOURSPACES + "Single images count:0\n"
126 _str += FOURSPACES + "Maximum intensity:%.1f\n" % max_intensity
127 _str += FOURSPACES + "Process as 3D?:%s\n" % process_3d
128
129 else:
130 #the below lines are not relevant to "images matching rules", but needed in pipeline file
131 _str += FOURSPACES + "Select the image type:Grayscale image\n"
132 _str += FOURSPACES + "Name to assign these images:DNA\n"
133 _str += FOURSPACES + "Match metadata:[]\n"
134
135 _str += FOURSPACES + "Image set matching method:%s\n" % nameandtypes['con_assign_a_name_to']['matching_method']
136 _str += FOURSPACES + "Set intensity range from:Image metadata\n"
137 _str += FOURSPACES + "Assignments count:%d\n" % rule_count
138 _str += FOURSPACES + "Single images count:0\n"
139 _str += FOURSPACES + "Maximum intensity:%.1f\n" % max_intensity
140 _str += FOURSPACES + "Process as 3D?:%s\n" % process_3d
141
142 _str += FOURSPACES + "Relative pixel spacing in X:%.1f\n" % x_spacing
143 _str += FOURSPACES + "Relative pixel spacing in Y:%.1f\n" % y_spacing
144 _str += FOURSPACES + "Relative pixel spacing in Z:%.1f\n" % z_spacing
145
146 if assign_a_name == "Images matching rules":
147 for rule in nameandtypes["con_assign_a_name_to"]["r_match_rule"]:
148
149 rule_str = ""
150 if len(rule["r_match"]) >0 :
151 for r in rule["r_match"]:
152 if r["con_match"]["rule_type"] == "file" or r["con_match"]["rule_type"] == "directory":
153 rule_str += " (" + r["con_match"]["rule_type"] + " "+r["con_match"]["operator"]+" "+\
154 r["con_match"]["contain"]+" \"" + r["con_match"]["match_value"] +"\")"
155 else:
156 rule_str += " ("+ r["con_match"]["rule_type"] + " " + r["con_match"]["operator"] + " " + \
157 r["con_match"]["match_type"] + ")"
158 else:
159 rule_str = " (file does contain \"\")" #need to have a value even if it is not used
160
161 _str += FOURSPACES + "Select the rule criteria:" + rule["match_all_any"] + rule_str +"\n"
162
163 img_or_obj = rule["con_select_image_type"]["select_image_type"]
164
165 if img_or_obj == "Objects":
166 _str += FOURSPACES + "Name to assign these images:DNA\n"
167 _str += FOURSPACES + "Name to assign these objects:%s\n" % rule["con_select_image_type"]["name_to_assign"]
168 else:
169 _str += FOURSPACES + "Name to assign these images:%s\n" % rule["con_select_image_type"]["name_to_assign"]
170 _str += FOURSPACES + "Name to assign these objects:Cell\n"
171
172 _str += FOURSPACES + "Select the image type:%s\n" % img_or_obj
173
174
175 intensity_range="Image metadata" #default value
176 if img_or_obj == "Grayscale image" or img_or_obj == "Color image":
177 intensity_range = rule["con_select_image_type"]["con_set_intensity"]["set_intensity_range_from"]
178
179 _str += FOURSPACES + "Set intensity range from:%s\n" % intensity_range
180
181 if intensity_range == "Manual":
182 _str += FOURSPACES + "Maximum intensity:%s\n" % rule["con_select_image_type"]["con_set_intensity"]["maximum_intensity"]
183 else:
184 _str += FOURSPACES + "Maximum intensity:255.0\n"
185
186
187 return _str
188
189
190 def write_groups():
191 groups = params['groups']
192
193 _str = "\nGroups:[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]\n"
194
195 group_images = groups["con_groups"]["group_images"]
196
197 _str += FOURSPACES + "Do you want to group your images?:%s\n" % group_images
198 _str += FOURSPACES + "grouping metadata count:1\n"
199
200 if group_images == "Yes":
201 _str += FOURSPACES + "Metadata category:%s\n" % groups["con_groups"]["group_category"]
202 else:
203 _str += FOURSPACES + "Metadata category:None\n"
204
205 return _str
206
207
208 with open("output.cppipe", "w") as f:
209 headers = ["CellProfiler Pipeline: http://www.cellprofiler.org\n",
210 "Version:3\n",
211 "DateRevision:319\n",
212 "GitHash:\n",
213 "ModuleCount:4\n",
214 "HasImagePlaneDetails:False",
215 "\n"]
216
217 f.writelines(headers)
218
219 img_str = write_images()
220 metadata_str = write_metadata()
221 nameandtypes_str = write_nameandtypes()
222 groups_str = write_groups()
223
224 output_str = img_str + metadata_str + nameandtypes_str + groups_str
225
226 f.write(output_str)
227 f.close()