Mercurial > repos > bgruening > cp_color_to_gray
diff starting_modules.py @ 0:4395ea2a01f4 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 35da2dcd86747c9bff138e100dbe08c6106f3780"
| author | bgruening |
|---|---|
| date | Sat, 06 Feb 2021 10:00:10 +0000 |
| parents | |
| children | e8f822eeb9fd |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/starting_modules.py Sat Feb 06 10:00:10 2021 +0000 @@ -0,0 +1,223 @@ +import json +import sys + +FOURSPACES = " " + +input_json_path = sys.argv[1] + +params = json.load(open(input_json_path, "r")) + + +def write_images(): + filter_images = params['images']['filter_images'] + + _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" + _str += FOURSPACES + ":\n" + _str += FOURSPACES + "Filter images?:%s\n" % filter_images + _str += FOURSPACES + "Select the rule criteria:and (extension does isimage) (directory doesnot startwith \".\")\n" + + return _str + + +def write_metadata(): + metadata_extraction = params['metadata']['con_metadata_extraction'] + extract = metadata_extraction['extract'] + + if 'extraction_method' in metadata_extraction: + method_count = len(metadata_extraction['extraction_method']) + else: + method_count = 1 + + _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" + _str += FOURSPACES + "Extract metadata?:%s\n" % extract + + if extract == "No": + _str += FOURSPACES + "Metadata data type:Text\n" + _str += FOURSPACES + "Metadata types:{}\n" + _str += FOURSPACES + "Extraction method count:%d\n" % method_count + _str += FOURSPACES + "Metadata extraction method:Extract from file/folder names\n" + _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" + _str += FOURSPACES + "Regular expression to extract from folder name:(?P<Date>\x5B0-9\x5D{4}_\x5B0-9\x5D{2}_\x5B0-9\x5D{2})$\n" + _str += FOURSPACES + "Extract metadata from:All images\n" + _str += FOURSPACES + "Select the filtering criteria:and (file does contain \"\")\n" + _str += FOURSPACES + "Metadata file location:\n" + _str += FOURSPACES + "Match file and image metadata:\x5B\x5D\n" + _str += FOURSPACES + "Use case insensitive matching?:No\n" + else: + _str += FOURSPACES + "Metadata data type:Text\n" # default Text,not possible to select in Galaxy + _str += FOURSPACES + "Metadata types:{}\n" + _str += FOURSPACES + "Extraction method count:%d\n" % method_count + + for methods in metadata_extraction["extraction_method"]: + _str += FOURSPACES + "Metadata extraction method:%s\n" % methods["metadata_extraction_method"] + _str += FOURSPACES + "Metadata source:%s\n" % methods["con_metadata_source"]["metadata_source"] + + if "file_name_regex" in methods["con_metadata_source"]: + file_regex = methods["con_metadata_source"]["file_name_regex"] + folder_regex = "(?P<folderField1>.*)" + elif "folder_name_regex" in methods["con_metadata_source"]: + file_regex = "(?P<field1>.*)_(?P<field2>[a-zA-Z0-9]+)" + folder_regex = methods["con_metadata_source"]["folder_name_regex"] + else: + # default regex + file_regex = "(?P<field1>.*)_(?P<field2>[a-zA-Z0-9]+)" + folder_regex = "(?P<folderField1>.*)" + + _str += FOURSPACES + "Regular expression to extract from file name:%s\n" % file_regex + _str += FOURSPACES + "Regular expression to extract from folder name:%s\n" % folder_regex + + _str += FOURSPACES + "Extract metadata from:%s\n" % methods["con_metadata_extract_from"]["extract_metadata_from"] + + if methods["con_metadata_extract_from"]["extract_metadata_from"] == "Images matching a rule": + rule_str = "" + for r in methods["con_metadata_extract_from"]["r_match"]: + if r["con_match"]["rule_type"] == "extension": + rule_str += " (" + r["con_match"]["rule_type"] + " " + r["con_match"]["operator"] + " " + \ + r["con_match"]["match_type"] + ")" + else: + rule_str += " (" + r["con_match"]["rule_type"] + " " + r["con_match"]["operator"] + " " +\ + r["con_match"]["contain"] + " \"" + r["con_match"]["match_value"] + "\")" + + _str += FOURSPACES + "Select the filtering criteria:" + methods["con_metadata_extract_from"]["match_all_any"] + rule_str + "\n" + else: + _str += FOURSPACES + "Select the filtering criteria:and (file does contain \"\")\n" # this line is required even if it's not used + + _str += FOURSPACES + "Metadata file location:\n" + _str += FOURSPACES + "Match file and image metadata:\x5B\x5D\n" + _str += FOURSPACES + "Use case insensitive matching?:No\n" + + return _str + + +def write_nameandtypes(): + nameandtypes = params['nameandtypes'] + assign_a_name = nameandtypes['con_assign_a_name_to']['assign_a_name_to'] + + if "con_select_image_type" in nameandtypes['con_assign_a_name_to']: + con_set_intensity = nameandtypes['con_assign_a_name_to']['con_select_image_type']['con_set_intensity'] + max_intensity = con_set_intensity['maximum_intensity'] if "maximum_intensity" in con_set_intensity else 255.0 + else: + max_intensity = 255.0 + + pixel_space = nameandtypes['pixel_space'] + + 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 + + process_3d = nameandtypes['pixel_space']['process_3d'] + x_spacing = 1.0 if "x_spacing" not in pixel_space else pixel_space["x_spacing"] + y_spacing = 1.0 if "y_spacing" not in pixel_space else pixel_space["y_spacing"] + z_spacing = 1.0 if "z_spacing" not in pixel_space else pixel_space["z_spacing"] + + _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" + + _str += FOURSPACES + "Assign a name to:%s\n" % assign_a_name + + if assign_a_name == "All images": + _str += FOURSPACES + "Select the image type:%s\n" % nameandtypes['con_assign_a_name_to']['con_select_image_type']['select_image_type'] + _str += FOURSPACES + "Name to assign these images:%s\n" % nameandtypes['con_assign_a_name_to']['name_to_assign'] + _str += FOURSPACES + "Match metadata:[]\n" + + _str += FOURSPACES + "Image set matching method:Order\n" + _str += FOURSPACES + "Set intensity range from:%s\n" % con_set_intensity['set_intensity_range_from'] + _str += FOURSPACES + "Assignments count:%s\n" % rule_count + _str += FOURSPACES + "Single images count:0\n" + _str += FOURSPACES + "Maximum intensity:%.1f\n" % max_intensity + _str += FOURSPACES + "Process as 3D?:%s\n" % process_3d + + else: + # the below lines are not relevant to "images matching rules", but needed in pipeline file + _str += FOURSPACES + "Select the image type:Grayscale image\n" + _str += FOURSPACES + "Name to assign these images:DNA\n" + _str += FOURSPACES + "Match metadata:[]\n" + + _str += FOURSPACES + "Image set matching method:%s\n" % nameandtypes['con_assign_a_name_to']['matching_method'] + _str += FOURSPACES + "Set intensity range from:Image metadata\n" + _str += FOURSPACES + "Assignments count:%d\n" % rule_count + _str += FOURSPACES + "Single images count:0\n" + _str += FOURSPACES + "Maximum intensity:%.1f\n" % max_intensity + _str += FOURSPACES + "Process as 3D?:%s\n" % process_3d + + _str += FOURSPACES + "Relative pixel spacing in X:%.1f\n" % x_spacing + _str += FOURSPACES + "Relative pixel spacing in Y:%.1f\n" % y_spacing + _str += FOURSPACES + "Relative pixel spacing in Z:%.1f\n" % z_spacing + + if assign_a_name == "Images matching rules": + for rule in nameandtypes["con_assign_a_name_to"]["r_match_rule"]: + + rule_str = "" + if len(rule["r_match"]) > 0: + for r in rule["r_match"]: + if r["con_match"]["rule_type"] == "file" or r["con_match"]["rule_type"] == "directory": + rule_str += " (" + r["con_match"]["rule_type"] + " " + r["con_match"]["operator"] + " " + \ + r["con_match"]["contain"] + " \"" + r["con_match"]["match_value"] + "\")" + else: + rule_str += " (" + r["con_match"]["rule_type"] + " " + r["con_match"]["operator"] + " " + \ + r["con_match"]["match_type"] + ")" + else: + rule_str = " (file does contain \"\")" # need to have a value even if it is not used + + _str += FOURSPACES + "Select the rule criteria:" + rule["match_all_any"] + rule_str + "\n" + + img_or_obj = rule["con_select_image_type"]["select_image_type"] + + if img_or_obj == "Objects": + _str += FOURSPACES + "Name to assign these images:DNA\n" + _str += FOURSPACES + "Name to assign these objects:%s\n" % rule["con_select_image_type"]["name_to_assign"] + else: + _str += FOURSPACES + "Name to assign these images:%s\n" % rule["con_select_image_type"]["name_to_assign"] + _str += FOURSPACES + "Name to assign these objects:Cell\n" + + _str += FOURSPACES + "Select the image type:%s\n" % img_or_obj + + intensity_range = "Image metadata" # default value + if img_or_obj == "Grayscale image" or img_or_obj == "Color image": + intensity_range = rule["con_select_image_type"]["con_set_intensity"]["set_intensity_range_from"] + + _str += FOURSPACES + "Set intensity range from:%s\n" % intensity_range + + if intensity_range == "Manual": + _str += FOURSPACES + "Maximum intensity:%s\n" % rule["con_select_image_type"]["con_set_intensity"]["maximum_intensity"] + else: + _str += FOURSPACES + "Maximum intensity:255.0\n" + + return _str + + +def write_groups(): + groups = params['groups'] + + _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" + + group_images = groups["con_groups"]["group_images"] + + _str += FOURSPACES + "Do you want to group your images?:%s\n" % group_images + _str += FOURSPACES + "grouping metadata count:1\n" + + if group_images == "Yes": + _str += FOURSPACES + "Metadata category:%s\n" % groups["con_groups"]["group_category"] + else: + _str += FOURSPACES + "Metadata category:None\n" + + return _str + + +with open("output.cppipe", "w") as f: + headers = ["CellProfiler Pipeline: http://www.cellprofiler.org\n", + "Version:3\n", + "DateRevision:319\n", + "GitHash:\n", + "ModuleCount:4\n", + "HasImagePlaneDetails:False", + "\n"] + + f.writelines(headers) + + img_str = write_images() + metadata_str = write_metadata() + nameandtypes_str = write_nameandtypes() + groups_str = write_groups() + + output_str = img_str + metadata_str + nameandtypes_str + groups_str + + f.write(output_str) + f.close()