Mercurial > repos > bgruening > cp_cellprofiler
view color_to_gray.py @ 5:e917a2424690 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 09:58:14 +0000 |
parents | |
children | 0e4dccaafef5 |
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#!/usr/bin/env python import argparse import json from cp_common_functions import get_json_value from cp_common_functions import get_pipeline_lines from cp_common_functions import get_total_number_of_modules from cp_common_functions import INDENTATION from cp_common_functions import update_module_count from cp_common_functions import write_pipeline MODULE_NAME = "ColorToGray" OUTPUT_FILENAME = "output.cppipe" def build_ctg_header(module_name, module_number): """Creates the first line of a module given the name and module number""" result = "|".join([f"{module_name}:[module_num:{module_number}", "svn_version:\\'Unknown\\'", "variable_revision_number:4", "show_window:True", "notes:\\x5B\\'Convert the color image to grayscale.\\'\\x5D", "batch_state:array(\\x5B\\x5D, dtype=uint8)", "enabled:True", "wants_pause:False]\n"]) return result def build_main_block(input_params): """Creates the main block of the CP pipeline with the parameters that don't depend on conditional choices""" result = INDENTATION.join([f"{INDENTATION}Select the input image:{get_json_value(input_params,'name_input_image')}\n", f"Conversion method:{get_json_value(input_params,'con_conversion_method.conversion_method')}\n", f"Image type:{get_json_value(input_params,'con_conversion_method.con_image_type.image_type')}\n", ]) conversion_method = get_json_value(input_params, 'con_conversion_method.conversion_method') image_type = get_json_value(input_params, 'con_conversion_method.con_image_type.image_type') rgb_comb_name_out = "OrigGray" combine_w_red = 1.0 combine_w_green = 1.0 combine_w_blue = 1.0 split_red = "Yes" split_green = "Yes" split_blue = "Yes" red_output_name = "OrigRed" green_output_name = "OrigGreen" blue_output_name = "OrigBlue" split_hue = "Yes" split_saturation = "Yes" split_value = "Yes" hue_output_name = "OrigHue" saturation_output_name = "OrigSaturation" value_output_name = "OrigValue" channel_count = 1 if conversion_method == "Combine": if image_type == "RGB" or image_type == "HSV": rgb_comb_name_out = get_json_value(input_params, 'con_conversion_method.name_output_image') combine_w_red = get_json_value(input_params, 'con_conversion_method.con_image_type.weight_red_channel') combine_w_green = get_json_value(input_params, 'con_conversion_method.con_image_type.weight_green_channel') combine_w_blue = get_json_value(input_params, 'con_conversion_method.con_image_type.weight_blue_channel') elif conversion_method == "Split": if image_type == "RGB": split_red = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_red.yes_no') red_output_name = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_red.name_output_image') split_green = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_green.yes_no') green_output_name = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_green.name_output_image') split_blue = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_blue.yes_no') blue_output_name = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_blue.name_output_image') elif image_type == "HSV": split_hue = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_hue.yes_no') hue_output_name = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_hue.name_output_image') split_saturation = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_saturation.yes_no') saturation_output_name = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_saturation.name_output_image') split_value = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_value.yes_no') value_output_name = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_value.name_output_image') result += INDENTATION.join( [f"{INDENTATION}Name the output image:{rgb_comb_name_out}\n", f"Relative weight of the red channel:{str(combine_w_red)}\n", f"Relative weight of the green channel:{str(combine_w_green)}\n", f"Relative weight of the blue channel:{str(combine_w_blue)}\n", f"Convert red to gray?:{split_red}\n", f"Name the output image:{red_output_name}\n", f"Convert green to gray?:{split_green}\n", f"Name the output image:{green_output_name}\n", f"Convert blue to gray?:{split_blue}\n", f"Name the output image:{blue_output_name}\n", f"Convert hue to gray?:{split_hue}\n", f"Name the output image:{hue_output_name}\n", f"Convert saturation to gray?:{split_saturation}\n", f"Name the output image:{saturation_output_name}\n", f"Convert value to gray?:{split_value}\n", f"Name the output image:{value_output_name}\n" ]) channel_count = 1 if image_type == "Channels": channels = input_params['con_conversion_method']['con_image_type']['rpt_channel'] channel_count = len(channels) result += INDENTATION.join( [f"{INDENTATION}Channel count:{channel_count}\n" ]) for ch in channels: rel_weight_ch = 1.0 image_name = "Channel1" if conversion_method == "Combine": rel_weight_ch = get_json_value(ch, 'weight_of_channel') else: image_name = get_json_value(ch, 'image_name') result += INDENTATION.join( [f"{INDENTATION}Channel number:{get_json_value(ch,'channel_no')}\n", f"Relative weight of the channel:{str(rel_weight_ch)}\n", f"Image name:{image_name}\n" ]) else: result += INDENTATION.join( [f"{INDENTATION}Channel count:{channel_count}\n", "Channel number:Red\\x3A 1\n", "Relative weight of the channel:1.0\n", "Image name:Channel1\n" ]) return result if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument( '-p', '--pipeline', help='CellProfiler pipeline' ) parser.add_argument( '-i', '--inputs', help='JSON inputs from Galaxy' ) args = parser.parse_args() pipeline_lines = get_pipeline_lines(args.pipeline) inputs_galaxy = json.load(open(args.inputs, "r")) current_module_num = get_total_number_of_modules(pipeline_lines) current_module_num += 1 pipeline_lines = update_module_count(pipeline_lines, current_module_num) header_block = build_ctg_header(MODULE_NAME, current_module_num) main_block = build_main_block(inputs_galaxy) module_pipeline = f"\n{header_block}{main_block}\n" pipeline_lines.append(module_pipeline) write_pipeline(OUTPUT_FILENAME, pipeline_lines)