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annotate tomo_setup.py @ 48:059819ea1f0e draft

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"planemo upload for repository https://github.com/rolfverberg/galaxytools commit b97c6a8f181dea6d2f9cfa2069b86d30dcc47b4d"
author rv43
date Wed, 27 Apr 2022 17:28:26 +0000
parents ef5c2f7b49ec
children 26f99fdd8d61
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1 #!/usr/bin/env python3
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3 import logging
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5 import os
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6 import sys
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7 import re
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8 import yaml
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9 import argparse
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10 import numpy as np
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11 import tracemalloc
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13 from tomo import Tomo
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14 import msnc_tools as msnc
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15
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16 #from memory_profiler import profile
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17 #@profile
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18 def __main__():
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20 # Parse command line arguments
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21 parser = argparse.ArgumentParser(
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22 description='Setup tomography reconstruction')
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23 parser.add_argument('-i', '--inputfiles',
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24 default='inputfiles.txt',
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25 help='Input file collections')
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26 parser.add_argument('-c', '--config',
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27 help='Input config')
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28 parser.add_argument('--theta_range',
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29 help='Theta range (lower bound, upper bound, number of angles)')
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30 parser.add_argument('--output_config',
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31 help='Output config')
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32 parser.add_argument('--output_data',
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33 help='Preprocessed tomography data')
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34 parser.add_argument('-l', '--log',
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35 type=argparse.FileType('w'),
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36 default=sys.stdout,
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37 help='Log file')
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38 parser.add_argument('tomo_ranges', metavar='N', type=int, nargs='+')
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39 args = parser.parse_args()
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40
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41 # Starting memory monitoring
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42 tracemalloc.start()
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44 # Set basic log configuration
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45 logging_format = '%(asctime)s : %(levelname)s - %(module)s : %(funcName)s - %(message)s'
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46 log_level = 'INFO'
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47 level = getattr(logging, log_level.upper(), None)
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48 if not isinstance(level, int):
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49 raise ValueError(f'Invalid log_level: {log_level}')
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50 logging.basicConfig(format=logging_format, level=level, force=True,
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51 handlers=[logging.StreamHandler()])
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52
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53 logging.debug(f'config = {args.config}')
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54 logging.debug(f'theta_range = {args.theta_range.split()}')
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55 logging.debug(f'output_config = {args.output_config}')
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56 logging.debug(f'output_data = {args.output_data}')
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57 logging.debug(f'log = {args.log}')
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58 logging.debug(f'is log stdout? {args.log is sys.stdout}')
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59 logging.debug(f'tomoranges = {args.tomo_ranges}')
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60
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61 # Read input files and collect data files info
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62 datasets = []
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63 with open(args.inputfiles) as cf:
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64 for line in cf:
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65 if not line.strip() or line.startswith('#'):
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66 continue
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67 fields = [x.strip() for x in line.split('\t')]
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68 filepath = fields[0]
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69 element_identifier = fields[1] if len(fields) > 1 else fields[0].split('/')[-1]
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70 datasets.append({'element_identifier' : fields[1], 'filepath' : filepath})
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71 logging.debug(f'datasets:\n{datasets}')
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72
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73 # Read and sort data files
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74 collections = []
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75 for dataset in datasets:
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76 element_identifier = [x.strip() for x in dataset['element_identifier'].split('_')]
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77 if len(element_identifier) > 1:
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78 name = element_identifier[0]
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79 else:
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80 name = 'other'
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81 filepath = dataset['filepath']
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82 if not len(collections):
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83 collections = [{'name' : name, 'filepaths' : [filepath]}]
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84 else:
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85 collection = [c for c in collections if c['name'] == name]
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86 if len(collection):
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87 collection[0]['filepaths'].append(filepath)
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88 else:
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89 collection = {'name' : name, 'filepaths' : [filepath]}
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90 collections.append(collection)
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91 logging.debug(f'collections:\n{collections}')
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92 if len(args.tomo_ranges) != 2*len(collections):
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93 raise ValueError('Inconsistent tomo ranges size.')
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94
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95 # Instantiate Tomo object
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96 tomo = Tomo(config_file=args.config, config_out=args.output_config, log_level=log_level,
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97 log_stream=args.log, galaxy_flag=True)
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98 if not tomo.is_valid:
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99 raise ValueError('Invalid config file provided.')
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100 logging.debug(f'config:\n{tomo.config}')
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101
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102 # Set theta inputs
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103 theta_range = args.theta_range.split()
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104 config_theta_range = tomo.config.get('theta_range')
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105 if config_theta_range is None:
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106 config_tomo.config['theta_range'] = {'start' : float(theta_range[0]),
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107 'end' : float(theta_range[1]), 'num' : int(theta_range[2])}
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108 else:
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109 config_theta_range['start'] = float(theta_range[0])
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110 config_theta_range['end'] = float(theta_range[1])
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111 config_theta_range['num'] = int(theta_range[2])
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112
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113 # Find dark field files
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114 dark_field = tomo.config['dark_field']
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115 tdf_files = [c['filepaths'] for c in collections if c['name'] == 'tdf']
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116 if len(tdf_files) != 1 or len(tdf_files[0]) < 1:
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117 logging.warning('Unable to obtain dark field files')
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118 assert(dark_field['data_path'] is None)
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119 assert(dark_field['img_start'] == -1)
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120 assert(not dark_field['num'])
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121 tdf_files = [None]
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122 num_collections = 0
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123 else:
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124 dark_field['img_offset'] = args.tomo_ranges[0]
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125 dark_field['num'] = args.tomo_ranges[1]
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126 num_collections = 1
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127
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128 # Find bright field files
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129 bright_field = tomo.config['bright_field']
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130 bright_field['img_offset'] = args.tomo_ranges[2*num_collections]
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131 bright_field['num'] = args.tomo_ranges[2*num_collections+1]
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132 tbf_files = [c['filepaths'] for c in collections if c['name'] == 'tbf']
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133 if len(tbf_files) != 1 or len(tbf_files[0]) < 1:
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134 exit('Unable to obtain bright field files')
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135 num_collections += 1
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136
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137 # Find tomography files
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138 stack_info = tomo.config['stack_info']
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139 if stack_info['num'] != len(collections) - num_collections:
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140 raise ValueError('Inconsistent number of tomography data image sets')
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141 tomo_stack_files = []
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142 for stack in stack_info['stacks']:
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143 stack['img_offset'] = args.tomo_ranges[2*num_collections]
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144 stack['num'] = args.tomo_ranges[2*num_collections+1]
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145 tomo_files = [c['filepaths'] for c in collections if c['name'] == f'set{stack["index"]}']
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146 if len(tomo_files) != 1 or len(tomo_files[0]) < 1:
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147 exit(f'Unable to obtain tomography images for set {stack["index"]}')
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148 tomo_stack_files.append(tomo_files[0])
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149 num_collections += 1
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150
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151 # Preprocess the image files
15
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152 galaxy_param = {'tdf_files' : tdf_files[0], 'tbf_files' : tbf_files[0],
41
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153 'tomo_stack_files' : tomo_stack_files, 'output_name' : args.output_data}
15
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154 tomo.genTomoStacks(galaxy_param)
0
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155 if not tomo.is_valid:
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156 IOError('Unable to load all required image files.')
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157
15
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158 # Displaying memory usage
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159 logging.info(f'Memory usage: {tracemalloc.get_traced_memory()}')
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160
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161 # stopping memory monitoring
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162 tracemalloc.stop()
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163
0
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164 if __name__ == "__main__":
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165 __main__()
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166