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annotate tomo_setup.py @ 60:52db7707ff48 draft

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"planemo upload for repository https://github.com/rolfverberg/galaxytools commit 9a07ab3099737ee0d99e82739b55048f89c36bc6-dirty"
author rv43
date Tue, 16 Aug 2022 21:23:10 +0000
parents feb2a5fc7c76
children 75dd6e15f628
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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 from general import get_trailing_int
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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('--inputconfig',
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24 default='inputconfig.txt',
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25 help='Input config from tool form')
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26 parser.add_argument('--inputfiles',
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27 default='inputfiles.txt',
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28 help='Input file collections')
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29 parser.add_argument('-c', '--config',
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30 help='Input config file')
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31 parser.add_argument('--detector',
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32 help='Detector info (number of rows and columns, and pixel size)')
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33 parser.add_argument('--num_theta',
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34 help='Number of theta angles')
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35 parser.add_argument('--theta_range',
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36 help='Theta range (lower bound, upper bound)')
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37 parser.add_argument('--output_config',
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38 help='Output config')
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39 parser.add_argument('--output_data',
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40 help='Preprocessed tomography data')
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41 parser.add_argument('-l', '--log',
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42 type=argparse.FileType('w'),
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43 default=sys.stdout,
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44 help='Log file')
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45 args = parser.parse_args()
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46
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47 # Starting memory monitoring
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48 tracemalloc.start()
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50 # Set basic log configuration
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51 logging_format = '%(asctime)s : %(levelname)s - %(module)s : %(funcName)s - %(message)s'
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52 log_level = 'INFO'
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53 level = getattr(logging, log_level.upper(), None)
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54 if not isinstance(level, int):
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55 raise ValueError(f'Invalid log_level: {log_level}')
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56 logging.basicConfig(format=logging_format, level=level, force=True,
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57 handlers=[logging.StreamHandler()])
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58
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59 # Check command line arguments
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60 logging.info(f'config = {args.config}')
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61 if args.detector is None:
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62 logging.info(f'detector = {args.detector}')
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63 else:
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64 logging.info(f'detector = {args.detector.split()}')
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65 logging.info(f'num_theta = {args.num_theta}')
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66 if args.theta_range is None:
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67 logging.info(f'theta_range = {args.theta_range}')
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68 else:
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69 logging.info(f'theta_range = {args.theta_range.split()}')
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70 logging.info(f'output_config = {args.output_config}')
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71 logging.info(f'output_data = {args.output_data}')
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72 logging.info(f'log = {args.log}')
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73 logging.debug(f'is log stdout? {args.log is sys.stdout}')
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74 if args.detector is not None and len(args.detector.split()) != 3:
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75 raise ValueError(f'Invalid detector: {args.detector}')
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76 if args.num_theta is None or int(args.num_theta) < 1:
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77 raise ValueError(f'Invalid num_theta: {args.num_theta}')
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78 if args.theta_range is not None and len(args.theta_range.split()) != 2:
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79 raise ValueError(f'Invalid theta_range: {args.theta_range}')
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80 num_theta = int(args.num_theta)
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81
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82 # Read and check tool config input
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83 inputconfig = []
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84 with open(args.inputconfig) as f:
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85 inputconfig = [line.strip() for line in f if line.strip() and not line.startswith('#')]
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86 assert(len(inputconfig) >= 6)
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87 config_type = inputconfig[0]
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88 input_type = inputconfig[1]
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89 num_stack = int(inputconfig[2])
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90 stack_types = [x.strip() for x in inputconfig[3].split()]
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91 num_imgs = [int(x.strip()) for x in inputconfig[4].split()]
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92 img_offsets = [int(x.strip()) for x in inputconfig[5].split()]
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93 if config_type == 'config_manual':
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94 assert(len(inputconfig) == 7)
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95 ref_heights = [float(x.strip()) for x in inputconfig[6].split()]
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96 assert(args.detector is not None)
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97 assert(args.theta_range is not None)
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98 else:
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99 ref_heights = None
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100 logging.info(f'config_type = {config_type} {type(config_type)}')
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101 logging.info(f'input_type = {input_type} {type(input_type)}')
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102 logging.info(f'num_stack = {num_stack} {type(num_stack)}')
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103 logging.info(f'stack_types = {stack_types} {type(stack_types)}')
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104 logging.info(f'num_imgs = {num_imgs} {type(num_imgs)}')
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105 logging.info(f'img_offsets = {img_offsets} {type(img_offsets)}')
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106 logging.info(f'ref_heights = {ref_heights} {type(ref_heights)}')
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107 if config_type != 'config_file' and config_type != 'config_manual':
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108 raise ValueError('Invalid input config provided.')
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109 if input_type != 'collections' and input_type != 'files':
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110 raise ValueError('Invalid input config provided.')
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111 if len(stack_types) != num_stack:
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112 raise ValueError('Invalid input config provided.')
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113 if len(num_imgs) != num_stack:
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114 raise ValueError('Invalid input config provided.')
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115 if len(img_offsets) != num_stack:
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116 raise ValueError('Invalid input config provided.')
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117 if ref_heights is not None and len(ref_heights) != num_stack:
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118 raise ValueError('Invalid input config provided.')
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119
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120 # Read input files and collect data files info
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121 datasets = []
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122 with open(args.inputfiles) as f:
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123 for line in f:
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124 if not line.strip() or line.startswith('#'):
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125 continue
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126 fields = [x.strip() for x in line.split('\t')]
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127 filepath = fields[0]
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128 element_identifier = fields[1] if len(fields) > 1 else fields[0].split('/')[-1]
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129 datasets.append({'element_identifier' : element_identifier, 'filepath' : filepath})
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130 print(f'datasets:\n{datasets}')
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131 logging.debug(f'datasets:\n{datasets}')
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132 if input_type == 'files' and len(datasets) != num_stack:
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133 raise ValueError('Inconsistent number of input files provided.')
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134
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135 # Read and sort data files
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136 collections = []
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137 stack_index = 1
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138 for i, dataset in enumerate(datasets):
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139 if input_type == 'collections':
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140 element_identifier = [x.strip() for x in dataset['element_identifier'].split('_')]
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141 if len(element_identifier) > 1:
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142 name = element_identifier[0]
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143 else:
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144 name = 'other'
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145 else:
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146 if stack_types[i] == 'tdf' or stack_types[i] == 'tbf':
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147 name = stack_types[i]
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148 elif stack_types[i] == 'data':
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149 name = f'set{stack_index}'
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150 stack_index += 1
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151 else:
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152 raise ValueError('Invalid input config provided.')
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153 filepath = dataset['filepath']
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154 if not len(collections):
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155 collections = [{'name' : name, 'filepaths' : [filepath]}]
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156 else:
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157 collection = [c for c in collections if c['name'] == name]
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158 if len(collection):
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159 collection[0]['filepaths'].append(filepath)
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160 else:
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161 collection = {'name' : name, 'filepaths' : [filepath]}
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162 collections.append(collection)
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163 print(f'collections:\n{collections}')
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164 logging.debug(f'collections:\n{collections}')
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165
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166 # Instantiate Tomo object
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167 tomo = Tomo(config_file=args.config, config_out=args.output_config, log_level=log_level,
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168 log_stream=args.log, galaxy_flag=True)
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169 if config_type == 'config_file':
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170 if not tomo.is_valid:
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171 raise ValueError('Invalid config file provided.')
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172 else:
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173 assert(tomo.config is None)
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174 tomo.config = {}
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175 logging.debug(f'config:\n{tomo.config}')
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176
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177 # Set detector inputs
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178 if config_type == 'config_manual':
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179 detector = args.detector.split()
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180 tomo.config['detector'] = {'rows' : int(detector[0]),
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181 'columns' : int(detector[1]), 'pixel_size' : float(detector[2])}
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182
0
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183 # Set theta inputs
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184 config_theta_range = tomo.config.get('theta_range')
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185 if config_theta_range is None:
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186 tomo.config['theta_range'] = {'num' : num_theta}
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187 config_theta_range = tomo.config['theta_range']
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188 else:
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189 config_theta_range['num'] = num_theta
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190 if config_type == 'config_manual':
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191 theta_range = args.theta_range.split()
0
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192 config_theta_range['start'] = float(theta_range[0])
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193 config_theta_range['end'] = float(theta_range[1])
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194
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195 # Find dark field files
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196 dark_field = tomo.config.get('dark_field')
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197 tdf_files = [c['filepaths'] for c in collections if c['name'] == 'tdf']
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198 if len(tdf_files) != 1 or len(tdf_files[0]) < 1:
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199 logging.warning('Unable to obtain dark field files')
60
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200 if config_type == 'config_file':
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201 assert(dark_field is not None)
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202 assert(dark_field['data_path'] is None)
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203 assert(dark_field['img_start'] == -1)
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204 assert(not dark_field['num'])
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205 else:
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206 tomo.config['dark_field'] = {'data_path' : None, 'img_start' : -1, 'num' : 0}
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207 tdf_files = [None]
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208 num_collections = 0
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209 else:
60
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210 if config_type == 'config_file':
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211 assert(dark_field is not None)
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212 assert(dark_field['data_path'] is not None)
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213 assert(dark_field.get('img_start') is not None)
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214 else:
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215 tomo.config['dark_field'] = {'data_path' : tdf_files[0], 'img_start' : 0}
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216 dark_field = tomo.config['dark_field']
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217 tdf_index = [i for i,c in enumerate(collections) if c['name'] == 'tdf']
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218 tdf_index_check = [i for i,s in enumerate(stack_types) if s == 'tdf']
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219 if tdf_index != tdf_index_check:
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220 raise ValueError(f'Inconsistent tdf_index ({tdf_index} vs. {tdf_index_check}).')
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221 tdf_index = tdf_index[0]
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222 dark_field['img_offset'] = img_offsets[tdf_index]
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223 dark_field['num'] = num_imgs[tdf_index]
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224 num_collections = 1
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225
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226 # Find bright field files
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227 bright_field = tomo.config.get('bright_field')
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228 tbf_files = [c['filepaths'] for c in collections if c['name'] == 'tbf']
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229 if len(tbf_files) != 1 or len(tbf_files[0]) < 1:
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230 exit('Unable to obtain bright field files')
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231 if config_type == 'config_file':
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232 assert(bright_field is not None)
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233 assert(bright_field['data_path'] is not None)
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234 assert(bright_field.get('img_start') is not None)
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235 else:
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236 tomo.config['bright_field'] = {'data_path' : tbf_files[0], 'img_start' : 0}
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237 bright_field = tomo.config['bright_field']
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238 tbf_index = [i for i,c in enumerate(collections) if c['name'] == 'tbf']
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239 tbf_index_check = [i for i,s in enumerate(stack_types) if s == 'tbf']
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240 if tbf_index != tbf_index_check:
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241 raise ValueError(f'Inconsistent tbf_index ({tbf_index} vs. {tbf_index_check}).')
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242 tbf_index = tbf_index[0]
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243 bright_field['img_offset'] = img_offsets[tbf_index]
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244 bright_field['num'] = num_imgs[tbf_index]
0
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245 num_collections += 1
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246
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247 # Find tomography files
60
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248 stack_info = tomo.config.get('stack_info')
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249 if config_type == 'config_file':
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250 assert(stack_info is not None)
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251 if stack_info['num'] != len(collections) - num_collections:
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252 raise ValueError('Inconsistent number of tomography data image sets')
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253 assert(stack_info.get('stacks') is not None)
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254 for stack in stack_info['stacks']:
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255 assert(stack['data_path'] is not None)
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256 assert(stack.get('img_start') is not None)
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257 assert(stack.get('index') is not None)
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258 assert(stack.get('ref_height') is not None)
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259 else:
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260 tomo.config['stack_info'] = {'num' : len(collections) - num_collections, 'stacks' : []}
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261 stack_info = tomo.config['stack_info']
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262 for i in range(stack_info['num']):
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263 stack_info['stacks'].append({'img_start' : 0, 'index' : i+1})
0
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264 tomo_stack_files = []
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265 for stack in stack_info['stacks']:
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266 index = stack['index']
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267 tomo_files = [c['filepaths'] for c in collections if c['name'] == f'set{index}']
0
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268 if len(tomo_files) != 1 or len(tomo_files[0]) < 1:
60
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269 exit(f'Unable to obtain tomography images for set {index}')
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270 tomo_index = [i for i,c in enumerate(collections) if c['name'] == f'set{index}']
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271 if len(tomo_index) != 1:
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272 raise ValueError(f'Illegal tomo_index ({tomo_index}).')
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273 tomo_index = tomo_index[0]
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274 stack['img_offset'] = img_offsets[tomo_index]
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275 assert(num_imgs[tomo_index] == -1)
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276 stack['num'] = num_theta
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277 if config_type == 'config_manual':
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278 if len(tomo_files) == 1:
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279 stack['data_path'] = tomo_files[0]
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280 stack['ref_height'] = ref_heights[tomo_index]
0
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281 tomo_stack_files.append(tomo_files[0])
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282 num_collections += 1
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283 if num_collections != num_stack:
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284 raise ValueError('Inconsistent number of data image sets')
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285 print(f'config:\n{tomo.config}')
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286 return
0
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287
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288 # Preprocess the image files
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289 galaxy_param = {'tdf_files' : tdf_files[0], 'tbf_files' : tbf_files[0],
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290 'tomo_stack_files' : tomo_stack_files, 'output_name' : args.output_data}
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291 tomo.genTomoStacks(galaxy_param)
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292 if not tomo.is_valid:
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293 IOError('Unable to load all required image files.')
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294
15
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295 # Displaying memory usage
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296 logging.info(f'Memory usage: {tracemalloc.get_traced_memory()}')
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297
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298 # stopping memory monitoring
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299 tracemalloc.stop()
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300
0
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301 if __name__ == "__main__":
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302 __main__()
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303