annotate build/bdist.linux-x86_64/egg/CHAP/models/integration.py @ 0:cbbe42422d56 draft

planemo upload for repository https://github.com/CHESSComputing/ChessAnalysisPipeline/tree/galaxy commit 1401a7e1ae007a6bda260d147f9b879e789b73e0-dirty
author kls286
date Tue, 28 Mar 2023 15:07:30 +0000
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1 import copy
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2 from functools import cache, lru_cache
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3 import json
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4 import logging
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5 import os
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6 from time import time
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7 from typing import Literal, Optional
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8
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9 from msnctools.general import input_menu
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10 from multiprocessing.pool import ThreadPool
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11 from nexusformat.nexus import (NXdata,
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12 NXdetector,
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13 NXfield,
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14 NXprocess,
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15 NXroot)
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16 import numpy as np
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17 from pydantic import (BaseModel,
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18 validator,
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19 constr,
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20 conlist,
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21 conint,
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22 confloat,
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23 FilePath)
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24 import pyFAI, pyFAI.multi_geometry, pyFAI.units
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25 from pyspec.file.tiff import TiffFile
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26
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27 from .map import MapConfig, SpecScans
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28
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29
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30 class Detector(BaseModel):
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31 """
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32 Detector class to represent a single detector used in the experiment.
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33
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34 :param prefix: Prefix of the detector in the SPEC file.
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35 :type prefix: str
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36 :param poni_file: Path to the poni file.
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37 :type poni_file: str
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38 :param mask_file: Optional path to the mask file.
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39 :type mask_file: str, optional
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40 """
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41 prefix: constr(strip_whitespace=True, min_length=1)
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42 poni_file: FilePath
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43 mask_file: Optional[FilePath]
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44 @validator('poni_file', allow_reuse=True)
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45 def validate_poni_file(cls, poni_file):
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46 """
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47 Validate the poni file by checking if it's a valid PONI file.
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48
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49 :param poni_file: Path to the poni file.
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50 :type poni_file: str
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51 :raises ValueError: If poni_file is not a valid PONI file.
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52 :returns: Absolute path to the poni file.
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53 :rtype: str
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54 """
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55 poni_file = os.path.abspath(poni_file)
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56 try:
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57 ai = azimuthal_integrator(poni_file)
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58 except:
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59 raise(ValueError(f'{poni_file} is not a valid PONI file'))
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60 else:
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61 return(poni_file)
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62 @validator('mask_file', allow_reuse=True)
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63 def validate_mask_file(cls, mask_file, values):
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64 """
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65 Validate the mask file. If a mask file is provided, it checks if it's a valid TIFF file.
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66
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67 :param mask_file: Path to the mask file.
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68 :type mask_file: str or None
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69 :param values: A dictionary of the Detector fields.
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70 :type values: dict
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71 :raises ValueError: If mask_file is provided and it's not a valid TIFF file.
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72 :raises ValueError: If `'poni_file'` is not provided in `values`.
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73 :returns: Absolute path to the mask file or None.
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74 :rtype: str or None
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75 """
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76 if mask_file is None:
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77 return(mask_file)
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78 else:
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79 mask_file = os.path.abspath(mask_file)
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80 poni_file = values.get('poni_file')
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81 if poni_file is None:
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82 raise(ValueError('Cannot validate mask file without a PONI file.'))
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83 else:
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84 try:
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85 mask_array = get_mask_array(mask_file, poni_file)
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86 except BaseException as e:
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87 raise(ValueError(f'Unable to open {mask_file} as a TIFF file'))
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88 else:
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89 return(mask_file)
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90 @property
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91 def azimuthal_integrator(self):
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92 return(azimuthal_integrator(self.poni_file))
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93 @property
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94 def mask_array(self):
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95 return(get_mask_array(self.mask_file, self.poni_file))
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96
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97 @cache
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98 def azimuthal_integrator(poni_file:str):
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99 if not isinstance(poni_file, str):
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100 poni_file = str(poni_file)
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101 return(pyFAI.load(poni_file))
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102 @cache
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103 def get_mask_array(mask_file:str, poni_file:str):
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104 if mask_file is not None:
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105 if not isinstance(mask_file, str):
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106 mask_file = str(mask_file)
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107 with TiffFile(mask_file) as tiff:
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108 mask_array = tiff.asarray()
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109 else:
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110 mask_array = np.zeros(azimuthal_integrator(poni_file).detector.shape)
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111 return(mask_array)
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112
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113 class IntegrationConfig(BaseModel):
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114 """
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115 Class representing the configuration for a raw detector data integration.
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116
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117 :ivar tool_type: type of integration tool; always set to "integration"
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118 :type tool_type: str, optional
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119 :ivar title: title of the integration
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120 :type title: str
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121 :ivar integration_type: type of integration, one of "azimuthal", "radial", or "cake"
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122 :type integration_type: str
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123 :ivar detectors: list of detectors used in the integration
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124 :type detectors: List[Detector]
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125 :ivar radial_units: radial units for the integration, defaults to `'q_A^-1'`
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126 :type radial_units: str, optional
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127 :ivar radial_min: minimum radial value for the integration range
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128 :type radial_min: float, optional
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129 :ivar radial_max: maximum radial value for the integration range
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130 :type radial_max: float, optional
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131 :ivar radial_npt: number of points in the radial range for the integration
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132 :type radial_npt: int, optional
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133 :ivar azimuthal_units: azimuthal units for the integration
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134 :type azimuthal_units: str, optional
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135 :ivar azimuthal_min: minimum azimuthal value for the integration range
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136 :type azimuthal_min: float, optional
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137 :ivar azimuthal_max: maximum azimuthal value for the integration range
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138 :type azimuthal_max: float, optional
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139 :ivar azimuthal_npt: number of points in the azimuthal range for the integration
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140 :type azimuthal_npt: int, optional
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141 :ivar error_model: error model for the integration, one of "poisson" or "azimuthal"
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142 :type error_model: str, optional
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143 """
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144 tool_type: Literal['integration'] = 'integration'
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145 title: constr(strip_whitespace=True, min_length=1)
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146 integration_type: Literal['azimuthal', 'radial', 'cake']
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147 detectors: conlist(item_type=Detector, min_items=1)
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148 radial_units: str = 'q_A^-1'
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149 radial_min: confloat(ge=0)
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150 radial_max: confloat(gt=0)
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151 radial_npt: conint(gt=0) = 1800
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152 azimuthal_units: str = 'chi_deg'
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153 azimuthal_min: confloat(ge=-180) = -180
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154 azimuthal_max: confloat(le=360) = 180
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155 azimuthal_npt: conint(gt=0) = 3600
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156 error_model: Optional[Literal['poisson', 'azimuthal']]
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157 sequence_index: Optional[conint(gt=0)]
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158 @validator('radial_units', allow_reuse=True)
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159 def validate_radial_units(cls, radial_units):
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160 """
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161 Validate the radial units for the integration.
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162
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163 :param radial_units: unvalidated radial units for the integration
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164 :type radial_units: str
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165 :raises ValueError: if radial units are not one of the recognized radial units
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166 :return: validated radial units
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167 :rtype: str
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168 """
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169 if radial_units in pyFAI.units.RADIAL_UNITS.keys():
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170 return(radial_units)
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171 else:
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172 raise(ValueError(f'Invalid radial units: {radial_units}. Must be one of {", ".join(pyFAI.units.RADIAL_UNITS.keys())}'))
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173 @validator('azimuthal_units', allow_reuse=True)
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174 def validate_azimuthal_units(cls, azimuthal_units):
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175 """
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176 Validate that `azimuthal_units` is one of the keys in the
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177 `pyFAI.units.AZIMUTHAL_UNITS` dictionary.
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178
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179 :param azimuthal_units: The string representing the unit to be validated.
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180 :type azimuthal_units: str
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181 :raises ValueError: If `azimuthal_units` is not one of the keys in `pyFAI.units.AZIMUTHAL_UNITS`
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182 :return: The original supplied value, if is one of the keys in `pyFAI.units.AZIMUTHAL_UNITS`.
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183 :rtype: str
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184 """
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185 if azimuthal_units in pyFAI.units.AZIMUTHAL_UNITS.keys():
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186 return(azimuthal_units)
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187 else:
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188 raise(ValueError(f'Invalid azimuthal units: {azimuthal_units}. Must be one of {", ".join(pyFAI.units.AZIMUTHAL_UNITS.keys())}'))
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189 def validate_range_max(range_name:str):
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190 """Validate the maximum value of an integration range.
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191
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192 :param range_name: The name of the integration range (e.g. radial, azimuthal).
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193 :type range_name: str
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194 :return: The callable that performs the validation.
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195 :rtype: callable
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196 """
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197 def _validate_range_max(cls, range_max, values):
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198 """Check if the maximum value of the integration range is greater than its minimum value.
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199
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200 :param range_max: The maximum value of the integration range.
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201 :type range_max: float
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202 :param values: The values of the other fields being validated.
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203 :type values: dict
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204 :raises ValueError: If the maximum value of the integration range is not greater than its minimum value.
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205 :return: The validated maximum range value
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206 :rtype: float
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207 """
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208 range_min = values.get(f'{range_name}_min')
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209 if range_min < range_max:
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210 return(range_max)
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211 else:
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212 raise(ValueError(f'Maximum value of integration range must be greater than minimum value of integration range ({range_name}_min={range_min}).'))
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213 return(_validate_range_max)
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214 _validate_radial_max = validator('radial_max', allow_reuse=True)(validate_range_max('radial'))
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215 _validate_azimuthal_max = validator('azimuthal_max', allow_reuse=True)(validate_range_max('azimuthal'))
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216 def validate_for_map_config(self, map_config:MapConfig):
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217 """
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218 Validate the existence of the detector data file for all scan points in `map_config`.
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219
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220 :param map_config: The `MapConfig` instance to validate against.
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221 :type map_config: MapConfig
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222 :raises RuntimeError: If a detector data file could not be found for a scan point occurring in `map_config`.
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223 :return: None
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224 :rtype: None
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225 """
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226 for detector in self.detectors:
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227 for scans in map_config.spec_scans:
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228 for scan_number in scans.scan_numbers:
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229 scanparser = scans.get_scanparser(scan_number)
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230 for scan_step_index in range(scanparser.spec_scan_npts):
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231 # Make sure the detector data file exists for all scan points
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232 try:
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233 detector_data_file = scanparser.get_detector_data_file(detector.prefix, scan_step_index)
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234 except:
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235 raise(RuntimeError(f'Could not find data file for detector prefix {detector.prefix} on scan number {scan_number} in spec file {scans.spec_file}'))
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236 def get_azimuthal_adjustments(self):
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237 """To enable a continuous range of integration in the azimuthal direction
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238 for radial and cake integration, obtain adjusted values for this
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239 `IntegrationConfig`'s `azimuthal_min` and `azimuthal_max` values, the
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240 angle amount by which those values were adjusted, and the proper location
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241 of the discontinuity in the azimuthal direction.
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242
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243 :return: Adjusted chi_min, adjusted chi_max, chi_offset, chi_discontinuity
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244 :rtype: tuple[float,float,float,float]
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245 """
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246 return(get_azimuthal_adjustments(self.azimuthal_min, self.azimuthal_max))
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247 def get_azimuthal_integrators(self):
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248 """Get a list of `AzimuthalIntegrator`s that correspond to the detector
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249 configurations in this instance of `IntegrationConfig`.
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250
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251 The returned `AzimuthalIntegrator`s are (if need be) artificially rotated
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252 in the azimuthal direction to achieve a continuous range of integration
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253 in the azimuthal direction.
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254
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255 :returns: A list of `AzimuthalIntegrator`s appropriate for use by this
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256 `IntegrationConfig` tool
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257 :rtype: list[pyFAI.azimuthalIntegrator.AzimuthalIntegrator]
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258 """
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259 chi_min, chi_max, chi_offset, chi_disc = self.get_azimuthal_adjustments()
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260 return(get_azimuthal_integrators(tuple([detector.poni_file for detector in self.detectors]), chi_offset=chi_offset))
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261 def get_multi_geometry_integrator(self):
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262 """Get a `MultiGeometry` integrator suitable for use by this instance of
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263 `IntegrationConfig`.
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264
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265 :return: A `MultiGeometry` integrator
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266 :rtype: pyFAI.multi_geometry.MultiGeometry
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267 """
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268 poni_files = tuple([detector.poni_file for detector in self.detectors])
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269 radial_range = (self.radial_min, self.radial_max)
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270 azimuthal_range = (self.azimuthal_min, self.azimuthal_max)
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271 return(get_multi_geometry_integrator(poni_files, self.radial_units, radial_range, azimuthal_range))
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272 def get_azimuthally_integrated_data(self, spec_scans:SpecScans, scan_number:int, scan_step_index:int):
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273 """Return azimuthally-integrated data for the scan step specified.
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274
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275 :param spec_scans: An instance of `SpecScans` containing the scan step requested.
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276 :type spec_scans: SpecScans
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277 :param scan_number: The number of the scan containing the scan step requested.
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278 :type scan_number: int
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279 :param scan_step_index: The index of the scan step requested.
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280 :type scan_step_index: int
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281 :return: A 1D array of azimuthally-integrated raw detector intensities.
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282 :rtype: np.ndarray
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283 """
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284 detector_data = spec_scans.get_detector_data(self.detectors, scan_number, scan_step_index)
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285 integrator = self.get_multi_geometry_integrator()
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286 lst_mask = [detector.mask_array for detector in self.detectors]
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287 result = integrator.integrate1d(detector_data, lst_mask=lst_mask, npt=self.radial_npt, error_model=self.error_model)
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288 if result.sigma is None:
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289 return(result.intensity)
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290 else:
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291 return(result.intensity, result.sigma)
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292 def get_radially_integrated_data(self, spec_scans:SpecScans, scan_number:int, scan_step_index:int):
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293 """Return radially-integrated data for the scan step specified.
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294
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295 :param spec_scans: An instance of `SpecScans` containing the scan step requested.
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296 :type spec_scans: SpecScans
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297 :param scan_number: The number of the scan containing the scan step requested.
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298 :type scan_number: int
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299 :param scan_step_index: The index of the scan step requested.
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300 :type scan_step_index: int
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301 :return: A 1D array of radially-integrated raw detector intensities.
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302 :rtype: np.ndarray
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303 """
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304 # Handle idiosyncracies of azimuthal ranges in pyFAI
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305 # Adjust chi ranges to get a continuous range of iintegrated data
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306 chi_min, chi_max, chi_offset, chi_disc = self.get_azimuthal_adjustments()
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307 # Perform radial integration on a detector-by-detector basis.
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308 I_each_detector = []
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309 variance_each_detector = []
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310 integrators = self.get_azimuthal_integrators()
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311 for i,(integrator,detector) in enumerate(zip(integrators,self.detectors)):
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312 detector_data = spec_scans.get_detector_data([detector], scan_number, scan_step_index)[0]
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313 result = integrator.integrate_radial(detector_data, self.azimuthal_npt,
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314 unit=self.azimuthal_units, azimuth_range=(chi_min,chi_max),
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315 radial_unit=self.radial_units, radial_range=(self.radial_min,self.radial_max),
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316 mask=detector.mask_array) #, error_model=self.error_model)
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317 I_each_detector.append(result.intensity)
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318 if result.sigma is not None:
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319 variance_each_detector.append(result.sigma**2)
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320 # Add the individual detectors' integrated intensities together
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321 I = np.nansum(I_each_detector, axis=0)
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322 # Ignore data at values of chi for which there was no data
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323 I = np.where(I==0, np.nan, I)
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324 if len(I_each_detector) != len(variance_each_detector):
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325 return(I)
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326 else:
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327 # Get the standard deviation of the summed detectors' intensities
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328 sigma = np.sqrt(np.nansum(variance_each_detector, axis=0))
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329 return(I, sigma)
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330 def get_cake_integrated_data(self, spec_scans:SpecScans, scan_number:int, scan_step_index:int):
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331 """Return cake-integrated data for the scan step specified.
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332
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333 :param spec_scans: An instance of `SpecScans` containing the scan step requested.
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334 :type spec_scans: SpecScans
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335 :param scan_number: The number of the scan containing the scan step requested.
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336 :type scan_number: int
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337 :param scan_step_index: The index of the scan step requested.
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338 :type scan_step_index: int
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339 :return: A 2D array of cake-integrated raw detector intensities.
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340 :rtype: np.ndarray
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341 """
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342 detector_data = spec_scans.get_detector_data(self.detectors, scan_number, scan_step_index)
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343 integrator = self.get_multi_geometry_integrator()
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344 lst_mask = [detector.mask_array for detector in self.detectors]
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345 result = integrator.integrate2d(detector_data, lst_mask=lst_mask,
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346 npt_rad=self.radial_npt, npt_azim=self.azimuthal_npt,
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347 method='bbox',
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348 error_model=self.error_model)
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349 if result.sigma is None:
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350 return(result.intensity)
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351 else:
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352 return(result.intensity, result.sigma)
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353 def get_integrated_data(self, spec_scans:SpecScans, scan_number:int, scan_step_index:int):
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354 """Return integrated data for the scan step specified.
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355
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356 :param spec_scans: An instance of `SpecScans` containing the scan step requested.
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357 :type spec_scans: SpecScans
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358 :param scan_number: The number of the scan containing the scan step requested.
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359 :type scan_number: int
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360 :param scan_step_index: The index of the scan step requested.
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361 :type scan_step_index: int
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362 :return: An array of integrated raw detector intensities.
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363 :rtype: np.ndarray
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364 """
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365 if self.integration_type == 'azimuthal':
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366 return(self.get_azimuthally_integrated_data(spec_scans, scan_number, scan_step_index))
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367 elif self.integration_type == 'radial':
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368 return(self.get_radially_integrated_data(spec_scans, scan_number, scan_step_index))
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369 elif self.integration_type == 'cake':
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370 return(self.get_cake_integrated_data(spec_scans, scan_number, scan_step_index))
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371
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372 @property
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373 def integrated_data_coordinates(self):
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374 """
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375 Return a dictionary of coordinate arrays for navigating the dimension(s)
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376 of the integrated data produced by this instance of `IntegrationConfig`.
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377
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378 :return: A dictionary with either one or two keys: 'azimuthal' and/or
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379 'radial', each of which points to a 1-D `numpy` array of coordinate
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380 values.
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381 :rtype: dict[str,np.ndarray]
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382 """
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383 if self.integration_type == 'azimuthal':
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384 return(get_integrated_data_coordinates(radial_range=(self.radial_min,self.radial_max),
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385 radial_npt=self.radial_npt))
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386 elif self.integration_type == 'radial':
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387 return(get_integrated_data_coordinates(azimuthal_range=(self.azimuthal_min,self.azimuthal_max),
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388 azimuthal_npt=self.azimuthal_npt))
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389 elif self.integration_type == 'cake':
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390 return(get_integrated_data_coordinates(radial_range=(self.radial_min,self.radial_max),
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391 radial_npt=self.radial_npt,
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392 azimuthal_range=(self.azimuthal_min,self.azimuthal_max),
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393 azimuthal_npt=self.azimuthal_npt))
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394 @property
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395 def integrated_data_dims(self):
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396 """Return a tuple of the coordinate labels for the integrated data
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397 produced by this instance of `IntegrationConfig`.
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398 """
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399 directions = list(self.integrated_data_coordinates.keys())
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400 dim_names = [getattr(self, f'{direction}_units') for direction in directions]
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401 return(dim_names)
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402 @property
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403 def integrated_data_shape(self):
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404 """Return a tuple representing the shape of the integrated data
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405 produced by this instance of `IntegrationConfig` for a single scan step.
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406 """
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407 return(tuple([len(coordinate_values) for coordinate_name,coordinate_values in self.integrated_data_coordinates.items()]))
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408
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409 @cache
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410 def get_azimuthal_adjustments(chi_min:float, chi_max:float):
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411 """
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412 Fix chi discontinuity at 180 degrees and return the adjusted chi range,
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413 offset, and discontinuty.
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414
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415 If the discontinuity is crossed, obtain the offset to artificially rotate
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416 detectors to achieve a continuous azimuthal integration range.
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417
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418 :param chi_min: The minimum value of the azimuthal range.
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419 :type chi_min: float
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420 :param chi_max: The maximum value of the azimuthal range.
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421 :type chi_max: float
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422 :return: The following four values: the adjusted minimum value of the
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423 azimuthal range, the adjusted maximum value of the azimuthal range, the
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424 value by which the chi angle was adjusted, the position of the chi
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425 discontinuity.
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426 """
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427 # Fix chi discontinuity at 180 degrees for now.
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428 chi_disc = 180
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429 # If the discontinuity is crossed, artificially rotate the detectors to
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430 # achieve a continuous azimuthal integration range
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431 if chi_min < chi_disc and chi_max > chi_disc:
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432 chi_offset = chi_max - chi_disc
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433 else:
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434 chi_offset = 0
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435 return(chi_min-chi_offset, chi_max-chi_offset, chi_offset, chi_disc)
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436 @cache
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437 def get_azimuthal_integrators(poni_files:tuple, chi_offset=0):
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438 """
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439 Return a list of `AzimuthalIntegrator` objects generated from PONI files.
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440
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441 :param poni_files: Tuple of strings, each string being a path to a PONI file. : tuple
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442 :type poni_files: tuple
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443 :param chi_offset: The angle in degrees by which the `AzimuthalIntegrator` objects will be rotated, defaults to 0.
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444 :type chi_offset: float, optional
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445 :return: List of `AzimuthalIntegrator` objects
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446 :rtype: list[pyFAI.azimuthalIntegrator.AzimuthalIntegrator]
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447 """
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448 ais = []
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449 for poni_file in poni_files:
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450 ai = copy.deepcopy(azimuthal_integrator(poni_file))
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451 ai.rot3 += chi_offset * np.pi/180
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452 ais.append(ai)
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453 return(ais)
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454 @cache
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455 def get_multi_geometry_integrator(poni_files:tuple, radial_unit:str, radial_range:tuple, azimuthal_range:tuple):
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456 """Return a `MultiGeometry` instance that can be used for azimuthal or cake
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457 integration.
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458
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459 :param poni_files: Tuple of PONI files that describe the detectors to be
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460 integrated.
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461 :type poni_files: tuple
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462 :param radial_unit: Unit to use for radial integration range.
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463 :type radial_unit: str
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464 :param radial_range: Tuple describing the range for radial integration.
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465 :type radial_range: tuple[float,float]
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466 :param azimuthal_range:Tuple describing the range for azimuthal integration.
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467 :type azimuthal_range: tuple[float,float]
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468 :return: `MultiGeometry` instance that can be used for azimuthal or cake
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469 integration.
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470 :rtype: pyFAI.multi_geometry.MultiGeometry
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471 """
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472 chi_min, chi_max, chi_offset, chi_disc = get_azimuthal_adjustments(*azimuthal_range)
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473 ais = copy.deepcopy(get_azimuthal_integrators(poni_files, chi_offset=chi_offset))
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474 multi_geometry = pyFAI.multi_geometry.MultiGeometry(ais,
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475 unit=radial_unit,
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476 radial_range=radial_range,
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477 azimuth_range=(chi_min,chi_max),
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478 wavelength=sum([ai.wavelength for ai in ais])/len(ais),
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479 chi_disc=chi_disc)
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480 return(multi_geometry)
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481 @cache
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482 def get_integrated_data_coordinates(azimuthal_range:tuple=None, azimuthal_npt:int=None, radial_range:tuple=None, radial_npt:int=None):
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483 """
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484 Return a dictionary of coordinate arrays for the specified radial and/or
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485 azimuthal integration ranges.
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486
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487 :param azimuthal_range: Tuple specifying the range of azimuthal angles over
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488 which to generate coordinates, in the format (min, max), defaults to
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489 None.
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490 :type azimuthal_range: tuple[float,float], optional
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491 :param azimuthal_npt: Number of azimuthal coordinate points to generate,
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492 defaults to None.
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493 :type azimuthal_npt: int, optional
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494 :param radial_range: Tuple specifying the range of radial distances over
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495 which to generate coordinates, in the format (min, max), defaults to
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496 None.
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497 :type radial_range: tuple[float,float], optional
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498 :param radial_npt: Number of radial coordinate points to generate, defaults
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499 to None.
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500 :type radial_npt: int, optional
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501 :return: A dictionary with either one or two keys: 'azimuthal' and/or
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502 'radial', each of which points to a 1-D `numpy` array of coordinate
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503 values.
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504 :rtype: dict[str,np.ndarray]
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505 """
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506 integrated_data_coordinates = {}
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507 if azimuthal_range is not None and azimuthal_npt is not None:
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508 integrated_data_coordinates['azimuthal'] = np.linspace(*azimuthal_range, azimuthal_npt)
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509 if radial_range is not None and radial_npt is not None:
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510 integrated_data_coordinates['radial'] = np.linspace(*radial_range, radial_npt)
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511 return(integrated_data_coordinates)