1 | """ |
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2 | Module that contains classes to hold information read from |
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3 | reduced data files. |
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4 | |
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5 | A good description of the data members can be found in |
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6 | the CanSAS 1D XML data format: |
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7 | |
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8 | http://www.smallangles.net/wgwiki/index.php/cansas1d_documentation |
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9 | """ |
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10 | ##################################################################### |
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11 | #This software was developed by the University of Tennessee as part of the |
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12 | #Distributed Data Analysis of Neutron Scattering Experiments (DANSE) |
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13 | #project funded by the US National Science Foundation. |
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14 | #See the license text in license.txt |
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15 | #copyright 2008, University of Tennessee |
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16 | ###################################################################### |
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17 | |
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18 | from __future__ import print_function |
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19 | |
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20 | #TODO: Keep track of data manipulation in the 'process' data structure. |
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21 | #TODO: This module should be independent of plottables. We should write |
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22 | # an adapter class for plottables when needed. |
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23 | |
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24 | #from sas.guitools.plottables import Data1D as plottable_1D |
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25 | from sas.sascalc.data_util.uncertainty import Uncertainty |
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26 | import numpy as np |
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27 | import math |
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28 | |
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29 | class plottable_1D(object): |
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30 | """ |
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31 | Data1D is a place holder for 1D plottables. |
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32 | """ |
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33 | # The presence of these should be mutually |
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34 | # exclusive with the presence of Qdev (dx) |
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35 | x = None |
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36 | y = None |
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37 | dx = None |
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38 | dy = None |
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39 | ## Slit smearing length |
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40 | dxl = None |
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41 | ## Slit smearing width |
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42 | dxw = None |
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43 | ## SESANS specific params (wavelengths for spin echo length calculation) |
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44 | lam = None |
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45 | dlam = None |
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46 | |
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47 | # Units |
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48 | _xaxis = '' |
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49 | _xunit = '' |
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50 | _yaxis = '' |
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51 | _yunit = '' |
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52 | |
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53 | def __init__(self, x, y, dx=None, dy=None, dxl=None, dxw=None, lam=None, dlam=None): |
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54 | self.x = np.asarray(x) |
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55 | self.y = np.asarray(y) |
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56 | if dx is not None: |
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57 | self.dx = np.asarray(dx) |
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58 | if dy is not None: |
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59 | self.dy = np.asarray(dy) |
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60 | if dxl is not None: |
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61 | self.dxl = np.asarray(dxl) |
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62 | if dxw is not None: |
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63 | self.dxw = np.asarray(dxw) |
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64 | if lam is not None: |
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65 | self.lam = np.asarray(lam) |
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66 | if dlam is not None: |
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67 | self.dlam = np.asarray(dlam) |
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68 | |
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69 | def xaxis(self, label, unit): |
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70 | """ |
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71 | set the x axis label and unit |
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72 | """ |
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73 | self._xaxis = label |
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74 | self._xunit = unit |
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75 | |
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76 | def yaxis(self, label, unit): |
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77 | """ |
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78 | set the y axis label and unit |
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79 | """ |
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80 | self._yaxis = label |
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81 | self._yunit = unit |
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82 | |
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83 | |
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84 | class plottable_2D(object): |
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85 | """ |
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86 | Data2D is a place holder for 2D plottables. |
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87 | """ |
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88 | xmin = None |
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89 | xmax = None |
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90 | ymin = None |
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91 | ymax = None |
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92 | data = None |
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93 | qx_data = None |
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94 | qy_data = None |
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95 | q_data = None |
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96 | err_data = None |
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97 | dqx_data = None |
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98 | dqy_data = None |
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99 | mask = None |
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100 | |
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101 | # Units |
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102 | _xaxis = '' |
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103 | _xunit = '' |
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104 | _yaxis = '' |
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105 | _yunit = '' |
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106 | _zaxis = '' |
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107 | _zunit = '' |
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108 | |
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109 | def __init__(self, data=None, err_data=None, qx_data=None, |
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110 | qy_data=None, q_data=None, mask=None, |
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111 | dqx_data=None, dqy_data=None): |
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112 | self.data = np.asarray(data) |
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113 | self.qx_data = np.asarray(qx_data) |
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114 | self.qy_data = np.asarray(qy_data) |
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115 | self.q_data = np.asarray(q_data) |
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116 | self.mask = np.asarray(mask) |
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117 | self.err_data = np.asarray(err_data) |
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118 | if dqx_data is not None: |
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119 | self.dqx_data = np.asarray(dqx_data) |
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120 | if dqy_data is not None: |
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121 | self.dqy_data = np.asarray(dqy_data) |
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122 | |
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123 | def xaxis(self, label, unit): |
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124 | """ |
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125 | set the x axis label and unit |
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126 | """ |
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127 | self._xaxis = label |
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128 | self._xunit = unit |
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129 | |
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130 | def yaxis(self, label, unit): |
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131 | """ |
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132 | set the y axis label and unit |
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133 | """ |
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134 | self._yaxis = label |
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135 | self._yunit = unit |
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136 | |
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137 | def zaxis(self, label, unit): |
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138 | """ |
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139 | set the z axis label and unit |
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140 | """ |
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141 | self._zaxis = label |
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142 | self._zunit = unit |
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143 | |
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144 | |
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145 | class Vector(object): |
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146 | """ |
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147 | Vector class to hold multi-dimensional objects |
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148 | """ |
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149 | ## x component |
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150 | x = None |
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151 | ## y component |
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152 | y = None |
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153 | ## z component |
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154 | z = None |
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155 | |
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156 | def __init__(self, x=None, y=None, z=None): |
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157 | """ |
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158 | Initialization. Components that are not |
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159 | set a set to None by default. |
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160 | |
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161 | :param x: x component |
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162 | :param y: y component |
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163 | :param z: z component |
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164 | """ |
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165 | self.x = x |
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166 | self.y = y |
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167 | self.z = z |
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168 | |
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169 | def __str__(self): |
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170 | msg = "x = %s\ty = %s\tz = %s" % (str(self.x), str(self.y), str(self.z)) |
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171 | return msg |
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172 | |
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173 | |
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174 | class Detector(object): |
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175 | """ |
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176 | Class to hold detector information |
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177 | """ |
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178 | ## Name of the instrument [string] |
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179 | name = None |
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180 | ## Sample to detector distance [float] [mm] |
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181 | distance = None |
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182 | distance_unit = 'mm' |
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183 | ## Offset of this detector position in X, Y, |
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184 | #(and Z if necessary) [Vector] [mm] |
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185 | offset = None |
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186 | offset_unit = 'm' |
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187 | ## Orientation (rotation) of this detector in roll, |
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188 | # pitch, and yaw [Vector] [degrees] |
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189 | orientation = None |
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190 | orientation_unit = 'degree' |
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191 | ## Center of the beam on the detector in X and Y |
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192 | #(and Z if necessary) [Vector] [mm] |
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193 | beam_center = None |
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194 | beam_center_unit = 'mm' |
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195 | ## Pixel size in X, Y, (and Z if necessary) [Vector] [mm] |
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196 | pixel_size = None |
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197 | pixel_size_unit = 'mm' |
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198 | ## Slit length of the instrument for this detector.[float] [mm] |
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199 | slit_length = None |
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200 | slit_length_unit = 'mm' |
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201 | |
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202 | def __init__(self): |
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203 | """ |
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204 | Initialize class attribute that are objects... |
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205 | """ |
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206 | self.offset = Vector() |
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207 | self.orientation = Vector() |
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208 | self.beam_center = Vector() |
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209 | self.pixel_size = Vector() |
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210 | |
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211 | def __str__(self): |
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212 | _str = "Detector:\n" |
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213 | _str += " Name: %s\n" % self.name |
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214 | _str += " Distance: %s [%s]\n" % \ |
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215 | (str(self.distance), str(self.distance_unit)) |
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216 | _str += " Offset: %s [%s]\n" % \ |
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217 | (str(self.offset), str(self.offset_unit)) |
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218 | _str += " Orientation: %s [%s]\n" % \ |
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219 | (str(self.orientation), str(self.orientation_unit)) |
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220 | _str += " Beam center: %s [%s]\n" % \ |
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221 | (str(self.beam_center), str(self.beam_center_unit)) |
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222 | _str += " Pixel size: %s [%s]\n" % \ |
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223 | (str(self.pixel_size), str(self.pixel_size_unit)) |
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224 | _str += " Slit length: %s [%s]\n" % \ |
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225 | (str(self.slit_length), str(self.slit_length_unit)) |
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226 | return _str |
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227 | |
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228 | |
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229 | class Aperture(object): |
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230 | ## Name |
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231 | name = None |
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232 | ## Type |
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233 | type = None |
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234 | ## Size name |
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235 | size_name = None |
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236 | ## Aperture size [Vector] |
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237 | size = None |
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238 | size_unit = 'mm' |
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239 | ## Aperture distance [float] |
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240 | distance = None |
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241 | distance_unit = 'mm' |
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242 | |
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243 | def __init__(self): |
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244 | self.size = Vector() |
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245 | |
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246 | |
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247 | class Collimation(object): |
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248 | """ |
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249 | Class to hold collimation information |
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250 | """ |
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251 | ## Name |
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252 | name = None |
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253 | ## Length [float] [mm] |
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254 | length = None |
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255 | length_unit = 'mm' |
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256 | ## Aperture |
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257 | aperture = None |
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258 | |
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259 | def __init__(self): |
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260 | self.aperture = [] |
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261 | |
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262 | def __str__(self): |
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263 | _str = "Collimation:\n" |
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264 | _str += " Length: %s [%s]\n" % \ |
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265 | (str(self.length), str(self.length_unit)) |
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266 | for item in self.aperture: |
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267 | _str += " Aperture size:%s [%s]\n" % \ |
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268 | (str(item.size), str(item.size_unit)) |
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269 | _str += " Aperture_dist:%s [%s]\n" % \ |
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270 | (str(item.distance), str(item.distance_unit)) |
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271 | return _str |
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272 | |
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273 | |
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274 | class Source(object): |
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275 | """ |
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276 | Class to hold source information |
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277 | """ |
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278 | ## Name |
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279 | name = None |
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280 | ## Radiation type [string] |
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281 | radiation = None |
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282 | ## Beam size name |
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283 | beam_size_name = None |
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284 | ## Beam size [Vector] [mm] |
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285 | beam_size = None |
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286 | beam_size_unit = 'mm' |
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287 | ## Beam shape [string] |
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288 | beam_shape = None |
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289 | ## Wavelength [float] [Angstrom] |
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290 | wavelength = None |
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291 | wavelength_unit = 'A' |
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292 | ## Minimum wavelength [float] [Angstrom] |
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293 | wavelength_min = None |
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294 | wavelength_min_unit = 'nm' |
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295 | ## Maximum wavelength [float] [Angstrom] |
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296 | wavelength_max = None |
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297 | wavelength_max_unit = 'nm' |
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298 | ## Wavelength spread [float] [Angstrom] |
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299 | wavelength_spread = None |
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300 | wavelength_spread_unit = 'percent' |
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301 | |
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302 | def __init__(self): |
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303 | self.beam_size = Vector() |
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304 | |
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305 | def __str__(self): |
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306 | _str = "Source:\n" |
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307 | _str += " Radiation: %s\n" % str(self.radiation) |
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308 | _str += " Shape: %s\n" % str(self.beam_shape) |
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309 | _str += " Wavelength: %s [%s]\n" % \ |
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310 | (str(self.wavelength), str(self.wavelength_unit)) |
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311 | _str += " Waveln_min: %s [%s]\n" % \ |
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312 | (str(self.wavelength_min), str(self.wavelength_min_unit)) |
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313 | _str += " Waveln_max: %s [%s]\n" % \ |
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314 | (str(self.wavelength_max), str(self.wavelength_max_unit)) |
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315 | _str += " Waveln_spread:%s [%s]\n" % \ |
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316 | (str(self.wavelength_spread), str(self.wavelength_spread_unit)) |
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317 | _str += " Beam_size: %s [%s]\n" % \ |
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318 | (str(self.beam_size), str(self.beam_size_unit)) |
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319 | return _str |
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320 | |
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321 | |
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322 | """ |
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323 | Definitions of radiation types |
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324 | """ |
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325 | NEUTRON = 'neutron' |
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326 | XRAY = 'x-ray' |
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327 | MUON = 'muon' |
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328 | ELECTRON = 'electron' |
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329 | |
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330 | |
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331 | class Sample(object): |
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332 | """ |
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333 | Class to hold the sample description |
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334 | """ |
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335 | ## Short name for sample |
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336 | name = '' |
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337 | ## ID |
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338 | ID = '' |
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339 | ## Thickness [float] [mm] |
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340 | thickness = None |
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341 | thickness_unit = 'mm' |
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342 | ## Transmission [float] [fraction] |
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343 | transmission = None |
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344 | ## Temperature [float] [No Default] |
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345 | temperature = None |
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346 | temperature_unit = None |
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347 | ## Position [Vector] [mm] |
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348 | position = None |
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349 | position_unit = 'mm' |
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350 | ## Orientation [Vector] [degrees] |
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351 | orientation = None |
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352 | orientation_unit = 'degree' |
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353 | ## Details |
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354 | details = None |
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355 | ## SESANS zacceptance |
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356 | zacceptance = (0,"") |
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357 | yacceptance = (0,"") |
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358 | |
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359 | def __init__(self): |
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360 | self.position = Vector() |
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361 | self.orientation = Vector() |
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362 | self.details = [] |
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363 | |
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364 | def __str__(self): |
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365 | _str = "Sample:\n" |
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366 | _str += " ID: %s\n" % str(self.ID) |
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367 | _str += " Transmission: %s\n" % str(self.transmission) |
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368 | _str += " Thickness: %s [%s]\n" % \ |
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369 | (str(self.thickness), str(self.thickness_unit)) |
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370 | _str += " Temperature: %s [%s]\n" % \ |
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371 | (str(self.temperature), str(self.temperature_unit)) |
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372 | _str += " Position: %s [%s]\n" % \ |
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373 | (str(self.position), str(self.position_unit)) |
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374 | _str += " Orientation: %s [%s]\n" % \ |
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375 | (str(self.orientation), str(self.orientation_unit)) |
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376 | |
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377 | _str += " Details:\n" |
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378 | for item in self.details: |
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379 | _str += " %s\n" % item |
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380 | |
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381 | return _str |
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382 | |
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383 | |
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384 | class Process(object): |
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385 | """ |
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386 | Class that holds information about the processes |
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387 | performed on the data. |
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388 | """ |
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389 | name = '' |
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390 | date = '' |
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391 | description = '' |
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392 | term = None |
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393 | notes = None |
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394 | |
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395 | def __init__(self): |
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396 | self.term = [] |
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397 | self.notes = [] |
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398 | |
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399 | def is_empty(self): |
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400 | """ |
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401 | Return True if the object is empty |
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402 | """ |
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403 | return len(self.name) == 0 and len(self.date) == 0 and len(self.description) == 0 \ |
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404 | and len(self.term) == 0 and len(self.notes) == 0 |
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405 | |
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406 | def single_line_desc(self): |
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407 | """ |
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408 | Return a single line string representing the process |
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409 | """ |
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410 | return "%s %s %s" % (self.name, self.date, self.description) |
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411 | |
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412 | def __str__(self): |
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413 | _str = "Process:\n" |
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414 | _str += " Name: %s\n" % self.name |
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415 | _str += " Date: %s\n" % self.date |
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416 | _str += " Description: %s\n" % self.description |
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417 | for item in self.term: |
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418 | _str += " Term: %s\n" % item |
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419 | for item in self.notes: |
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420 | _str += " Note: %s\n" % item |
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421 | return _str |
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422 | |
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423 | |
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424 | class TransmissionSpectrum(object): |
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425 | """ |
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426 | Class that holds information about transmission spectrum |
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427 | for white beams and spallation sources. |
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428 | """ |
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429 | name = '' |
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430 | timestamp = '' |
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431 | ## Wavelength (float) [A] |
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432 | wavelength = None |
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433 | wavelength_unit = 'A' |
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434 | ## Transmission (float) [unit less] |
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435 | transmission = None |
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436 | transmission_unit = '' |
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437 | ## Transmission Deviation (float) [unit less] |
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438 | transmission_deviation = None |
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439 | transmission_deviation_unit = '' |
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440 | |
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441 | def __init__(self): |
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442 | self.wavelength = [] |
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443 | self.transmission = [] |
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444 | self.transmission_deviation = [] |
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445 | |
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446 | def __str__(self): |
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447 | _str = "Transmission Spectrum:\n" |
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448 | _str += " Name: \t{0}\n".format(self.name) |
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449 | _str += " Timestamp: \t{0}\n".format(self.timestamp) |
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450 | _str += " Wavelength unit: \t{0}\n".format(self.wavelength_unit) |
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451 | _str += " Transmission unit:\t{0}\n".format(self.transmission_unit) |
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452 | _str += " Trans. Dev. unit: \t{0}\n".format(\ |
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453 | self.transmission_deviation_unit) |
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454 | length_list = [len(self.wavelength), len(self.transmission), \ |
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455 | len(self.transmission_deviation)] |
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456 | _str += " Number of Pts: \t{0}\n".format(max(length_list)) |
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457 | return _str |
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458 | |
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459 | |
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460 | class DataInfo(object): |
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461 | """ |
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462 | Class to hold the data read from a file. |
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463 | It includes four blocks of data for the |
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464 | instrument description, the sample description, |
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465 | the data itself and any other meta data. |
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466 | """ |
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467 | ## Title |
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468 | title = '' |
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469 | ## Run number |
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470 | run = None |
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471 | ## Run name |
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472 | run_name = None |
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473 | ## File name |
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474 | filename = '' |
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475 | ## Notes |
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476 | notes = None |
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477 | ## Processes (Action on the data) |
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478 | process = None |
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479 | ## Instrument name |
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480 | instrument = '' |
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481 | ## Detector information |
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482 | detector = None |
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483 | ## Sample information |
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484 | sample = None |
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485 | ## Source information |
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486 | source = None |
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487 | ## Collimation information |
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488 | collimation = None |
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489 | ## Transmission Spectrum INfo |
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490 | trans_spectrum = None |
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491 | ## Additional meta-data |
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492 | meta_data = None |
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493 | ## Loading errors |
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494 | errors = None |
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495 | ## SESANS data check |
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496 | isSesans = None |
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497 | |
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498 | |
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499 | def __init__(self): |
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500 | """ |
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501 | Initialization |
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502 | """ |
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503 | ## Title |
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504 | self.title = '' |
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505 | ## Run number |
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506 | self.run = [] |
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507 | self.run_name = {} |
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508 | ## File name |
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509 | self.filename = '' |
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510 | ## Notes |
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511 | self.notes = [] |
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512 | ## Processes (Action on the data) |
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513 | self.process = [] |
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514 | ## Instrument name |
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515 | self.instrument = '' |
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516 | ## Detector information |
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517 | self.detector = [] |
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518 | ## Sample information |
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519 | self.sample = Sample() |
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520 | ## Source information |
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521 | self.source = Source() |
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522 | ## Collimation information |
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523 | self.collimation = [] |
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524 | ## Transmission Spectrum |
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525 | self.trans_spectrum = [] |
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526 | ## Additional meta-data |
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527 | self.meta_data = {} |
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528 | ## Loading errors |
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529 | self.errors = [] |
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530 | ## SESANS data check |
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531 | self.isSesans = False |
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532 | |
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533 | def append_empty_process(self): |
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534 | """ |
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535 | """ |
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536 | self.process.append(Process()) |
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537 | |
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538 | def add_notes(self, message=""): |
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539 | """ |
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540 | Add notes to datainfo |
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541 | """ |
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542 | self.notes.append(message) |
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543 | |
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544 | def __str__(self): |
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545 | """ |
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546 | Nice printout |
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547 | """ |
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548 | _str = "File: %s\n" % self.filename |
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549 | _str += "Title: %s\n" % self.title |
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550 | _str += "Run: %s\n" % str(self.run) |
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551 | _str += "SESANS: %s\n" % str(self.isSesans) |
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552 | _str += "Instrument: %s\n" % str(self.instrument) |
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553 | _str += "%s\n" % str(self.sample) |
---|
554 | _str += "%s\n" % str(self.source) |
---|
555 | for item in self.detector: |
---|
556 | _str += "%s\n" % str(item) |
---|
557 | for item in self.collimation: |
---|
558 | _str += "%s\n" % str(item) |
---|
559 | for item in self.process: |
---|
560 | _str += "%s\n" % str(item) |
---|
561 | for item in self.notes: |
---|
562 | _str += "%s\n" % str(item) |
---|
563 | for item in self.trans_spectrum: |
---|
564 | _str += "%s\n" % str(item) |
---|
565 | return _str |
---|
566 | |
---|
567 | # Private method to perform operation. Not implemented for DataInfo, |
---|
568 | # but should be implemented for each data class inherited from DataInfo |
---|
569 | # that holds actual data (ex.: Data1D) |
---|
570 | def _perform_operation(self, other, operation): |
---|
571 | """ |
---|
572 | Private method to perform operation. Not implemented for DataInfo, |
---|
573 | but should be implemented for each data class inherited from DataInfo |
---|
574 | that holds actual data (ex.: Data1D) |
---|
575 | """ |
---|
576 | return NotImplemented |
---|
577 | |
---|
578 | def _perform_union(self, other): |
---|
579 | """ |
---|
580 | Private method to perform union operation. Not implemented for DataInfo, |
---|
581 | but should be implemented for each data class inherited from DataInfo |
---|
582 | that holds actual data (ex.: Data1D) |
---|
583 | """ |
---|
584 | return NotImplemented |
---|
585 | |
---|
586 | def __add__(self, other): |
---|
587 | """ |
---|
588 | Add two data sets |
---|
589 | |
---|
590 | :param other: data set to add to the current one |
---|
591 | :return: new data set |
---|
592 | :raise ValueError: raised when two data sets are incompatible |
---|
593 | """ |
---|
594 | def operation(a, b): |
---|
595 | return a + b |
---|
596 | return self._perform_operation(other, operation) |
---|
597 | |
---|
598 | def __radd__(self, other): |
---|
599 | """ |
---|
600 | Add two data sets |
---|
601 | |
---|
602 | :param other: data set to add to the current one |
---|
603 | :return: new data set |
---|
604 | :raise ValueError: raised when two data sets are incompatible |
---|
605 | """ |
---|
606 | def operation(a, b): |
---|
607 | return b + a |
---|
608 | return self._perform_operation(other, operation) |
---|
609 | |
---|
610 | def __sub__(self, other): |
---|
611 | """ |
---|
612 | Subtract two data sets |
---|
613 | |
---|
614 | :param other: data set to subtract from the current one |
---|
615 | :return: new data set |
---|
616 | :raise ValueError: raised when two data sets are incompatible |
---|
617 | """ |
---|
618 | def operation(a, b): |
---|
619 | return a - b |
---|
620 | return self._perform_operation(other, operation) |
---|
621 | |
---|
622 | def __rsub__(self, other): |
---|
623 | """ |
---|
624 | Subtract two data sets |
---|
625 | |
---|
626 | :param other: data set to subtract from the current one |
---|
627 | :return: new data set |
---|
628 | :raise ValueError: raised when two data sets are incompatible |
---|
629 | """ |
---|
630 | def operation(a, b): |
---|
631 | return b - a |
---|
632 | return self._perform_operation(other, operation) |
---|
633 | |
---|
634 | def __mul__(self, other): |
---|
635 | """ |
---|
636 | Multiply two data sets |
---|
637 | |
---|
638 | :param other: data set to subtract from the current one |
---|
639 | :return: new data set |
---|
640 | :raise ValueError: raised when two data sets are incompatible |
---|
641 | """ |
---|
642 | def operation(a, b): |
---|
643 | return a * b |
---|
644 | return self._perform_operation(other, operation) |
---|
645 | |
---|
646 | def __rmul__(self, other): |
---|
647 | """ |
---|
648 | Multiply two data sets |
---|
649 | |
---|
650 | :param other: data set to subtract from the current one |
---|
651 | :return: new data set |
---|
652 | :raise ValueError: raised when two data sets are incompatible |
---|
653 | """ |
---|
654 | def operation(a, b): |
---|
655 | return b * a |
---|
656 | return self._perform_operation(other, operation) |
---|
657 | |
---|
658 | def __div__(self, other): |
---|
659 | """ |
---|
660 | Divided a data set by another |
---|
661 | |
---|
662 | :param other: data set that the current one is divided by |
---|
663 | :return: new data set |
---|
664 | :raise ValueError: raised when two data sets are incompatible |
---|
665 | """ |
---|
666 | def operation(a, b): |
---|
667 | return a/b |
---|
668 | return self._perform_operation(other, operation) |
---|
669 | |
---|
670 | def __rdiv__(self, other): |
---|
671 | """ |
---|
672 | Divided a data set by another |
---|
673 | |
---|
674 | :param other: data set that the current one is divided by |
---|
675 | :return: new data set |
---|
676 | :raise ValueError: raised when two data sets are incompatible |
---|
677 | """ |
---|
678 | def operation(a, b): |
---|
679 | return b/a |
---|
680 | return self._perform_operation(other, operation) |
---|
681 | |
---|
682 | def __or__(self, other): |
---|
683 | """ |
---|
684 | Union a data set with another |
---|
685 | |
---|
686 | :param other: data set to be unified |
---|
687 | :return: new data set |
---|
688 | :raise ValueError: raised when two data sets are incompatible |
---|
689 | """ |
---|
690 | return self._perform_union(other) |
---|
691 | |
---|
692 | def __ror__(self, other): |
---|
693 | """ |
---|
694 | Union a data set with another |
---|
695 | |
---|
696 | :param other: data set to be unified |
---|
697 | :return: new data set |
---|
698 | :raise ValueError: raised when two data sets are incompatible |
---|
699 | """ |
---|
700 | return self._perform_union(other) |
---|
701 | |
---|
702 | class Data1D(plottable_1D, DataInfo): |
---|
703 | """ |
---|
704 | 1D data class |
---|
705 | """ |
---|
706 | def __init__(self, x=None, y=None, dx=None, dy=None, lam=None, dlam=None, isSesans=None): |
---|
707 | DataInfo.__init__(self) |
---|
708 | plottable_1D.__init__(self, x, y, dx, dy,None, None, lam, dlam) |
---|
709 | self.isSesans = isSesans |
---|
710 | try: |
---|
711 | if self.isSesans: # the data is SESANS |
---|
712 | self.x_unit = 'A' |
---|
713 | self.y_unit = 'pol' |
---|
714 | elif not self.isSesans: # the data is SANS |
---|
715 | self.x_unit = '1/A' |
---|
716 | self.y_unit = '1/cm' |
---|
717 | except: # the data is not recognized/supported, and the user is notified |
---|
718 | raise TypeError('data not recognized, check documentation for supported 1D data formats') |
---|
719 | |
---|
720 | def __str__(self): |
---|
721 | """ |
---|
722 | Nice printout |
---|
723 | """ |
---|
724 | _str = "%s\n" % DataInfo.__str__(self) |
---|
725 | _str += "Data:\n" |
---|
726 | _str += " Type: %s\n" % self.__class__.__name__ |
---|
727 | _str += " X-axis: %s\t[%s]\n" % (self._xaxis, self._xunit) |
---|
728 | _str += " Y-axis: %s\t[%s]\n" % (self._yaxis, self._yunit) |
---|
729 | _str += " Length: %g\n" % len(self.x) |
---|
730 | return _str |
---|
731 | |
---|
732 | def is_slit_smeared(self): |
---|
733 | """ |
---|
734 | Check whether the data has slit smearing information |
---|
735 | :return: True is slit smearing info is present, False otherwise |
---|
736 | """ |
---|
737 | def _check(v): |
---|
738 | if (v.__class__ == list or v.__class__ == np.ndarray) \ |
---|
739 | and len(v) > 0 and min(v) > 0: |
---|
740 | return True |
---|
741 | return False |
---|
742 | return _check(self.dxl) or _check(self.dxw) |
---|
743 | |
---|
744 | def clone_without_data(self, length=0, clone=None): |
---|
745 | """ |
---|
746 | Clone the current object, without copying the data (which |
---|
747 | will be filled out by a subsequent operation). |
---|
748 | The data arrays will be initialized to zero. |
---|
749 | |
---|
750 | :param length: length of the data array to be initialized |
---|
751 | :param clone: if provided, the data will be copied to clone |
---|
752 | """ |
---|
753 | from copy import deepcopy |
---|
754 | |
---|
755 | if clone is None or not issubclass(clone.__class__, Data1D): |
---|
756 | x = np.zeros(length) |
---|
757 | dx = np.zeros(length) |
---|
758 | y = np.zeros(length) |
---|
759 | dy = np.zeros(length) |
---|
760 | lam = np.zeros(length) |
---|
761 | dlam = np.zeros(length) |
---|
762 | clone = Data1D(x, y, lam=lam, dx=dx, dy=dy, dlam=dlam) |
---|
763 | |
---|
764 | clone.title = self.title |
---|
765 | clone.run = self.run |
---|
766 | clone.filename = self.filename |
---|
767 | clone.instrument = self.instrument |
---|
768 | clone.notes = deepcopy(self.notes) |
---|
769 | clone.process = deepcopy(self.process) |
---|
770 | clone.detector = deepcopy(self.detector) |
---|
771 | clone.sample = deepcopy(self.sample) |
---|
772 | clone.source = deepcopy(self.source) |
---|
773 | clone.collimation = deepcopy(self.collimation) |
---|
774 | clone.trans_spectrum = deepcopy(self.trans_spectrum) |
---|
775 | clone.meta_data = deepcopy(self.meta_data) |
---|
776 | clone.errors = deepcopy(self.errors) |
---|
777 | clone.isSesans = self.isSesans |
---|
778 | |
---|
779 | return clone |
---|
780 | |
---|
781 | def _validity_check(self, other): |
---|
782 | """ |
---|
783 | Checks that the data lengths are compatible. |
---|
784 | Checks that the x vectors are compatible. |
---|
785 | Returns errors vectors equal to original |
---|
786 | errors vectors if they were present or vectors |
---|
787 | of zeros when none was found. |
---|
788 | |
---|
789 | :param other: other data set for operation |
---|
790 | :return: dy for self, dy for other [numpy arrays] |
---|
791 | :raise ValueError: when lengths are not compatible |
---|
792 | """ |
---|
793 | dy_other = None |
---|
794 | if isinstance(other, Data1D): |
---|
795 | # Check that data lengths are the same |
---|
796 | if len(self.x) != len(other.x) or \ |
---|
797 | len(self.y) != len(other.y): |
---|
798 | msg = "Unable to perform operation: data length are not equal" |
---|
799 | raise ValueError(msg) |
---|
800 | # Here we could also extrapolate between data points |
---|
801 | TOLERANCE = 0.01 |
---|
802 | for i in range(len(self.x)): |
---|
803 | if math.fabs((self.x[i] - other.x[i])/self.x[i]) > TOLERANCE: |
---|
804 | msg = "Incompatible data sets: x-values do not match" |
---|
805 | raise ValueError(msg) |
---|
806 | |
---|
807 | # Check that the other data set has errors, otherwise |
---|
808 | # create zero vector |
---|
809 | dy_other = other.dy |
---|
810 | if other.dy is None or (len(other.dy) != len(other.y)): |
---|
811 | dy_other = np.zeros(len(other.y)) |
---|
812 | |
---|
813 | # Check that we have errors, otherwise create zero vector |
---|
814 | dy = self.dy |
---|
815 | if self.dy is None or (len(self.dy) != len(self.y)): |
---|
816 | dy = np.zeros(len(self.y)) |
---|
817 | |
---|
818 | return dy, dy_other |
---|
819 | |
---|
820 | def _perform_operation(self, other, operation): |
---|
821 | """ |
---|
822 | """ |
---|
823 | # First, check the data compatibility |
---|
824 | dy, dy_other = self._validity_check(other) |
---|
825 | result = self.clone_without_data(len(self.x)) |
---|
826 | if self.dxw is None: |
---|
827 | result.dxw = None |
---|
828 | else: |
---|
829 | result.dxw = np.zeros(len(self.x)) |
---|
830 | if self.dxl is None: |
---|
831 | result.dxl = None |
---|
832 | else: |
---|
833 | result.dxl = np.zeros(len(self.x)) |
---|
834 | |
---|
835 | for i in range(len(self.x)): |
---|
836 | result.x[i] = self.x[i] |
---|
837 | if self.dx is not None and len(self.x) == len(self.dx): |
---|
838 | result.dx[i] = self.dx[i] |
---|
839 | if self.dxw is not None and len(self.x) == len(self.dxw): |
---|
840 | result.dxw[i] = self.dxw[i] |
---|
841 | if self.dxl is not None and len(self.x) == len(self.dxl): |
---|
842 | result.dxl[i] = self.dxl[i] |
---|
843 | |
---|
844 | a = Uncertainty(self.y[i], dy[i]**2) |
---|
845 | if isinstance(other, Data1D): |
---|
846 | b = Uncertainty(other.y[i], dy_other[i]**2) |
---|
847 | if other.dx is not None: |
---|
848 | result.dx[i] *= self.dx[i] |
---|
849 | result.dx[i] += (other.dx[i]**2) |
---|
850 | result.dx[i] /= 2 |
---|
851 | result.dx[i] = math.sqrt(result.dx[i]) |
---|
852 | if result.dxl is not None and other.dxl is not None: |
---|
853 | result.dxl[i] *= self.dxl[i] |
---|
854 | result.dxl[i] += (other.dxl[i]**2) |
---|
855 | result.dxl[i] /= 2 |
---|
856 | result.dxl[i] = math.sqrt(result.dxl[i]) |
---|
857 | else: |
---|
858 | b = other |
---|
859 | |
---|
860 | output = operation(a, b) |
---|
861 | result.y[i] = output.x |
---|
862 | result.dy[i] = math.sqrt(math.fabs(output.variance)) |
---|
863 | return result |
---|
864 | |
---|
865 | def _validity_check_union(self, other): |
---|
866 | """ |
---|
867 | Checks that the data lengths are compatible. |
---|
868 | Checks that the x vectors are compatible. |
---|
869 | Returns errors vectors equal to original |
---|
870 | errors vectors if they were present or vectors |
---|
871 | of zeros when none was found. |
---|
872 | |
---|
873 | :param other: other data set for operation |
---|
874 | :return: bool |
---|
875 | :raise ValueError: when data types are not compatible |
---|
876 | """ |
---|
877 | if not isinstance(other, Data1D): |
---|
878 | msg = "Unable to perform operation: different types of data set" |
---|
879 | raise ValueError(msg) |
---|
880 | return True |
---|
881 | |
---|
882 | def _perform_union(self, other): |
---|
883 | """ |
---|
884 | """ |
---|
885 | # First, check the data compatibility |
---|
886 | self._validity_check_union(other) |
---|
887 | result = self.clone_without_data(len(self.x) + len(other.x)) |
---|
888 | if self.dy is None or other.dy is None: |
---|
889 | result.dy = None |
---|
890 | else: |
---|
891 | result.dy = np.zeros(len(self.x) + len(other.x)) |
---|
892 | if self.dx is None or other.dx is None: |
---|
893 | result.dx = None |
---|
894 | else: |
---|
895 | result.dx = np.zeros(len(self.x) + len(other.x)) |
---|
896 | if self.dxw is None or other.dxw is None: |
---|
897 | result.dxw = None |
---|
898 | else: |
---|
899 | result.dxw = np.zeros(len(self.x) + len(other.x)) |
---|
900 | if self.dxl is None or other.dxl is None: |
---|
901 | result.dxl = None |
---|
902 | else: |
---|
903 | result.dxl = np.zeros(len(self.x) + len(other.x)) |
---|
904 | |
---|
905 | result.x = np.append(self.x, other.x) |
---|
906 | #argsorting |
---|
907 | ind = np.argsort(result.x) |
---|
908 | result.x = result.x[ind] |
---|
909 | result.y = np.append(self.y, other.y) |
---|
910 | result.y = result.y[ind] |
---|
911 | if result.dy is not None: |
---|
912 | result.dy = np.append(self.dy, other.dy) |
---|
913 | result.dy = result.dy[ind] |
---|
914 | if result.dx is not None: |
---|
915 | result.dx = np.append(self.dx, other.dx) |
---|
916 | result.dx = result.dx[ind] |
---|
917 | if result.dxw is not None: |
---|
918 | result.dxw = np.append(self.dxw, other.dxw) |
---|
919 | result.dxw = result.dxw[ind] |
---|
920 | if result.dxl is not None: |
---|
921 | result.dxl = np.append(self.dxl, other.dxl) |
---|
922 | result.dxl = result.dxl[ind] |
---|
923 | return result |
---|
924 | |
---|
925 | |
---|
926 | class Data2D(plottable_2D, DataInfo): |
---|
927 | """ |
---|
928 | 2D data class |
---|
929 | """ |
---|
930 | ## Units for Q-values |
---|
931 | Q_unit = '1/A' |
---|
932 | ## Units for I(Q) values |
---|
933 | I_unit = '1/cm' |
---|
934 | ## Vector of Q-values at the center of each bin in x |
---|
935 | x_bins = None |
---|
936 | ## Vector of Q-values at the center of each bin in y |
---|
937 | y_bins = None |
---|
938 | ## No 2D SESANS data as of yet. Always set it to False |
---|
939 | isSesans = False |
---|
940 | |
---|
941 | def __init__(self, data=None, err_data=None, qx_data=None, |
---|
942 | qy_data=None, q_data=None, mask=None, |
---|
943 | dqx_data=None, dqy_data=None): |
---|
944 | DataInfo.__init__(self) |
---|
945 | plottable_2D.__init__(self, data, err_data, qx_data, |
---|
946 | qy_data, q_data, mask, dqx_data, dqy_data) |
---|
947 | self.y_bins = [] |
---|
948 | self.x_bins = [] |
---|
949 | |
---|
950 | if len(self.detector) > 0: |
---|
951 | raise RuntimeError("Data2D: Detector bank already filled at init") |
---|
952 | |
---|
953 | def __str__(self): |
---|
954 | _str = "%s\n" % DataInfo.__str__(self) |
---|
955 | _str += "Data:\n" |
---|
956 | _str += " Type: %s\n" % self.__class__.__name__ |
---|
957 | _str += " X- & Y-axis: %s\t[%s]\n" % (self._yaxis, self._yunit) |
---|
958 | _str += " Z-axis: %s\t[%s]\n" % (self._zaxis, self._zunit) |
---|
959 | _str += " Length: %g \n" % (len(self.data)) |
---|
960 | _str += " Shape: (%d, %d)\n" % (len(self.y_bins), len(self.x_bins)) |
---|
961 | return _str |
---|
962 | |
---|
963 | def clone_without_data(self, length=0, clone=None): |
---|
964 | """ |
---|
965 | Clone the current object, without copying the data (which |
---|
966 | will be filled out by a subsequent operation). |
---|
967 | The data arrays will be initialized to zero. |
---|
968 | |
---|
969 | :param length: length of the data array to be initialized |
---|
970 | :param clone: if provided, the data will be copied to clone |
---|
971 | """ |
---|
972 | from copy import deepcopy |
---|
973 | |
---|
974 | if clone is None or not issubclass(clone.__class__, Data2D): |
---|
975 | data = np.zeros(length) |
---|
976 | err_data = np.zeros(length) |
---|
977 | qx_data = np.zeros(length) |
---|
978 | qy_data = np.zeros(length) |
---|
979 | q_data = np.zeros(length) |
---|
980 | mask = np.zeros(length) |
---|
981 | dqx_data = None |
---|
982 | dqy_data = None |
---|
983 | clone = Data2D(data=data, err_data=err_data, |
---|
984 | qx_data=qx_data, qy_data=qy_data, |
---|
985 | q_data=q_data, mask=mask) |
---|
986 | |
---|
987 | clone.title = self.title |
---|
988 | clone.run = self.run |
---|
989 | clone.filename = self.filename |
---|
990 | clone.instrument = self.instrument |
---|
991 | clone.notes = deepcopy(self.notes) |
---|
992 | clone.process = deepcopy(self.process) |
---|
993 | clone.detector = deepcopy(self.detector) |
---|
994 | clone.sample = deepcopy(self.sample) |
---|
995 | clone.source = deepcopy(self.source) |
---|
996 | clone.collimation = deepcopy(self.collimation) |
---|
997 | clone.trans_spectrum = deepcopy(self.trans_spectrum) |
---|
998 | clone.meta_data = deepcopy(self.meta_data) |
---|
999 | clone.errors = deepcopy(self.errors) |
---|
1000 | |
---|
1001 | return clone |
---|
1002 | |
---|
1003 | def _validity_check(self, other): |
---|
1004 | """ |
---|
1005 | Checks that the data lengths are compatible. |
---|
1006 | Checks that the x vectors are compatible. |
---|
1007 | Returns errors vectors equal to original |
---|
1008 | errors vectors if they were present or vectors |
---|
1009 | of zeros when none was found. |
---|
1010 | |
---|
1011 | :param other: other data set for operation |
---|
1012 | :return: dy for self, dy for other [numpy arrays] |
---|
1013 | :raise ValueError: when lengths are not compatible |
---|
1014 | """ |
---|
1015 | err_other = None |
---|
1016 | TOLERANCE = 0.01 |
---|
1017 | if isinstance(other, Data2D): |
---|
1018 | # Check that data lengths are the same |
---|
1019 | if len(self.data) != len(other.data) or \ |
---|
1020 | len(self.qx_data) != len(other.qx_data) or \ |
---|
1021 | len(self.qy_data) != len(other.qy_data): |
---|
1022 | msg = "Unable to perform operation: data length are not equal" |
---|
1023 | raise ValueError(msg) |
---|
1024 | for ind in range(len(self.data)): |
---|
1025 | if math.fabs((self.qx_data[ind] - other.qx_data[ind])/self.qx_data[ind]) > TOLERANCE: |
---|
1026 | msg = "Incompatible data sets: qx-values do not match: %s %s" % (self.qx_data[ind], other.qx_data[ind]) |
---|
1027 | raise ValueError(msg) |
---|
1028 | if math.fabs((self.qy_data[ind] - other.qy_data[ind])/self.qy_data[ind]) > TOLERANCE: |
---|
1029 | msg = "Incompatible data sets: qy-values do not match: %s %s" % (self.qy_data[ind], other.qy_data[ind]) |
---|
1030 | raise ValueError(msg) |
---|
1031 | |
---|
1032 | # Check that the scales match |
---|
1033 | err_other = other.err_data |
---|
1034 | if other.err_data is None or \ |
---|
1035 | (len(other.err_data) != len(other.data)): |
---|
1036 | err_other = np.zeros(len(other.data)) |
---|
1037 | |
---|
1038 | # Check that we have errors, otherwise create zero vector |
---|
1039 | err = self.err_data |
---|
1040 | if self.err_data is None or \ |
---|
1041 | (len(self.err_data) != len(self.data)): |
---|
1042 | err = np.zeros(len(other.data)) |
---|
1043 | return err, err_other |
---|
1044 | |
---|
1045 | def _perform_operation(self, other, operation): |
---|
1046 | """ |
---|
1047 | Perform 2D operations between data sets |
---|
1048 | |
---|
1049 | :param other: other data set |
---|
1050 | :param operation: function defining the operation |
---|
1051 | """ |
---|
1052 | # First, check the data compatibility |
---|
1053 | dy, dy_other = self._validity_check(other) |
---|
1054 | result = self.clone_without_data(np.size(self.data)) |
---|
1055 | if self.dqx_data is None or self.dqy_data is None: |
---|
1056 | result.dqx_data = None |
---|
1057 | result.dqy_data = None |
---|
1058 | else: |
---|
1059 | result.dqx_data = np.zeros(len(self.data)) |
---|
1060 | result.dqy_data = np.zeros(len(self.data)) |
---|
1061 | for i in range(np.size(self.data)): |
---|
1062 | result.data[i] = self.data[i] |
---|
1063 | if self.err_data is not None and \ |
---|
1064 | np.size(self.data) == np.size(self.err_data): |
---|
1065 | result.err_data[i] = self.err_data[i] |
---|
1066 | if self.dqx_data is not None: |
---|
1067 | result.dqx_data[i] = self.dqx_data[i] |
---|
1068 | if self.dqy_data is not None: |
---|
1069 | result.dqy_data[i] = self.dqy_data[i] |
---|
1070 | result.qx_data[i] = self.qx_data[i] |
---|
1071 | result.qy_data[i] = self.qy_data[i] |
---|
1072 | result.q_data[i] = self.q_data[i] |
---|
1073 | result.mask[i] = self.mask[i] |
---|
1074 | |
---|
1075 | a = Uncertainty(self.data[i], dy[i]**2) |
---|
1076 | if isinstance(other, Data2D): |
---|
1077 | b = Uncertainty(other.data[i], dy_other[i]**2) |
---|
1078 | if other.dqx_data is not None and \ |
---|
1079 | result.dqx_data is not None: |
---|
1080 | result.dqx_data[i] *= self.dqx_data[i] |
---|
1081 | result.dqx_data[i] += (other.dqx_data[i]**2) |
---|
1082 | result.dqx_data[i] /= 2 |
---|
1083 | result.dqx_data[i] = math.sqrt(result.dqx_data[i]) |
---|
1084 | if other.dqy_data is not None and \ |
---|
1085 | result.dqy_data is not None: |
---|
1086 | result.dqy_data[i] *= self.dqy_data[i] |
---|
1087 | result.dqy_data[i] += (other.dqy_data[i]**2) |
---|
1088 | result.dqy_data[i] /= 2 |
---|
1089 | result.dqy_data[i] = math.sqrt(result.dqy_data[i]) |
---|
1090 | else: |
---|
1091 | b = other |
---|
1092 | output = operation(a, b) |
---|
1093 | result.data[i] = output.x |
---|
1094 | result.err_data[i] = math.sqrt(math.fabs(output.variance)) |
---|
1095 | return result |
---|
1096 | |
---|
1097 | def _validity_check_union(self, other): |
---|
1098 | """ |
---|
1099 | Checks that the data lengths are compatible. |
---|
1100 | Checks that the x vectors are compatible. |
---|
1101 | Returns errors vectors equal to original |
---|
1102 | errors vectors if they were present or vectors |
---|
1103 | of zeros when none was found. |
---|
1104 | |
---|
1105 | :param other: other data set for operation |
---|
1106 | :return: bool |
---|
1107 | :raise ValueError: when data types are not compatible |
---|
1108 | """ |
---|
1109 | if not isinstance(other, Data2D): |
---|
1110 | msg = "Unable to perform operation: different types of data set" |
---|
1111 | raise ValueError(msg) |
---|
1112 | return True |
---|
1113 | |
---|
1114 | def _perform_union(self, other): |
---|
1115 | """ |
---|
1116 | Perform 2D operations between data sets |
---|
1117 | |
---|
1118 | :param other: other data set |
---|
1119 | :param operation: function defining the operation |
---|
1120 | """ |
---|
1121 | # First, check the data compatibility |
---|
1122 | self._validity_check_union(other) |
---|
1123 | result = self.clone_without_data(np.size(self.data) + \ |
---|
1124 | np.size(other.data)) |
---|
1125 | result.xmin = self.xmin |
---|
1126 | result.xmax = self.xmax |
---|
1127 | result.ymin = self.ymin |
---|
1128 | result.ymax = self.ymax |
---|
1129 | if self.dqx_data is None or self.dqy_data is None or \ |
---|
1130 | other.dqx_data is None or other.dqy_data is None: |
---|
1131 | result.dqx_data = None |
---|
1132 | result.dqy_data = None |
---|
1133 | else: |
---|
1134 | result.dqx_data = np.zeros(len(self.data) + \ |
---|
1135 | np.size(other.data)) |
---|
1136 | result.dqy_data = np.zeros(len(self.data) + \ |
---|
1137 | np.size(other.data)) |
---|
1138 | |
---|
1139 | result.data = np.append(self.data, other.data) |
---|
1140 | result.qx_data = np.append(self.qx_data, other.qx_data) |
---|
1141 | result.qy_data = np.append(self.qy_data, other.qy_data) |
---|
1142 | result.q_data = np.append(self.q_data, other.q_data) |
---|
1143 | result.mask = np.append(self.mask, other.mask) |
---|
1144 | if result.err_data is not None: |
---|
1145 | result.err_data = np.append(self.err_data, other.err_data) |
---|
1146 | if self.dqx_data is not None: |
---|
1147 | result.dqx_data = np.append(self.dqx_data, other.dqx_data) |
---|
1148 | if self.dqy_data is not None: |
---|
1149 | result.dqy_data = np.append(self.dqy_data, other.dqy_data) |
---|
1150 | |
---|
1151 | return result |
---|
1152 | |
---|
1153 | |
---|
1154 | def combine_data_info_with_plottable(data, datainfo): |
---|
1155 | """ |
---|
1156 | A function that combines the DataInfo data in self.current_datainto with a plottable_1D or 2D data object. |
---|
1157 | |
---|
1158 | :param data: A plottable_1D or plottable_2D data object |
---|
1159 | :return: A fully specified Data1D or Data2D object |
---|
1160 | """ |
---|
1161 | |
---|
1162 | final_dataset = None |
---|
1163 | if isinstance(data, plottable_1D): |
---|
1164 | final_dataset = Data1D(data.x, data.y, isSesans=datainfo.isSesans) |
---|
1165 | final_dataset.dx = data.dx |
---|
1166 | final_dataset.dy = data.dy |
---|
1167 | final_dataset.dxl = data.dxl |
---|
1168 | final_dataset.dxw = data.dxw |
---|
1169 | final_dataset.x_unit = data._xunit |
---|
1170 | final_dataset.y_unit = data._yunit |
---|
1171 | final_dataset.xaxis(data._xaxis, data._xunit) |
---|
1172 | final_dataset.yaxis(data._yaxis, data._yunit) |
---|
1173 | elif isinstance(data, plottable_2D): |
---|
1174 | final_dataset = Data2D(data.data, data.err_data, data.qx_data, data.qy_data, data.q_data, |
---|
1175 | data.mask, data.dqx_data, data.dqy_data) |
---|
1176 | final_dataset.xaxis(data._xaxis, data._xunit) |
---|
1177 | final_dataset.yaxis(data._yaxis, data._yunit) |
---|
1178 | final_dataset.zaxis(data._zaxis, data._zunit) |
---|
1179 | if len(data.data.shape) == 2: |
---|
1180 | n_rows, n_cols = data.data.shape |
---|
1181 | final_dataset.y_bins = data.qy_data[0::int(n_cols)] |
---|
1182 | final_dataset.x_bins = data.qx_data[:int(n_cols)] |
---|
1183 | else: |
---|
1184 | return_string = "Should Never Happen: _combine_data_info_with_plottable input is not a plottable1d or " + \ |
---|
1185 | "plottable2d data object" |
---|
1186 | return return_string |
---|
1187 | |
---|
1188 | if hasattr(data, "xmax"): |
---|
1189 | final_dataset.xmax = data.xmax |
---|
1190 | if hasattr(data, "ymax"): |
---|
1191 | final_dataset.ymax = data.ymax |
---|
1192 | if hasattr(data, "xmin"): |
---|
1193 | final_dataset.xmin = data.xmin |
---|
1194 | if hasattr(data, "ymin"): |
---|
1195 | final_dataset.ymin = data.ymin |
---|
1196 | final_dataset.isSesans = datainfo.isSesans |
---|
1197 | final_dataset.title = datainfo.title |
---|
1198 | final_dataset.run = datainfo.run |
---|
1199 | final_dataset.run_name = datainfo.run_name |
---|
1200 | final_dataset.filename = datainfo.filename |
---|
1201 | final_dataset.notes = datainfo.notes |
---|
1202 | final_dataset.process = datainfo.process |
---|
1203 | final_dataset.instrument = datainfo.instrument |
---|
1204 | final_dataset.detector = datainfo.detector |
---|
1205 | final_dataset.sample = datainfo.sample |
---|
1206 | final_dataset.source = datainfo.source |
---|
1207 | final_dataset.collimation = datainfo.collimation |
---|
1208 | final_dataset.trans_spectrum = datainfo.trans_spectrum |
---|
1209 | final_dataset.meta_data = datainfo.meta_data |
---|
1210 | final_dataset.errors = datainfo.errors |
---|
1211 | return final_dataset |
---|