1 | """ |
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2 | Adapters for fitting module |
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3 | """ |
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4 | import copy |
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5 | import numpy |
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6 | import math |
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7 | from sas.sascalc.data_util.uncertainty import Uncertainty |
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8 | from sas.sasgui.plottools.plottables import Data1D as PlotData1D |
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9 | from sas.sasgui.plottools.plottables import Data2D as PlotData2D |
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10 | from sas.sasgui.plottools.plottables import Theory1D as PlotTheory1D |
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11 | |
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12 | from sas.sascalc.dataloader.data_info import Data1D as LoadData1D |
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13 | from sas.sascalc.dataloader.data_info import Data2D as LoadData2D |
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14 | |
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15 | |
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16 | class Data1D(PlotData1D, LoadData1D): |
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17 | """ |
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18 | """ |
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19 | |
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20 | def __init__(self, x=None, y=None, dx=None, dy=None, lam=None, dlam=None, isSesans=False): |
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21 | """ |
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22 | """ |
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23 | if x is None: |
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24 | x = [] |
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25 | if y is None: |
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26 | y = [] |
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27 | self.isSesans = isSesans |
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28 | PlotData1D.__init__(self, x, y, dx, dy, lam, dlam) |
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29 | LoadData1D.__init__(self, x, y, dx, dy, lam, dlam, isSesans) |
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30 | |
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31 | self.id = None |
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32 | self.list_group_id = [] |
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33 | self.group_id = None |
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34 | self.is_data = True |
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35 | self.path = None |
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36 | self.xtransform = None |
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37 | if self.isSesans: |
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38 | self.xtransform = "x" |
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39 | self.ytransform = None |
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40 | if self.isSesans: |
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41 | self.ytransform = "y" |
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42 | self.title = "" |
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43 | self.scale = None |
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44 | |
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45 | def copy_from_datainfo(self, data1d): |
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46 | """ |
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47 | copy values of Data1D of type DataLaoder.Data_info |
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48 | """ |
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49 | self.x = copy.deepcopy(data1d.x) |
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50 | self.y = copy.deepcopy(data1d.y) |
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51 | self.dy = copy.deepcopy(data1d.dy) |
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52 | |
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53 | if hasattr(data1d, "dx"): |
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54 | self.dx = copy.deepcopy(data1d.dx) |
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55 | if hasattr(data1d, "dxl"): |
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56 | self.dxl = copy.deepcopy(data1d.dxl) |
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57 | if hasattr(data1d, "dxw"): |
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58 | self.dxw = copy.deepcopy(data1d.dxw) |
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59 | |
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60 | self.xaxis(data1d._xaxis, data1d._xunit) |
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61 | self.yaxis(data1d._yaxis, data1d._yunit) |
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62 | self.title = data1d.title |
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63 | |
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64 | def __str__(self): |
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65 | """ |
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66 | print data |
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67 | """ |
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68 | _str = "%s\n" % LoadData1D.__str__(self) |
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69 | |
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70 | return _str |
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71 | |
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72 | def _perform_operation(self, other, operation): |
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73 | """ |
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74 | """ |
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75 | # First, check the data compatibility |
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76 | dy, dy_other = self._validity_check(other) |
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77 | result = Data1D(x=[], y=[], lam=[], dx=None, dy=None, dlam=None) |
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78 | result.clone_without_data(length=len(self.x), clone=self) |
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79 | result.copy_from_datainfo(data1d=self) |
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80 | if self.dxw == None: |
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81 | result.dxw = None |
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82 | else: |
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83 | result.dxw = numpy.zeros(len(self.x)) |
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84 | if self.dxl == None: |
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85 | result.dxl = None |
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86 | else: |
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87 | result.dxl = numpy.zeros(len(self.x)) |
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88 | |
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89 | for i in range(len(self.x)): |
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90 | result.x[i] = self.x[i] |
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91 | if self.dx is not None and len(self.x) == len(self.dx): |
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92 | result.dx[i] = self.dx[i] |
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93 | if self.dxw is not None and len(self.x) == len(self.dxw): |
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94 | result.dxw[i] = self.dxw[i] |
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95 | if self.dxl is not None and len(self.x) == len(self.dxl): |
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96 | result.dxl[i] = self.dxl[i] |
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97 | |
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98 | a = Uncertainty(self.y[i], dy[i]**2) |
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99 | if isinstance(other, Data1D): |
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100 | b = Uncertainty(other.y[i], dy_other[i]**2) |
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101 | if other.dx is not None: |
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102 | result.dx[i] *= self.dx[i] |
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103 | result.dx[i] += (other.dx[i]**2) |
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104 | result.dx[i] /= 2 |
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105 | result.dx[i] = math.sqrt(result.dx[i]) |
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106 | if result.dxl is not None and other.dxl is not None: |
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107 | result.dxl[i] *= self.dxl[i] |
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108 | result.dxl[i] += (other.dxl[i]**2) |
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109 | result.dxl[i] /= 2 |
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110 | result.dxl[i] = math.sqrt(result.dxl[i]) |
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111 | else: |
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112 | b = other |
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113 | |
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114 | output = operation(a, b) |
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115 | result.y[i] = output.x |
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116 | result.dy[i] = math.sqrt(math.fabs(output.variance)) |
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117 | return result |
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118 | |
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119 | def _perform_union(self, other): |
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120 | """ |
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121 | """ |
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122 | # First, check the data compatibility |
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123 | self._validity_check_union(other) |
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124 | result = Data1D(x=[], y=[], lam=[], dx=None, dy=None, dlam=None) |
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125 | tot_length = len(self.x) + len(other.x) |
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126 | result = self.clone_without_data(length=tot_length, clone=result) |
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127 | if self.dlam == None or other.dlam is None: |
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128 | result.dlam = None |
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129 | else: |
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130 | result.dlam = numpy.zeros(tot_length) |
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131 | if self.dy == None or other.dy is None: |
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132 | result.dy = None |
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133 | else: |
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134 | result.dy = numpy.zeros(tot_length) |
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135 | if self.dx == None or other.dx is None: |
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136 | result.dx = None |
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137 | else: |
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138 | result.dx = numpy.zeros(tot_length) |
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139 | if self.dxw == None or other.dxw is None: |
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140 | result.dxw = None |
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141 | else: |
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142 | result.dxw = numpy.zeros(tot_length) |
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143 | if self.dxl == None or other.dxl is None: |
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144 | result.dxl = None |
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145 | else: |
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146 | result.dxl = numpy.zeros(tot_length) |
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147 | |
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148 | result.x = numpy.append(self.x, other.x) |
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149 | #argsorting |
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150 | ind = numpy.argsort(result.x) |
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151 | result.x = result.x[ind] |
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152 | result.y = numpy.append(self.y, other.y) |
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153 | result.y = result.y[ind] |
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154 | result.lam = numpy.append(self.lam, other.lam) |
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155 | result.lam = result.lam[ind] |
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156 | if result.dlam != None: |
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157 | result.dlam = numpy.append(self.dlam, other.dlam) |
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158 | result.dlam = result.dlam[ind] |
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159 | if result.dy != None: |
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160 | result.dy = numpy.append(self.dy, other.dy) |
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161 | result.dy = result.dy[ind] |
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162 | if result.dx is not None: |
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163 | result.dx = numpy.append(self.dx, other.dx) |
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164 | result.dx = result.dx[ind] |
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165 | if result.dxw is not None: |
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166 | result.dxw = numpy.append(self.dxw, other.dxw) |
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167 | result.dxw = result.dxw[ind] |
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168 | if result.dxl is not None: |
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169 | result.dxl = numpy.append(self.dxl, other.dxl) |
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170 | result.dxl = result.dxl[ind] |
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171 | return result |
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172 | |
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173 | |
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174 | |
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175 | class Theory1D(PlotTheory1D, LoadData1D): |
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176 | """ |
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177 | """ |
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178 | def __init__(self, x=None, y=None, dy=None): |
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179 | """ |
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180 | """ |
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181 | if x is None: |
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182 | x = [] |
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183 | if y is None: |
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184 | y = [] |
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185 | PlotTheory1D.__init__(self, x, y, dy) |
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186 | LoadData1D.__init__(self, x, y, dy) |
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187 | self.id = None |
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188 | self.list_group_id = [] |
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189 | self.group_id = None |
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190 | self.is_data = True |
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191 | self.path = None |
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192 | self.xtransform = None |
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193 | self.ytransform = None |
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194 | self.title = "" |
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195 | self.scale = None |
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196 | |
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197 | def copy_from_datainfo(self, data1d): |
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198 | """ |
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199 | copy values of Data1D of type DataLaoder.Data_info |
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200 | """ |
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201 | self.x = copy.deepcopy(data1d.x) |
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202 | self.y = copy.deepcopy(data1d.y) |
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203 | self.dy = copy.deepcopy(data1d.dy) |
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204 | if hasattr(data1d, "dx"): |
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205 | self.dx = copy.deepcopy(data1d.dx) |
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206 | if hasattr(data1d, "dxl"): |
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207 | self.dxl = copy.deepcopy(data1d.dxl) |
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208 | if hasattr(data1d, "dxw"): |
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209 | self.dxw = copy.deepcopy(data1d.dxw) |
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210 | self.xaxis(data1d._xaxis, data1d._xunit) |
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211 | self.yaxis(data1d._yaxis, data1d._yunit) |
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212 | self.title = data1d.title |
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213 | |
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214 | def __str__(self): |
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215 | """ |
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216 | print data |
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217 | """ |
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218 | _str = "%s\n" % LoadData1D.__str__(self) |
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219 | |
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220 | return _str |
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221 | |
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222 | def _perform_operation(self, other, operation): |
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223 | """ |
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224 | """ |
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225 | # First, check the data compatibility |
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226 | dy, dy_other = self._validity_check(other) |
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227 | result = self.clone_without_data(len(self.x)) |
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228 | result.copy_from_datainfo(data1d=self) |
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229 | if self.dxw == None: |
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230 | result.dxw = None |
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231 | else: |
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232 | result.dxw = numpy.zeros(len(self.x)) |
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233 | if self.dxl == None: |
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234 | result.dxl = None |
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235 | else: |
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236 | result.dxl = numpy.zeros(len(self.x)) |
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237 | |
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238 | for i in range(numpy.size(self.x)): |
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239 | result.x[i] = self.x[i] |
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240 | if self.dx is not None and len(self.x) == len(self.dx): |
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241 | result.dx[i] = self.dx[i] |
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242 | if self.dxw is not None and len(self.x) == len(self.dxw): |
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243 | result.dxw[i] = self.dxw[i] |
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244 | if self.dxl is not None and len(self.x) == len(self.dxl): |
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245 | result.dxl[i] = self.dxl[i] |
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246 | |
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247 | a = Uncertainty(self.y[i], dy[i]**2) |
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248 | if isinstance(other, Data1D): |
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249 | b = Uncertainty(other.y[i], dy_other[i]**2) |
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250 | if other.dx is not None: |
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251 | result.dx[i] *= self.dx[i] |
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252 | result.dx[i] += (other.dx[i]**2) |
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253 | result.dx[i] /= 2 |
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254 | result.dx[i] = math.sqrt(result.dx[i]) |
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255 | if result.dxl is not None and other.dxl is not None: |
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256 | result.dxl[i] *= self.dxl[i] |
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257 | other.dxl[i] += (other.dxl[i]**2) |
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258 | result.dxl[i] /= 2 |
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259 | result.dxl[i] = math.sqrt(result.dxl[i]) |
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260 | if result.dxw is not None and self.dxw is not None: |
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261 | result.dxw[i] *= self.dxw[i] |
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262 | other.dxw[i] += (other.dxw[i]**2) |
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263 | result.dxw[i] /= 2 |
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264 | result.dxw[i] = math.sqrt(result.dxw[i]) |
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265 | else: |
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266 | b = other |
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267 | |
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268 | output = operation(a, b) |
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269 | result.y[i] = output.x |
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270 | result.dy[i] = math.sqrt(math.fabs(output.variance)) |
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271 | return result |
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272 | |
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273 | def _perform_union(self, other): |
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274 | """ |
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275 | """ |
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276 | # First, check the data compatibility |
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277 | self._validity_check_union(other) |
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278 | result = Data1D(x=[], y=[], lam=[], dx=None, dy=None, dlam=[]) |
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279 | tot_length = len(self.x)+len(other.x) |
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280 | result.clone_without_data(length=tot_length, clone=self) |
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281 | if self.dlam == None or other.dlam is None: |
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282 | result.dlam = None |
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283 | else: |
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284 | result.dlam = numpy.zeros(tot_length) |
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285 | if self.dy == None or other.dy is None: |
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286 | result.dy = None |
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287 | else: |
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288 | result.dy = numpy.zeros(tot_length) |
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289 | if self.dx == None or other.dx is None: |
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290 | result.dx = None |
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291 | else: |
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292 | result.dx = numpy.zeros(tot_length) |
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293 | if self.dxw == None or other.dxw is None: |
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294 | result.dxw = None |
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295 | else: |
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296 | result.dxw = numpy.zeros(tot_length) |
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297 | if self.dxl == None or other.dxl is None: |
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298 | result.dxl = None |
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299 | else: |
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300 | result.dxl = numpy.zeros(tot_length) |
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301 | result.x = numpy.append(self.x, other.x) |
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302 | #argsorting |
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303 | ind = numpy.argsort(result.x) |
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304 | result.x = result.x[ind] |
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305 | result.y = numpy.append(self.y, other.y) |
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306 | result.y = result.y[ind] |
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307 | result.lam = numpy.append(self.lam, other.lam) |
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308 | result.lam = result.lam[ind] |
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309 | if result.dy != None: |
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310 | result.dy = numpy.append(self.dy, other.dy) |
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311 | result.dy = result.dy[ind] |
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312 | if result.dx is not None: |
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313 | result.dx = numpy.append(self.dx, other.dx) |
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314 | result.dx = result.dx[ind] |
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315 | if result.dxw is not None: |
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316 | result.dxw = numpy.append(self.dxw, other.dxw) |
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317 | result.dxw = result.dxw[ind] |
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318 | if result.dxl is not None: |
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319 | result.dxl = numpy.append(self.dxl, other.dxl) |
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320 | result.dxl = result.dxl[ind] |
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321 | return result |
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322 | |
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323 | |
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324 | class Data2D(PlotData2D, LoadData2D): |
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325 | """ |
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326 | """ |
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327 | def __init__(self, image=None, err_image=None, |
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328 | qx_data=None, qy_data=None, q_data=None, |
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329 | mask=None, dqx_data=None, dqy_data=None, |
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330 | xmin=None, xmax=None, ymin=None, ymax=None, |
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331 | zmin=None, zmax=None): |
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332 | """ |
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333 | """ |
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334 | PlotData2D.__init__(self, image=image, err_image=err_image, |
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335 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, |
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336 | zmin=zmin, zmax=zmax, qx_data=qx_data, |
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337 | qy_data=qy_data) |
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338 | |
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339 | LoadData2D.__init__(self, data=image, err_data=err_image, |
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340 | qx_data=qx_data, qy_data=qy_data, |
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341 | dqx_data=dqx_data, dqy_data=dqy_data, |
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342 | q_data=q_data, mask=mask) |
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343 | self.id = None |
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344 | self.list_group_id = [] |
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345 | self.group_id = None |
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346 | self.is_data = True |
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347 | self.path = None |
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348 | self.xtransform = None |
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349 | self.ytransform = None |
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350 | self.title = "" |
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351 | self.scale = None |
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352 | |
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353 | def copy_from_datainfo(self, data2d): |
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354 | """ |
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355 | copy value of Data2D of type DataLoader.data_info |
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356 | """ |
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357 | self.data = copy.deepcopy(data2d.data) |
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358 | self.qx_data = copy.deepcopy(data2d.qx_data) |
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359 | self.qy_data = copy.deepcopy(data2d.qy_data) |
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360 | self.q_data = copy.deepcopy(data2d.q_data) |
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361 | self.mask = copy.deepcopy(data2d.mask) |
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362 | self.err_data = copy.deepcopy(data2d.err_data) |
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363 | self.x_bins = copy.deepcopy(data2d.x_bins) |
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364 | self.y_bins = copy.deepcopy(data2d.y_bins) |
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365 | if data2d.dqx_data is not None: |
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366 | self.dqx_data = copy.deepcopy(data2d.dqx_data) |
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367 | if data2d.dqy_data is not None: |
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368 | self.dqy_data = copy.deepcopy(data2d.dqy_data) |
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369 | self.xmin = data2d.xmin |
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370 | self.xmax = data2d.xmax |
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371 | self.ymin = data2d.ymin |
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372 | self.ymax = data2d.ymax |
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373 | if hasattr(data2d, "zmin"): |
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374 | self.zmin = data2d.zmin |
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375 | if hasattr(data2d, "zmax"): |
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376 | self.zmax = data2d.zmax |
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377 | self.xaxis(data2d._xaxis, data2d._xunit) |
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378 | self.yaxis(data2d._yaxis, data2d._yunit) |
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379 | self.title = data2d.title |
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380 | |
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381 | def __str__(self): |
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382 | """ |
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383 | print data |
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384 | """ |
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385 | _str = "%s\n" % LoadData2D.__str__(self) |
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386 | return _str |
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387 | |
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388 | def _perform_operation(self, other, operation): |
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389 | """ |
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390 | Perform 2D operations between data sets |
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391 | |
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392 | :param other: other data set |
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393 | :param operation: function defining the operation |
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394 | |
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395 | """ |
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396 | # First, check the data compatibility |
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397 | dy, dy_other = self._validity_check(other) |
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398 | result = Data2D(image=None, qx_data=None, qy_data=None, |
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399 | q_data=None, err_image=None, xmin=None, xmax=None, |
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400 | ymin=None, ymax=None, zmin=None, zmax=None) |
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401 | result.clone_without_data(len(self.data)) |
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402 | result.copy_from_datainfo(data2d=self) |
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403 | result.xmin = self.xmin |
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404 | result.xmax = self.xmax |
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405 | result.ymin = self.ymin |
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406 | result.ymax = self.ymax |
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407 | if self.dqx_data == None or self.dqy_data == None: |
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408 | result.dqx_data = None |
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409 | result.dqy_data = None |
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410 | else: |
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411 | result.dqx_data = numpy.zeros(len(self.data)) |
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412 | result.dqy_data = numpy.zeros(len(self.data)) |
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413 | for i in range(numpy.size(self.data)): |
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414 | result.data[i] = self.data[i] |
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415 | if self.err_data is not None and \ |
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416 | numpy.size(self.data) == numpy.size(self.err_data): |
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417 | result.err_data[i] = self.err_data[i] |
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418 | if self.dqx_data is not None: |
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419 | result.dqx_data[i] = self.dqx_data[i] |
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420 | if self.dqy_data is not None: |
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421 | result.dqy_data[i] = self.dqy_data[i] |
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422 | result.qx_data[i] = self.qx_data[i] |
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423 | result.qy_data[i] = self.qy_data[i] |
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424 | result.q_data[i] = self.q_data[i] |
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425 | result.mask[i] = self.mask[i] |
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426 | |
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427 | a = Uncertainty(self.data[i], dy[i]**2) |
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428 | if isinstance(other, Data2D): |
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429 | b = Uncertainty(other.data[i], dy_other[i]**2) |
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430 | if other.dqx_data is not None and \ |
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431 | result.dqx_data is not None: |
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432 | result.dqx_data[i] *= self.dqx_data[i] |
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433 | result.dqx_data[i] += (other.dqx_data[i]**2) |
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434 | result.dqx_data[i] /= 2 |
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435 | result.dqx_data[i] = math.sqrt(result.dqx_data[i]) |
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436 | if other.dqy_data is not None and \ |
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437 | result.dqy_data is not None: |
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438 | result.dqy_data[i] *= self.dqy_data[i] |
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439 | result.dqy_data[i] += (other.dqy_data[i]**2) |
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440 | result.dqy_data[i] /= 2 |
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441 | result.dqy_data[i] = math.sqrt(result.dqy_data[i]) |
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442 | else: |
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443 | b = other |
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444 | |
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445 | output = operation(a, b) |
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446 | result.data[i] = output.x |
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447 | result.err_data[i] = math.sqrt(math.fabs(output.variance)) |
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448 | return result |
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449 | |
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450 | def _perform_union(self, other): |
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451 | """ |
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452 | Perform 2D operations between data sets |
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453 | |
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454 | :param other: other data set |
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455 | :param operation: function defining the operation |
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456 | |
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457 | """ |
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458 | # First, check the data compatibility |
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459 | self._validity_check_union(other) |
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460 | result = Data2D(image=None, qx_data=None, qy_data=None, |
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461 | q_data=None, err_image=None, xmin=None, xmax=None, |
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462 | ymin=None, ymax=None, zmin=None, zmax=None) |
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463 | length = len(self.data) |
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464 | tot_length = length + len(other.data) |
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465 | result.clone_without_data(tot_length) |
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466 | result.xmin = self.xmin |
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467 | result.xmax = self.xmax |
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468 | result.ymin = self.ymin |
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469 | result.ymax = self.ymax |
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470 | if self.dqx_data == None or self.dqy_data == None or \ |
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471 | other.dqx_data == None or other.dqy_data == None : |
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472 | result.dqx_data = None |
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473 | result.dqy_data = None |
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474 | else: |
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475 | result.dqx_data = numpy.zeros(len(self.data) + \ |
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476 | numpy.size(other.data)) |
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477 | result.dqy_data = numpy.zeros(len(self.data) + \ |
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478 | numpy.size(other.data)) |
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479 | |
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480 | result.data = numpy.append(self.data, other.data) |
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481 | result.qx_data = numpy.append(self.qx_data, other.qx_data) |
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482 | result.qy_data = numpy.append(self.qy_data, other.qy_data) |
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483 | result.q_data = numpy.append(self.q_data, other.q_data) |
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484 | result.mask = numpy.append(self.mask, other.mask) |
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485 | if result.err_data is not None: |
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486 | result.err_data = numpy.append(self.err_data, other.err_data) |
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487 | if self.dqx_data is not None: |
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488 | result.dqx_data = numpy.append(self.dqx_data, other.dqx_data) |
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489 | if self.dqy_data is not None: |
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490 | result.dqy_data = numpy.append(self.dqy_data, other.dqy_data) |
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491 | |
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492 | return result |
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493 | |
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494 | def check_data_validity(data): |
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495 | """ |
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496 | Return True is data is valid enough to compute chisqr, else False |
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497 | """ |
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498 | flag = True |
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499 | if data is not None: |
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500 | if issubclass(data.__class__, Data2D): |
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501 | if (data.data is None) or (len(data.data) == 0)\ |
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502 | or (len(data.err_data) == 0): |
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503 | flag = False |
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504 | else: |
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505 | if (data.y is None) or (len(data.y) == 0): |
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506 | flag = False |
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507 | if not data.is_data: |
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508 | flag = False |
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509 | else: |
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510 | flag = False |
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511 | return flag |
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