1 | """ |
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2 | IGOR 2D reduced file reader |
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3 | """ |
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4 | |
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5 | """ |
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6 | This software was developed by the University of Tennessee as part of the |
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7 | Distributed Data Analysis of Neutron Scattering Experiments (DANSE) |
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8 | project funded by the US National Science Foundation. |
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9 | |
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10 | If you use DANSE applications to do scientific research that leads to |
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11 | publication, we ask that you acknowledge the use of the software with the |
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12 | following sentence: |
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13 | |
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14 | "This work benefited from DANSE software developed under NSF award DMR-0520547." |
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15 | |
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16 | copyright 2008, University of Tennessee |
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17 | """ |
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18 | |
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19 | import os, sys |
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20 | import numpy |
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21 | import math, logging |
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22 | from DataLoader.data_info import Data2D, Detector |
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23 | |
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24 | # Look for unit converter |
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25 | has_converter = True |
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26 | try: |
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27 | from data_util.nxsunit import Converter |
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28 | except: |
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29 | has_converter = False |
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30 | |
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31 | class Reader: |
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32 | """ Simple data reader for Igor data files """ |
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33 | ## File type |
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34 | type = ["IGOR 2D files (*.ASC)|*.ASC"] |
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35 | ## Extension |
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36 | ext=['.ASC', '.asc'] |
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37 | |
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38 | def read(self,filename=None): |
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39 | """ Read file """ |
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40 | if not os.path.isfile(filename): |
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41 | raise ValueError, \ |
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42 | "Specified file %s is not a regular file" % filename |
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43 | |
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44 | # Read file |
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45 | f = open(filename,'r') |
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46 | buf = f.read() |
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47 | |
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48 | # Instantiate data object |
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49 | output = Data2D() |
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50 | output.filename = os.path.basename(filename) |
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51 | detector = Detector() |
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52 | if len(output.detector)>0: print str(output.detector[0]) |
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53 | output.detector.append(detector) |
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54 | |
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55 | # Get content |
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56 | dataStarted = False |
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57 | |
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58 | |
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59 | lines = buf.split('\n') |
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60 | itot = 0 |
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61 | x = [] |
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62 | y = [] |
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63 | |
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64 | ncounts = 0 |
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65 | |
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66 | xmin = None |
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67 | xmax = None |
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68 | ymin = None |
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69 | ymax = None |
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70 | |
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71 | i_x = 0 |
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72 | i_y = -1 |
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73 | i_tot_row = 0 |
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74 | |
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75 | isInfo = False |
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76 | isCenter = False |
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77 | |
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78 | data_conv_q = None |
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79 | data_conv_i = None |
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80 | |
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81 | if has_converter == True and output.Q_unit != '1/A': |
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82 | data_conv_q = Converter('1/A') |
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83 | # Test it |
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84 | data_conv_q(1.0, output.Q_unit) |
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85 | |
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86 | if has_converter == True and output.I_unit != '1/cm': |
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87 | data_conv_i = Converter('1/cm') |
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88 | # Test it |
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89 | data_conv_i(1.0, output.I_unit) |
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90 | |
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91 | for line in lines: |
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92 | |
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93 | # Find setup info line |
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94 | if isInfo: |
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95 | isInfo = False |
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96 | line_toks = line.split() |
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97 | # Wavelength in Angstrom |
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98 | try: |
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99 | wavelength = float(line_toks[1]) |
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100 | except: |
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101 | raise ValueError,"IgorReader: can't read this file, missing wavelength" |
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102 | |
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103 | #Find # of bins in a row assuming the detector is square. |
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104 | if dataStarted == True: |
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105 | try: |
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106 | value = float(line) |
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107 | except: |
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108 | # Found a non-float entry, skip it |
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109 | continue |
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110 | |
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111 | # Get total bin number |
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112 | |
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113 | i_tot_row += 1 |
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114 | i_tot_row=math.ceil(math.sqrt(i_tot_row))-1 |
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115 | #print "i_tot", i_tot_row |
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116 | size_x = i_tot_row#192#128 |
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117 | size_y = i_tot_row#192#128 |
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118 | output.data = numpy.zeros([size_x,size_y]) |
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119 | output.err_data = numpy.zeros([size_x,size_y]) |
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120 | |
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121 | #Read Header and 2D data |
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122 | for line in lines: |
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123 | # Find setup info line |
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124 | if isInfo: |
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125 | isInfo = False |
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126 | line_toks = line.split() |
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127 | # Wavelength in Angstrom |
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128 | try: |
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129 | wavelength = float(line_toks[1]) |
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130 | except: |
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131 | raise ValueError,"IgorReader: can't read this file, missing wavelength" |
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132 | # Distance in meters |
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133 | try: |
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134 | distance = float(line_toks[3]) |
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135 | except: |
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136 | raise ValueError,"IgorReader: can't read this file, missing distance" |
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137 | |
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138 | # Distance in meters |
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139 | try: |
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140 | transmission = float(line_toks[4]) |
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141 | except: |
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142 | raise ValueError,"IgorReader: can't read this file, missing transmission" |
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143 | |
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144 | if line.count("LAMBDA")>0: |
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145 | isInfo = True |
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146 | |
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147 | # Find center info line |
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148 | if isCenter: |
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149 | isCenter = False |
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150 | line_toks = line.split() |
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151 | # Center in bin number |
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152 | center_x = float(line_toks[0]) |
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153 | center_y = float(line_toks[1]) |
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154 | |
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155 | if line.count("BCENT")>0: |
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156 | isCenter = True |
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157 | |
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158 | |
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159 | # Find data start |
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160 | if line.count("***")>0: |
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161 | dataStarted = True |
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162 | |
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163 | # Check that we have all the info |
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164 | if wavelength == None \ |
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165 | or distance == None \ |
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166 | or center_x == None \ |
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167 | or center_y == None: |
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168 | raise ValueError, "IgorReader:Missing information in data file" |
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169 | |
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170 | if dataStarted == True: |
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171 | try: |
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172 | value = float(line) |
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173 | except: |
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174 | # Found a non-float entry, skip it |
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175 | continue |
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176 | |
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177 | # Get bin number |
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178 | if math.fmod(itot, i_tot_row)==0: |
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179 | i_x = 0 |
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180 | i_y += 1 |
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181 | else: |
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182 | i_x += 1 |
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183 | |
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184 | output.data[i_y][i_x] = value |
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185 | ncounts += 1 |
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186 | |
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187 | # Det 640 x 640 mm |
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188 | # Q = 4pi/lambda sin(theta/2) |
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189 | # Bin size is 0.5 cm |
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190 | #REmoved +1 from theta = (i_x-center_x+1)*0.5 / distance / 100.0 and |
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191 | #REmoved +1 from theta = (i_y-center_y+1)*0.5 / distance / 100.0 |
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192 | #ToDo: Need complete check if the following covert process is consistent with fitting.py. |
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193 | theta = (i_x-center_x)*0.5 / distance / 100.0 |
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194 | qx = 4.0*math.pi/wavelength * math.sin(theta/2.0) |
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195 | |
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196 | if has_converter == True and output.Q_unit != '1/A': |
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197 | qx = data_conv_q(qx, units=output.Q_unit) |
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198 | |
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199 | if xmin==None or qx<xmin: |
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200 | xmin = qx |
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201 | if xmax==None or qx>xmax: |
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202 | xmax = qx |
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203 | |
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204 | theta = (i_y-center_y)*0.5 / distance / 100.0 |
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205 | qy = 4.0*math.pi/wavelength * math.sin(theta/2.0) |
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206 | |
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207 | if has_converter == True and output.Q_unit != '1/A': |
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208 | qy = data_conv_q(qy, units=output.Q_unit) |
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209 | |
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210 | if ymin==None or qy<ymin: |
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211 | ymin = qy |
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212 | if ymax==None or qy>ymax: |
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213 | ymax = qy |
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214 | |
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215 | if not qx in x: |
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216 | x.append(qx) |
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217 | if not qy in y: |
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218 | y.append(qy) |
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219 | |
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220 | itot += 1 |
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221 | |
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222 | |
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223 | theta = 0.25 / distance / 100.0 |
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224 | xstep = 4.0*math.pi/wavelength * math.sin(theta/2.0) |
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225 | |
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226 | theta = 0.25 / distance / 100.0 |
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227 | ystep = 4.0*math.pi/wavelength * math.sin(theta/2.0) |
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228 | |
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229 | # Store all data ###################################### |
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230 | # Store wavelength |
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231 | if has_converter==True and output.source.wavelength_unit != 'A': |
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232 | conv = Converter('A') |
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233 | wavelength = conv(wavelength, units=output.source.wavelength_unit) |
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234 | output.source.wavelength = wavelength |
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235 | |
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236 | # Store distance |
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237 | if has_converter==True and detector.distance_unit != 'm': |
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238 | conv = Converter('m') |
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239 | distance = conv(distance, units=detector.distance_unit) |
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240 | detector.distance = distance |
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241 | |
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242 | # Store transmission |
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243 | output.sample.transmission = transmission |
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244 | |
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245 | # Store pixel size |
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246 | pixel = 5.0 |
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247 | if has_converter==True and detector.pixel_size_unit != 'mm': |
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248 | conv = Converter('mm') |
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249 | pixel = conv(pixel, units=detector.pixel_size_unit) |
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250 | detector.pixel_size.x = pixel |
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251 | detector.pixel_size.y = pixel |
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252 | |
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253 | # Store beam center in distance units |
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254 | detector.beam_center.x = center_x*pixel |
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255 | detector.beam_center.y = center_y*pixel |
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256 | |
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257 | |
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258 | # Store limits of the image (2D array) |
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259 | xmin =xmin-xstep/2.0 |
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260 | xmax =xmax+xstep/2.0 |
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261 | ymin =ymin-ystep/2.0 |
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262 | ymax =ymax+ystep/2.0 |
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263 | if has_converter == True and output.Q_unit != '1/A': |
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264 | xmin = data_conv_q(xmin, units=output.Q_unit) |
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265 | xmax = data_conv_q(xmax, units=output.Q_unit) |
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266 | ymin = data_conv_q(ymin, units=output.Q_unit) |
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267 | ymax = data_conv_q(ymax, units=output.Q_unit) |
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268 | output.xmin = xmin |
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269 | output.xmax = xmax |
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270 | output.ymin = ymin |
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271 | output.ymax = ymax |
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272 | |
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273 | # Store x and y axis bin centers |
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274 | output.x_bins = x |
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275 | output.y_bins = y |
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276 | |
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277 | # Units |
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278 | if data_conv_q is not None: |
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279 | output.xaxis("\\rm{Q_{x}}", output.Q_unit) |
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280 | output.yaxis("\\rm{Q_{y}}", output.Q_unit) |
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281 | else: |
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282 | output.xaxis("\\rm{Q_{x}}", 'A^{-1}') |
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283 | output.yaxis("\\rm{Q_{y}}", 'A^{-1}') |
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284 | |
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285 | if data_conv_i is not None: |
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286 | output.zaxis("\\rm{Intensity}", output.I_unit) |
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287 | else: |
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288 | output.zaxis("\\rm{Intensity}","cm^{-1}") |
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289 | |
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290 | |
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291 | return output |
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292 | |
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293 | if __name__ == "__main__": |
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294 | reader = Reader() |
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295 | print reader.read("../test/MAR07232_rest.ASC") |
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296 | |
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