1 | """ |
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2 | SESANS reader |
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3 | """ |
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4 | |
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5 | import numpy |
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6 | import os |
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7 | from sas.dataloader.data_info import SESANSData1D |
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8 | |
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9 | # Check whether we have a converter available |
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10 | has_converter = True |
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11 | try: |
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12 | from sas.data_util.nxsunit import Converter |
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13 | except: |
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14 | has_converter = False |
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15 | _ZERO = 1e-16 |
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16 | |
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17 | class Reader: |
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18 | """ |
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19 | Class to load sesans files (6 columns). |
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20 | """ |
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21 | ## File type |
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22 | type_name = "SESANS" |
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23 | |
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24 | ## Wildcards |
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25 | type = ["SESANS files (*.ses)|*.ses", |
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26 | "SESANS files (*..sesans)|*.sesans"] |
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27 | ## List of allowed extensions |
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28 | ext = ['.ses', '.SES', '.sesans', '.SESANS'] |
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29 | |
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30 | ## Flag to bypass extension check |
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31 | allow_all = True |
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32 | |
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33 | def read(self, path): |
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34 | |
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35 | # print "reader triggered" |
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36 | |
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37 | """ |
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38 | Load data file |
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39 | |
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40 | :param path: file path |
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41 | |
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42 | :return: SESANSData1D object, or None |
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43 | |
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44 | :raise RuntimeError: when the file can't be opened |
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45 | :raise ValueError: when the length of the data vectors are inconsistent |
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46 | """ |
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47 | if os.path.isfile(path): |
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48 | basename = os.path.basename(path) |
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49 | _, extension = os.path.splitext(basename) |
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50 | if self.allow_all or extension.lower() in self.ext: |
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51 | try: |
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52 | # Read in binary mode since GRASP frequently has no-ascii |
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53 | # characters that brakes the open operation |
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54 | input_f = open(path,'rb') |
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55 | except: |
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56 | raise RuntimeError, "sesans_reader: cannot open %s" % path |
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57 | buff = input_f.read() |
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58 | # print buff |
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59 | lines = buff.splitlines() |
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60 | # print lines |
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61 | #Jae could not find python universal line spliter: |
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62 | #keep the below for now |
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63 | # some ascii data has \r line separator, |
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64 | # try it when the data is on only one long line |
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65 | # if len(lines) < 2 : |
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66 | # lines = buff.split('\r') |
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67 | |
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68 | x = numpy.zeros(0) |
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69 | y = numpy.zeros(0) |
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70 | dy = numpy.zeros(0) |
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71 | lam = numpy.zeros(0) |
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72 | dlam = numpy.zeros(0) |
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73 | dx = numpy.zeros(0) |
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74 | |
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75 | #temp. space to sort data |
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76 | tx = numpy.zeros(0) |
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77 | ty = numpy.zeros(0) |
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78 | tdy = numpy.zeros(0) |
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79 | tlam = numpy.zeros(0) |
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80 | tdlam = numpy.zeros(0) |
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81 | tdx = numpy.zeros(0) |
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82 | # print "all good" |
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83 | output = SESANSData1D(x=x, y=y, lam=lam, dy=dy, dx=dx, dlam=dlam) |
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84 | # print output |
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85 | self.filename = output.filename = basename |
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86 | |
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87 | |
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88 | data_conv_z = None |
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89 | data_conv_P = None |
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90 | # print "passing" |
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91 | if has_converter == True and output.x_unit != 'A': |
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92 | data_conv_z = Converter('nm') |
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93 | # Test it |
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94 | data_conv_z(1.0, output.x_unit) |
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95 | # print data_conv_z |
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96 | # print data_conv_z(1.0, output.x_unit) |
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97 | if has_converter == True and output.y_unit != ' ': |
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98 | data_conv_P = Converter('a.u.') |
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99 | # Test it |
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100 | data_conv_P(1.0, output.y_unit) |
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101 | # print data_conv_P |
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102 | # print data_conv_P(1.0, output.y_unit) |
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103 | # The first good line of data will define whether |
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104 | # we have 2-column or 3-column ascii |
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105 | # print output.x_unit |
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106 | # print output.y_unit |
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107 | |
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108 | # print "past output" |
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109 | |
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110 | # has_error_dx = None |
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111 | # has_error_dy = None |
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112 | |
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113 | # #Initialize counters for data lines and header lines. |
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114 | # is_data = False # Has more than 5 lines |
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115 | # # More than "5" lines of data is considered as actual |
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116 | # # data unless that is the only data |
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117 | # mum_data_lines = 5 |
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118 | # # To count # of current data candidate lines |
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119 | # i = -1 |
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120 | # # To count total # of previous data candidate lines |
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121 | # i1 = -1 |
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122 | # # To count # of header lines |
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123 | # j = -1 |
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124 | # # Helps to count # of header lines |
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125 | # j1 = -1 |
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126 | # #minimum required number of columns of data; ( <= 4). |
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127 | # lentoks = 2 |
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128 | paramnames=[] |
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129 | paramvals=[] |
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130 | zvals=[] |
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131 | dzvals=[] |
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132 | lamvals=[] |
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133 | dlamvals=[] |
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134 | Pvals=[] |
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135 | dPvals=[] |
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136 | # print x |
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137 | # print zvals |
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138 | for line in lines: |
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139 | # Initial try for CSV (split on ,) |
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140 | # print line |
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141 | line=line.strip() |
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142 | # print line |
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143 | toks = line.split('\t') |
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144 | # print toks |
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145 | if len(toks)==2: |
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146 | paramnames.append(toks[0]) |
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147 | # print paramnames |
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148 | paramvals.append(toks[1]) |
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149 | # print paramvals |
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150 | if len(toks)>5: |
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151 | zvals.append(toks[0]) |
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152 | dzvals.append(toks[1]) |
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153 | lamvals.append(toks[2]) |
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154 | dlamvals.append(toks[3]) |
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155 | Pvals.append(toks[4]) |
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156 | dPvals.append(toks[5]) |
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157 | else: |
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158 | continue |
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159 | # print varheaders |
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160 | # print paramnames |
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161 | # print paramvals |
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162 | # print zvals |
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163 | # print len(zvals) |
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164 | |
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165 | x=[] |
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166 | y=[] |
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167 | lam=[] |
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168 | dx=[] |
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169 | dy=[] |
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170 | dlam=[] |
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171 | varheader=[zvals[0],dzvals[0],lamvals[0],dlamvals[0],Pvals[0],dPvals[0]] |
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172 | # print varheader |
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173 | valrange=range(len(zvals)-1) |
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174 | # print valrange |
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175 | for i in valrange: |
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176 | x.append(float(zvals[i+1])) |
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177 | y.append(float(Pvals[i+1])) |
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178 | lam.append(float(lamvals[i+1])) |
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179 | dy.append(float(dPvals[i+1])) |
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180 | dx.append(float(dzvals[i+1])) |
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181 | dlam.append(float(dlamvals[i+1])) |
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182 | |
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183 | x,y,lam,dy,dx,dlam = [ |
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184 | numpy.asarray(v, 'double') |
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185 | for v in (x,y,lam,dy,dx,dlam) |
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186 | ] |
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187 | |
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188 | # print x |
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189 | # print y |
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190 | # print dx |
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191 | # print dy |
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192 | # print len(x) |
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193 | # print len(y) |
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194 | # print len(dx) |
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195 | # print len(dy) |
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196 | |
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197 | |
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198 | input_f.close() |
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199 | # Sanity check |
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200 | # if has_error_dy == True and not len(y) == len(dy): |
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201 | # msg = "sesans_reader: y and dy have different length" |
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202 | # raise RuntimeError, msg |
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203 | # if has_error_dx == True and not len(x) == len(dx): |
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204 | # msg = "sesans_reader: y and dy have different length" |
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205 | # raise RuntimeError, msg |
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206 | # # If the data length is zero, consider this as |
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207 | # # though we were not able to read the file. |
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208 | # if len(x) == 0: |
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209 | # raise RuntimeError, "sesans_reader: could not load file" |
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210 | # print "alive" |
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211 | #Let's re-order the data to make cal. |
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212 | # curve look better some cases |
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213 | # ind = numpy.lexsort((ty, tx)) |
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214 | # for i in ind: |
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215 | # x[i] = tx[ind[i]] |
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216 | # y[i] = ty[ind[i]] |
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217 | # if has_error_dy == True: |
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218 | # dy[i] = tdy[ind[i]] |
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219 | # if has_error_dx == True: |
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220 | # dx[i] = tdx[ind[i]] |
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221 | # Zeros in dx, dy |
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222 | # if has_error_dx: |
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223 | # dx[dx == 0] = _ZERO |
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224 | # if has_error_dy: |
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225 | # dy[dy == 0] = _ZERO |
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226 | #Data |
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227 | output.x = x #[x != 0] |
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228 | # print output.x |
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229 | output.y = y #[x != 0] |
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230 | # print output.y |
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231 | # output.dy = dy[x != 0] if has_error_dy == True\ |
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232 | # else numpy.zeros(len(output.y)) |
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233 | # output.dx = dx[x != 0] if has_error_dx == True\ |
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234 | # else numpy.zeros(len(output.x)) |
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235 | output.dy = dy |
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236 | output.dx = dx |
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237 | output.lam = lam |
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238 | output.dlam = dlam |
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239 | |
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240 | |
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241 | # print "still alive" |
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242 | # if data_conv_z is not None: |
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243 | # output.xaxis("\\rm{z}", output.x_unit) |
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244 | # else: |
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245 | # output.xaxis("\\rm{z}", 'nm') |
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246 | # if data_conv_P is not None: |
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247 | # output.yaxis("\\rm{P/P0}", output.y_unit) |
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248 | # else: |
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249 | # output.yaxis("\\rm{P/P0}", "a.u.") |
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250 | output.xaxis("\\rm{z}", 'A') |
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251 | output.yaxis("\\rm{P/P0}", " ") |
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252 | # Store loading process information |
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253 | output.meta_data['loader'] = self.type_name |
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254 | output.sample.thickness = float(paramvals[6]) |
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255 | output.sample.name = paramvals[1] |
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256 | output.sample.ID = paramvals[0] |
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257 | output.sample.zacceptance=float(paramvals[7]) |
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258 | # print output |
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259 | |
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260 | # print "sesans_reader end" |
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261 | |
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262 | if len(output.x) < 1: |
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263 | raise RuntimeError, "%s is empty" % path |
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264 | # print output |
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265 | |
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266 | return output |
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267 | |
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268 | else: |
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269 | raise RuntimeError, "%s is not a file" % path |
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270 | return None |
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