1 | """ |
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2 | ASCII reader |
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3 | """ |
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4 | ############################################################################ |
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5 | #This software was developed by the University of Tennessee as part of the |
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6 | #Distributed Data Analysis of Neutron Scattering Experiments (DANSE) |
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7 | #project funded by the US National Science Foundation. |
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8 | #If you use DANSE applications to do scientific research that leads to |
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9 | #publication, we ask that you acknowledge the use of the software with the |
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10 | #following sentence: |
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11 | #This work benefited from DANSE software developed under NSF award DMR-0520547. |
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12 | #copyright 2008, University of Tennessee |
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13 | ############################################################################# |
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14 | |
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15 | |
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16 | import numpy |
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17 | import os |
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18 | from sas.sascalc.dataloader.data_info import Data1D |
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19 | |
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20 | # Check whether we have a converter available |
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21 | has_converter = True |
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22 | try: |
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23 | from sas.sascalc.data_util.nxsunit import Converter |
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24 | except: |
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25 | has_converter = False |
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26 | _ZERO = 1e-16 |
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27 | |
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28 | |
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29 | class Reader: |
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30 | """ |
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31 | Class to load ascii files (2, 3 or 4 columns). |
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32 | """ |
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33 | ## File type |
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34 | type_name = "ASCII" |
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35 | |
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36 | ## Wildcards |
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37 | type = ["ASCII files (*.txt)|*.txt", |
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38 | "ASCII files (*.dat)|*.dat", |
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39 | "ASCII files (*.abs)|*.abs", |
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40 | "CSV files (*.csv)|*.csv"] |
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41 | ## List of allowed extensions |
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42 | ext = ['.txt', '.TXT', '.dat', '.DAT', '.abs', '.ABS', 'csv', 'CSV'] |
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43 | |
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44 | ## Flag to bypass extension check |
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45 | allow_all = True |
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46 | |
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47 | def read(self, path): |
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48 | """ |
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49 | Load data file |
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50 | |
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51 | :param path: file path |
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52 | :return: Data1D object, or None |
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53 | |
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54 | :raise RuntimeError: when the file can't be opened |
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55 | :raise ValueError: when the length of the data vectors are inconsistent |
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56 | """ |
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57 | if os.path.isfile(path): |
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58 | basename = os.path.basename(path) |
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59 | _, extension = os.path.splitext(basename) |
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60 | if self.allow_all or extension.lower() in self.ext: |
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61 | try: |
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62 | # Read in binary mode since GRASP frequently has no-ascii |
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63 | # characters that breaks the open operation |
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64 | input_f = open(path,'rb') |
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65 | except: |
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66 | raise RuntimeError, "ascii_reader: cannot open %s" % path |
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67 | buff = input_f.read() |
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68 | lines = buff.splitlines() |
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69 | |
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70 | # Arrays for data storage |
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71 | tx = numpy.zeros(0) |
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72 | ty = numpy.zeros(0) |
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73 | tdy = numpy.zeros(0) |
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74 | tdx = numpy.zeros(0) |
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75 | |
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76 | # The first good line of data will define whether |
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77 | # we have 2-column or 3-column ascii |
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78 | has_error_dx = None |
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79 | has_error_dy = None |
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80 | |
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81 | #Initialize counters for data lines and header lines. |
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82 | is_data = False |
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83 | # More than "5" lines of data is considered as actual |
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84 | # data unless that is the only data |
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85 | min_data_pts = 5 |
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86 | # To count # of current data candidate lines |
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87 | candidate_lines = 0 |
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88 | # To count total # of previous data candidate lines |
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89 | candidate_lines_previous = 0 |
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90 | #minimum required number of columns of data |
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91 | lentoks = 2 |
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92 | for line in lines: |
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93 | toks = self.splitline(line) |
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94 | # To remember the # of columns in the current line of data |
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95 | new_lentoks = len(toks) |
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96 | try: |
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97 | if new_lentoks == 1 and not is_data: |
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98 | ## If only one item in list, no longer data |
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99 | raise ValueError |
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100 | elif new_lentoks == 0: |
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101 | ## If the line is blank, skip and continue on |
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102 | ## In case of breaks within data sets. |
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103 | continue |
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104 | elif new_lentoks != lentoks and is_data: |
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105 | ## If a footer is found, break the loop and save the data |
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106 | break |
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107 | elif new_lentoks != lentoks and not is_data: |
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108 | ## If header lines are numerical |
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109 | candidate_lines = 0 |
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110 | candidate_lines_previous = 0 |
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111 | |
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112 | #Make sure that all columns are numbers. |
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113 | for colnum in range(len(toks)): |
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114 | # Any non-floating point values throw ValueError |
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115 | float(toks[colnum]) |
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116 | |
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117 | candidate_lines += 1 |
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118 | _x = float(toks[0]) |
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119 | _y = float(toks[1]) |
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120 | _dx = None |
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121 | _dy = None |
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122 | |
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123 | #If 5 or more lines, this is considering the set data |
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124 | if candidate_lines >= min_data_pts: |
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125 | is_data = True |
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126 | |
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127 | # If a 3rd row is present, consider it dy |
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128 | if new_lentoks > 2: |
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129 | _dy = float(toks[2]) |
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130 | has_error_dy = False if _dy == None else True |
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131 | |
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132 | # If a 4th row is present, consider it dx |
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133 | if new_lentoks > 3: |
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134 | _dx = float(toks[3]) |
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135 | has_error_dx = False if _dx == None else True |
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136 | |
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137 | # Delete the previously stored lines of data candidates if |
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138 | # the list is not data |
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139 | if candidate_lines == 1 and -1 < candidate_lines_previous < min_data_pts and \ |
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140 | is_data == False: |
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141 | try: |
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142 | tx = numpy.zeros(0) |
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143 | ty = numpy.zeros(0) |
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144 | tdy = numpy.zeros(0) |
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145 | tdx = numpy.zeros(0) |
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146 | except: |
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147 | pass |
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148 | |
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149 | if has_error_dy == True: |
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150 | tdy = numpy.append(tdy, _dy) |
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151 | if has_error_dx == True: |
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152 | tdx = numpy.append(tdx, _dx) |
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153 | tx = numpy.append(tx, _x) |
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154 | ty = numpy.append(ty, _y) |
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155 | |
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156 | #To remember the # of columns on the current line |
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157 | # for the next line of data |
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158 | lentoks = new_lentoks |
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159 | candidate_lines_previous = candidate_lines |
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160 | except ValueError: |
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161 | # It is data and meet non - number, then stop reading |
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162 | if is_data == True: |
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163 | break |
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164 | lentoks = 2 |
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165 | has_error_dx = None |
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166 | has_error_dy = None |
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167 | #Reset # of lines of data candidates |
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168 | candidate_lines = 0 |
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169 | except: |
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170 | pass |
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171 | |
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172 | input_f.close() |
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173 | # Sanity check |
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174 | if has_error_dy == True and not len(ty) == len(tdy): |
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175 | msg = "ascii_reader: y and dy have different length" |
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176 | raise RuntimeError, msg |
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177 | if has_error_dx == True and not len(tx) == len(tdx): |
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178 | msg = "ascii_reader: y and dy have different length" |
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179 | raise RuntimeError, msg |
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180 | # If the data length is zero, consider this as |
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181 | # though we were not able to read the file. |
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182 | if len(tx) == 0: |
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183 | raise RuntimeError, "ascii_reader: could not load file" |
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184 | |
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185 | #Let's re-order the data to make cal. |
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186 | # curve look better some cases |
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187 | ind = numpy.lexsort((ty, tx)) |
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188 | x = numpy.zeros(len(tx)) |
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189 | y = numpy.zeros(len(ty)) |
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190 | dy = numpy.zeros(len(tdy)) |
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191 | dx = numpy.zeros(len(tdx)) |
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192 | output = Data1D(x, y, dy=dy, dx=dx) |
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193 | self.filename = output.filename = basename |
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194 | |
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195 | for i in ind: |
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196 | x[i] = tx[ind[i]] |
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197 | y[i] = ty[ind[i]] |
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198 | if has_error_dy == True: |
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199 | dy[i] = tdy[ind[i]] |
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200 | if has_error_dx == True: |
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201 | dx[i] = tdx[ind[i]] |
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202 | # Zeros in dx, dy |
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203 | if has_error_dx: |
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204 | dx[dx == 0] = _ZERO |
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205 | if has_error_dy: |
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206 | dy[dy == 0] = _ZERO |
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207 | #Data |
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208 | output.x = x[x != 0] |
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209 | output.y = y[x != 0] |
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210 | output.dy = dy[x != 0] if has_error_dy == True\ |
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211 | else numpy.zeros(len(output.y)) |
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212 | output.dx = dx[x != 0] if has_error_dx == True\ |
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213 | else numpy.zeros(len(output.x)) |
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214 | |
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215 | output.xaxis("\\rm{Q}", 'A^{-1}') |
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216 | output.yaxis("\\rm{Intensity}", "cm^{-1}") |
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217 | |
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218 | # Store loading process information |
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219 | output.meta_data['loader'] = self.type_name |
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220 | if len(output.x) < 1: |
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221 | raise RuntimeError, "%s is empty" % path |
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222 | return output |
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223 | |
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224 | else: |
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225 | raise RuntimeError, "%s is not a file" % path |
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226 | return None |
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227 | |
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228 | def splitline(self, line): |
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229 | """ |
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230 | Splits a line into pieces based on common delimeters |
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231 | :param line: A single line of text |
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232 | :return: list of values |
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233 | """ |
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234 | # Initial try for CSV (split on ,) |
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235 | toks = line.split(',') |
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236 | # Now try SCSV (split on ;) |
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237 | if len(toks) < 2: |
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238 | toks = line.split(';') |
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239 | # Now go for whitespace |
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240 | if len(toks) < 2: |
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241 | toks = line.split() |
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242 | return toks |
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