1 | """ |
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2 | DANSE/SANS 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 math |
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20 | import os |
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21 | import copy |
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22 | import numpy |
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23 | import logging |
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24 | from DataLoader.data_info import Data2D, Detector |
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25 | |
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26 | # Look for unit converter |
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27 | has_converter = True |
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28 | try: |
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29 | from data_util.nxsunit import Converter |
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30 | except: |
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31 | has_converter = False |
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32 | |
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33 | class Reader: |
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34 | """ |
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35 | Example data manipulation |
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36 | """ |
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37 | ## File type |
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38 | type = ["DANSE files (*.sans)|*.sans"] |
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39 | ## Extension |
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40 | ext = ['.sans', '.SANS'] |
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41 | |
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42 | def read(self, filename=None): |
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43 | """ |
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44 | Open and read the data in a file |
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45 | @param file: path of the file |
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46 | """ |
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47 | |
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48 | read_it = False |
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49 | for item in self.ext: |
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50 | if filename.lower().find(item)>=0: |
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51 | read_it = True |
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52 | |
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53 | if read_it: |
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54 | try: |
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55 | datafile = open(filename, 'r') |
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56 | except : |
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57 | raise RuntimeError,"danse_reader cannot open %s"%(filename) |
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58 | |
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59 | |
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60 | # defaults |
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61 | # wavelength in Angstrom |
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62 | wavelength = 10.0 |
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63 | # Distance in meter |
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64 | distance = 11.0 |
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65 | # Pixel number of center in x |
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66 | center_x = 65 |
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67 | # Pixel number of center in y |
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68 | center_y = 65 |
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69 | # Pixel size [mm] |
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70 | pixel = 5.0 |
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71 | # Size in x, in pixels |
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72 | size_x = 128 |
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73 | # Size in y, in pixels |
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74 | size_y = 128 |
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75 | # Format version |
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76 | fversion = 1.0 |
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77 | |
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78 | output = Data2D() |
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79 | output.filename = os.path.basename(filename) |
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80 | detector = Detector() |
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81 | output.detector.append(detector) |
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82 | |
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83 | output.data = numpy.zeros([size_x,size_y]) |
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84 | output.err_data = numpy.zeros([size_x,size_y]) |
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85 | |
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86 | data_conv_q = None |
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87 | data_conv_i = None |
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88 | |
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89 | if has_converter == True and output.Q_unit != '1/A': |
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90 | data_conv_q = Converter('1/A') |
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91 | # Test it |
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92 | data_conv_q(1.0, output.Q_unit) |
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93 | |
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94 | if has_converter == True and output.I_unit != '1/cm': |
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95 | data_conv_i = Converter('1/cm') |
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96 | # Test it |
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97 | data_conv_i(1.0, output.I_unit) |
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98 | |
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99 | read_on = True |
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100 | while read_on: |
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101 | line = datafile.readline() |
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102 | if line.find("DATA:")>=0: |
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103 | read_on = False |
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104 | break |
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105 | toks = line.split(':') |
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106 | if toks[0]=="FORMATVERSION": |
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107 | fversion = float(toks[1]) |
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108 | if toks[0]=="WAVELENGTH": |
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109 | wavelength = float(toks[1]) |
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110 | elif toks[0]=="DISTANCE": |
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111 | distance = float(toks[1]) |
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112 | elif toks[0]=="CENTER_X": |
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113 | center_x = float(toks[1]) |
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114 | elif toks[0]=="CENTER_Y": |
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115 | center_y = float(toks[1]) |
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116 | elif toks[0]=="PIXELSIZE": |
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117 | pixel = float(toks[1]) |
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118 | elif toks[0]=="SIZE_X": |
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119 | size_x = int(toks[1]) |
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120 | elif toks[0]=="SIZE_Y": |
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121 | size_y = int(toks[1]) |
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122 | |
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123 | # Read the data |
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124 | data = [] |
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125 | error = [] |
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126 | if fversion==1.0: |
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127 | data_str = datafile.readline() |
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128 | data = data_str.split(' ') |
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129 | else: |
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130 | read_on = True |
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131 | while read_on: |
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132 | data_str = datafile.readline() |
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133 | if len(data_str)==0: |
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134 | read_on = False |
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135 | else: |
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136 | toks = data_str.split() |
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137 | try: |
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138 | val = float(toks[0]) |
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139 | err = float(toks[1]) |
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140 | if data_conv_i is not None: |
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141 | val = data_conv_i(val, units=output.y_unit) |
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142 | err = data_conv_i(err, units=output.y_unit) |
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143 | data.append(val) |
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144 | error.append(err) |
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145 | except: |
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146 | logging.info("Skipping line:%s,%s" %( data_str,sys.exc_value)) |
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147 | |
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148 | # Initialize |
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149 | x_vals = [] |
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150 | y_vals = [] |
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151 | ymin = None |
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152 | ymax = None |
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153 | xmin = None |
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154 | xmax = None |
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155 | |
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156 | # Qx and Qy vectors |
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157 | theta = pixel / distance / 100.0 |
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158 | stepq = 4.0*math.pi/wavelength * math.sin(theta/2.0) |
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159 | for i_x in range(size_x): |
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160 | theta = (i_x-center_x+1)*pixel / distance / 100.0 |
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161 | qx = 4.0*math.pi/wavelength * math.sin(theta/2.0) |
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162 | |
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163 | if has_converter == True and output.Q_unit != '1/A': |
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164 | qx = data_conv_q(qx, units=output.Q_unit) |
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165 | |
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166 | x_vals.append(qx) |
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167 | if xmin==None or qx<xmin: |
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168 | xmin = qx |
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169 | if xmax==None or qx>xmax: |
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170 | xmax = qx |
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171 | |
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172 | ymin = None |
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173 | ymax = None |
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174 | for i_y in range(size_y): |
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175 | theta = (i_y-center_y+1)*pixel / distance / 100.0 |
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176 | qy = 4.0*math.pi/wavelength * math.sin(theta/2.0) |
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177 | |
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178 | if has_converter == True and output.Q_unit != '1/A': |
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179 | qy = data_conv_q(qy, units=output.Q_unit) |
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180 | |
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181 | y_vals.append(qy) |
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182 | if ymin==None or qy<ymin: |
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183 | ymin = qy |
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184 | if ymax==None or qy>ymax: |
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185 | ymax = qy |
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186 | |
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187 | # Store the data in the 2D array |
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188 | itot = 0 |
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189 | i_x = 0 |
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190 | i_y = -1 |
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191 | |
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192 | for i_pt in range(len(data)): |
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193 | try: |
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194 | value = float(data[i_pt]) |
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195 | except: |
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196 | # For version 1.0, the data were still |
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197 | # stored as strings at this point. |
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198 | logging.info("Skipping entry (v1.0):%s,%s" %(str(data[i_pt]), sys.exc_value)) |
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199 | |
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200 | # Get bin number |
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201 | if math.fmod(i_pt, size_x)==0: |
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202 | i_x = 0 |
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203 | i_y += 1 |
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204 | else: |
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205 | i_x += 1 |
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206 | |
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207 | output.data[i_y][i_x] = value |
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208 | #output.data[size_y-1-i_y][i_x] = value |
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209 | if fversion>1.0: |
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210 | output.err_data[i_y][i_x] = error[i_pt] |
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211 | #output.err_data[size_y-1-i_y][i_x] = error[i_pt] |
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212 | |
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213 | |
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214 | # Store all data ###################################### |
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215 | # Store wavelength |
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216 | if has_converter==True and output.source.wavelength_unit != 'A': |
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217 | conv = Converter('A') |
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218 | wavelength = conv(wavelength, units=output.source.wavelength_unit) |
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219 | output.source.wavelength = wavelength |
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220 | |
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221 | # Store distance |
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222 | if has_converter==True and detector.distance_unit != 'm': |
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223 | conv = Converter('m') |
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224 | distance = conv(distance, units=detector.distance_unit) |
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225 | detector.distance = distance |
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226 | |
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227 | # Store pixel size |
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228 | if has_converter==True and detector.pixel_size_unit != 'mm': |
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229 | conv = Converter('mm') |
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230 | pixel = conv(pixel, units=detector.pixel_size_unit) |
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231 | detector.pixel_size.x = pixel |
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232 | detector.pixel_size.y = pixel |
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233 | |
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234 | # Store beam center in distance units |
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235 | detector.beam_center.x = center_x*pixel |
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236 | detector.beam_center.y = center_y*pixel |
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237 | |
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238 | # Store limits of the image (2D array) |
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239 | xmin =xmin-stepq/2.0 |
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240 | xmax =xmax+stepq/2.0 |
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241 | ymin =ymin-stepq/2.0 |
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242 | ymax =ymax+stepq/2.0 |
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243 | |
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244 | if has_converter == True and output.Q_unit != '1/A': |
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245 | xmin = data_conv_q(xmin, units=output.Q_unit) |
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246 | xmax = data_conv_q(xmax, units=output.Q_unit) |
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247 | ymin = data_conv_q(ymin, units=output.Q_unit) |
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248 | ymax = data_conv_q(ymax, units=output.Q_unit) |
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249 | output.xmin = xmin |
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250 | output.xmax = xmax |
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251 | output.ymin = ymin |
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252 | output.ymax = ymax |
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253 | |
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254 | # Store x and y axis bin centers |
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255 | output.x_bins = x_vals |
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256 | output.y_bins = y_vals |
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257 | |
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258 | # Units |
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259 | if data_conv_q is not None: |
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260 | output.xaxis("\\rm{Q_{x}}", output.Q_unit) |
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261 | output.yaxis("\\rm{Q_{y}}", output.Q_unit) |
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262 | else: |
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263 | output.xaxis("\\rm{Q_{x}}", 'A^{-1}') |
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264 | output.yaxis("\\rm{Q_{y}}", 'A^{-1}') |
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265 | |
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266 | if data_conv_i is not None: |
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267 | output.zaxis("\\{I(Q)}", output.I_unit) |
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268 | else: |
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269 | output.zaxis("\\rm{I(Q)}","cm^{-1}") |
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270 | |
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271 | if not fversion>=1.0: |
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272 | raise ValueError,"Danse_reader can't read this file %s"%filename |
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273 | else: |
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274 | logging.info("Danse_reader Reading %s \n"%filename) |
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275 | return output |
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276 | |
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277 | return None |
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278 | |
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279 | if __name__ == "__main__": |
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280 | reader = Reader() |
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281 | print reader.read("../test/MP_New.sans") |
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282 | |
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