1 | |
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2 | import Image |
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3 | import math |
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4 | class ReaderInfo: |
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5 | """ |
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6 | """ |
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7 | ## Wavelength [A] |
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8 | wavelength = 0.0 |
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9 | ## Number of x bins |
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10 | xbins = 128 |
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11 | ## Number of y bins |
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12 | ybins = 128 |
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13 | ## Beam center X [pixel number] |
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14 | center_x = 65 |
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15 | ## Beam center Y [pixel number] |
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16 | center_y = 65 |
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17 | ## Distance from sample to detector [m] |
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18 | distance = 11.0 |
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19 | ## Qx values [A-1] |
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20 | x_vals = [] |
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21 | ## Qy xalues [A-1] |
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22 | y_vals = [] |
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23 | ## Qx min |
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24 | xmin = 0.0 |
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25 | ## Qx max |
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26 | xmax = 1.0 |
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27 | ## Qy min |
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28 | ymin = 0.0 |
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29 | ## Qy max |
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30 | ymax = 1.0 |
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31 | ## Image |
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32 | image = None |
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33 | ## Pixel size |
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34 | pixel_size = 0.5 |
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35 | ## Error on each pixel |
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36 | error = None |
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37 | |
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38 | class Reader: |
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39 | """ |
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40 | Example data manipulation |
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41 | """ |
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42 | ## File type |
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43 | type = [] |
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44 | ## Extension |
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45 | ext = ['tif', 'jpg', '.png', 'jpeg', '.tiff', 'gif', 'bmp'] |
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46 | |
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47 | def read(self, filename=None): |
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48 | """ |
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49 | Open and read the data in a file |
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50 | @param file: path of the file |
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51 | """ |
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52 | |
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53 | read_it = False |
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54 | for item in self.ext: |
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55 | if filename.lower().find(item)>=0: |
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56 | read_it = True |
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57 | |
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58 | if read_it: |
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59 | import Image |
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60 | import pylab |
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61 | import copy |
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62 | import numpy |
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63 | |
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64 | wavelength, distance, center_x, center_y, pixel = 10.0, 11.0, 65, 65, 1.0 |
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65 | |
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66 | |
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67 | |
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68 | # Initialize |
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69 | x_vals = [] |
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70 | y_vals = [] |
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71 | ymin = None |
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72 | ymax = None |
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73 | xmin = None |
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74 | xmax = None |
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75 | Z = None |
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76 | |
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77 | |
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78 | im = Image.open(filename) |
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79 | |
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80 | # Detector size should be 128x128, the file is 190x190 |
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81 | print "-> Image size:", im.size, im.format, im.mode |
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82 | data = im.getdata() |
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83 | x = numpy.zeros(im.size[0]) |
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84 | y = numpy.zeros(im.size[1]) |
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85 | X, Y = pylab.meshgrid(x, y) |
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86 | Z = copy.deepcopy(X) |
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87 | itot = 0 |
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88 | i_x = 0 |
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89 | i_y = 0 |
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90 | |
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91 | # Qx and Qy vectors |
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92 | for i_x in range(im.size[0]): |
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93 | theta = (i_x-center_x+1)*pixel / distance / 100.0 |
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94 | qx = 4.0*math.pi/wavelength * math.sin(theta/2.0) |
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95 | x_vals.append(qx) |
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96 | if xmin==None or qx<xmin: |
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97 | xmin = qx |
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98 | if xmax==None or qx>xmax: |
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99 | xmax = qx |
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100 | |
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101 | ymin = None |
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102 | ymax = None |
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103 | for i_y in range(im.size[1]): |
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104 | theta = (i_y-center_y+1)*pixel / distance / 100.0 |
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105 | qy = 4.0*math.pi/wavelength * math.sin(theta/2.0) |
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106 | y_vals.append(qy) |
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107 | if ymin==None or qy<ymin: |
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108 | ymin = qy |
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109 | if ymax==None or qy>ymax: |
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110 | ymax = qy |
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111 | |
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112 | for val in data: |
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113 | |
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114 | try: |
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115 | value = float(val) |
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116 | except: |
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117 | continue |
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118 | |
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119 | # Get bin number |
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120 | if math.fmod(itot, im.size[0])==0: |
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121 | i_x = 0 |
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122 | i_y += 1 |
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123 | else: |
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124 | i_x += 1 |
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125 | |
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126 | Z[im.size[1]-1-i_y][i_x] = value |
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127 | |
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128 | itot += 1 |
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129 | |
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130 | output = ReaderInfo() |
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131 | output.wavelength = wavelength |
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132 | output.xbins = im.size[0] |
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133 | output.ybins = im.size[1] |
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134 | output.center_x = center_x |
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135 | output.center_y = center_y |
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136 | output.distance = distance |
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137 | output.x_vals = x_vals |
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138 | output.y_vals = y_vals |
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139 | output.xmin = xmin |
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140 | output.xmax = xmax |
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141 | output.ymin = ymin |
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142 | output.ymax = ymax |
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143 | output.image = Z |
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144 | output.pixel_size = pixel |
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145 | |
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146 | return output |
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147 | |
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148 | return None |
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149 | |
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150 | |
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