[c35e8492] | 1 | """ |
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| 2 | Image reader. Untested. |
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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 | See the license text in license.txt |
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| 11 | |
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| 12 | copyright 2008, University of Tennessee |
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| 13 | """ |
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| 14 | #TODO: load and check data and orientation of the image (needs rendering) |
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| 15 | |
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| 16 | import math, logging, os |
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| 17 | import numpy |
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| 18 | from DataLoader.data_info import Data2D |
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| 19 | |
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| 20 | class Reader: |
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| 21 | """ |
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| 22 | Example data manipulation |
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| 23 | """ |
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| 24 | ## File type |
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| 25 | type = ["TIF files (*.tif)|*.tif", |
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| 26 | "JPG files (*.jpg)|*.jpg", |
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| 27 | "JPEG files (*.jpeg)|*.jpeg", |
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| 28 | "PNG files (*.png)|*.png", |
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| 29 | "TIFF files (*.tiff)|*.tiff", |
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| 30 | "BMP files (*.bmp)|*.bmp", |
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| 31 | "GIF files (*.gif)|*.gif", |
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| 32 | ] |
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| 33 | ## Extension |
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| 34 | ext = ['.tif', '.jpg', '.png', '.jpeg', '.tiff', '.gif', '.bmp'] |
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| 35 | |
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| 36 | def read(self, filename=None): |
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| 37 | """ |
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| 38 | Open and read the data in a file |
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| 39 | @param file: path of the file |
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| 40 | """ |
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| 41 | try: |
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| 42 | import Image |
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| 43 | except: |
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| 44 | raise RuntimeError, "tiff_reader: could not load file. Missing Image module." |
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| 45 | |
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| 46 | # Instantiate data object |
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| 47 | output = Data2D() |
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| 48 | output.filename = os.path.basename(filename) |
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| 49 | |
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| 50 | # Read in the image |
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| 51 | try: |
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| 52 | im = Image.open(filename) |
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| 53 | except : |
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| 54 | raise RuntimeError,"cannot open %s"%(filename) |
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| 55 | data = im.getdata() |
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| 56 | |
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| 57 | # Initiazed the output data object |
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| 58 | output.data = numpy.zeros([im.size[0],im.size[1]]) |
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| 59 | |
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| 60 | # Initialize |
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| 61 | x_vals = [] |
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| 62 | y_vals = [] |
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| 63 | |
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| 64 | # x and y vectors |
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| 65 | for i_x in range(im.size[0]): |
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| 66 | x_vals.append(i_x) |
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| 67 | |
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| 68 | itot = 0 |
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| 69 | for i_y in range(im.size[1]): |
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| 70 | y_vals.append(i_y) |
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| 71 | |
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| 72 | for val in data: |
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| 73 | try: |
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| 74 | value = float(val) |
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| 75 | except: |
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| 76 | logging.error("tiff_reader: had to skip a non-float point") |
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| 77 | continue |
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| 78 | |
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| 79 | # Get bin number |
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| 80 | if math.fmod(itot, im.size[0])==0: |
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| 81 | i_x = 0 |
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| 82 | i_y += 1 |
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| 83 | else: |
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| 84 | i_x += 1 |
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| 85 | |
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| 86 | output.data[im.size[1]-1-i_y][i_x] = value |
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| 87 | |
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| 88 | itot += 1 |
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| 89 | |
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| 90 | output.xbins = im.size[0] |
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| 91 | output.ybins = im.size[1] |
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| 92 | output.x_bins = x_vals |
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| 93 | output.y_bins = y_vals |
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| 94 | output.xmin = 0 |
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| 95 | output.xmax = im.size[0]-1 |
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| 96 | output.ymin = 0 |
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| 97 | output.ymax = im.size[0]-1 |
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| 98 | |
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| 99 | return data#output |
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| 100 | |
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| 101 | |
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| 102 | |
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