src/graphical_analysis.py

   1 #coding: utf-8
   2 #file name: graphical_analysis_pyqt4.py
   3 #Laueye - A program to analyze Laue diffraction diagrams.
   4 #Copyright (C) <2008>  <Grissiom>
   5
   6 #This program is free software: you can redistribute it and/or modify
   7 #it under the terms of the GNU General Public License as published by
   8 #the Free Software Foundation, either version 3 of the License, or
   9 #(at your option) any later version.
  10
  11 #This program is distributed in the hope that it will be useful,
  12 #but WITHOUT ANY WARRANTY; without even the implied warranty of
  13 #MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  14 #GNU General Public License for more details.
  15
  16 #You should have received a copy of the GNU General Public License
  17 #along with this program.  If not, see <http://www.gnu.org/licenses/>.
  18
  19 import Image
  20
  21 class circle:
  22         '''a circle's data'''
  23         def __init__(self):
  24                 self.x_list = []
  25                 self.y_list = []
  26                 self.x_boundry = [None, None]
  27                 self.y_boundry = [None, None]
  28         def center(self):
  29                 '''return the location of the circle, in flaot format'''
  30                 x = 0
  31                 for i in self.x_list:
  32                         x += i
  33                 y = 0
  34                 for i in self.y_list:
  35                         y += i
  36                 return x / len(self.x_list), y / len(self.y_list)
  37
  38
  39 scope = 1
  40
  41 def figure_out_circles(im_in, threshold):
  42         '''figure out the circles in it
  43
  44         @param im_in the img to analyz
  45         @param threshold the threshold we use to determin the boundry
  46         @return return a list of circles
  47         '''
  48         return _get_circles(_setup_status(im_in, threshold))
  49
  50 def _setup_status(im_in, threshold):
  51         '''figure out the boundry of circles for the image im_in.
  52         this function should run *BEFORE* get_boundry() and run only once
  53
  54         @param im_in the image to setup.
  55         @param threshold the threshold of black and white
  56         @return the setuped status table.
  57         0 for black, 1 for white, 2 if the pixel is just stand on the
  58         edge, 4 for the pixels which is ready calculated into a
  59         circle.'''
  60         #TODO:This function is the most time wasting function.
  61         #waite for further optimize.
  62         width, height = im_in.size
  63
  64         # setup a temp matrices list here on status, 0 for black and 1 for white.
  65         status = []
  66         im_in = im_in.convert('L')
  67         pix = im_in.load()
  68         for i in range(width):
  69                 status.append([])
  70                 for k in range(height):
  71                         if pix[i, k] > threshold:
  72                                 status[i].append(1)
  73                         else:
  74                                 status[i].append(0)
  75
  76         li_range = range(-scope, scope + 1)
  77         def is_boundry(i, k):
  78                 for n in li_range:
  79                         for m in li_range:
  80                                 if status[i + n][k + m] == 0:
  81                                         return True
  82
  83         for i in range(scope, width - scope):
  84                 for k in range(scope, height - scope):
  85                         if status[i][k] == 1:
  86                                 if is_boundry(i, k):
  87                                         status[i][k] = 2
  88         return status
  89
  90 def _get_boundry(in_list, status):
  91         '''get the boundry of the whole circle based on the status table.
  92
  93         @param in_list a point on the circle.
  94         @param status the status table which is the base to analyze
  95         @return x_list and y_listto store the boundry's xs and ys
  96         '''
  97         x_list = []
  98         y_list = []
  99         while len(in_list) != 0:
 100                 (x,  y) = in_list.pop()
 101                 x_list.append(x)
 102                 y_list.append(y)
 103                 status[x][y] = 4
 104                 for i in range(-scope, scope + 1):
 105                         for k in range(-scope, scope + 1):
 106                                 if status[x + i][y + k] == 2:
 107                                         in_list.append([x + i, y + k])
 108         return (x_list,  y_list)
 109
 110 def _get_circles(status):
 111         '''get the circles in the whole image.
 112
 113         @param status the status table which is the base of analyze.
 114         @return a list of circles.'''
 115         width = len(status)
 116         height = len(status[0])
 117         #TODO:maybe we need to check whether im_status is a matrices here.
 118         # i.e, all the len(im_status[:]) have the same value.
 119         circles = []
 120         for i in range(scope,  width - scope):
 121                 for k in range(scope,  height - scope):
 122                         if status[i][k] == 2:
 123                                 circles.append(circle())
 124                                 circles[-1].x_list, circles[-1].y_list \
 125                                         = _get_boundry([[i, k]], status)
 126                                 if len(circles[-1].x_list) < 4:
 127                                         del circles[-1]
 128         return circles
 129
 130 if __name__ == '__main__':
 131 #       im = Laue_diagram('../test/test.png')
 132         circles = figure_out_circles(Image.open('../test/test.png'), 128)
 133         print 'we have', len(circles),'circles'
 134 else:
 135         pass
 136 pass
 137